Neutrino Mass Ordering from Oscillations and Beyond: 2018 Status and Future Prospects

1. Introduction

The Royal Swedish Academy of Sciences decided to award the 2015 Nobel Prize in Physics to Takaaki Kajita and Arthur B. McDonald “for the discovery of neutrino oscillations, which shows that neutrinos have mass. […] New discoveries about the deepest neutrino secrets are expected to change our current understanding of the history, structure and future fate of the Universe” (see Fukuda et al., 1998; Ahmad et al., 2001, 2002; Eguchi et al., 2003; Abe et al., 2011a; An et al., 2012) for essential publications. These discoveries robustly established that neutrinos are massive particles. However, neutrinos are massless particles in the Standard Model (SM) of particle physics: in the absence of any direct indication for their mass available at the time, they were introduced as fermions for which no gauge invariant renormalizable mass term can be constructed. As a consequence, in the SM there is neither mixing nor CP violation in the lepton sector. Therefore, neutrino oscillations and masses imply the first known departure from the SM of particle physics.

Despite the good precision that neutrino experiments have reached in the recent years, still many neutrino properties remain unknown. Among them, the neutrino character, Dirac vs. Majorana, the existence of CP violation in the leptonic sector, the absolute scale of neutrino masses, and the type of the neutrino mass spectrum. Future laboratory, accelerator and reactor, astrophysical and cosmological probes will address all these open questions, that may further reinforce the evidence for physics beyond the SM. The main focus of this review is, however, the last of the aforementioned unknowns. We will discuss what we know and how we could improve our current knowledge of the neutrino mass ordering.

Neutrino oscillation physics is only sensitive to the squared mass differences ($\Delta m_{ij}^2=m_i^2-m_j^2$). Current oscillation data can be remarkably well-fitted in terms of two squared mass differences, dubbed as the solar mass splitting ($\Delta m_{21}^2\simeq 7.6\times 10^{-5}$ eV²) and the atmospheric mass splitting ($\left|\Delta m_{31}^2\right|\simeq 2.5\times 10^{-3}$ eV²) (de Salas et al., 2018)¹. Thanks to matter effects in the Sun, we know that $\Delta m_{21}^2>0$². Since the atmospheric mass splitting $\Delta m_{31}^2$ is essentially measured only via neutrino oscillations in vacuum, which exclusively depend on its absolute value, its sign is unknown at the moment. As a consequence, we have two possibilities for the ordering of neutrino masses: normal ordering (NO, $\Delta m_{31}^2>0$) or inverted ordering (IO, $\Delta m_{31}^2<0$).

The situation for the mass ordering has changed a lot in the last few months. The 2017 analyses dealing with global oscillation neutrino data have only shown a mild preference for the normal ordering. Namely, the authors of Capozzi et al. (2017), by means of a frequentist analysis, found ${\chi }_{\mathrm{\text{IO}}}^2-{\chi }_{\mathrm{\text{NO}}}^2=3.6$ from all the oscillation data considered in their analyses. Very similar results were reported in the first version of de Salas et al. (2018)³., where a value of ${\chi }_{\mathrm{\text{IO}}}^2-{\chi }_{\mathrm{\text{NO}}}^2=4.3$ was quoted⁴ (nufit)⁵ Furthermore, in Gariazzo et al. (2018a), the authors verified that the use of a Bayesian approach and the introduction of cosmological or neutrinoless double beta decay data did not alter the main result, which was a weak-to-moderate evidence for the normal neutrino mass ordering according to the Jeffreys' scale (see Table 2). The most recent global fit to neutrino oscillation data, however, reported a strengthened preference for normal ordering that is mainly due to the new data from the Super-Kamiokande Abe et al. (2018a), T2K Hartz (2017), and NOνA Radovic (2018) experiments. The inclusion of these new data in both the analyses of Capozzi et al. (2018a) and the 2018 update of de Salas et al. (2018)¹ increases the preference for normal ordering, which now lies mildly above the 3σ level. In this review we will comment these new results (see section 2) and use them to perform an updated global analysis, following the method of Gariazzo et al. (2018a) (see section 5).

The two possible hierarchical⁶ neutrino mass scenarios are shown in Figure 1, inspired by Mena and Parke (2004), which provides a graphical representation of the neutrino flavor content of each of the neutrino mass eigenstates given the current preferred values of the oscillation parameters de Salas et al. (2018), see section 2. At present, even if the current preferred value of δ_CP for both normal and inverted mass orderings lies close to 3π/2 de Salas et al. (2018), the precise value of the CP violating phase in the leptonic sector remains unknown. Consequently, in Figure 1, we have varied δ_CP within its entire range, ranging from 0 to 2π.

FIGURE 1

Figure 1. Probability of finding the α neutrino flavor in the i-th neutrino mass eigenstate as the CP-violating phase, δ_CP, is varied. Inspired by Mena and Parke (2004).

Given the two known mass splittings that oscillation experiments provide us, we are sure that at least two neutrinos have a mass above $\sqrt{\Delta m_{21}^2}\simeq 8$ meV and that at least one of these two neutrinos has a mass larger than $\sqrt{\left|\Delta m_{31}^2\right|}\simeq 50$ meV. For the same reason, we also know that there exists a lower bound on the sum of the three active neutrino masses (∑m_ν = m₁+m₂+m₃):

$\begin{array}{cc}\begin{array}{l}{{\displaystyle \sum m}}_{\nu }^{\text{NO}}=m_1+\sqrt{m_1^2+\Delta m_{21}^2}+\sqrt{m_1^2+\Delta m_{31}^2},\\ {{\displaystyle \sum m}}_{\nu }^{\text{IO}}=m_3+\sqrt{m_3^2+\left|\Delta m_{31}^2\right|}+\sqrt{m_3^2+\left|\Delta m_{31}^2\right|+\Delta m_{21}^2},\end{array}& (1)\end{array}$

where the lightest neutrino mass eigenstate corresponds to m₁ (m₃) in the normal (inverted) ordering. Using the best-fit values for the neutrino mass splittings in Table 1 one finds that ∑m_ν ≳ 0.06 eV in normal ordering, while ∑m_ν ≳ 0.10 eV in inverted ordering. Figure 2 illustrates the values of ∑m_ν as a function of the lightest neutrino mass for the two possible ordering schemes. We also show the two representative bounds on the sum of the neutrino masses from cosmology (discussed later in section 4) which is currently providing the strongest limits on ∑m_ν thanks to the fact that neutrinos affect both the evolution of the cosmological background and perturbation quantities (see e.g., the excellent detailed reviews of Lesgourgues and Pastor, 2006, 2012, 2014; Lesgourgues et al., 2013; Lattanzi and Gerbino, 2018).

TABLE 1

Table 1. Neutrino oscillation parameters summary determined from the global analysis.

FIGURE 2

Figure 2. The sum of the neutrino masses ∑m_ν as a function of the mass of the lightest neutrino, m₁ (m₃) for the normal (inverted) ordering, in red (blue) respectively. The (indistinguishable) width of the lines represents the present 3σ uncertainties in the neutrino mass splittings from the global fit to neutrino oscillation data (de Salas et al., 2018). The horizontal bands illustrate two distinct 95% Confidence Level (CL) limits on ∑m_ν from cosmology, see the text for details.

The state-of-knowledge of cosmological observations Ade et al. (2016b) points to a flat Universe whose mass-energy density includes 5% of ordinary matter (baryons), 22% non-baryonic dark matter, and that is dominated by the dark energy, identified as the motor for the accelerated expansion. This is the so-called ΛCDM Universe, which fits extremely well the Cosmic Microwave Background (CMB) fluctuations, distant Supernovae Ia and galaxy clustering data.

Using the known neutrino oscillation parameters and the standard cosmological evolution, it is possible to compute the thermalization and the decoupling of neutrinos in the early universe (see e.g., Mangano et al., 2005; de Salas and Pastor, 2016). While neutrinos decoupled as ultra-relativistic particles, currently at least two out of the three neutrino mass eigenstates are non-relativistic. Neutrinos constitute the first and only known form of dark matter so far. Indeed, neutrinos behave as hot dark matter particles, possessing large thermal velocities, clustering only at scales below their free streaming scale, modifying the evolution of matter overdensities and suppressing structure formation at small scales. The CMB is also affected by the presence of massive neutrinos, as these particles may turn non-relativistic around the decoupling period. However, the strong degeneracy between the Hubble constant and the total neutrino mass requires additional constraints (from Baryon Acoustic Oscillations, Supernovae Ia luminosity distance data and/or direct measurements of the Hubble constant) to be added in the global analyses. In this regard, CMB lensing is also helpful and improves the CMB temperature and polarization constraints, as the presence of massive neutrinos modify the matter distribution along the line of sight through their free streaming nature, reducing clustering and, consequently, CMB lensing. The most constraining cosmological upper bounds to date on ∑m_ν can be obtained combining CMB with different large scale structure observations and range from ∑m_ν < 0.12 eV to ∑m_ν < 0.15 eV at 95% CL (Palanque-Delabrouille et al., 2015; Cuesta et al., 2016; Di Valentino et al., 2016c; Giusarma et al., 2016; Vagnozzi et al., 2017, 2018; Lattanzi and Gerbino, 2018), as illustrated in Figure 2.

If the massive neutrino spectrum does not lie in the degenerate region, the three distinct neutrino masses affect the cosmological observables in a different way. For instance, the transition to the non-relativistic period takes place at different cosmic times, and the associated free-streaming scale is different for each of the neutrino mass eigenstates. However, the effect on the power spectrum is very small (permille level) and therefore an extraction of the neutrino mass hierarchy via singling out each of the massive neutrino states seems a very futuristic challenge. This will be possibly attainable only via huge effective volume surveys, as those tracing the 21 cm spin-flip transition in neutral hydrogen, see sections 6.4 and 6.5. On the other hand, should the cosmological measurements of ∑m_ν be strong enough to rule out the ∑m_ν parameter space corresponding to the inverted ordering (i.e., strong enough to establish in a very significant way that ∑m_ν < 0.1 eV), we would know that the neutrino mass ordering must be normal. A word of caution is needed here when dealing with Bayesian analyses, usually performed when dealing with cosmological data: a detection of the neutrino mass ordering could be driven by volume effects in the marginalization, and therefore the prior choice can make a huge difference, if data are not powerful enough (Schwetz et al., 2017).

Another way to probe the neutrino mass ordering, apart from direct determinations of the sign of the atmospheric mass splitting $\Delta m_{31}^2$ in neutrino oscillation experiments and, indirectly, from cosmological bounds on the sum of the neutrino masses, is neutrinoless double β decay (Rodejohann, 2011; Gomez-Cadenas et al., 2012; Vergados et al., 2012; Dell'Oro et al., 2016). This process is a spontaneous nuclear transition in which the charge of two isobaric nuclei would change by two units with the simultaneous emission of two electrons and without the emission of neutrinos. This process is only possible if the neutrino is a Majorana particle and an experimental signal of the existence of this process would constitute evidence of the putative Majorana neutrino character. The non-observation of the process provides bounds on the so-called effective Majorana mass m_ββ, which is a combination of the (Majorana) neutrino masses weighted by the leptonic flavor mixing effects (see section 3). Figure 3 illustrates the (Bayesian) 95.5% and 99.7% credible intervals for m_ββ as a function of the lightest neutrino mass in the case of three neutrino mixing, considering a logarithmic prior on the lightest neutrino mass. The picture differs from the plot that is usually shown, which features an open band toward increasingly smaller values of m_ββ for m_lightest≃5 meV, due to cancellations which depend on the values of the Majorana phases α_i (see section 3). In the Bayesian sense of credible intervals, the values of α_i which produce such a suppression of m_ββ represent an extremely small fraction of the parameter space, which is therefore not relevant when computing the 95.5% and 99.7% credible intervals. In other words, given our knowledge of the neutrino mixing parameters, having $m_{\beta \beta }\lesssim 2\times 10^{-4}$ eV would require some amount of fine tuning in the Majorana phases. This figure is in perfect agreement with the results shown in Figure 1 of Agostini et al. (2017a), which shows that most of the allowed parameter space is not concentrated at small m_ββ if one considers a linear prior on the lightest neutrino mass. We also show the most conservative version of some of the most competitive current limits, as those from KamLAND-Zen (m_ββ < 61− 165 meV at 90% CL) Gando et al. (2016), GERDA Phase II (m_ββ < 120− 260 meV at 90% CL) Agostini et al. (2018) and CUORE (m_ββ < 110− 520 meV at 90% CL) Alduino et al. (2018a). Please note that a detection of the effective Majorana mass will not be sufficient to determine the mass ordering if the lightest neutrino mass is above ~40 meV: in this case, indeed, the normal and the inverted ordering become indistinguishable from the point of view of neutrinoless double beta decay. Similarly to the case of the cosmological bounds on the neutrino mass ∑m_ν, in which only constraining ∑m_ν to be below 0.1 eV could be used to disfavor the inverted mass ordering, only a limit on m_ββ below ~10 meV could be used to rule out the inverted ordering scheme, and only assuming that neutrinos are Majorana particles.

FIGURE 3

Figure 3. 95.5 and 99.7% Bayesian credible intervals for the effective Majorana mass, m_ββ, as a function of the lightest neutrino mass (Left) or of the sum of the neutrino masses ∑m_ν (Right), taking into account the current uncertainties on the neutrino mixing parameters (angles and phases), when three neutrinos are considered. The horizontal bands indicate the most conservative version (obtained by each collaboration when assuming a disfavorable value for the nuclear matrix element of the process) of some of the most competitive upper bounds, as those reported by KamLAND-Zen Gando et al. (2016), GERDA Phase II Agostini et al. (2018) and CUORE Alduino et al. (2018a). The vertical band in the Right indicates the strongest limit reported by Planck Aghanim et al. (2016b), using the Planck TT,TE,EE + SimLow + lensing data combination.

Since neutrino oscillation measurements, cosmological observations and neutrinoless double beta decay experiments are cornering the inverted mass ordering region, it makes sense to combine their present results. Indeed, plenty of works have been recently devoted to test whether a preference for one mass ordering over the other exists, given current oscillation, neutrinoless double beta decay and cosmological data. A number of studies on the subject (Hannestad and Schwetz, 2016; Caldwell et al., 2017; Capozzi et al., 2017; Gerbino et al., 2017b; Wang and Xia, 2018) found that the preference for the normal vs. the inverted mass scenario is rather mild with current data, regardless the frequentist vs. Bayesian approach. In the latter case, however, the results may be subject-dependent, as a consequence of different possible choices of priors and parameterizations when describing the theoretical model, for example in the case of sampling over the three individual neutrino mass states. Therefore, one must be careful when playing with different priors, as recently shown in Gariazzo et al. (2018a). The current status of the preference of normal vs. inverted ordering will be further investigated carefully throughout this review. Furthermore, as it will be carefully detailed in section 5, the Bayesian global fit to the 2018 publicly available oscillation and cosmological data points to a strong preference (3.5 standard deviations) for the normal neutrino mass ordering vs. the inverted one.

To summarize and conclude this introductory part, we resume that the current available methods to determine the neutrino mass ordering can be grouped as:

i) neutrino oscillation facilities;

ii) neutrinoless double beta decay experiments, with the caveat that the results will only apply in case neutrinos are Majorana fermions;

iii) CMB and large scale structure surveys.

For each of these three categories we will review the current status and also analyse the future prospects, with a particular focus on the existing experiments which will be improved in the future and on new facilities which aim at determining the neutrino mass ordering in the next 22 years⁷ In the second part of this review we will also focus on possible novel methods that in the future will enable us to determine the neutrino mass ordering, as for example future cosmological observations of the 21 cm line, the detection of neutrinos emitted by core-collapse supernovae, measurements of the electron spectrum of β-decaying nuclei and the direct detection of relic neutrinos.

We shall exploit the complementarity of both cosmology and particle physics approaches, profiting from the highly multidisciplinary character of the topic. We dedicate sections 2, 3, and 4 to explain the extraction of the neutrino mass ordering via neutrino oscillations, β and neutrinoless double β decays and cosmological observations, which will be combined in section 5 where we present the analysis of current data related to these three data sets. Future perspectives are described throughout section 6 and its subsections, while the final remarks will be outlined in section 7.

2. Neutrino Oscillations

Our current knowledge on the neutrino mass ordering comes mainly from the analysis of the available neutrino oscillation data. The sensitivity to the neutrino mass spectrum at oscillation experiments is mostly due to the presence of matter effects in the neutrino propagation. Therefore, one can expect that this sensitivity will increase with the size of matter effects, being larger for atmospheric neutrino experiments, where a fraction of neutrinos travel through the Earth. For long-baseline accelerator experiments, matter effects will increase with the baseline, while these effects will be negligible at short-baseline and medium-baseline experiments.

When neutrinos travel through the Earth, the effective matter potential due to the electron (anti)neutrino charged-current elastic scatterings with the electrons in the medium will modify the three-flavor mixing processes. The effect will strongly depend on the neutrino mass ordering: in the normal (inverted) mass ordering scenario, the neutrino flavor transition probabilities will get enhanced (suppressed). In the case of antineutrino propagation, instead, the flavor transition probabilities will get suppressed (enhanced) in the normal (inverted) mass ordering scenario. This is the Wolfenstein effect (Wolfenstein, 1978), later expanded by Mikheev and Smirnov 1985, Mikheev and Smirnov (1986), and commonly named as the Mikheev-Smirnov-Wolfenstein (MSW) effect (see e.g., Blennow and Smirnov, 2013 for a detailed description of neutrino oscillations in matter).

Matter effects in long-baseline accelerator or atmospheric neutrino oscillation experiments depend on the size of the effective mixing angle θ₁₃ in matter, which leads the transitions ν_e ↔ ν_{μ, τ} governed by the atmospheric mass-squared difference ${\Delta }_{31}=\Delta m_{31}^2/2E$. Within the simple two-flavor mixing framework, the effective θ₁₃ angle in matter reads as

$\begin{array}{cc}\begin{array}{r}{sin}^{2}2{\theta }_{13}^{\mathrm{\text{m}}}=\frac{{sin}^{2}2{\theta }_{13}}{{sin}^{2}2{\theta }_{13}+{\left(cos2{\theta }_{13}\mp \frac{\sqrt{2}{G}_F{N}_e}{{\Delta }_{31}}\right)}^2},\end{array}& (2)\end{array}$

where the minus (plus) sign refers to neutrinos (antineutrinos) and N_e is the electron number density in the Earth interior. The neutrino mass ordering fixes the sign of Δ₃₁, that is positive (negative) for normal (inverted) ordering: notice that, in the presence of matter effects, the neutrino (antineutrino) oscillation probability P(ν_μ → ν_e) [$P({\bar{\nu }}_{\mu }\to {\bar{\nu }}_e)$] gets enhanced if the ordering is normal (inverted). Exploiting the different matter effects for neutrinos and antineutrinos provides therefore the ideal tool to unravel the mass ordering.

Matter effects are expected to be particularly relevant when the following resonance condition is satisfied:

$\begin{array}{cc}\begin{array}{r}\Delta m_{31}^{2}cos2{\theta }_{13}=2\sqrt{2}{G}_F{N}_{e}E.\end{array}& (3)\end{array}$

The precise location of the resonance will depend on both the neutrino path and the neutrino energy. For instance, for $\Delta m_{31}^2~2.5\times 10^{-3}$ eV² and distances of several thousand kilometers, as it is the case of atmospheric neutrinos, the resonance effect is expected to happen for neutrino energies ~3−8 GeV.

In the case of muon disappearance experiments, in the ~ GeV energy range relevant for long-baseline and atmospheric neutrino beams, the P_μμ survival probabilities are suppressed (enhanced) due to matter effects if the ordering is normal (inverted). If the matter density is constant, the P_μμ survival probability at terrestrial baselines⁸ is given by

$\begin{array}{cc}\begin{array}{l}{P}_{\mu \mu }=1-{\cos }^2{\theta }_{13}^{\text{m}}{\sin }^{2}2{\theta }_{23}\times {\sin }^2\left[1.27\left(\frac{\Delta m_{31}^2+A+{(\Delta m_{31}^2)}^{\text{m}}}{2}\right)\frac{L}{E}\right]\\ -{\sin }^2{\theta }_{13}^{\text{m}}{\sin }^{2}2{\theta }_{23}\times {\sin }^2\left[1.27\left(\frac{\Delta m_{31}^2+A-{(\Delta m_{31}^2)}^{\text{m}}}{2}\right)\frac{L}{E}\right]\\ -{\sin }^4{\theta }_{23}{\sin }^{2}2{\theta }_{13}^{\text{m}}{\sin }^2\left[1.27{(\Delta m_{31}^2)}^{\text{m}}\frac{L}{E}\right],\end{array}& (4)\end{array}$

where $A=2\sqrt{2}{G}_F{N}_{e}E$, ${\theta }_{13}^{\mathrm{\text{m}}}$ is that of Equation (2) and

$\begin{array}{cc}\begin{array}{r}{(\Delta m_{31}^2)}^{\mathrm{\text{m}}}=\Delta m_{31}^2\sqrt{{sin}^{2}2{\theta }_{13}+{\left(cos2{\theta }_{13}\mp \frac{2\sqrt{2}{G}_F{N}_{e}E}{\Delta m_{31}^2}\right)}^2}.\end{array}& (5)\end{array}$

The dependence of the survival probability P_μμ on the neutrino energy E and the cosine of the zenith angle cosθ_z, related to the distance the atmospheric neutrinos travel inside the Earth before being detected at the experiments, is shown in Figure 4 for normal (Left) and inverted (Right) ordering. There, we can see that reconstructing the oscillation pattern at different distances and energies allows to determine the neutrino mass ordering (see also section 6.1).

FIGURE 4

Figure 4. Survival probability P_μμ, as a function of the neutrino energy E and the cosine of the zenith angle cosθ_z, for normal (inverted) ordering in the (Left, Right).

Until very recently, oscillation experiments were not showing a particular preference for any of the mass orderings, not even when combined in a global analysis (see for instance Forero et al., 2014). Lately, however, the most recent data releases from some of the experiments have become more sensitive to the ordering of the neutrino mass spectrum. In particular, the long-baseline experiments T2K and NOνA on their own obtain a slight preference in favor of normal mass ordering, with Δχ² ≈ 4 each (Hartz, 2017; Radovic, 2018). Note that these results have been obtained imposing a prior on the mixing angle θ₁₃, according to its most recent determination at reactor experiments. Relaxing the prior on the reactor angle results in a milder preference for normal over inverted mass ordering. The latest atmospheric neutrino results from Super-Kamiokande also show some sensitivity to the neutrino mass ordering. In this case, the collaboration obtains a preference for normal ordering with Δχ² ≈ 3.5, without any prior on the reactor angle. Constraining the value of θ₁₃, the preference for normal mass ordering increases up to Δχ² ≈ 4.5 Abe et al. (2018a).

The full sensitivity to the ordering of the neutrino mass spectrum from oscillations is obtained after combining the data samples described above with all the available experimental results in a global fit (de Salas et al., 2018). This type of analysis exploits the complementarity among the different results as well as the correlations among the oscillation parameters to obtain improved sensitivities on them. In the global analysis to neutrino oscillations, the parameters ${sin}^2{\theta }_{12}$ and $\Delta m_{21}^2$ are rather well measured by the solar experiments (Cleveland et al., 1998; Hosaka et al., 2006; Aharmim et al., 2008, 2010; Cravens et al., 2008; Abdurashitov et al., 2009; Kaether et al., 2010; Abe et al., 2011b; Bellini et al., 2014; Nakano, 2016) and the long-baseline reactor experiment KamLAND Gando et al. (2011). The short-baseline reactor neutrino experiments Daya Bay An et al. (2017), RENO Pac (2018) and Double Chooz Abe et al. (2014) are the most efficient ones in measuring the reactor angle θ₁₃ and also measure very well the atmospheric mass splitting, $\Delta m_{31}^2$. Notice however that the atmospheric mass splitting is best measured by the combined data from MINOS (beam and atmospheric) and MINOS+, as shown in Adam (2018). This mass splitting is also measured, together with the atmospheric angle θ₂₃, by the atmospheric experiments IceCube-DeepCore Aartsen et al. (2015), ANTARES Adrian-Martinez et al. (2012) and Super-Kamiokande Abe et al. (2018a), where the latter shows some sensitivity to θ₁₃ and δ_CP, too. The long-baseline accelerator experiments are also sensitive to these four parameters through their appearance and disappearance neutrino channels. Apart from the already mentioned T2K Hartz (2017) and NOνA Radovic (2018), the global fit also includes the previous experiments K2K Ahn et al. (2006) and MINOS Adamson et al. (2014).

The result of the global analysis is summarized in Table 1 and Figure 5. Before discussing the sensitivity to the neutrino mass ordering, we shall briefly discuss some other features of this global fit. Notice first that now the best-fit value for the atmospheric mixing angle θ₂₃ lies in the second octant, although values in the first octant are still allowed with Δχ² = 1.6 (3.2) for normal (inverted) ordering. Therefore, the octant problem remains unsolved so far. Note also that, for the first time, the CP violating phase δ_CP is determined with rather good accuracy. The best-fit values for this parameter lie close to maximal CP violation, being δ_CP = 1.32π for normal ordering and δ_CP = 1.56π for inverted ordering. As can be seen from the Δχ² profile in Figure 5, values around δ_CP≈0.5π are now highly disfavored by data. Indeed, only around 50% of the parameter space remains allowed at the 3σ level, roughly the interval [0.9π, 1.9π] for normal and [1.1π, 1.9π] for inverted ordering. In the case of normal ordering, CP conservation remains allowed at 2σ, while it is slightly more disfavored for inverted ordering. For the remaining oscillation parameters, one clearly sees that neutrino oscillations are entering the precision era, with relative uncertainties on their determination of 5% or below. For a more detailed discussion about these parameters we refer the reader to de Salas et al. (2018) and¹.

FIGURE 5

Figure 5. Summary of neutrino oscillation parameters, 2018. Red (blue) lines correspond to normal ordering (inverted ordering). Notice that the Δχ² profiles for inverted ordering are plotted with respect to the minimum for normal neutrino mass ordering.

Concerning the neutrino mass ordering, we obtain a global preference of 3.4σ (Δχ² = 11.7) in favor of normal ordering. This result emerges from the combination of all the neutrino oscillation experiments, as we explain in the following. Starting with long-baseline data alone, the inverted mass ordering is disfavored with Δχ² = 2.0, when no prior is considered on the value of θ₁₃. However, as explained above, the separate analysis of the latest T2K and NOνA data independently report a Δχ²≈4 among the two possible mass orderings when a prior on the reactor angle is imposed. This comes from the mismatch between the value of θ₁₃ preferred by short-baseline reactor and long-baseline accelerator experiments, which is more important for inverted ordering. Besides that, the combination of T2K and reactor data results in an additional tension relative to the preferred value of the atmospheric mass splitting $\Delta m_{31}^2$, which is again larger for the inverted mass ordering. This further discrepancy results in a preference for normal ordering with Δχ² = 5.3 for the combination of “T2K plus reactors” and Δχ² = 3.7 for the combination of “NOνA plus reactors”. From the combined analysis of all long-baseline accelerator and short-baseline reactor data one obtains a Δχ² = 7.5 between normal and inverted ordering, which corresponds to a preference of 2.7σ in favor of normal mass ordering. By adding the atmospheric data to the neutrino oscillations fit, we finally obtain Δχ² = 11.7⁹, indicating a global preference for normal ordering at the level of 3.4σ.

3. Mass Ordering and Decay Experiments

3.1. Mass Ordering Through β-Decay Experiments

The most reliable method to determine the absolute neutrino masses in a completely model independent way is to measure the spectrum of β-decay near the endpoint of the electron spectrum. The reason for this is related to the fact that, if neutrinos are massive, part of the released energy must go into the neutrino mass and the electron spectrum endpoint shifts to lower energies. When there are more than one massive neutrino, each of the separate mass eigenstates contributes to the suppression of the electron energy spectrum and it becomes possible to study the pattern of the neutrino masses. Nowadays none of the β-decay experiments can reach the energy resolution required to be able to determine the mass hierarchy¹⁰, but we will explain in the following how, in principle, future experiments may aim at such result.

The best way to depict the effects of the separate mass eigenstates is to compute the Kurie function for β-decay. The complete expression can be written as (see e.g., Giunti and Kim, 2007):

$\begin{array}{cc}\begin{array}{r}K(T)={\left[(Q_{\beta }-T){\displaystyle \sum _{i=1}^N}|U_{ei}{|}^2\sqrt{{(Q_{\beta }-T)}^2-m_i^2}\text{Θ}(Q_{\beta }-T-m_i)\right]}^{1/2},\end{array}& (6)\end{array}$

where Q_β is the Q-value of the considered β-decay, T is the electron kinetic energy, Θ is the Heaviside step function and $|U_{ei}{|}^2$ is the mixing matrix element that defines the mixing between the electron neutrino flavor and the i-th mass eigenstate with a mass m_i. The standard scenario features N = 3, but the formula is valid also if a larger number of neutrinos exists (i.e., if there are sterile neutrinos, as explained for example in Gariazzo et al., 2016).

The Kurie function of Equation (6) is depicted in Figure 6, where we show in red (blue) the result obtained using a massless lightest neutrino and the current best-fit mixing angles and mass splittings for normal (inverted) ordering, as described in the previous section. As a reference, we also plot K(T) for a case with massless neutrinos only (in black). Should we consider higher values for the lightest neutrino mass, the detection of the mass ordering would be increasingly more difficult, since the separation of the mass eigenstates would decrease, eventually becoming negligible in the degenerate case. For this reason we will only discuss the case of a massless lightest neutrino from the perspective of the β-decay experiments.

FIGURE 6

Figure 6. Kurie function in β-decays. The red (blue) line indicates the normal (inverted) ordering case for a massless lightest neutrino, while the black line is for the case of three massless neutrinos. The green curve shows how the Kurie function of a normal ordering scenario with $m_{\text{lightest}}\simeq \sqrt{\Delta m_{31}^2}$ can mimic the inverted ordering case.

Given the unitarity of the mixing matrix ($\sum _{i=1}^N|U_{ei}{|}^2=1$), the normalization of the Kurie function is the same at Q_β − T ≫ m_i. Since we are interested in the small differences which appear near the endpoint, the plot only focuses on the very end of the electron spectrum and the common normalization is not visible for the inverted ordering case. In the considered range, however, the effect of the different correspondence between the mass eigenstates and the mixing matrix elements introduces a difference which in principle would allow to determine the mass ordering through the observation of the β-decay spectrum. The observation of the kinks in the electron spectrum is very challenging, especially in the case of normal ordering, for which even the more pronounced kink (at $Q_{\beta }-T\simeq \sqrt{\Delta m_{21}^2}\simeq 8$ meV) is barely visible in Figure 6. In the case of inverted ordering, since the mass difference between the two lightest mass eigenstates is the largest possible one ($\sqrt{\Delta m_{31}^2}\simeq 50$ meV), and the lightest neutrino is the one with the smallest mixing with the electron neutrino, the amplitude of the kink is much larger. As a consequence, an experiment with enough energy resolution to measure the spectrum in the relevant energy range can directly probe the mass ordering observing the presence of a kink. Note that this measurement can be obtained even without a detection of the lightest neutrino mass. As we show in Figure 6, however, it is crucial to have a non-zero observation of the electron spectrum between Q_β and $Q_{\beta }-\sqrt{\Delta m_{31}^2}$, otherwise one could confuse the inverted ordering spectrum with a normal ordering spectrum obtained with a larger lightest neutrino mass $m_{\text{lightest}}\simeq \sqrt{\Delta m_{31}^2}$ (green curve).

Another consideration is due. One could think to probe the neutrino mass ordering just using the fact that the expected number of events is smaller in the inverted ordering than in the normal ordering case. As we discussed above, this could be possible only if some independent experiment would be able to determine the mass of the lightest neutrino, in order to break the possible degeneracy between m_lightest and the mass ordering depicted by the blue and green curves in Figure 6, otherwise the conditions required to observe the electron spectrum between Q_β and $Q_{\beta }-\sqrt{\Delta m_{31}^2}$ would be probably sufficient to guarantee a direct observation or exclusion of the kink. The best way to determine the neutrino mass ordering, however, may be to use an estimator which compares the binned spectra in the normal and inverted ordering cases, as proposed for example in Stanco et al. (2017) in the context of reactor neutrino experiments. The authors of the study, indeed, find that a dedicated estimator can enhance the detection significance with respect to a standard χ² comparison.

To conclude, today the status of β-decay experiments is far from the level of determining the mass ordering, since the energy resolution achieved in past and current measurements is not sufficient to guarantee a precise probe of the interesting part of the spectrum. KATRIN, for example, aims at a sensitivity of 0.2 eV on the effective electron neutrino mass (Angrik et al., 2004; Sejersen Riis et al., 2011), only sufficient to probe the fully degenerate region of the neutrino mass spectrum.

3.2. Mass Ordering From Neutrinoless Double Beta Decay

In the second part of this section we shall discuss instead the perspectives from the neutrinoless double beta decay (see e.g., the reviews Gomez-Cadenas et al., 2012; Dell'Oro et al., 2016 and also Pascoli and Petcov (2002)), a process allowed only if neutrinos are Majorana particles (Schechter and Valle, 1982), since it requires the lepton number to be violated by two units. Neutrinoless double beta decay experiments therefore aim at measuring the life time $T_{1/2}^{0\nu }$ of the decay, which can be written as:

$\begin{array}{cc}\begin{array}{r}\frac{1}{T_{1/2}^{0\nu }({N})}=G_{0\nu }^{{N}}|{{M}}_{{N}}^{0\nu }{|}^2{(\frac{|m_{\beta \beta }|}{m_e})}^2,\end{array}& (7)\end{array}$

where m_e is the electron mass, $G_{0\nu }^{{N}}$ is the phase space factor, ${{M}}_{{N}}^{0\nu }$ is the nuclear matrix element (NME) of the neutrinoless double beta decay process, ${N}$ indicates the chemical element which is adopted to build the experiment and m_ββ is the effective Majorana mass, see below. In case no events are observed, a lower bound on $T_{1/2}^{0\nu }$ can be derived. Recent constraints on the neutrinoless double beta decay half-life come from the EXO-200 Albert et al. (2014), KamLAND-Zen Gando et al. (2016), CUORE Alduino et al. (2018a), Majorana Aalseth et al. (2018), CUPID-0 Azzolini et al. (2018), Gerda Agostini et al. (2018), and NEMO-3 Arnold et al. (2018) experiments. The strongest bounds to date on the half-life of the different isotopes are: $T_{1/2}^{0v}{(}^{76}\text{Ge})>8.0\times {10}^{25}$ year from Gerda Agostini et al. (2018), $T_{1/2}^{0v}{(}^{82}\text{Se})>2.4\times {10}^{24}$ year from CUPID-0 Azzolini et al. (2018), $T_{1/2}^{0v}{(}^{130}\text{Te})>1.5\times {10}^{25}$ year from CUORE Alduino et al. (2018a) and $T_{1/2}^{0v}{(}^{136}\text{Xe})>1.07\times {10}^{27}$ year from KamLAND-Zen, Gando et al. (2016).

The effective Majorana mass reads as:

$\begin{array}{cc}\begin{array}{r}{m}_{\beta \beta }={\displaystyle \sum _{k=1}^N}{e}^{i{\alpha }_k}|U_{ek}{|}^2{m}_k,\end{array}& (8)\end{array}$

where N is the number of neutrino mass eigenstates, each with its mass m_k, α_k are the Majorana phases (one of which can be rotated away, so that there are N−1 independent phases), and U_ek represents the mixing between the electron flavor neutrino and the k-th mass eigenstate. Notice that the conversion between the half-life of the process and the effective Majorana mass depends on the NMEs (see e.g., Vergados et al., 2016; Engel and Menéndez, 2017), which are typically difficult to compute. Several methods can be employed and there is no full agreement between the results obtained with the different methods. As a consequence, the quoted limits on $T_{1/2}^{0\nu }$ can be translated into limits on m_ββ which depend on the NMEs. If the most conservative values for the NMEs are considered, none of the current constraints reaches the level required to start constraining the inverted ordering in the framework of three neutrinos, see Figure 3.

If we compute m_ββ as a function of the lightest neutrino mass with the current preferred values of the mixing parameters and in the context of three neutrinos, we discover that the value of m_ββ depends on the mass ordering only for m_lightest ≲ 40 meV, see Figure 3. For this reason, neutrinoless double beta experiments can aim to distinguish the mass ordering only for the smallest values of the lightest neutrino mass. Please note that this also means that if the lightest neutrino has a mass above ~40 meV, perfectly allowed by all the present constraints on the neutrino mass scale, the two mass orderings will never be distinguished in the context of neutrinoless double beta decay experiments.

When going to smaller m_lightest, the situation changes, as m_ββ becomes independent of m_lightest. In the region m_lightest≲10 meV, a difference between the two mass orderings appears, since the effective Majorana mass is constrained by the mass splittings to be larger than ~ 10 meV for inverted ordering, while it must be below ~ 7 meV for normal ordering. This means that experiments which can test the region m_ββ < 10 meV can rule out the inverted scenario. Note that a positive detection of $T_{1/2}^{0\nu }$ in the range that corresponds to m_ββ ≳ 10 meV, on the other hand, would not give sufficient information to determine the mass ordering without an independent determination of m_lightest. To resume, in the context of three neutrino mixing, neutrinoless double beta decay experiments alone will be able to determine the neutrino mass ordering only ruling out the inverted scheme, that is to say if the ordering is normal and m_lightest ≲ 10 meV.

In any case, we should remember that if no neutrinoless double beta decay candidate event will ever be observed we will not have determined the mass ordering univocally: Dirac neutrinos escape the constraints from this kind of process, so that it would be still perfectly allowed to have an inverted ordering scheme and no Majorana fermions in the neutrino sector. Due to the presence of the Majorana phases in Equation (8), unfortunately, there is a small window for m_lightest in normal ordering that can correspond to almost vanishing values of m_ββ, which will possibly never be observable. As we show in Figure 3, however, the region of parameter space where this happens has a very small volume if one considers the phases to vary between 0 and 2π, so that the credible region for m_ββ in a Bayesian context shows that it is rather unlikely to have $m_{\beta \beta }\lesssim 2\times 10^{-4}$ eV, as a significant amount of fine tuning would be needed in the (completely unknown) Majorana phases. Our statement, which arises from assuming a logarithmic prior on m_lightest, is in perfect agreement with the results of Agostini et al. (2017a), where a linear prior on m_lightest is assumed.

Please note that the situation depicted in Figure 3 is only valid if there are only three neutrinos. If, as the current DANSS Alekseev et al. (2018) and NEOS Ko et al. (2017) experiments may suggest, a sterile neutrino with a mass around 1 eV exists (see e.g., Dentler et al., 2017, 2018; Gariazzo et al., 2017, 2018b), the situation would be significantly different. The allowed bands for m_ββ as a function of the lightest neutrino mass when a light sterile neutrino is introduced are reported for example in Giunti and Zavanin (2015) (see also Gariazzo et al., 2016). In this three active plus one sterile neutrino case (3+1), the contribution of the fourth neutrino mass eigenstate (mainly mixed with the sterile flavor) must be added in Equation (8), with the consequence that the allowed bands are located at higher m_ββ. In Figure 7, adapted from Giunti (2017), we reproduce the dependence of the effective Majorana mass on the lightest neutrino mass when one assumes the 3+1 neutrino scenario, compared with the standard three neutrino case. As we can see, with the introduction of an extra sterile neutrino state, m_ββ is significantly increased for the normal ordering case, reaching the level of the inverted ordering bands, which are less shifted toward higher values of m_ββ. Furthermore, in the 3+1 scenario, also in the inverted ordering case it is possible to have accidental cancellations due to the three independent Majorana phases in Equation (8) (see the detailed discussion of Giunti and Zavanin, 2015), so that a non-detection of the neutrinoless double beta decay process would never be sufficient to rule out the inverted ordering. The opposite situation may occur in case the lightest neutrino mass will be independently constrained to be below ~ 10 meV while m_ββ ≲ 10 meV: in this case, however, we would rule out normal ordering. Consequently, if a light sterile neutrino exists, neutrinoless double beta experiments will never be able to determine the mass ordering if the mass ordering is normal, while some possibility remains if the ordering of the three active neutrino masses is inverted, provided that the lightest neutrino is very light and the Majorana phases are tuned enough. The KamLAND-Zen, Gerda, and CUORE experiments, using three different materials, may very soon start probing the inverted ordering region in the case of 3+1 neutrino mixing for all the possible values of the NMEs, see Figure 7, where the current KamLAND-Zen Gando et al. (2016) constraints are reported.

FIGURE 7

Figure 7. Effective Majorana mass as a function of the lightest neutrino mass in the three neutrino (Left) and 3+1 neutrino (Right) scenarios, at 99.7% CL, comparing normal (red) and inverted (blue) ordering of the three active neutrinos. Adapted from Giunti (2017). The green band represents the 90% CL bounds from KamLAND-Zen Gando et al. (2016), given the uncertainty on the NME.

To conclude and summarize the current status: neutrinoless double beta decay cannot yet provide constraints on the neutrino mass ordering. Depending on the lightest neutrino mass and on the existence of a fourth (sterile) neutrino, it would be possible that not even far-future experiments could be able to reach this goal.

4. Results From Cosmology

Massive neutrinos affect the cosmological observables in different ways, that we shall summarize in what follows. For a comprehensive review of the effects of neutrino masses in cosmology, we refer the reader to the recent work presented in Lattanzi and Gerbino (2018).

A very important epoch when discussing the impact of massive neutrinos in the cosmological expansion history and in the perturbation evolution is the redshift at which neutrinos become non-relativistic. This redshift is given by

$\begin{array}{cc}\begin{array}{r}1+z_{\mathrm{\text{nr}},i}\simeq 1890(\frac{m_i}{1\mathrm{\text{eV}}}),\end{array}& (9)\end{array}$

with m_i referring to the mass of each massive neutrino eigenstate. Current bounds on neutrino masses imply that at least two out of the three massive eigenstates became non-relativistic in the matter dominated period of the universe. As stated in the introductory section, and as we shall further illustrate along this section, cosmological measurements are currently unable to extract individually the masses of the neutrino eigenstates and the ordering of their mass spectrum and, therefore, concerning current cosmological data, all the limits on the neutrino mass ordering will come from the sensitivity to the total neutrino mass ∑m_ν. Consequently, in what follows, we shall mainly concentrate on the effects on the cosmological observables of ∑m_ν, providing additional insights on the sensitivity to the ordering of the individual mass eigenstates whenever relevant.

4.1. CMB

There are several imprints of neutrino masses on the CMB temperature fluctuations pattern once neutrinos become non-relativistic: a shift in the matter-radiation equality redshift or a change in the amount of non-relativistic energy density at late times, both induced by the evolution of the neutrino background, that will, respectively, affect the angular location of the acoustic peaks and the slope of the CMB tail, through the Late Integrated Sachs Wolfe (ISW) effect. The former will mostly modify Θ_s, i.e., the angular position of the CMB peaks, which is given by the ratio of the sound horizon and the angular diameter distance, both evaluated at the recombination epoch. Massive neutrinos enhance the Hubble expansion rate, with a consequent reduction of the angular diameter distance and an increase of Θ_s, which would correspond to a shift of the peaks toward larger (smaller) angular scales (multipoles). The latter, the Late ISW effect, is related to the fact that the gravitational potentials are constant in a matter-dominated universe. The inclusion of massive neutrinos will delay the dark energy dominated period and consequently reduce the time variation of the gravitational potential at late times, suppressing the photon temperature anisotropies in the multipole region 2 < ℓ < 50. A very similar effect occurs at early times through the so-called Early ISW effect, which governs the height of the first CMB peak. Light active neutrino species, indeed, reduce the time variations of the gravitational potential also around the recombination period, due to the different evolution of these potentials in radiation/matter dominated epochs, leaving a signature on the CMB photon fluctuations when they become non-relativistic. Massive neutrinos will therefore decrease the temperature anisotropies by ΔC_ℓ/C _ℓ ~(m_{ν, i}/0.1 eV)% in the multipole range 20 < ℓ < 500 (Lesgourgues and Pastor, 2012).

Unfortunately, the Late ISW effect affects the CMB spectrum in a region where cosmic variance does not allow for very accurate measurements. From what regards the other two effects, i.e., the shift in the location of the acoustic peaks and the Early ISW effect, they can both easily be compensated varying other parameters which govern the expansion of the universe. For example, within the minimal ΛCDM framework, the total amount of matter in the universe and the Hubble constant H₀ can be tuned in order to compensate the effects of massive neutrinos. Therefore, CMB primary anisotropies alone can not provide very tight bounds on the neutrino masses, due to the strong parameter degeneracies. This automatically implies that CMB measurements alone are unable to extract any information concerning the neutrino mass ordering, as shown in Figure 8, obtained by means of the publicly available Boltzmann solver Cosmic Linear Anisotropy Solving System (CLASS) (Blas et al., 2011; Lesgourgues, 2011a,b; Lesgourgues and Tram, 2014). In the figure we can notice that the difference between normal and inverted neutrino mass orderings, for ∑m_ν = 0.12 eV¹¹ is almost negligible. Moreover, the largest differences appear in the multipole range where cosmic variance dominates.

FIGURE 8

Figure 8. Relative ratio of the temperature and polarization anisotropies for the inverted over the normal mass orderings, see the text for details.

Among the secondary CMB anisotropies, i.e., those generated along the photon line of sight and not produced at recombination, there are two effects that can notably improve the sensitivity to the total neutrino mass ∑m_ν from CMB observations. One of them is CMB lensing, that is, a distortion of the photon paths because of the presence of matter inhomogeneities along the line of sight. Due to such distortion, the CMB acoustic oscillation features will be smeared out in a scale-dependent way, mostly due to matter overdensities at z ≲ 5. By measuring the non-gaussianities of CMB polarization and temperature maps it is possible to extract the power spectrum of the lensing potential. This, in turn, contains very useful information on the integrated matter distribution along the line of sight. Since massive neutrinos behave differently from a pure cold dark matter component, characterized by zero velocities, the small-scale structure suppression induced by the non-negligible neutrino dispersion velocities will decrease the CMB lensing signal expected in the absence of neutrino masses (Kaplinghat et al., 2003; Song and Knox, 2004; Lesgourgues et al., 2006; Smith et al., 2006; de Putter et al., 2009; Allison et al., 2015), leaving unchanged the power spectrum of the lensing potential at large scales, and suppressing it at small scales. Furthermore, since CMB lensing involves high redshifts, non-linearities do not enter in the calculation of the matter density field. Therefore, CMB lensing enhances the capabilities to bound the neutrino masses using CMB data. In the future, this technique may even surpass weak lensing capabilities, based on statistical analyses of the ellipticity of remote galaxies, see below and section 6.4. Indeed, nowadays, measurements from the Planck satellite constrain the neutrino masses dominantly through CMB gravitational lensing. As stated in Ade et al. (2014), increasing the neutrino mass implies an increase on the expansion rate at redshifts z ≥ 1, corresponding to a suppression of clustering at scales below the size of the horizon at the non-relativistic transition. This effect leads to a decrease in CMB lensing that, at multipoles ℓ = 1, 000, is ~10% for ∑m_ν = 0.66 eV.

On the other hand, we have the reionization process in the late universe, when the first generation of galaxies emitted ultraviolet (UV) photons that ionized the neutral hydrogen, leading to the end of the so-called dark ages. Reionization increases the number density of free electrons n_e which can scatter the CMB with a probability given by a quantity named reionization optical depth, τ, which can be computed as an integral over the line of sight of n_e. The consequence of an increase of τ on the CMB temperature fluctuations is the suppression of the acoustic peaks by a factor exp(−2τ) at scales smaller than the Hubble horizon at the reionization epoch. Even if from the point of view of CMB temperature anisotropies this effect is highly degenerate with a change in the amplitude of the primordial power spectrum A_s, which governs the overall amplitude of the CMB spectra, reionization induces linear polarization on the CMB spectrum, leading to a “reionization bump” in the polarization spectra at large scales, which otherwise would vanish. Even if the reionization signal is rather weak, as it amounts to no more than ~10% of the primary polarization signal (Aghanim et al., 2008), very accurate measurements of the reionization optical depth τ sharpen considerably the CMB neutrino mass bounds (Vagnozzi et al., 2017), as they alleviate the degeneracy between A_s and τ and consequently the existing one between ∑m_ν and A_s.

4.2. Large Scale Structure of the Universe

The largest effect of neutrino masses on the cosmological observables is imprinted in the matter power spectrum (Bond et al., 1980; Hu et al., 1998). Neutrinos are hot dark matter particles and, therefore, due to the pressure gradient, at a given redshift z, the non-relativistic neutrino overdensities can only cluster at scales for which the wavenumber of perturbations is below the neutrino free streaming scale k_fs (i.e., at scales k < k_fs), with

$\begin{array}{cc}\begin{array}{r}{k}_{f_s}(z)=\frac{0.677}{{(1+z)}^{1/2}}\left(\frac{m_{\nu }}{1\mathrm{\text{eV}}}\right)\sqrt{{\Omega }_m}h{\mathrm{\text{Mpc}}}^{-1},\end{array}& (10)\end{array}$

being Ω_m the ratio of the total matter energy density over the critical density at redshift zero. The free-streaming nature of the neutrino will be directly translated into a suppression of the growth of matter fluctuations at small scales. One could then conclude that extracting the neutrino relic masses and their ordering is a straightforward task, once that measurements of the matter power spectrum at the relevant scales are available at a different number of redshifts. The former statement is incorrect, not only because it does not consider the existence of degeneracies with the remaining cosmological parameters, but also because a number of subtleties must be taken into account, as we shall explain in what follows. The decrease of the matter power spectrum due to the total neutrino mass ∑m_ν is, in principle, currently measurable. Nonetheless, when fixing ∑m_ν, the total mass could be splitted differently among the three neutrino mass eigenstates (i.e., m₁, m₂ and m₃), modifying slightly the relativistic to non-relativistic transition. This will affect both the background evolution and the perturbation observables (Lesgourgues et al., 2004): the different free-streaming scales associated to each of the three neutrino mass eigenstates will be imprinted in the matter power spectrum. Figure 9 shows the ratios of the matter power spectrum for normal over degenerate, inverted over degenerate, and inverted over normal neutrino mass spectra for a total neutrino mass of 0.12 eV. We illustrate such ratios at different redshifts. Notice that the differences among the possible neutrino mass schemes are tiny, saturating at the 0.06% level at k>0.2h Mpc⁻¹. Therefore, only very futuristic means of measuring the matter power spectrum could be directly sensitive to the neutrino mass ordering, and, eventually, be able to isolate each of the free-streaming scales associated to each individual neutrino mass eigenstate. We shall comment on these future probes in section 6.5.

FIGURE 9

Figure 9. The Top (Middle) shows the ratios of the matter power spectrum of normal (inverted) ordering over the degenerate case. The Bottom shows the ratio of the matter power spectra for the normal and inverted mass orderings. See the text for details.

Since, at present, matter power spectrum data constrain exclusively ∑m_ν, it is only via these bounds, combined with CMB or other external data sets, that nowadays a limit on the neutrino mass ordering can be obtained, see section 4.3. Nevertheless, and as aforementioned, there are a number of problems which may interfere with a proper understanding of the scale-dependent neutrino mass suppression of clustering. The first of them is due to the fact that observations measure the spatial distributions (or their Fourier transforms, the power spectra) of galaxies, clusters, or quasars, e.g., of given tracers, mapping the large scale structure of the Universe at a number of redshifts, by measuring the growth of fluctuations at different scales. However, the matter distribution is not directly measured, i.e., it needs to be inferred from the tracers observed. A simple model of structure formation suggests that at large scales and, therefore, when the perturbation evolution is still in the linear regime, the galaxy power spectrum is related to the matter one by a constant named b, the light-to-mass bias (Desjacques et al., 2018). The galaxy bias can be determined either separately by independent methods or to be considered as an additional free parameter to be measured together with the neutrino mass ∑m_ν. This approach has been followed in many studies in the past (Cuesta et al., 2016; Giusarma et al., 2016; Vagnozzi et al., 2017). However, when dealing with neutrino masses, the relationship between the tracers and the underlying matter field may be more complicated, as neutrinos themselves may induce scale-dependent features in the bias (Castorina et al., 2014; LoVerde and Zaldarriaga, 2014; Muñ~oz and Dvorkin, 2018) due to their free-streaming nature (see also the recent work of Giusarma et al., 2018 for a new method to extract a scale-dependent bias, based on the cross-correlation of CMB lensing maps and galaxy samples).

Another additional complication when extracting the neutrino mass from clustering observations arises from to the presence of non-linearities at scales $k\gtrsim k_{\text{NL}}^0\equiv 0.1-0.2$ h Mpc⁻¹ at z = 0. The effect of neutrino masses is very-well understood on linear scales, i.e., scales below k_NL at z = 0 (or located at slightly larger values of k but at higher redshifts). Massive neutrinos induce a suppression in the linear matter power spectrum below their free streaming scale ΔP/P ∝ − 8f_ν, with f_ν the fraction of matter in the form of massive neutrinos (Hu et al., 1998). Accurate descriptions of the matter power spectrum in the non-linear regime are therefore mandatory in order to be sensitive to the full neutrino mass signature. This is particularly important in the case of galaxy surveys, in which the information depends on the number of independent modes available, and where going to smaller scales (i.e., larger values of k) has a profound impact on the sensitivity to neutrino masses. Several approaches have been followed in the literature to account for the effect of massive neutrinos in the non-linear regime, most of them relying on N-body cosmological simulations, which have been upgraded to include the effects of neutrino clustering in the evolution of the cosmological structures. Methods range from perturbative attempts (Saito et al., 2008; Brandbyge and Hannestad, 2009; Shoji and Komatsu, 2010; Ali-Haimoud and Bird, 2012; Archidiacono and Hannestad, 2016; Upadhye et al., 2016; Dakin et al., 2017; Senatore and Zaldarriaga, 2017) to the fully non-linear inclusion (Villaescusa-Navarro et al., 2014a; Inman et al., 2015; Banerjee and Dalal, 2016; Dakin et al., 2017; Banerjee et al., 2018; Liu et al., 2018) of neutrinos as an extra set of particles. A conservative alternative consists on using exclusively power spectrum measurements within the linear regime (i.e., k < 0.1 h Mpc⁻¹). Some of the cosmological constraints have also been obtained using the mildly non-linear regime (k < 0.2 h Mpc⁻¹) by means of the so-called Halofit formalism (Smith et al., 2003; Takahashi et al., 2012). The Halofit prescription models the non-linear matter power spectrum, and it has been calibrated against a wide range of CDM simulations. It has also been extended for massive neutrino cosmologies (Bird et al., 2012). Other predictions for the non-linear matter power spectrum include the Coyote emulator (Heitmann et al., 2014), which is based on a set of high-accuracy N-body simulations.

However, there is also another avenue to use large scale structure information, the geometrical approach, which exploits the so-called Baryon Acoustic Oscillations (BAO) rather than the measurements of the broad-band shape of the galaxy power spectrum. The BAO signal appears as a peak in the two-point mass correlation function corresponding to the distance a sound wave can travel in the photon-baryon fluid from very early in the universe until the drag epoch, when the baryon optical depth equals one. The BAO signature provides a standard ruler to measure the distance to various redshifts, and it can be measured either along the line of sight, in which the radial distance is inversely proportional to the Hubble expansion rate H(z), or across the line of sight, in which case the angular distance is proportional to an integral of H(z), the angular diameter distance d_A(z). To use the BAO method, one must, therefore, extract the acoustic scale from the clustering of some tracer of the baryon distribution (galaxies, quasars). This is typically done statistically using the two-point correlation function of the spatial distribution of tracers, or from its Fourier transform, the power spectrum. From these functions, it is possible to measure two different quantities corresponding to the oscillations parallel and perpendicular to the line of sight, that is r_sH(z) and d_A(z)/r_s, with r_s the sound horizon at the drag epoch. Many of the BAO analyses to date have used spherically averaged clustering statistics, measuring an effective distance $D_V\equiv {(z{d}_A{(z)}^2/H(z))}^{\frac{1}{3}}$, which is the volume-averaged distance. Some of the most recent BAO extractions by the Sloan Digital Sky Survey III (SDSS-III) (Eisenstein et al., 2011) Baryon Oscillation Spectroscopic Survey (BOSS) (Dawson et al., 2013) have achieved, by measuring the clustering of 1.2 million galaxies with redshifts 0.2 < z < 0.75, 1.8% precision on the radial BAO distance and 1.1% precision on the transverse distance in the z < 0.75 redshift region (Beutler et al., 2017b; Ross et al., 2017; Vargas-Magaña et al., 2018). These results improve former determinations from previous data releases of BOSS and SDSS (Eisenstein et al., 2005; Anderson et al., 2013, 2014; Tojeiro et al., 2014; Ross et al., 2015) or other galaxy surveys (Percival et al., 2001; Cole et al., 2005; Beutler et al., 2011; Blake et al., 2011; Kazin et al., 2014), see also the recent works of Bautista et al. (2017b) for a 2.6% measurement of D_V at 2.8σ significance with the extended Baryon Oscillation Spectroscopic Survey (eBOSS) from SDSS-IV Dawson et al. (2016). The Dark Energy Survey (DES) has also achieved a 4.4% accuracy on the measurement of d_A(z)/r_s at z = 0.81 Abbott et al. (2017).

Galaxy clustering measurements can also be exploited to constrain, at a number of redshifts, the product of the linear growth rate f × σ₈¹², by means of the so-called redshift space distortions, caused by galaxy peculiar velocities, see the recent analyses of Beutler et al. (2017a), Satpathy et al. (2016), and Sanchez et al. (2017).

Apart from the spatial distribution of galaxies, there are also other ways of mapping the large scale structure of the universe at different cosmic times. The Lyman-α forest power spectrum from distant quasars plays a major role for constraining the neutrino masses, as it is sensitive to smaller scales, where the effect of neutrino masses is more pronounced. We refer the reader to the seminal works of Croft et al. (1999), Seljak et al. (2005), Goobar et al. (2006), Seljak et al. (2006), Gratton et al. (2008), Fogli et al. (2008), and Viel et al. (2010). In addition, since the redshifts at which Lyman-α forest probes are sensitive to are higher than those corresponding to galaxy surveys, a fixed scale k will be closer to the linear regime in the Lyman-α case. An additional benefit of going to higher redshifts is that uncertainties related to the evolution of the dark energy fluid will be sub-dominant, as dark energy effects are expected to be more prominent at very low redshifts. However, modeling the neutrino mass effect in the Lyman-α forest power spectrum is highly non-trivial as it may strongly rely on hydrodynamical simulations (Viel et al., 2010). These numerical calculations try to properly account for the late time non-linear evolution of the intergalactic medium (IGM), including reionization processes (Viel et al., 2010; Villaescusa-Navarro et al., 2013). The BAO signature can also be measured in the flux correlation function of the Lyman-α forest of quasars, first detected at a mean redshift z = 2.3 in Busca et al. (2013, see also Slosar et al., 2013; Font-Ribera et al., 2014a; Delubac et al., 2015; Bautista et al., 2017a; Bourboux et al., 2017 and Aubourg et al., 2015), in which joint constraints from the BAO signature from galaxies and quasars have been presented.

Galaxy clusters provide yet another test which allows us to trace the clustering of matter perturbations and, therefore, to test the suppression due to the presence of a non-zero ∑m_ν. Galaxy clusters are, by far, the largest virialised objects in the universe, providing a measurement of the so-called cluster number count function dN/dz. This function gives the number of clusters of a certain mass M within a redshift interval (bin) z+δz and, for a given survey:

$\begin{array}{cc}\frac{dN}{dz}{|}_{M>M_{\text{min}}}=f_{\text{sky}}\frac{dV(z)}{dz}{\displaystyle {\int }_{M_{\text{min}}}^{\infty }d}M\frac{dn}{dM}(M,z).& (11)\end{array}$

The quantity f_sky = ΔΩ/4π refers to the fraction of sky covered by the survey and the unit volume is given by

$\begin{array}{cc}\frac{dV(z)}{dz}=\frac{4\pi }{H(z)}{\displaystyle {\int }_0^{z}d}{z}^{\prime }\frac{1}{H{(z^{\prime })}^2}.& (12)\end{array}$

While the redshift is relatively easy to measure, the main uncertainty of this method comes from the cluster mass estimates, determined through four main available methods: X-rays, velocity dispersion, Sunyaev-Zeldovich (SZ) effect¹³ and weak lensing. The overall error in the cluster mass determination is usually around ΔM/M ~ 10%. Furthermore, in order to relate the cluster number count function to the underlying cosmological parameters, one needs as an input a mass function dn(z, M)/dM describing the abundance of virialised objects at a given redshift, usually obtained by means of N-body simulations (Tinker et al., 2008; Costanzi et al., 2013). This mass function depends on both the matter mass-energy density and on the standard deviation (computed in linear perturbation theory) of the density perturbations:

$\begin{array}{cc}{\sigma }^2=\frac{1}{2{\pi }^2}{\displaystyle {\int }_0^{\infty }d}k{k}^{2}P(k)W^2(kR),& (13)\end{array}$

where P(k) is the matter power spectrum, W(kR) is the top-hat window function, R is the comoving fluctuation size, related to the cluster mass M as $R={(3M/4\pi {\rho }_m)}^{1/3}$, and

$\begin{array}{cc}W(kR)=\frac{3\left(\sin (kR)-(kR)\cos (kR)\right)}{{(kR)}^3}.& (14)\end{array}$

There are still some degeneracies in the cosmological parameters probed by cluster surveys, whose results are reported by means of a relationship between the matter clustering amplitude σ₈ (obtained from Equation 13), and the matter mass-energy density Ω_m parameters. More concretely, cluster catalogs measure the so-called cluster normalization condition, ${\sigma }_8{\Omega }_m^{\gamma }$, where γ~0.4 (Allen et al., 2011; Weinberg et al., 2013). Current cluster catalogs include X ray clusters (see e.g., Hilton et al., 2018; Sohn et al., 2018 and references therein), the optically detected SDSS photometric redMaPPer cluster catalog (Rozo and Rykoff, 2014; Rykoff et al., 2014; Rozo et al., 2015) and the Planck SZ galaxy clusters (PSZ2) Ade et al. (2016a), which contains more than a thousand confirmed clusters. Other SZ cluster catalogs are those detected from the Atacama Cosmology Telescope (ACT) (Hilton et al., 2018) and from the South Pole Telescope (SPT) (de Haan et al., 2016).

Last but not least, weak lensing surveys are also an additional probe of the large scale structure effects of massive neutrinos (Cooray, 1999; Abazajian and Dodelson, 2003; Hannestad et al., 2006b; Kitching et al., 2008; De Bernardis et al., 2009; Ichiki et al., 2009; Tereno et al., 2009; Debono et al., 2010; Jimenez et al., 2010). Light rays from distant galaxies are bent by the matter density perturbations between the source galaxies and the observer, thereby inducing distortions in the observed images of the source galaxies (see the reviews Munshi et al., 2008; Kilbinger, 2015). Commonly, the deformations in the source galaxies are rather weak and to extract the lensing signature one needs a correlation among different galaxy images, the so-called shear-correlation functions. By measuring the angular correlation of these distortions, one can probe the clustering statistics of the intervening matter density field along the line of sight, without relying strongly on bias assumptions, setting therefore independent constraints on the neutrino masses. Weak lensing surveys usually report their cosmological constraints in terms of the clustering amplitude σ₈ and the current matter energy density Ω_m. More specifically, they make use of the combination $S\equiv {\sigma }_8\sqrt{{\Omega }_m}$ as an accurate description of the amplitude of structure growth in the universe. The most recent weak lensing cosmological analyses profiting of weak lensing data from DES and from the Kilo Degree Survey (KiDS), consisting of ~450 deg² of imaging data, are presented in Abbott et al. (2018), Hildebrandt et al. (2017) ,Joudaki et al. (2017), and Köhlinger et al. (2017), respectively.

4.3. Cosmological Bounds on Neutrino Masses and Their Ordering

In the following, we shall review the current cosmological bounds on neutrino masses and on their ordering, firstly in the standard ΛCDM scenario and then when considering extended cosmological models.

4.3.1. Constraints Within the ΛCDM Universe

Focusing on bounds exclusively from the Planck collaboration, making use of their CMB temperature anisotropies measurements in the multipole range ℓ ≲ 2500 (Planck TT) and of their low-multipole (up to ℓ = 29) polarization data, lowP, a bound of ∑m_ν < 0.72 eV at 95% CL Ade et al. (2016b) is reported. When high-multipole (i.e., small scale, ℓ > 30) polarization measurements are included in the analyses (Planck TT,TE,EE + lowP), the quoted constraint is ∑m_ν < 0.49 eV at 95% CL. As the Planck TT,TE,EE data combination may still have some systematics due to temperature-to-polarization leakage (Ade et al., 2016b), the bounds including these measurements provide the less conservative approach when exploiting CMB data. In 2016, the Planck collaboration presented a series of new results based on a new analysis, in which the modeling and removal of unexplained systematics in the large angular polarization data were accounted for Aghanim et al. (2016b). The value of the optical depth τ found in these refined analyses (using the SimLow likelihood) was smaller than that quoted in previous analyses (Ade et al., 2016b): while the lowP data was providing τ = 0.067±0.022, the SimLow likelihood results in τ = 0.055±0.009. The most important consequence of this lower value of τ on the CMB bounds on ∑m_ν is related to the degeneracy between the amplitude of the primordial power spectrum, A_s, and τ, as already introduced in section 4.1: a lower value of τ will imply a lower value of A_s, thus implying a lower overall normalization of the spectrum, leading therefore to tighter constraints on neutrino masses. The 95% CL limits of ∑m_ν < 0.72 eV and ∑m_ν < 0.49 eV, respectively from the Planck TT + lowP and Planck TT,TE,EE + lowP analyses, are updated to ∑m_ν < 0.59 eV and ∑m_ν < 0.34 eV when using Planck TT + SimLow and Planck TT,TE,EE + SimLow, respectively. These constraints are clearly located away from the region in which a preference for a given mass ordering (normal vs. inverted) may show up. Indeed, the CMB data alone were used by the authors of Gerbino et al. (2017b) which, by means of a novel approach to quantify the neutrino mass ordering, have shown that the odds favoring normal ordering vs. inverted ordering are 1:1 and 9:8 in the case of the Planck TT + lowP and Planck TT,TE,EE + lowP data combinations, respectively. These results point to an inconclusive strength of evidence, see Table 2. Based on a full Bayesian comparison analysis, Gariazzo et al. (2018a) has shown, using Planck TT,TE,EE + lowP measurements together with global neutrino oscillation data, that the Bayes factor for such a combination is log(B_{NO, IO}) ≃ 2.5 for almost all the possible parameterizations and prior choices considered. This valuev of the Bayes factor, which only points to weak preference for normal ordering, is entirely due to neutrino oscillation data, in agreement with the results of Caldwell et al. (2017). Therefore, Planck temperature and polarization measurements alone can not further improve our current knowledge of the neutrino mass ordering from global oscillation data.

TABLE 2

Table 2. Jeffreys' scale Jeffreys (1961) for estimating the strength of the preference for one model over the other (adapted from Trotta (2008)) when performing Bayesian model comparison analysis.

The CMB limits on neutrino masses can also include the lensing likelihood, which leads to ∑m_ν < 0.59 eV at 95% CL for the case of Planck TT,TE,EE + lowP + lensing measurements (Ade et al., 2016b). Notice that the bound with the lensing likelihood is less tight than that obtained without the lensing potential extraction (∑m_ν < 0.49 eV at 95% CL from Planck TT,TE,EE + lowP). The reason is related to the fact that, while the Planck CMB power spectra favor a larger lensing amplitude, the lensing potential reconstructions prefer a lower one. Since increasing the neutrino masses reduces the lensing amplitude, the one dimensional posterior distribution of ∑m_ν arising from the combination of CMB temperature, polarization and lensing data sets shifts the neutrino mass constraints away from zero, so that less posterior volume is found near zero than when constraining ∑m_ν only with CMB temperature and polarization data.

A significant strengthening on the aforementioned limits can be obtained by means of additional data sets, which help enormously in breaking the degeneracies which are allowed when only CMB data are considered. Among them, the one existing between ∑m_ν and the Hubble constant H₀ (see e.g Giusarma et al. (2013b)). Large scale structure data from galaxy clustering are of great help in breaking degeneracies. When exploited in the geometrical (BAO) form, the Planck collaboration quotes 95% CL limits of ∑m_ν < 0.17 eV from the combination Planck TT,TE,EE + SimLow + lensing + BAO data Aghanim et al. (2016b)¹⁴. Concerning the neutrino mass ordering, the addition of BAO measurements to CMB Planck measurements leads to odds for the normal vs. the inverted ordering of 4:3 and of 3:2, in the case of the Planck TT + lowP + BAO and Planck TT,TE,EE + lowP + BAO respectively, suggesting only very mild evidence for the normal ordering case Gerbino et al. (2017b). These results confirmed the previous findings obtained in Hannestad and Schwetz (2016). The authors of Vagnozzi et al. (2017) reported odds for the normal vs. the inverted ordering of 2.4:1 from the combination of Planck TT,TE,EE + BAO plus the SimLow prior on the reionization optical depth, i.e., τ = 0.05 ± 0.009. Notice that if data are not informative enough, the choice of prior on m_lightest will make a difference in the odds ratio¹⁵.

Another possible avenue to exploit galaxy clustering data is to use the information contained in the full-shape of the galaxy power spectrum (see e.g., Allen et al., 2003; Elgaroy and Lahav, 2003; Hannestad, 2003; Spergel et al., 2003; Barger et al., 2004; Crotty et al., 2004; Hannestad and Raffelt, 2004; Tegmark et al., 2004, 2006; Fogli et al., 2007, 2008; Hamann et al., 2007b, 2008, 2010a; de Putter et al., 2012, 2014; Riemer-Sorensen et al., 2012, 2014; Giusarma et al., 2013a, 2016; Zhao et al., 2013; Cuesta et al., 2016; Vagnozzi et al., 2017). Notice however that using BAO is currently a more robust method, as the effects of the galaxy bias and non-linearities are not as severe as in the shape approach. In the minimal ΛCDM scenario, the BAO geometrical approach can supersede the neutrino mass constraints obtained from the shape one (see e.g., Hamann et al., 2010a; Giusarma et al., 2013b). Indeed, a dedicated analysis has been devoted in Vagnozzi et al. (2017) to compare the constraining power of these two different approaches to large scale structure data with the SDSS-III BOSS measurements. The conclusions are that, even if the latest measurements of the galaxy power spectrum map a large volume of our universe, the geometric approach is still more powerful, at least within the minimal ΛCDM + ∑m_ν cosmology. The better performance of BAO measurements is partly due to the upper cutoff applied in the scale k of the power spectrum when dealing with shape analyses (mandatory to avoid non-linearities), and partly due to the fact that two additional nuisance parameters are further required to relate the galaxy power spectrum to the matter power one¹⁶. As an example, the 95% CL bound of ∑m_ν < 0.118 eV obtained with Planck TT,TE,EE + BAO plus SimLow is degraded to ∑m_ν < 0.177 eV when replacing part of the BAO data [more concretely, the high redshift BOSS CMASS Data Release 11 (DR11) sample by the full-shape power spectrum measurements from the BOSS CMASS Data Release 12 (DR12)].

An alternative tracer to map out the large scale structure in our universe and improve the CMB-only bounds on the sum of the three active neutrinos is the Lyman-α forest, leading to neutrino mass bounds which turn out to be among the most constraining ones. By means of the one-dimensional Lyman-α forest power spectrum extracted by Palanque-Delabrouille et al. (2013) and combining these measurements with Planck TT,TE,EE + lowP + BAO, the authors of Palanque-Delabrouille et al. (2015) find a 95% CL upper limit of ∑m_ν < 0.12 eV. It is also remarkable the fact that, even without the addition of CMB data, the combination of the Lyman-α forest power spectrum of Palanque-Delabrouille et al. (2013), together with those from the XQ-100 quasars at z≃3.5−4.5 and the high-resolution HIRES/MIKE spectrographs at z = 4.2 and z = 4.6 (Viel et al., 2013), is already able to provide a limit of ∑m_ν < 0.8 eV (Yeche et al., 2017), showing clearly the enormous potential of small-scale probes to extract the neutrino masses.

The degeneracies among ∑m_ν and the other cosmological parameters that appear when considering CMB data only can also be strongly alleviated by the addition of Supernova Ia luminosity distance data and/or local measurements of the Hubble parameter¹⁷. Concerning Supernovae Ia data, the most complete photometric redshift calibrated sample joins the SuperNova Legacy Survey (SNLS) and SDSS supernova catalogs. This Joint Light-Curve Analysis (JLA) catalog (Betoule et al., 2013, 2014; Mosher et al., 2014) has been used by the Planck collaboration and by other analyses to improve the constraints on ∑m_ν, being its impact particularly crucial in non-minimal cosmologies (Vagnozzi et al., 2018), as we shall explain toward the end of this section. Concerning the value of H₀, as there exists a strong anti-correlation between the Hubble constant and ∑m_ν when considering CMB measurements, larger mean values of H₀ will lead to tighter constraints on the neutrino mass and consequently on the inverted mass ordering. When performing combined analyses of CMB and H₀ data, the 2015 Planck release relies on the reanalysis Efstathiou (2014) of a former H₀ measurement based on the Hubble Space Telescope (HST) (H₀ = (73.8 ± 2.4) km s⁻¹ Mpc⁻¹;Riess et al., 2011), which was in mild (2.5σ) tension with the value of the Hubble parameter derived from 2013 Planck CMB data Ade et al. (2014). This reanalysis (Efstathiou, 2014) considers the original Cepheid data of Riess et al. (2011) and uses a new geometric maser distance estimate to the active galaxy NGC 4,258 (Humphreys et al., 2013), which is used as a distance anchor to find a value of the Hubble constant H₀ = (70.6 ± 3.3) km s⁻¹ Mpc⁻¹¹⁸. The limit on the sum of the three active neutrino masses reported by the Planck collaboration using this value of H₀ is ∑m_ν < 0.23 eV at 95% CL, when combined with Planck TT + lowP + lensing + BAO + SNIa data. Other estimates of the Hubble constant, however, exist. The 2.4% determination of Riess et al. (2016) profits from new, near-infrared observations of Cepheid variables, and it provides the value H₀ = (73.02 ± 1.79) km s⁻¹ Mpc⁻¹ Riess et al. (2016). As the former mean H₀ value is higher than the one considered by the Planck collaboration, it will lead to tighter limits on ∑m_ν. Indeed, the work of Vagnozzi et al. (2017) quotes the 95% CL bounds of ∑m_ν < 0.196 eV and ∑m_ν < 0.132 eV when combining with external data sets using the priors H₀ = (70.6±3.3) km s⁻¹ Mpc⁻¹ and H₀ = (73.02±1.79) km s⁻¹ Mpc⁻¹, respectively. Focusing on the less conservative choice H₀ = (73.02±1.79) km s⁻¹ Mpc⁻¹, odds for the normal vs. the inverted neutrino mass ordering of 3.3:1 were found for both the Planck TT,TE,EE + BAO + SimLow + H₀ and the Planck TT,TE,EE + BAO + SimLow + H₀ + Planck SZ data sets (Vagnozzi et al., 2017). The 95% CL upper bounds on the neutrino mass for these two combinations are ∑m_ν < 0.094 eV and ∑m_ν < 0.093 eV, respectively. These results indicate, once again, very mild evidence for the normal mass ordering, even within these more aggressive and less conservative scenarios, in which the very tight limit on ∑m_ν is mostly due to the tension between CMB and direct measurements of the Hubble constant H₀, together with the strong degeneracy between ∑m_ν and H₀. Using these results, we stress that having an upper bound ∑m_ν≲0.1 eV at 95% CL is not equivalent to having a 95% CL preference for normal ordering: the probabilities for normal ordering and inverted ordering, as computed from the odds 3.3:1, are approximately 77 and 23% (see also section 5.1).

In general, the combination of data sets that are inconsistent is potentially dangerous. Apart from the constraining effect on the neutrino mass limits when considering a particular prior on the Hubble constant H₀, there have been also other related cases in which the neutrino masses were a tool to accommodate tensions among different data sets. For instance, in the case of galaxy cluster counts, a larger neutrino mass could in principle fit both CMB and low-redshift universe constraints on the power spectrum normalization σ₈ Allen et al. (2003). The effect of combining CMB and BAO observations with clusters and/or shear data is presented in Costanzi et al. (2014), where it is shown that the inclusion of either cluster or shear measurements in the Planck + BAO joint analysis indicates a preference for ∑m_ν > 0 at more than 2σ. However, the authors clearly state that these results can not be interpreted as a claim for a cosmological detection of the neutrino mass, but rather as a remedy to palliate the existing tension between clusters/shear data and Planck/BAO observations.

Finally, weak lensing constraints from the Dark Energy Survey Year 1 results Abbott et al. (2018) (DES Y1), have also recently provided bounds on the sum of the total neutrino mass. Based on 1321 deg² imaging data, DES Y1 analyses exploit the galaxy correlation function (from 650.000 luminous red galaxies divided into five redshift bins) and the shear correlation function (from twenty-six million source galaxies from four different redshift bins) as well as the galaxy-shear cross-correlation. The 95% CL upper bound reported on the neutrino mass after combining their measurements with Planck TT,TE,EE + lowP + BAO +JLA is ∑m_ν < 0.29 eV, ~20% higher than without DES measurements. The reason for this higher value of ∑m_ν is that the clustering amplitude in the case of DES Y1 is mildly below the one preferred by Planck measurements. Since larger values of the neutrino mass will decrease the value of the clustering amplitude, the upper limit on the total neutrino mass is loosened by ~20% after the DES results are also considered.

4.3.2. Extensions to the Minimal ΛCDM Universe

So far we have discussed the neutrino mass and neutrino mass ordering sensitivities within the minimal ΛCDM universe. However, these limits will change when additional parameters are introduced in the analyses.

The first and most obvious scenario one can consider is to test the stability of the neutrino mass limits when new physics is added in the neutrino sector. As already mentioned in section 3.2, short baseline neutrino experiments indicate that a light sterile neutrino at the eV scale may exist. These extra sterile species will contribute to the effective number of relativistic degrees of freedom, N_eff, defined by

$\begin{array}{cc}\begin{array}{r}{\rho }_{\mathrm{\text{rad}}}=\left(1+\frac{7}{8}{\left(\frac{4}{11}\right)}^{4/3}{N}_{\text{eff}}\right){\rho }_{\gamma },\end{array}& (15)\end{array}$

where ρ_rad (ρ_γ) is the total radiation (CMB photons) energy density. In the standard picture N_eff = 3.046 (Mangano et al., 2005; de Salas and Pastor, 2016). This number accounts for the three active neutrino contribution and considers effects related to non-instantaneous neutrino decoupling and QED finite temperature corrections to the plasma evolution¹⁹. Variations in N_eff, apart from the light sterile neutrino, may be related to the existence of additional relativistic particles, as thermally-produced axions (see below). Analyses in which both the active neutrino masses and the number of additional massless or massive species are varied simultaneously have been extensively carried out in the literature (Hamann et al., 2007a, 2010b, 2011; Giusarma et al., 2011, 2013b; Archidiacono et al., 2013a,b; Di Valentino et al., 2013; Riemer-Sorensen et al., 2013), showing that the bounds on the active neutrino mass are relaxed when additional sterile species are added to the fermion content of the SM of particle physics. The constraints on the total neutrino mass ∑m_ν are less stringent than in the standard three neutrino case due to the large degeneracy between ∑m_ν and N_eff, which arises from the fact that a number of massless or sub-eV sterile neutrino species contributing to the radiation content of the universe will shift both the matter-radiation equality era and the location of the CMB acoustic peaks. This effect could be compensated by enlarging the matter content of the universe, implying therefore that larger values for the neutrino masses could be allowed. Consequently, a priori, the constraints on ∑m_ν when N_eff is also a free parameter in the analyses are not very competitive. Fortunately, CMB measurements from the Planck collaboration help enormously in sharpening the measurement of N_eff, especially when considering polarization measurements at small scales: including data at high multipoles, one obtains ΔN_eff < 1 at more than 4σ significance from Planck CMB observations alone. Indeed, the limit on the sum of the three active neutrino species considering also additional radiation neutrino species (i.e., massless sterile neutrino species) is ∑m_ν < 0.178 eV at 95% CL from Planck TT,TE,EE + lowP + BAO data, very similar to the bound ∑m_ν < 0.168 eV at 95% CL arising from the very same dataset within the minimal ΛCDM scenario with three active massive neutrinos. Another possible way of relaxing (or even avoiding) the cosmological neutrino mass limits is via the addition of non-standard interactions in the active neutrino sector (Beacom et al., 2004; Fardon et al., 2004; Afshordi et al., 2005; Hannestad, 2005b; Bell et al., 2006; Brookfield et al., 2006a,b; Bjaelde et al., 2008; Ichiki and Keum, 2008; Mota et al., 2008; Boehm et al., 2012; Archidiacono and Hannestad, 2014; Dvali and Funcke, 2016; Di Valentino et al., 2018b).

Furthermore, additional relics different from sterile neutrinos, as thermal axions (Peccei and Quinn, 1977a,b; Weinberg, 1978; Wilczek, 1978), contributing to both N_eff at early times and to the hot dark matter component in the late-time universe, suppress small-scale structure formation and show effects very similar to those induced by the (active) three massive neutrino species. Therefore, the cosmological bounds on the three active neutrino masses are modified in scenarios with thermal axions (see Hannestad et al., 2007, 2008, 2010; Melchiorri et al., 2007; Archidiacono et al., 2013c; Giusarma et al., 2014; Di Valentino et al., 2015, 2016a,b), as these two species have to share the allowed amount of dark matter. Nonetheless, there are non-negligible differences among neutrinos and thermal axions: (a) axions are colder than neutrinos, as they decouple earlier; (b) since the axion is a scalar particle, an axion mass larger than the neutrino one is required in order to make identical contributions to the current mass-energy density of the universe; (c) in the case of axions, the contribution to N_eff is related to their mass, while for neutrinos this is usually not true. Consequently, the bounds on the axion mass are always less constraining than for the neutrino, and ∑m_ν is slightly more constrained in scenarios in which thermal axions are also present. For instance, Di Valentino et al. (2016c) quotes ∑m_ν < 0.175 eV at 95% CL from the Planck TT,TE,EE + lowP + BAO data combinations when considering only neutrinos, while the analyses in Di Valentino et al. (2016b), including massive axions, find ∑m_ν < 0.159 eV and m_a < 0.763 eV, both at 95% CL, for the very same data combination.

There are also other ways of relaxing the cosmological neutrino mass bounds, related either to the early or the late-time accelerating periods in the universe. In the former case one can play with inflationary processes. There have been a number of studies devoted to explore their degeneracies with the neutrino sector( see the recent works of Hamann et al., 2007b; Archidiacono et al., 2013b; Joudaki, 2013; de Putter et al., 2014; Canac et al., 2016; Di Valentino et al., 2016a; Gerbino et al., 2017a). The authors of Di Valentino et al. (2016a) have considered a non-standard and parametric form for the primordial power spectrum, parameterized with the PCHIP (piecewise cubic Hermite interpolating polynomial) formalism with twelve nodes between $k_1=5\times 10^{-6}$ Mpc⁻¹ and k₂ = 10 Mpc⁻¹ and derived the neutrino mass constraints within this more general scenario. When only Planck TT + lowP measurements were considered, the 95% CL mass bound of ∑m_ν < 0.75 eV obtained with the usual power-law description of the primordial power spectrum was relaxed to ∑m_ν < 2.16 eV. This large value is explained in terms of the strong degeneracy between ∑m_ν and the PCHIP nodes corresponding to the wave-numbers where the contribution of the Early ISW effect is located, in such a way that the effect induced by a non-zero neutrino mass is easily compensated by an increase of the primordial power spectrum at these scales only. BAO information improves considerably the limits in the PCHIP prescription, but it is the addition of high-ℓ polarization data what further constrains the effect. The 95% CL upper limit in the PCHIP scenario from the Planck TT,TE,EE + lowP + BAO data combination is ∑m_ν < 0.218 eV, quite close to the bound found when the usual power-law description is applied (∑m_ν < 0.175 eV). Reference Gerbino et al. (2017a) deals instead with the robustness of the constraints on the scalar spectral index n_s under several neutrino physics scenarios. The authors have explored the shifts induced in the inflationary parameters for different choices of the neutrino mass ordering, comparing the approximate massive neutrino case (one massive eigenstate plus two massless species when the total mass is close to the minimum allowed value by oscillation data, and three degenerate massive neutrinos otherwise) vs. the exact case (normal or inverted mass orderings). While the mass-ordering assumptions are not very significant when ∑m_ν is fixed to its minimum value, there is a shift in n_s when ∑m_ν is a free parameter, inherited from the strong degeneracies in the ∑m_ν, H₀ and ${\Omega }_m{h}^2$ parameter space. Fortunately, BAO measurements revert the ∑m_ν-n_s anti-correlation present with CMB data only, and the shift in the spectral index turns out to be negligible.

The other possibility is to play with the late-time acceleration period and study how the neutrino mass bounds change. The current accelerated expansion of the universe, explained in terms of a cosmological constant in the minimal ΛCDM scenario, may be due to a dynamical dark energy fluid with a constant equation of state w ≠ −1 or a time-dependent w(z) (Chevallier and Polarski, 2001; Linder, 2003), or to quintessence models, based on the existence of a cosmic scalar field (Peebles and Ratra, 1988; Ratra and Peebles, 1988; Wetterich, 1995; Caldwell et al., 1998; Zlatev et al., 1999; Wang et al., 2000), which provide a dynamical alternative to the cosmological constant scenario with w = −1. It is naturally expected that the neutrino mass bounds will increase when enlarging the parameter space. Indeed, when the dark energy equation of state is allowed to vary within the phantom region w < −1, there is a very well-known degeneracy between the dark energy equation of state w and the sum of the three active neutrino masses, as first noticed in Hannestad (2005a) (see also La Vacca and Kristiansen, 2009; Archidiacono et al., 2013b; Joudaki, 2013; Lorenz et al., 2017; Sutherland, 2018; Vagnozzi et al., 2018)²⁰. It has been pointed out that for very high neutrino masses only dark energy models lying within the phantom region will be allowed. The reason for that is the following: a larger ∑m_ν can be compensated by a larger Ω_m, which in turn can be compensated by a smaller equation of state of the dark energy component, i.e., w < −1. Interestingly, the recent work of Vagnozzi et al. (2018) shows that the cosmological bounds on ∑m_ν become more restrictive in the case of a dynamical dark energy component with w(z)≥−1. Following the usual dynamical dark energy description, whose redshift dependence is described by the standard Chevallier-Polarski-Linder (CPL) parametrization (Chevallier and Polarski, 2001; Linder, 2003), the authors of Vagnozzi et al. (2018) have shown that the combination of Planck TT,TE,EE + BAO + JLA plus the SimLow prior on the reionization optical depth provides, at 95% CL, ∑m_ν < 0.11 eV in the CPL case when restricting w(z)≥−1 (within the physical, non-phantom region), while ∑m_ν < 0.13 eV in the ΛCDM case. When w(z) is also allowed to be in the phantom region (w(z) < −1) within the CPL parameterization, the resulting 95% CL constraint on the three active neutrino masses is ∑m_ν < 0.37 eV. These results have a direct impact on the cosmological preference for a given neutrino mass ordering. Following Hannestad and Schwetz (2016) and Vagnozzi et al. (2017), it is found that the normal ordering is mildly preferred over the inverted one, with posterior odds 3:1 for the data combination quoted above when w(z)≥−1. On the contrary, if there is no such a restriction and w(z) can also take values in the phantom region, the odds are 1:1. The odds in the non-phantom dynamical dark energy case show a mild preference for normal ordering. Therefore, if neutrino oscillation experiments or neutrinoless double beta decay searches find that the neutrino mass ordering is the inverted one, if the current cosmic acceleration is due to a dynamical dark energy component, one would require this component to be phantom.

As a final point in this section, we would like to note that also in scenarios in which the current accelerated expansion is explained by means of modifications of gravity at ultra-large length scales, the cosmological limits on neutrino masses will differ from those in the standard ΛCDM model ( see e.g., Huterer and Linder (2007), Baldi et al. (2014), Hu et al. (2015), Shim et al. (2014), Barreira et al. (2014), Bellomo et al. (2017), Peirone et al. (2018), Renk et al. (2017), and Dirian (2017).

5. Global 2018 Data Analysis

In this section we shall combine the available measurements that allow us to constrain the neutrino mass ordering, updating the results presented in Gariazzo et al. (2018a).

5.1. Bayesian Model Comparison

Before performing the analysis, we will briefly summarize the method we will adopt to compare the two possible orderings.

We will follow a Bayesian approach to model comparison (see previous work suggesting the Bayesian method as the most suited one for the mass ordering extraction in Qian et al., 2012 and Blennow, 2014)²¹, which makes use of the Bayesian evidence Z. This quantity, which is also known as the marginal likelihood, is defined as the integral over the entire parameter space ${\Omega }_{{M}}$ of the prior $\pi (\theta )\equiv p(\theta |{M})$ times the likelihood ${L}(\theta )\equiv p(d|\theta ,{M})$, where θ is the set of parameters that describe the model ${M}$ and d represents the available data:

$\begin{array}{cc}{Z}_{ℳ}={\displaystyle {\int }_{{\Omega }_{ℳ}}ℒ}(\theta )\pi (\theta )d\theta .& (16)\end{array}$

The posterior probability of the model ${M}$ can be written in terms of its prior probability $\pi ({M})$ times the Bayesian evidence $Z_{{M}}$:

$\begin{array}{cc}\begin{array}{r}p({M}|d)\propto Z_{{M}}\pi ({M}),\end{array}& (17)\end{array}$

where the proportionality constant depends only on the data. In our case we will be interested in comparing normal ordering (NO) and inverted ordering (IO), which can be considered as two different competing models ${{M}}_1\equiv \mathrm{\text{NO}}$ and ${{M}}_2\equiv \mathrm{\text{IO}}$. The ratio of the posterior probabilities of the two models can be written as

$\begin{array}{cc}\begin{array}{r}\frac{p(\text{NO}|d)}{p(\text{IO}|d)}=B_{\text{NO},\text{IO}}\frac{\pi (\mathrm{\text{NO}})}{\pi (\mathrm{\text{IO}})},\end{array}& (18)\end{array}$

having defined the Bayes factor as

$\begin{array}{cc}\begin{array}{r}{B}_{\text{NO},\text{IO}}=Z_{\text{NO}}/Z_{\text{IO}}.\end{array}& (19)\end{array}$

Assuming the same prior probabilities for normal and inverted ordering, the Bayes factor is what determines the odds in favor of one of the competing models. In particular we will indicate the results in terms of its natural logarithm lnB_{NO, IO}, which will be positive when data will prefer normal ordering and negative otherwise. Quantitatively, the preference is given in terms of posterior odds, which are always |B_{NO, IO}|:1 in favor of the preferred model. The strength of the preference can be also translated into an empirical scale, which in our case is summarized in the third column of Table 2.

Let us briefly discuss the correspondence of the quoted levels that classify the strength of the preference in favor of one of the competing models. In the case of the neutrino mass ordering, we have only two possibilities (normal or inverted), so that p(NO|d)+p(IO|d) = π(NO)+π(IO) = 1. If we assign the same prior probability to the two cases, π(NO) = π(IO) = 1/2, it is easy to compute the posterior probability for each of the two cases, which will be

$\begin{array}{cc}\begin{array}{rcl}p(\text{NO}|d)& =& B_{\text{NO},\text{IO}}/(B_{\text{NO},\text{IO}}+1),\end{array}& (20)\end{array}$

$\begin{array}{cc}\begin{array}{rcl}p(\text{IO}|d)& =& 1/(B_{\text{NO},\text{IO}}+1),\end{array}& (21)\end{array}$

having used Equations (18, 19). The confidence levels for the rejection of the disfavored (e.g., inverted) mass ordering will then be $x=100\times (1-|B_{\text{NO},\text{IO}}{|}^{-1})\%$. For example, a Bayes factor B_{NO, IO} = 10 corresponds to a rejection of the inverted ordering at 90% CL. If, instead, we want to reproduce the probability levels $P=\mathrm{\text{erf}}(N/\sqrt{2})$ that are usually associated to the classical Nσ levels for a Gaussian measurement, being erf the error function and considering, for example, N ∈ (1, 2, 3, 4, 5), the corresponding Bayes factors B can be computed to be B = P/(1−P), which gives us ln B_Nσ≃0.77, 3, 5.9, 9.7, 14.37. Therefore, our “strong”, “very strong” and “decisive” levels roughly correspond to the >3σ, >4σ and >5σ probabilities, as indicated in the fourth column of Table 2.

5.2. Parameterization and Data

Our two competing models are described by the same number of parameters, listed with their priors in Table 3: the three neutrino mixing angles (${sin}^2{\theta }_{12}$, ${sin}^2{\theta }_{13}$, ${sin}^2{\theta }_{23}$), the CP violating phase δ_CP and the parameters associated with neutrino masses, neutrinoless double beta decay (0νββ) and cosmology, as we shall describe now.

TABLE 3

Table 3. Neutrino, cosmological and 0νββ parameters used in the analysis, with the adopted priors.

We consider in our analysis the parameterization that uses the two mass splittings ($\Delta m_{21}^2$ and $\Delta m_{31}^2$) and the lightest neutrino mass m_lightest with logarithmic priors. This parameterization, strongly motivated by the physical observables, was shown to provide the optimal strategy to successfully explore the neutrino parameter space (see Gariazzo et al., 2018a)²². Within the other possible choice, that is, within the parametrization that uses the three neutrino masses as free parameters, most of the parameter space at high neutrino masses is useless for the data fit. Therefore, this second possibility is penalized by the Occam's razor and we shall not explore it here.

The neutrino mixing parameters are constrained using the same data we described in section 2. The complete oscillation data set is indicated with the label “OSC” in the following.

For the cosmological part, we will describe the universe using the ΛCDM model and its six parameters: the baryon and cold dark matter densities, ${\Omega }_b{h}^2$ and ${\Omega }_c{h}^2$; the optical depth to reionization, τ; the angular scale of the acoustic peaks through Θ_s and the amplitude $log(10^{10}{A}_s)$ and tilt n_s of the power spectrum of initial curvature perturbations. In addition, we add the effect of the three massive neutrinos computing the evolution of the cosmological observables assuming three independent mass eigenstates, which, in terms of the parameters involved in our analyses, read as m₁ = m_lightest $(m_1=\sqrt{m_{\text{lightest}}^2+\left|\Delta m_{31}^2\right|})$, $m_2=\sqrt{m_{\text{lightest}}^2+\Delta m_{21}^2}$ $(m_2=\sqrt{m_{\text{lightest}}^2+\left|\Delta m_{31}^2\right|+\Delta m_{21}^2})$ and $m_3=\sqrt{m_{\text{lightest}}^2+\Delta m_{31}^2}$ (m₃ = m_lightest) for normal (inverted) neutrino mass orderings.

When considering cosmological data, we will focus on the Planck measurements of the CMB spectrum and on the most recent results from BAO observations. For the former we consider the 2015 Planck release (Adam et al., 2016; Ade et al., 2016b) of the high-ℓ likelihood (Aghanim et al., 2016a), together with a prior on τ as obtained in the 2016 intermediate results (Aghanim et al., 2016b). For the purposes of our analyses, this will be sufficient to mimic the final Planck release which is expected within the next few months. Complementary to the CMB, we include in our calculations the final constraints from the SDSS BOSS experiment, the DR12 release, in the form denoted as “final consensus” Alam et al. (2017), which provides constraints from observing 1.2 million massive galaxies in three separate bands at effective redshifts 0.38, 0.51, and 0.61, plus results from the 6DF survey at z = 0.106 (Beutler et al., 2011) and from the SDSS DR7 MGS survey at z = 0.15 (Ross et al., 2015). The combined dataset including the mentioned CMB and BAO data will be denoted as “Cosmo.”

In addition, we shall impose a prior on the Hubble parameter as obtained in the recent results from Riess et al. (2016): $H_0=(73.24\pm 1.74){\mathrm{\text{km s}}}^{-1}{\mathrm{\text{Mpc}}}^{-1}$. We will denote the data combinations including this prior with the label “H₀.”

Finally, concerning neutrinoless double beta decay, we vary the two Majorana phases in the entire available range (0–2π) and the NMEs according to the range allowed by recent theoretical calculations. We revised the NME ranges adopted in Gariazzo et al. (2018a), which were the ones suggested in Giuliani and Poves (2012). Here we use these new ranges: [3.3 – 5.7] for ⁷⁶Ge and [1.5 – 3.7] for ¹³⁶Xe, following the 1σ range proposed in Vergados et al. (2016).

We use 0νββ data from the ¹³⁶Xe experiments KamLAND-Zen Gando et al. (2016) and EXO-200 Albert et al. (2014) and from the ⁷⁶Ge experiment Gerda, for which we use the results in Agostini et al. (2017b), since the latest publication Agostini et al. (2018) does not contain enough information that allows us to parameterize a likelihood function. The most stringent bounds, anyways, still come from KamLAND-Zen, so that not including the new Gerda results does not affect significantly our results. For the very same reason we do not include the results of CUORE Alduino et al. (2018a), for which the uncertainty on the NME of ¹³⁰Te is very large and the constraints corresponding to most of the values of ${{M}}_{{}^{130}\text{Te}}^{0\nu }$ are much looser than the ones from KamLAND-Zen, and of CUPID-0 Azzolini et al. (2018), which establishes a much less stringent limit on the ⁸²Se half-life. The complete neutrinoless double beta set of data will be denoted as “0νββ.”

All the previously listed data are coded as likelihood terms in a full Bayesian analysis. We compute the cosmological quantities using the Boltzmann solver CAMB Lewis et al. (2000), the likelihoods using the interface provided by CosmoMC Lewis and Bridle (2002), modified in order to take into account the oscillation and neutrinoless double beta decay data, while the calculation of the Bayesian evidence is committed to PolyChord Handley et al. (2015a,b).

5.3. Constraints on the Mass Orderings

The main results are depicted in Figure 10. The first data point corresponds to the Bayesian evidence from oscillation data only. Notice that the Bayes factor [ln(B_{NO, IO}) = 6.5 ± 0.2 for concreteness] indicates strong evidence for the normal mass ordering from oscillation data only. This Bayes factor is translated into a ~ 3.2σ evidence favoring normal mass ordering. This result was expected in light of the results presented in section 2, arising from the frequentist joint analysis. There it was reported a Δχ² = 11.7 in favor of the normal mass ordering from the combination of all long baseline, reactor and atmospheric data, which corresponds, roughly, to ~ 3.4σ. Adding information from neutrinoless double beta decay searches does not affect the Bayesian analysis, as shown by the second data point in Figure 10, and as expected from previous work Gariazzo et al. (2018a).

FIGURE 10

Figure 10. Graphical visualization of the Bayesian factors comparing normal and inverted ordering.

Once CMB and BAO measurements are also added in the Bayesian analysis, ln(B_{NO, IO}) = 7.4±0.3 is obtained (see the third point in Figure 10), improving the significance of the preference for normal ordering from ~3.2σ to ~3.4σ. Notice that, even if the preference for the normal neutrino mass ordering is mostly driven by oscillation data, the information provided by cosmological observations is more powerful than that in the analysis carried out in Gariazzo et al. (2018a), as the Bayesian analyses here also include BAO measurements, together with CMB data. Indeed, from the two Bayes factors obtained considering oscillation data only [ln(B_{NO, IO}) = 6.5±0.2] and oscillation plus cosmological measurements [ln(B_{NO, IO}) = 7.4±0.3], it is straightforward to infer the probability odds for normal ordering arising exclusively from cosmology. By doing so, one obtains odds of 2.7:1 for the normal ordering against the inverted one, in perfect agreement with the analyses of Vagnozzi et al. (2017), where odds of 2.4:1 with cosmological data only were reported when considering the very same data sets adopted here (albeit the odds were derived with an alternative method).

Finally, the addition of the prior on the Hubble constant raises the evidence for the normal ordering to ln(B_{NO, IO}) = 7.7 ± 0.3 (i.e., ~ 3.5σ). This improvement is expected, as previously explained in section 4, since a prior on the Hubble constant breaks the degeneracy between ∑m_ν and H₀ and, therefore, sharpens the neutrino mass bounds from cosmology. By performing a similar exercise to the one previously quoted, one finds that the odds for normal vs. inverted ordering from cosmology data only are 3.3:1 for the combination of CMB, BAO plus the H₀ prior, again in excellent agreement with the results obtained in Vagnozzi et al. (2017).

6. Future Prospects

In this last section, we will explore the future prospects for the detection of the neutrino mass ordering. Let us clarify that many of the proposed methods are much less robust than the ones involving neutrino oscillations through matter (see section 6.1), and will likely give their first results much after the first experimental 5σ determinations which are likely to be reached in the next 5−10 years. Many of the discussed methods, indeed, will give constraints on the neutrino mass ordering only as a secondary product of their operation and not as a main result, hence they are not optimized nor mainly focused on the mass ordering determination. Nevertheless, it is interesting to discuss these additional methods for different reasons. First of all, independent tests of the neutrino mass ordering from different methods are surely welcome to have more robust results. Secondly, the different methods can provide complementary information: if some inconsistencies or anomalies will appear, we will have new hints for our quest toward new physics beyond our current knowledge. In conclusion, even if the question regarding the neutrino mass ordering will be solved within the next few years by the currently running experiments or their immediate extensions, its study through the other methods we discuss here will be useful to shed more light on the topic and provide more interesting information on neutrino physics and beyond. This is why we do not focus only on neutrino oscillation experiments (section 6.1), which will probably provide the first and strongest results, but also on more exotic cases as determinations from decay experiments (sections 6.2 and 6.3) cosmological constraints (section 6.4), measurements from the 21 cm surveys (section 6.5), and probes which involve neutrinos emitted by core-collapse supernova explosions (section 6.6) or relic neutrinos from the early Universe (section 6.7).

6.1. Prospects From Oscillations

As we have seen in section 2, the combination of all current neutrino experiments leads to a preference for normal ordering of 3.4σ, within the context of the latest frequentists global data analyses. The Bayesian analysis described in the previous section confirms these results, as we have reported a 3.2σ evidence for normal mass ordering. In principle, one may expect to achieve further sensitivity on the neutrino mass ordering from more precise data by the current long-baseline and atmospheric neutrino experiments, since these experiments will still run for some time before the new experiments will take over. However, it is not easy to predict the final results of current experiments, since the sensitivity to the mass ordering is highly correlated to the true value of the CP phase δ_CP. The NOνA experiment alone expects a 3σ sensitivity for 30–50% of the values of δ_CP by 2,024 Himmel (2018). If δ_CP = 3π/2, the expected sensitivity would be higher than that and, then, a very strong result could be obtained by 2,024 Himmel (2018). Note, however, that the NOνA sensitivity analysis considers a fixed value of θ₁₃ and does not marginalize over $\Delta m_{31}^2$. Upgrading T2K to T2K-II will improve the sensitivity substantially, since the experiment should gather around 20 × 10²¹ POT by 2026, which would be roughly 6 times the current amount of data²³. Combining beam data from T2K with atmospheric data from SK can improve the sensitivity even further, as shown in Abe et al. (2018a). Performing a combined fit of T2K, NOνA and eventually SK could bring the sensitivity to the 5σ level within a few years. In any case, apart from the combinations of different experiments, a very robust determination of the neutrino mass ordering from a single current experiment seems rather unlikely. Indeed, one of the main goals of the next-generation neutrino oscillation experiments, including new long-baseline, reactor, and atmospheric neutrino detectors, will be to perform the determination of the mass ordering by a single experiment. The upcoming facilities will be able to measure the neutrino mass ordering with astonishing precision. In this section we briefly discuss some of the proposed projects and their physics potential.

Long-Baseline Experiments

The Deep Underground Neutrino Experiment (DUNE) (Acciarri et al., 2015, 2016a,b; Strait et al., 2016) will be a new long-baseline accelerator experiment, with a small near detector and a huge far detector with a fiducial mass of 40 kton located 1,300 km away from the neutrino source at Fermilab. With its powerful 1.1 MW beam, it will be exposed to around 15 × 10²⁰ POTs (protons on target) per year, which will lead to a huge number of events and therefore to high precision measurements of the neutrino oscillation parameters. As explained in section 2, the presence of matter affects differently the neutrino appearance probabilities for normal and inverted mass orderings. DUNE, with the longest baseline ever for an accelerator neutrino experiment, will be able to measure the neutrino mass ordering with a significance above 5σ for any set of the oscillation parameters (θ₂₃, δ_CP) after 7 years of data taking. Note that this sensitivity could be further increased by using an improved energy reconstruction method, as shown in De Romeri et al. (2016). On the other hand, the sensitivities could also be biased by the potential presence of new physics beyond the SM, such as non-standard neutrino interactions (Miranda et al., 2006; Coloma, 2016; Coloma and Schwetz, 2016; de Gouvêa and Kelly, 2016; Forero and Huber, 2016; Masud and Mehta, 2016; Bakhti and Khan, 2017; Coloma et al., 2017; Deepthi et al., 2017; Forero and Huang, 2017; Farzan and Tortola, 2018), deviations from unitarity Blennow et al. (2017); Dutta et al. (2017); Escrihuela et al. (2017) or the presence of light-sterile neutrinos (Berryman et al., 2015, 2016; Agarwalla et al., 2016; Coloma et al., 2018). Indeed, besides providing very precise information about the neutrino oscillation mechanism, the DUNE experiment will also be very useful to test different models for neutrino masses and mixings (Chatterjee et al., 2017a,b; Pasquini et al., 2017; Agarwalla et al., 2018b; Chakraborty et al., 2018; Srivastava et al., 2018a,b) as well as to check for various effects of new physics such as the ones mentioned above, neutrino decay scenarios (Coloma and Peres, 2017; Ascencio-Sosa et al., 2018; Choubey et al., 2018c), quantum decoherence Balieiro Gomes et al. (2018) or even CPT invariance (de Gouvêa and Kelly, 2017; Barenboim et al., 2018b,c) and Lorentz invariance (Barenboim et al., 2018a; Jurkovich et al., 2018).

There are also plans to build a larger version of the Super-Kamiokande detector, Hyper-Kamiokande Abe et al. (2018b), that will be very similar to its predecessor but with a fiducial mass of 560 kton, 25 times larger than Super-Kamiokande. The Hyper-Kamiokande detector will be a requirement for the upgrade of T2K, the T2HK (Tokai-to-Hyper-Kamiokande) experiment (Abe et al., 2015). The very massive detector together with the upgraded neutrino beam from J-PARC will guarantee a huge number of neutrino events and therefore larger statistics. As a consequence, T2HK will be able to determine the neutrino mass ordering after few years of running time with very high significance, as well as to explore new physics scenarios (see for instance Abe et al., 2017, 2018b; Agarwalla et al., 2018a). In combination with atmospheric data from Hyper-Kamiokande, a 3σ rejection of the wrong mass ordering would be expected after 5 years of data taking. A third project has been proposed as an extension of T2HK to Korea, the T2HKK (Tokai-to-Hyper-Kamiokande-and-Korea) experiment (Abe et al., 2018c). This proposal includes a second far detector facility for the J-PARC neutrino beam, located at 1,000–1,300 km from the source. The longer path traveled within the Earth by the neutrinos detected in T2HKK will result in an enhanced sensitivity to the neutrino mass ordering if compared to T2HK alone.

The synergies and complementarities among the three long-baseline proposals above, DUNE, T2HK and T2HKK, have been discussed in Ballett et al. (2017). It is found that the combination of their experimental results may significantly mitigate the limitations of a given experiment, improving the precision in both the determination of the mass ordering and the measurement of CP violation.

Note that, although here we have focused on the long-baseline side of DUNE and Hyper-Kamiokande, they are actually designed as multi-purpose experiments, with a rich physics program aiming to study the neutrino oscillations with accelerator, atmospheric and solar neutrinos as well as to detect neutrinos from astrophysical sources and proton decay.

Atmospheric Experiments

In atmospheric neutrino experiments, the sensitivity to the mass ordering comes from the matter effects that distort the pattern of neutrino oscillations inside Earth, see Equation (4). Based on the oscillatory pattern that depends on the reconstructed neutrino energy and zenith angle, an ideal experiment would observe a given number of events in each energy and zenith angle bin as shown in Figure 11. Comparing the observed two-dimensional histograms with the theoretical ones for normal (Left) or inverted ordering (Right) allows to determine the true mass ordering that is realized in nature. In the following we list some of the future projects with this aim.

FIGURE 11

Figure 11. Expected number of events (arbitrary units) for an hypothetical atmospheric neutrino detector with perfect energy resolution as a function of the reconstructed neutrino energy E and the cosine of the zenith angle cosθ_z, for normal (Left) and inverted (Right) ordering.

The Oscillation Research with Cosmics in the Abyss (ORCA) experiment Adrian-Martinez et al. (2016) will be a large neutrino telescope placed deep inside the Mediterranean sea. It will detect the Cherenkov light emitted by the muons and electrons created by the interactions of atmospheric neutrinos in the sea and that propagate into water. Unlike its precursor, ANTARES, with 12 lines and a separation of 70 meters between neighboring optical modules, ORCA will have 60 lines with modules separated by 9 m. Due to the matter effects on the propagation of atmospheric neutrinos, the ORCA experiment will be able to measure the neutrino mass ordering with very good precision. In particular, a 3σ determination of the mass ordering can be expected after only 3 years of data taking, with even higher significance for the case in which nature has chosen normal ordering and the upper octant for the atmospheric mixing angle. Several studies have been performed in order to analyze the sensitivity of ORCA to the standard oscillation parameters (Ribordy and Smirnov, 2013; Yañez and Kouchner, 2015). Its potential to determine the Earth matter density through neutrino oscillation tomography Winter (2016) or to test new physics scenarios (Ge et al., 2017; Capozzi et al., 2018b) have also been extensively discussed.

PINGU (Precision IceCube Next Generation Upgrade) (Aartsen and Adelaide, 2014) is a planned upgrade of the IceCube DeepCore detector, an ice-Cherenkov neutrino telescope which uses the antarctic ice as a detection medium. The IceCube design aims at the detection of very high energy neutrinos, with an energy threshold above the relevant energy range for neutrino oscillations. However, the denser instrumented region DeepCore allows IceCube to decrease its energy threshold down to E_th = 6.3GeV. A further improvement with an even denser zone, PINGU, could lower E_th to only a few GeV. With this very low-energy threshold, one of the main purposes of PINGU is the determination of the neutrino mass ordering, with expected sensitivities similar to the ORCA experiment²⁴. Besides that, PINGU is expected to have the best sensitivity to ν_τ appearance and to determine accurately the octant of the atmospheric mixing angle. The PINGU capabilities to detect high-energy supernova neutrinos (Murase, 2018), and to investigate scenarios beyond the Standard Model, such as non-standard interactions (Choubey and Ohlsson, 2014) or dark matter self-interactions (Chen et al., 2014; Robertson and Albuquerque, 2018) have been also analyzed in the literature.

The India-based Neutrino Observatory (INO) is a very ambitious project, aiming to detect atmospheric neutrinos with a 50 kton magnetized iron calorimeter (ICAL) (Ahmed et al., 2017). The most outstanding feature of the INO experiment will be its capability to distinguish neutrinos from antineutrinos in an event by event basis. As a result, the identification of the matter effects in the neutrino and antineutrino propagation will be much cleaner in comparison with the sea water/ice Cherenkov detectors. Indeed, one of the main scientific goals of INO will be the determination of the neutrino mass ordering (Ghosh et al., 2013). According to the Physics White Paper of the ICAL (INO) Collaboration Ahmed et al. (2017), after 10 years run, INO will be able to identify the correct neutrino mass ordering with a significance larger than 3σ. As the experiments discussed above, the atmospheric neutrino results from INO can also be used to test the presence of new physics beyond the SM, such as CPT- or Lorentz violation (Chatterjee et al., 2014), sterile neutrinos (Behera et al., 2017; Thakore et al., 2018), dark matter related studies Dash et al. (2016); Choubey et al. (2018a), non-standard neutrino interactions Choubey et al. (2015) or decaying neutrinos (Choubey et al., 2018b).

Medium-Baseline Reactor Experiments

We have focused so far on extracting the neutrino mass ordering from matter effects in the neutrino propagation through the Earth interior. An alternative technique is that provided by medium-baseline reactor neutrino experiments Petcov and Piai (2002). For baselines of the order of 50 km, the survival probability for reactor antineutrinos exhibits a pattern that may allow the discrimination between normal and inverted mass orderings. Indeed, for such distances, the electron antineutrino survival probability is given by the following expression:

$\begin{array}{cc}\begin{array}{l}{P}_{{\overline{\nu }}_e\to {\overline{\nu }}_e}=1-{\cos }^4{\theta }_{13}{\sin }^{2}2{\theta }_{12}{\sin }^2{\Delta }_{21}\\ -{\sin }^{2}2{\theta }_{13}[{\sin }^2{\Delta }_{31}+{\sin }^2{\theta }_{12}{\sin }^2{\Delta }_{21}\cos 2{\Delta }_{31}\\ \mp \frac{{\sin }^2{\theta }_{12}}{2}\sin 2{\Delta }_{21}\sin 2\left|{\Delta }_{31}\right|],\end{array}& (22)\end{array}$

where ${\Delta }_{ij}=\frac{\Delta m_{ij}^{2}L}{4E}$ and the minus (plus) sign in the last term corresponds to normal (inverted) mass ordering. This probability contains a main oscillatory term with a frequency given by the solar neutrino mass splitting $\Delta m_{21}^2$, plus an additional term whose frequency depends on the sign of the atmospheric splitting $\Delta m_{31}^2$, i.e., on the neutrino mass ordering. The effect of the ordering over the neutrino survival probability in a medium-baseline reactor experiment is illustrated in Figure 12. There, we depict in black the oscillatory term corresponding to the solar splitting frequency. The red (blue) line corresponds to the full neutrino survival probability for normal (inverted) mass ordering. Note that this plot was obtained using the best-fit values from Table 1 for each ordering.

FIGURE 12

Figure 12. Electron antineutrino survival probabilities in a medium-baseline reactor experiment with L = 53 km. The red (blue) line corresponds to normal (inverted) mass ordering using the best-fit values from Table 2, while the black line contains the main term in the survival probability, given by the solar mass splitting frequency by setting $\Delta m_{31}^2=0$.

The Jiangmen Underground Neutrino Observatory (JUNO) An et al. (2016) is a 20 kton multi-purpose underground liquid scintillator detector. The site of the experiment, located 53 km away from the Yangjiang and Taishan nuclear power plants in China, was chosen to optimize its sensitivity to the neutrino mass ordering, one of its main physics goals. Like any other reactor neutrino experiment, JUNO will be sensitive to the disappearance of electron antineutrinos, with about 10⁵ events expected after 6 years of run time. From this high-statistics data sample, JUNO will try to reconstruct with extremely good precision the neutrino oscillation spectrum and to discriminate the different high-frequency behavior for normal and inverted mass ordering, as illustrated in Equation (22) and Figure 12. For a projected energy resolution of 3% at 1 MeV, JUNO will be able to establish the neutrino mass ordering at the level of 3-4σ in 6 years. Its combination with the PINGU facility could lead to a high significance improvement of the individual capabilities of these two experiments (see Blennow and Schwetz, 2013).

Apart from the mass ordering, JUNO will also provide precision measurements of the solar oscillation parameters, θ₁₂ and $\Delta m_{21}^2$, with an accuracy of around 1%. In this sense, JUNO might help to solve the observed disagreement between the mass splitting measured at solar experiments and at the reactor experiment KamLAND. If the discrepancy persists after new measurements by JUNO and future solar results by Super-Kamiokande, it could be considered as an indication of new physics Farzan and Tortola (2018). Moreover, JUNO will be sensitive to different types of new physics scenarios beyond the SM, as studied in Khan et al. (2013), Bakhti and Farzan (2014), Girardi et al. (2014), Li and Zhao (2014), Ohlsson et al. (2014), Abrahão et al. (2015), Liao et al. (2017), Zhao et al. (2017), and Krnjaic et al. (2018).

In parallel to JUNO, there is a proposal to extend the already existing experiment RENO with a third medium-baseline detector located at a distance of 47 km. This new project is known as RENO-50 Kim (2015), given its location, at approximately 50 km from the Hanbit power plant, in South Korea. The detector would consist of a 18 kton ultra-low-radioactive liquid scintillator instrumented with 15,000 high quantum efficiency photomultiplier tubes. Using the same technique described above, RENO-50 will be able to determine the neutrino mass ordering as well as the solar oscillation parameters with extremely good precision. Conceived as multi-purpose detectors, JUNO and RENO-50 will have a wide physics program, including not only the observation of reactor and solar neutrinos, but also neutrinos from supernova bursts, the diffuse supernova neutrino background, atmospheric neutrinos and geoneutrinos.

6.2. Prospects From Beta-Decay Experiments

As already mentioned in section 3, the determination of the mass ordering through the observation of the energy spectrum near the endpoint of β-decay or similar will be extremely challenging, because an impressive energy resolution is required to distinguish the kink due to the second and third mass eigenstates in the spectrum. We list here the main projects that aim at detecting the neutrino mass in the future and comment their perspectives for the mass ordering determination.

The first experiment we will comment on is KATRIN, which has recently started operations and aims at a detection of the effective electron antineutrino mass with a sensitivity of 0.2 eV (Angrik et al., 2004; Sejersen Riis et al., 2011). The first results from KATRIN are expected in early 2019, but the final target statistics will be reached after 3 year of data taking. Thanks to the detailed study of the detector systematics which has been carried out, it is possible that the final mass determination will reach a better sensitivity than the nominal one of 0.2 eV, eventually reaching something closer to 0.1 eV (Parno, 2018). Even with the more optimistic sensitivity, however, it will be impossible for KATRIN to determine the mass ordering.

Other tritium experiments exploiting different technologies include the Project-8 (Doe et al., 2013; Asner et al., 2015; Esfahani et al., 2017) experiment, which will use the Cyclotron Radiation Emission Spectroscopy (CRES) in order to determine the mass of the electron antineutrino. The technique consists in measuring the frequency of cyclotron radiation emitted by the electrons released during tritium decay and spiraling into a magnetic field. The frequency can then be related with the electron energy and consequently the energy spectrum can be determined. At the moment, Project-8 is in the calibration phase (phase-II) (Rybka, 2018) for a small prototype which will not have enough sensitivity to be competitive in the determination of the neutrino mass. Next phases include a large volume system using molecular tritium (phase-III), starting in 2020, which will be competitive in determining the neutrino mass and will serve as an intermediate step before moving to phase-IV, which will use atomic tritium, required in order to avoid uncertainties related to the existence of excited molecular tritium states. Project-8 in its atomic tritium phase is expected to reach the sensitivity $m_{{\bar{\nu }}_e}\lesssim 40$ meV with an exposure of 10−100 m³ year, sufficient to probe the values of $m_{{\bar{\nu }}_e}$ allowed in the context of inverted ordering (Esfahani et al., 2017), so that in case of no observation we will know that the ordering of neutrino masses must be normal.

Another interesting class of the experiments includes the HOLMES (Alpert et al., 2015; Giachero et al., 2017) and ECHo (Eliseev et al., 2015) experiments, which both aim at the determination of the electron neutrino mass through observations of the endpoint of the electron capture decay of ¹⁶³Ho, which practically proceeds through the measurement of de-excitation transitions of the Dy atoms, which are produced in the process ${}^{163}\mathrm{\text{Ho}}+e^{-}{\to }^{163}{\mathrm{\text{Dy}}}^{*}+{\nu }_e$ (De Rujula and Lusignoli, 1982). As for the tritium β-decay, also the endpoint of the ¹⁶³Ho electron capture spectrum depends on the value of the neutrino masses and, in principle, it would be possible to determine the mass ordering in this way. Besides the experimental and theoretical problems that the HOLMES and ECHo collaborations must face, however, it seems that the current technology is not yet at the level of precision required for the mass ordering determination. The HOLMES demonstrator, currently running, should reach a sensitivity of m_νe≲10 eV by the end of 2018, while the full-scale experiment, possibly starting in 2019, has a target sensitivity of m_νe≲1 eV (Gastaldo, 2018). ECHo, on the other hand, is running a first phase (ECHo-1k) which has also a target of m_νe≲10 eV in 1 year, while the full scale ECHo-100k will reach m_νe≲1.5 eV in 3 year of data taking, expected to start in 2019 (Gastaldo, 2018). Both results are impressive when compared with the current upper limit on the electron neutrino mass using the same isotope, which is 225 eV (Springer et al., 1987), more than two orders of magnitude larger.

Finally, to conclude this subsection we want to mention that the PTOLEMY proposal (Betts et al., 2013; Baracchini et al., 2018), aiming at the detection of the relic neutrino background and recently approved by the Scientific Committee of the Laboratori Nazionali del Gran Sasso (LNGS), will be able to study and possibly determine the mass ordering through the observation of the β-spectrum of tritium decay. PTOLEMY will be discussed later in section 6.7.

6.3. Prospects From Neutrinoless Double Beta Decay

We list here the future perspectives for neutrinoless double beta decay experiments in terms of sensitivity to the half-life for the processes of interest (where possible). As we already commented in section 3.2, the conversion between the half-life $T_{1/2}^{0\nu }$ and the effective Majorana mass m_ββ depends on the NME and the phase space factor of the process of interest, see Equation (7). In order to exclude the inverted ordering allowed range for m_ββ (in case there is no sterile neutrino), one would need to constrain m_ββ ≲ 10 meV, which corresponds to $T_{1/2}^{0\nu }\simeq 1\times 10^{28}$ year, with some dependence on the material (phase space and NME). This means that none of the current generation experiments will be able to reach the required sensitivity, and we will have to wait for next-generation upgrades and new projects. Many of the information listed in the following has been taken from Agostini et al. (2017a) and Giuliani (2018).

Current Generation Experiments

Let us firstly address the current generation of experiments, which at most will be able to start exploring the three-neutrino inverted mass ordering regime or to probe the upper range for m_ββ allowed within the 3+1 neutrino scenario. The experiments will be listed in alphabetical order.

AMoRE Alenkov et al. (2015) is an experiment devoted to determine the life-time of ¹⁰⁰Mo. After a first pilot run, the current status (AMoRE-I) is to test the technology with a ¹⁰⁰Mo mass of 5-6 kg, in order to demonstrate the scalability before moving to the full scale (AMoRE-II) detector, which will use 200 kg of material and is expected to start around 2020, with a final target sensitivity of $T_{1/2}^{0\nu }\simeq 5\times 10^{26}$ year.

CUORE Artusa et al. (2015) and Alduino et al. (2016, 2018b), already mentioned in section 3.2, works with ¹³⁰Te and is already taking data with the full scale detector, which will have as ultimate sensitivity $T_{1/2}^{0\nu }\simeq 9\times 10^{25}$ year after 5 year of data taking (Adams et al., 2018; Ouellet, 2018).

The KamLAND-Zen experiment (Gando et al., 2016; Gando, 2018), after the previous successful data taking period, is now upgrading the detector for a new observation run with approximately 750 kg of ¹³⁶Xe and a new balloon inside the KamLAND detector. The target sensitivity for the upcoming phase is around $T_{1/2}^{0\nu }\simeq 5\times 10^{26}$ year, a factor of five larger than the current limit (Gando et al., 2016).

A smaller experiment is NEXT (Mart́ın-Albo et al., 2016), which is running background studies in the Canfranc laboratories in Spain. NEXT will use high pressure ¹³⁶Xe TPCs, which will allow an impressive tracking of the emitted particles through scintillation and electroluminescence. A prototype with 10 kg of natural Xenon will start data taking this year to demonstrate that the expected background control and particle tracking have been achieved. In 2019 NEXT is expected to start a new phase with 100 kg of ¹³⁶Xe, which will reach $T_{1/2}^{0\nu }\simeq 1\times 10^{26}$ year with 5 year of data.

A similar project is called Panda-X-III (Chen et al., 2017), which is based in the Jinping underground laboratories in China. Panda-X-III will run the first phase using 200 kg of ¹³⁶Xe to reach $T_{1/2}^{0\nu }\simeq 1\times 10^{26}$ year in 3 year.

Going to a different concept, SNO+ (Andringa et al., 2016) will feature a detector of 760 ton of ultra-pure liquid scintillator. SNO+ will be a multipurpose detector, as it will be capable of studying reactor, solar, supernova and geoneutrinos, and also to probe proton decay (Orebi Gann, 2018). After the background studies will be completed, a 0.5% loading will be performed, inserting ¹³⁰Te in the detector to measure double beta decay processes. The target sensitivity after 5 year is $T_{1/2}^{0\nu }\simeq 2\times 10^{26}$ year. Future plans for the SNO+ experiment include the further ¹³⁰Te loading to 1%, or even more, of the detector mass, with the advantage that increasing the ¹³⁰Te amount will not influence the backgrounds but only the signal. The final target for this second phase is to reach $T_{1/2}^{0\nu }\simeq 1\times 10^{27}$ year, thus starting to cover the inverted ordering allowed range.

Let us finally comment the SuperNEMO experiment (Arnold et al., 2010; Patrick and Xie, 2017), which uses ⁸²Se for its study. SuperNEMO is particularly interesting because it will be able to perform a full topological reconstruction of the events, which is extremely important in case of detection because it opens the possibility to directly test the mechanism that underlies neutrinoless double beta decay and, in principle, to determine the lepton-number violating process. A first demonstrator of about 7 kg is expected to start in 2018 and to reach $T_{1/2}^{0\nu }\simeq 6\times 10^{24}$ year with 2.5 year of data. The subsequent plans include an extension with a ~100 kg scale detector with 20 modules, which will be able to probe $T_{1/2}^{0\nu }$ up to 1 × 10²⁶ year, and the possibility to use the ¹⁵⁰Nd isotope, for two reasons: to have a more favorable phase space when converting $T_{1/2}^{0\nu }$ to m_ββ and to get rid of the Rn background which affects the ⁸²Se measurements (Giuliani, 2018).

As a summary, some of the current generation experiments will be able to probe the inverted ordering range of m_ββ within the standard three neutrino framework and assuming an exchange of light Majorana neutrinos. However, none of them will be able to rule out completely the inverted mass ordering, because of the uncertainty related to the NMEs.

Next Generation Experiments

The situation will be different for the following generation of experiments, which are mostly the natural evolution of current experiments to the ton-scale of decaying material. With the increased amount of material, a larger statistics will be achieved and stronger bounds, of the order of $T_{1/2}^{0\nu }\simeq 1\times 10^{28}$ year, will be feasible. We briefly discuss here the main current proposals for the next 10–20 years. The time schedules for these projects will be necessarily vague, as they will depend on the results of the present ones.

Let us start with CUPID (CUORE Upgrade with Particle ID) (Wang et al., 2015; Azzolini et al., 2018), which will be the evolution of the previously discussed CUORE experiment. The goal of CUPID is to use particle tracking in order to have a better discrimination of background and ultimately allow a background-free experiment: the target is < 0.1 counts/(ton year) (Ouellet, 2018). A first demonstrator, named CUPID-0 (Azzolini et al., 2018), is already running with about 5 kg of ⁸²Se, and already obtained the strongest-to-date constraint on the life-time on this isotope. In order to reach the target sensitivity $T_{1/2}^{0\nu }\gtrsim 1\times 10^{27}$ year, however, further improvement in the crystals quality and radio-purity is required. A full development plan for CUPID is currently under discussion.

Although not specifically designed for neutrinoless double beta decay searches, the DARWIN (DARk matter WImp search with liquid xenoN) experiment (Aalbers et al., 2016) will have sensitivity to a number of rare decay phenomena. The primary target of DARWIN is to perform direct detection of dark matter in a wide mass-range of the experimentally accessible parameter space for Weakly Interacting Massive Particles (WIMPs), to the level at which neutrino interactions with the target become an irreducible background (the so-called neutrino floor). The core of the detector will be a multi-ton liquid xenon time projection chamber. Having a large mass, low-energy threshold and ultra-low background level, DARWIN will also search for solar axions or galactic axion-like particles, measure the low-energy solar neutrino flux with < 1% precision, observe coherent neutrino-nucleus interactions, detect galactic supernovae neutrinos and study the double beta decay of ¹³⁶Xe (Aalbers et al., 2016). Even if it will be build using natural Xenon without isotope enrichment, DARWIN will contain 3.5 t of ¹³⁶Xe. If the target energy resolution of 1−2% at 2.5 MeV will be achieved, the sensitivity of DARWIN will be $T_{1/2}^{0\nu }\simeq 5.6\times 10^{26}$ year with an exposure of 30 t yr (Aalbers et al., 2016). The estimated ultimate sensitivity, which will be achieved only with a complete mitigation of the material background and 140 t year of exposure, is claimed to be $T_{1/2}^{0\nu }\simeq 8.5\times 10^{27}$ year (Aalbers et al., 2016).

The successor of KamLAND-Zen, KamLAND2-Zen (Shirai, 2017; Gando, 2018; Giuliani, 2018) will benefit the upgrades of KamLAND into KamLAND2, including the improved light collection and better energy resolution guaranteed by the new photomultipliers, together with an increased amount of ¹³⁶Xe, to reach at least 1 ton of material. These upgrades will be performed after the completion of KamLAND-Zen 800, expected to start this year. The target sensitivity after 5 year will be m_ββ ≲ 20 meV²⁵, sufficient for “fully covering the inverted ordering region” (Shirai, 2017). Future studies will also test the possibility to accommodate scintillating crystals inside the detector and run a multi-isotope experiment.

Back to ⁷⁶Ge-based experiments, the efforts of the Gerda and Majorana collaborations will join to work on the LEGEND (Large Enriched Germanium Experiment for Neutrinoless Double beta decay) experiment. Learning from both its precursors, LEGEND will need further background rejection and will be built in different phases. The first module, LEGEND-200, made of 200 kg of Germanium and expected to start in 2021, will be built on top of the existing Gerda infrastructures and will have a target sensitivity $T_{1/2}^{0\nu }\simeq 1\times 10^{27}$ year in 5 year. The full scale detector, LEGEND-1000, consisting in several modules summing up to a total of 1 ton of material, will have as an ultimate goal $T_{1/2}^{0\nu }\simeq 1\times 10^{28}$ year in 10 year (Abgrall et al., 2017), giving a full coverage of the inverted mass ordering region.

Even larger in size, nEXO (Albert et al., 2018; Kharusi et al., 2018) will replace the EXO-200 experiment after its completion, expected this year. The new detector will use 5 ton of Xenon in order to reach $T_{1/2}^{0\nu }\simeq 1\times 10^{27}$ year with just 1 year of data and $T_{1/2}^{0\nu }\simeq 1\times 10^{28}$ year with the full statistics, after 10 year.

After the completion of the upcoming phase, NEXT-100 will be possibly upgraded into NEXT 2.0, which will need a 1.5 ton of Xenon to obtain the statistics for achieving $T_{1/2}^{0\nu }\simeq 1\times 10^{27}$ year after 5 year of running (Agostini et al., 2017a; Giuliani, 2018).

In the same way, the Panda-X-III collaboration is also planning a 1 ton scale phase II with a target of $T_{1/2}^{0\nu }\simeq 1\times 10^{27}$ year (Chen et al., 2017).

The last comment regards another interesting possibility related to the SNO+ experiment. The THEIA proposal (Orebi Gann, 2015) is a concept study for a gigantic detector of something around 30–100 kton of target material which will use water-based liquid scintillator. Such target allows to track both Cherenkov and delayed scintillation light, thus enabling high light yield and low-threshold detection with attenuation close to that of pure water. The result is that such a detector would be able to achieve excellent background rejection thanks to directionality, event topology, and particle ID, with very large statistics. Loading of metallic ions which can undergo neutrinoless double beta decay would enable to use the THEIA detector for studying the Dirac/Majorana nature of neutrinos. Given the size of the detector, a 0.5% loading will allow to store several tons of decaying material, which naturally result in huge statistics when compared with current experiments. A 3% loading with natural (not enriched) Tellurium will be sufficient to reach, assuming m_ββ≃15 meV, a 3σ discovery in 10 year (Alonso et al., 2014; Giuliani, 2018).

6.4. Prospects From Cosmology

There are a number of studies in the literature focused on forecasting the expected sensitivity from both future CMB and large scale structure surveys to the total neutrino mass ∑m_ν (de Putter et al., 2009; Abazajian et al., 2011; Carbone et al., 2011, 2012; Hamann et al., 2012; Basse et al., 2014; Font-Ribera et al., 2014b; Allison et al., 2015; Archidiacono et al., 2017; Amendola et al., 2018; Di Valentino et al., 2018a; Sprenger et al., 2018).

Awaiting for very futuristic measurements which may allow for the extraction of each of the individual masses associated to the neutrino mass eigenstates (see section 4), the extraction of the neutrino mass ordering strongly relies on the error achieved on ∑m_ν for a chosen fiducial value of the neutrino mass.

A complete, updated and useful summary is provided in Table II of (Lattanzi and Gerbino, 2018), which shows the expected sensitivity [σ(∑m_ν)] from different future cosmological probes, assuming the fiducial value ∑m_ν = 0.06 eV. Nevertheless, the authors of Gerbino et al. (2017b) considered different fiducial values for the total neutrino mass and computed the odds for the normal vs. the inverted ordering for possible combinations of future cosmological probes including the current information from oscillation experiments. We shall comment on these results toward the end of this section.

6.4.1. CMB Prospects

Two main missions are expected to lead the next decade generation of CMB experiments, albeit a number of other experiments are in progress between now and then. The latter list includes ground-based observatories as the ACT (Atacama Cosmology Telescope) (De Bernardis et al., 2016), the SPT-3G (South Pole Telescope-3G) (Benson et al., 2014), the Simons Array (Suzuki et al., 2016), CLASS (Essinger-Hileman et al., 2014), BICEP3 (Ahmed et al., 2014), and the Simons Observatory²⁶. The two main missions are expected to be the CMB-Stage IV project (Abazajian et al., 2016) and CORE (Cosmic Origin Explorer) (Delabrouille et al., 2018). The former, the CMB-Stage IV project (Abazajian et al., 2016), expected to be the definitive ground-based CMB experiment, aims at 250000 detectors operating for 4 years, covering a 40% fraction of the sky. Depending on the beam size and on the effective noise temperature, CMB Stage IV could reach sensitivities of σ(∑m_ν) = 0.073 − 0.11 eV, assuming ∑m_ν = 0.058 eV as the fiducial model and an external prior on the reionization optical depth of τ = 0.06 ± 0.01, see (Abazajian et al., 2016) for the precise configuration details. The latter, CORE, a medium-size space mission proposed to the European Space Agency (ESA) (Delabrouille et al., 2018), is expected to have an one order of magnitude larger number of frequency channels and a twice better angular resolution than Planck. With these improved capabilities, CORE could achieve a sensitivity of σ(∑m_ν) = 0.044 eV (Di Valentino et al., 2018a; Lattanzi and Gerbino, 2018), for a fiducial total neutrino mass of 0.06 eV. As it is evident from these estimates, future CMB experiments alone will not be able to determine the neutrino mass ordering.

6.4.2. Large Scale Structure Prospects

From the large scale structure perspective, in analogy to the future CMB probes, there are also two main surveys, DESI (Dark Energy Spectroscopic Instrument) (Levi et al., 2013; Aghamousa et al., 2016), a ground-based telescope which will improve the SDSS-III and IV legacies (BOSS Dawson et al., 2013 and eBOSS galaxy surveys Dawson et al., 2016), and the Euclid space mission (Amendola et al., 2018). The baseline design of DESI assumes that it will run over 5 years, covering 14000 deg² of the sky targeting four different tracers: Bright, Luminous Red and Emission Line Galaxies plus quasars in the redshift interval (0.05 < z < 1.85), and a Lyman-α survey in the 1.9 < z < 4 redshift interval. The expected error in ∑m_ν from DESI and Planck data is 0.02 eV. This number corresponds, approximately, to a 2σ determination of the neutrino mass ordering in case neutrinos have the minimal mass within the normal ordering scenario (Aghamousa et al., 2016). The authors of (Font-Ribera et al., 2014b) have also explored a number of possible combinations of DESI with other surveys. Namely, combining DESI measurements with the final results from DES, an error of 0.017 eV in ∑m_ν could be achieved. Their most constraining result, σ(∑m_ν) = 0.011 eV, however, arises from an extension of the DESI survey, together with data from Euclid and LSST (Large Synoptic Survey Telescope) (Ivezic et al., 2008; Abell et al., 2009) (see below). In case this small error is achieved, the neutrino mass ordering can be determined with a high accuracy, again assuming a massless lightest neutrino and normal ordering. Other analyses have also reduced the nominal σ(∑m_ν) = 0.02 eV expected from the DESI survey replacing the Planck CMB information with that expected from the future CMB Stage IV (Abazajian et al., 2016) or CORE (Di Valentino et al., 2018a) probes.

Euclid, an ESA mission expected to be launched early in the upcoming decade, mapping ~15, 000 deg² of the sky, has also been shown to provide excellent capabilities to test the neutrino properties (Amendola et al., 2018). Euclid will focus on both galaxy clustering and weak lensing measurements, which, combined with Planck CMB data, will provide errors on the sum of the neutrino masses of σ(∑m_ν) = 0.04 eV (Carbone et al., 2011) and σ(∑m_ν) = 0.05 eV (Kitching et al., 2008), respectively, albeit exploiting the mildly non-linear regime could highly reduce these errors (Audren et al., 2013). While these errors are large to extract useful information concerning the neutrino mass ordering, the weak gravitational lensing abilities from Euclid have also been considered to extract the neutrino mass ordering when it lies far enough from the degenerate region (see e.g., Amendola et al., 2018). The addition of future CMB measurements, as those from CORE, could notably improve the expected Euclid sensitivity. The authors of Archidiacono et al. (2017) have shown that CMB measurements from CORE, combined with full shape measurements of the galaxy power spectrum and weak lensing data from Euclid, could reach σ(∑m_ν) = 0.014 eV. This result clearly states the complementarity of cosmic shear and galaxy clustering probes, crucial to test the neutrino mass ordering. Further improved measurements of the reionization optical depth τ could strengthen this bound and consequently the sensitivity to the ordering of the neutrino masses (Liu et al., 2016; Archidiacono et al., 2017; Sprenger et al., 2018), see the following section. Other future large scale structure surveys are the aforementioned LSST and WFIRST (Spergel et al., 2013, 2015), that will lead as well to accurate measurements of the total neutrino mass. Their combination with e.g., Euclid could provide an error of a few meV on the total neutrino mass, σ(∑m_ν) ≲ 0.008 eV (Jain et al., 2015).

The above neutrino mass (neutrino mass ordering) projected errors (sensitivities), even if strongly constraining, are highly dependent on the fiducial value of ∑m_ν, in the sense that the majority of the forecasts (a) are usually carried out assuming the minimal neutrino mass allowed within the normal ordering scheme, i.e., ∑m_ν≃0.06 eV²⁷; (b) the quoted sensitivities in the neutrino mass ordering are computed via an extrapolation of the error on the sum of neutrino masses rather than from proper Bayesian comparison tools. The authors of Gerbino et al. (2017b) found that a future CMB CORE-like satellite mission, even combined with a 1% measurement of the Hubble constant H₀ and with the future DESI survey (Font-Ribera et al., 2014b; Aghamousa et al., 2016) can not extract the ordering if nature has chosen a value for the neutrino masses of ∑m_ν = 0.1 eV. Odds for the normal vs. the inverted ordering of 1:1 were reported (Gerbino et al., 2017b). When considering the minimum allowed value for the total neutrino mass set by neutrino oscillation experiments, i.e., ∑m_ν = 0.06 eV, they quote odds of 3:2 (9:1) for the case in which CORE and the prior on H₀ without (with) DESI measurements are considered²⁸. Therefore, the next generation of CMB and large scale structure surveys will be sensitive to the mass ordering only if it is normal and the lightest neutrino mass is close to zero. The significance of such a measurement will crucially depend on how far ∑m_ν lies from its minimum allowed value from oscillation probes.

6.5. Prospects From 21 cm Surveys

Cosmological measurements of the redshifted 21 cm hydrogen line provide a unique test of the Epoch of Reionization (EoR) and the “dark ages,” the period before the first stars formed. The 21 cm line is due to spin-flip transitions in neutral hydrogen between the more energetic triplet state and the ground singlet state, and its intensity depends on the ratio of the populations of these two neutral hydrogen hyperfine levels. At a given observed frequency ν, the 21 cm signal can be measured in emission or in absorption against the CMB. The so-called differential brightness temperature δT_b therefore refers to the contrast between the temperature of the hydrogen clouds and that of the CMB, which, for small frequencies and up to first order in perturbation theory, reads as Madau et al. (1997); Furlanetto et al. (2006); Pritchard and Loeb (2012); Furlanetto (2015)

$\begin{array}{cc}\begin{array}{l}\delta T_b(\nu )\simeq 27x_{\text{HI}}(1+{\delta }_b)\left(1-\frac{T_{\text{CMB}}}{T_S}\right)\left(\frac{1}{1+H^{-1}\partial v_r/\partial r}\right)\\ {\left(\frac{1+z}{10}\right)}^{1/2}{\left(\frac{0.15}{{\Omega }_m{h}^2}\right)}^{1/2}\left(\frac{{\Omega }_b{h}^2}{0.023}\right)\text{mK},\end{array}& (23)\end{array}$

where x_HI is the fraction of neutral hydrogen, δ_b is the baryon overdensity, ${\Omega }_b{h}^2$ and ${\Omega }_m{h}^2$ the present baryon and matter contributions to the mass-energy budget of the Universe, H(z) the Hubble parameter and ∂v_r/∂r the comoving peculiar velocity gradient along the line of sight. Therefore, 21 cm cosmology aims to trace the baryon overdensities via transitions in neutral hydrogen.

There are a number of current and future experimental setups devoted to detect the 21 cm global signal averaged over all directions in the sky, as EDGES (Experiment to Detect the Reionization Step) (Bowman and Rogers, 2010), the future LEDA (Large Aperture Experiment to Detect the Dark Ages) (Greenhill and Bernardi, 2012) or DARE (Moon space observatory Dark Ages Radio Experiment) (Burns et al., 2012). The EDGES experiment has quoted the observation of an absorption profile located at a frequency of 78 ± 1 MHz, corresponding to a redshift of z ~ 17, with an amplitude of about a factor of two larger than the maximum expected in the canonical ΛCDM framework (Bowman et al., 2018). This recent claim has led to a number of studies aiming either to explain the effect or to constrain some non-standard scenarios (Barkana, 2018; Barkana et al., 2018; Berlin et al., 2018; Cheung et al., 2018; Clark et al., 2018; Costa et al., 2018; D'Amico et al., 2018; Ewall-Wice et al., 2018; Falkowski and Petraki, 2018; Feng and Holder, 2018; Fialkov et al., 2018; Fraser et al., 2018; Hektor et al., 2018; Hill and Baxter, 2018; Hirano and Bromm, 2018; Kang, 2018; Liu and Slatyer, 2018; Mahdawi and Farrar, 2018; McGaugh, 2018; Mitridate and Podo, 2018; Muñoz and Loeb, 2018; Muñoz et al., 2018; Pospelov et al., 2018; Safarzadeh et al., 2018; Slatyer and Wu, 2018; Witte et al., 2018; Yang, 2018).

Fluctuations in the redshifted 21 cm signal can be used to compute the power spectrum of the differential brightness temperature. This is the major goal of experiments as GMRT (Giant Metrewave Radio Telescope) (Ananthakrishnan, 1995; Paciga et al., 2011), LOFAR (LOw Frequency ARray) (van Haarlem et al., 2013), MWA (Murchison Widefield Array) (Tingay et al., 2013) and PAPER (Precision Array for Probing the Epoch of Reionization) (Parsons et al., 2010; Ali et al., 2015; Pober et al., 2015), targeting statistical power-spectrum measurements of the 21 cm signal employing large radio interferometers. Even if current experiments have not yet detected the 21 cm cosmological signature, the PAPER collaboration has recently improved the previous upper limits at z = 8.4 (Ali et al., 2015). Next decade, high-redshift 21 cm experiments include the SKA (Square Kilometre Array) (Mellema et al., 2013) and HERA (Hydrogen Epoch of Reionization Array) (Beardsley et al., 2015). A three-dimensional map of the 21 cm signal could also be obtained by means of the so-called intensity mapping technique, which measures the collective emission from neutral hydrogen in dense clumps, targeting large regions without resolving individual galaxies in the post-reionization era (z≲3) (Chang et al., 2008; Loeb and Wyithe, 2008; Wyithe et al., 2008; Villaescusa-Navarro et al., 2014b). The experimental efforts for this technique include the GBT-HIM project, with the GBT (Green Bank Telescope) (Chang et al., 2016), CHIME (Canadian Hydrogen Intensity Mapping Experiment) (Newburgh et al., 2014), the Tianlai project (Chen and Xu, 2016) and SKA-mid frequency (Dewdney et al., 2015)(see e.g., Bull et al., 2015).

Despite the fact that the primary task of future 21 cm experiments is to improve our current knowledge of the reionization history, they provide as well an additional tool for fundamental cosmology (Scott and Rees, 1990; Tozzi et al., 2000; Iliev et al., 2002; Barkana and Loeb, 2005a,b; McQuinn et al., 2006; Santos and Cooray, 2006; Bowman et al., 2007; Mao et al., 2008; Visbal et al., 2009; Clesse et al., 2012; Liu and Parsons, 2016; Liu et al., 2016), complementary to CMB missions and galaxy surveys. Indeed, 21 cm cosmological observations will play a very important role concerning neutrino physics. As previously stated, there are two types of experiments. First of all, we will have observations focused on the pre-reionization and EoR periods, that can probe very large volumes (where the non-linear scale is small). Remember that the largest signal from relic neutrino masses and their ordering appears at scales which, at the redshifts attainable at galaxy clustering surveys, lie within the mildly non-linear regime. Therefore, one needs to rely on either N-body simulations or on analytical approximations for the matter power spectrum to simulate the massive neutrino signature. EoR 21 cm experiments will achieve the scales required to observe the neutrino signature within the linear regime, avoiding the simulation problems described in section 4.2. In this regard, these probes may widely surpass the constraints on neutrino masses expected from even very large galaxy surveys (McQuinn et al., 2006; Mao et al., 2008; Pritchard and Pierpaoli, 2008; Tegmark and Zaldarriaga, 2009; Abazajian et al., 2011; Oyama et al., 2013, 2016; Shimabukuro et al., 2014). Furthermore, the neutrino constraints will be largely independent of the uncertainties in the dark energy fluid, which, as we have seen in section 4.3.2, have instead a non-negligible impact in lower redshift, galaxy survey measurements. This is a byproduct of using the 21 cm line to trace the matter overdensities: at redshifts z ≲ 2, the universe starts to be dominated by the dark energy fluid and the growth of matter perturbations is modified depending on the dark energy equation of state w(z), whose precise time-evolution remains unknown. Consequently, for a given perturbation in the matter fluid, a suppression in its structure growth could be either due to the presence of massive neutrinos or to an evolving dark energy fluid. Focusing at higher redshifts, the neutrino mass constraints from 21 cm probes will be largely independent of the uncertainties in the dark energy fluid properties.

Expectations from MWA, SKA and FFTT (Fast Fourier Transform Telescope) (Tegmark and Zaldarriaga, 2009) were considered in Mao et al. (2008). Focusing on 4000 h of observations of two areas in the sky in a range of z = 6.8−8.2 (divided into three redshift bins) and a value of k_max = 2 Mpc⁻¹, the reported errors on ∑m_ν are 0.19 (0.027), 0.056 (0.017), 0.007 (0.003) for MWA, SKA and FFTT, respectively, in their middle (optimistic) scenarios²⁹, when combined with Planck measurements. These forecasts were performed for a fiducial ${\Omega }_{\nu }{h}^2=0.0875$, which corresponds to a quite high value for the neutrino mass, lying in the fully degenerate neutrino mass spectrum.

The authors of Oyama et al. (2013) devoted a dedicated analysis to establish the potential for extracting the neutrino mass ordering combining the FFTT capabilities with future CMB polarization measurements. Based exclusively on the induced effect of the neutrino mass ordering on the cosmic expansion rate, a robust 90% CL neutrino mass ordering extraction was reported if ∑m_ν < 0.1 eV, regardless the underlying true ordering (i.e., normal or inverted). In Oyama et al. (2016), the authors propose to combine ground-based CMB polarization observations, SKA Phase 2 and BAO measurements from DESI. With these data sets, a 2σ extraction of the neutrino mass ordering seems feasible, unless the neutrino spectrum is degenerate. Notice that these results arise from the signature induced by the neutrino mass ordering in the cosmic expansion rate, as the minimum cutoff of the wavenumber in the 21 cm observations is k_min = 0.06h Mpc⁻¹, while the wavenumber corresponding to the neutrino free-streaming scale is k_min ≃ 0.02h Mpc⁻¹ for a 0.05 eV massive neutrino.

More futuristic 21 cm experiments, as FFTT, may open the possibility of going beyond measurements of the total neutrino mass ∑m_ν and measure the individual neutrino masses, revealing the uniqueness of such experiments for constraining the neutrino properties. As shown in Figure 9 in section 4, the differences in the power spectra for the two possible mass orderings are tiny. Therefore, exquisite precision measurements are required to identify such signatures. Galaxy surveys, already discussed in the previous section, are limited by two facts. The first one is related to non-linearities, which will not allow for a measurement of the power spectrum at scales k>0.2h Mpc⁻¹ at small redshifts, see section 4.2. Since the non-linear scale at z = 8 is k ≃ 3h Mpc⁻¹, both SKA and FFTT can measure the entire linear region and be more sensitive to the scale-dependent suppression, which is different in the two neutrino mass orderings. The second one is related to the fact that a galaxy survey requires a large number density of tracers to ensure a good sensitivity at small scales, while for 21 cm surveys, tracing the ubiquitous permeating hydrogen, a high-density antennae distribution will already warrant excellent small-scale sensitivities. One drawback of 21 cm probes are foregrounds, which should be kept under control.

The authors of Pritchard and Pierpaoli (2008) have studied the perspectives for extracting the individual neutrino masses with SKA and FFTT, finding that FFTT could be able to distinguish all the three neutrino masses from zero at the 3σ level, due to its enormous effective volume (see Figure 3 of Pritchard and Pierpaoli, 2008). Extracting the neutrino mass ordering directly from the individual masses, however, was shown to be a very difficult achievement. Our calculations show that, for the total neutrino mass we use here as a reference, ∑m_ν = 0.12 eV, the differences among the lightest (l), medium (m) and heaviest (h) neutrino mass eigenstates between the normal and inverted orderings are (|Δm_l|, |Δm_m|, |Δm_h|) = (0.015, 0.0209, 0.0059) eV, which, especially for the case of |Δm_h| = 0.0059 eV, are tiny and very difficult to resolve, even with very futuristic 21 cm measurements. While increasing the exposure of FFTT may improve its capabilities for this purpose (the error in the most optimistic FFTT scenario of Mao et al. (2008) is 0.003 eV), it seems an extremely challenging task. Figure 13 depicts the differences in the values of the three neutrino masses as a function of the total neutrino mass between inverted and normal orderings. We show with a dashed vertical line our representative case ∑m_ν = 0.12 eV (the present most constraining 95% CL upper limit) and another one for ∑m_ν = 0.34 eV (the most recent 95% CL bound from the Planck collaboration after the removal of systematics in their polarization data at high angular scales Aghanim et al., 2016b). Notice that, as expected, the differences between the values of the three neutrino masses decrease with the total neutrino mass. In this regard, the lower the neutrino mass, the easier it could be to single out the three neutrino mass eigenstates, because they are more separated. However, an extraction of the mass ordering in the non-degenerate region via the values of the individual neutrino masses seems very difficult. Indeed, Figure 13 illustrates the values of the individual neutrino masses for the heaviest, medium and lightest states for the normal and inverted orderings as a function of the total neutrino mass. The bands, from Top to Bottom , depict the errors σ(m_i) = 0.02 eV and σ(m_i) = 0.01 eV, together with the very futuristic FFTT one, σ(m_i) = 0.005 eV. For an error of σ(m_i) = 0.02 eV, there is no hope to disentangle the individual neutrino masses, as the error bands overlap for the heaviest, medium and lightest masses in all the parameter space. If instead one could achieve σ(m_i) = 0.01 eV, a measurement of the individual neutrino masses in the non-degenerate region could be possible at the 1−2σ level, but in order to unravel the ordering one would need very extreme conditions as, for instance, a value of ∑m_ν very close to 0.1 eV independently determined with very small errors. The bottom plot in Figure 14 shows the results if we assume the futuristic value of σ(m_i) = 0.005, expected to be achieved by FFTT. In this case, a measurement of the three neutrino masses will be achieved. Furthermore, in this (very optimistic) situation, the error bars will be, in principle, sufficiently small to detect the presence (or the lack) of two massive neutrino states with masses in the 0.02–0.03 eV range, required if the ordering is normal to explain ∑m_ν≃0.1 eV, which would strongly confirm the normal (or inverted) neutrino mass ordering. If σ(m_i) = 0.005, the detection of the mass ordering will still be possible even if ∑m_ν≲0.1 eV, since the error on ∑m_ν will allow to exclude the inverted ordering with great accuracy.

FIGURE 13

Figure 13. Differences in the masses for three neutrino mass eigenstates as a function of the total neutrino mass between inverted and normal orderings. The vertical dashed lines depict the value ∑m_ν = 0.12 eV and ∑m_ν = 0.34 eV, which are the present most constraining 95% CL limit on ∑m_ν Palanque-Delabrouille et al. (2015) and the latest 95% CL bound quoted by the Planck collaboration (Aghanim et al., 2016b), respectively. Different shades of colored bands indicate the possible errors which could be achieved by future cosmological experiments on the determination of single neutrino masses: 0.02 eV, 0.01 eV or 0.005 eV.

FIGURE 14

Figure 14. Values of the individual neutrino masses for the heaviest, medium and lightest mass eigenstates for the normal and inverted orderings as a function of the total neutrino mass. The panels, from Top to Bottom, depict the error bands σ(m_i) = 0.02 eV, σ(m_i) = 0.01 eV and σ(m_i) = 0.005 eV.

As already mentioned, another possibility is the so-called 21 cm intensity mapping, which will focus on low redshifts z ≲ 3 and will measure, with low angular resolution, the integrated 21 cm flux emitted from unresolved sources observing large patches of the sky. The lack of high angular resolution will result in a less precise measurement of non-linear scales. On the other hand, low angular resolution will imply a much faster survey. Future planned intensity mapping surveys are developed within the Phase 1 of the SKA experiment, which will include a wide and deep survey at low redshifts (z ≲ 3, the SKA1-MID array) and a narrow and deep survey at higher redshift (3 ≲ z ≲ 6, the SKA1-LOW array), and within the Phase 2 of SKA (SKA2). Since, in some sense, these intensity mapping probes will be complementary to future planned optical surveys, as DESI or Euclid, it makes sense to combine their expected results. The intensity mapping technique, as galaxy clustering, is also affected by bias uncertainties and non-linearities at small scales. Several studies have been carried out in the literature to unravel the perspectives of the intensity mapping technique in unveiling the neutrino properties. Some of them include the combination of the expectations from future large scale structure and intensity mapping surveys (Loeb and Wyithe, 2008; Visbal et al., 2009; Abazajian et al., 2011; Villaescusa-Navarro et al., 2015; Archidiacono et al., 2017; Sprenger et al., 2018). Notice that all these studies rely on different assumptions on the cosmological parameters, on the foregrounds and on the systematic uncertainties, therefore we can not do comparisons among them. Instead, we quote the most recent findings and the impact for an eventual future detection of the neutrino mass ordering.

The authors of Villaescusa-Navarro et al. (2015) found that, by combining SKA1-LOW with Planck measurements, the 95% CL error on ∑m_ν could be ~ 0.089 eV. It is remarkable that such a combination could potentially rule out the inverted ordering scenario, assuming that normal ordering is realized in nature. These authors also find that, under identical assumptions in the forecasted analyses, their combination of intensity mapping surveys (SKA1-LOW and MID) should be regarded as competitive with future spectroscopic surveys concerning neutrino mass properties. The authors of Archidiacono et al. (2017) showed that constraints of the future CORE CMB mission and galaxy redshift/weak lensing large scale structure surveys (as Euclid) on the neutrino mass can be improved if a prior on the reionization optical depth from 21 cm probes as HERA or SKA is also included. A prior of σ(τ) = 0.001 will reduce the freedom in the amplitude of the primordial power spectrum A_s, as CMB measurements mostly constrain the combination A_sexp(−2τ), see section 4.1. Therefore, the direct correlation between ∑m_ν and A_s, both modifying the amplitude of the matter power spectrum (although the change induced by ∑m_ν is, obviously, scale dependent), is largely affected by the presence of a precise determination of τ. The 1σ sensitivity they find for the combination of CORE, Euclid plus the prior on the optical depth from future 21 cm observations is σ(∑m_ν) = 0.012 eV³⁰.

Nevertheless, as carefully detailed above, even if these tiny errors on ∑m_ν will be reached and extrapolated to an error on the individual neutrino mass eigenstates, the possibility of extracting the neutrino mass ordering via singling out the neutrino mass eigenstates with cosmological observables remains unfeasible, unless very visionary scenarios, as FFTT under the most optimistic assumptions, are envisaged.

6.6. Prospects From Core-Collapse Supernova

Neutrinos from core-collapse supernovae offer an independent and complementary way to test neutrino physics. The existence of these neutrinos was robustly confirmed by the detection of 25 events from Supernova 1987A in the Large Magellanic Cloud (Alekseev et al., 1987; Bionta et al., 1987; Hirata et al., 1987), located at ~50 kpc from our Milky Way galaxy. Such a detection allowed to set very compelling bounds on a number of neutrino properties (Schramm and Truran, 1990; Raffelt, 1999). Even if laboratory experiments have surpassed some of these limits, the eventual detection of supernovae neutrinos will still provide precious information about the details of the explosion process (see e.g., Janka, 2012; Mirizzi et al., 2016; Scholberg, 2018 and references therein), and also of neutrino mixing effects in dense media, see also Horiuchi and Kneller (2018).

Neutrino production in core-collapse supernovae occurs in a number of different stages. The first one is the infall, in which electron neutrinos are produced, confined, as a result of the process $e^{-}+p\to n+{\nu }_e$. When electrons are converted, the outwards pressure they generate disappears and the gravity forces are no more balanced: the core will start to collapse until its density reaches that of matter inside atomic nuclei, i.e., nuclear densities. Once these densities are reached, matter becomes incompressible, and a hydrodynamic shock is formed. As this shock wave propagates outwards, it heats up the nuclei and disintegrates them, releasing neutrinos. This initial neutrino release is commonly known as neutronization burst, and it is mainly composed of ν_e and may last for a few tens of milliseconds. After the neutronization burst, the remnant proto-neutron star may evolve into a neutron star or collapse to a black hole, depending on the mass of the progenitor star. During this phase of explosion and accretion, which lasts for 1–2 s, the ν_e contribution is still the dominant one, albeit there is also a contribution from other (anti)neutrino flavors, in particular ${\bar{\nu }}_e$. The neutrinos produced in the cooling stage give the main contribution to the total flux, as it is in this phase when the supernova releases its energy via all-flavor neutrino-antineutrino pair production, reaching its final cold state. This process lasts for about tens of seconds. The differences in the mean temperature of the neutrino fluxes of ν_e, ${\bar{\nu }}_e$ and ν_x (${\bar{\nu }}_x$) are due to the different medium opacity of each species. The larger the opacity, the lower the temperature that the (anti)neutrino will have at decoupling. The neutrino fluxes read as Scholberg (2018)

$\begin{array}{cc}\begin{array}{r}\varphi (E_{\nu })=N_0\frac{{(\alpha +1)}^{(\alpha +1)}}{\langle E_{\nu }\rangle \Gamma (\alpha +1)}{\left(\frac{E_{\nu }}{\langle E_{\nu }\rangle }\right)}^{\alpha }exp\left(-(\alpha +1)\frac{E_{\nu }}{\langle E_{\nu }\rangle }\right),\end{array}& (24)\end{array}$

where N₀ is the total number of emitted neutrinos, and both α and the mean energy 〈E_ν〉 are flavor dependent. The supernova neutrino energy spectra peaks around the 10−20 MeV region.

The most popular process for supernova neutrino detection is inverse beta decay on protons (${\bar{\nu }}_e+p\to n+e^{+}$). Other possibilities include elastic scattering on electrons (ν+e⁻ → ν+e⁻), whose kinematics may provide information on the supernova location. Supernova neutrinos can also interact with nuclei via charged current or neutral current interactions, giving rise to charged leptons and/or excited nuclei which may provide flavor tagging. A very important process on argon nuclei is ${\nu }_e{+}^{40}\text{Ar}\to e^{-}{+}^{40}{\text{K}}^{*}$, which allows for electron neutrino tagging. In practice, water Cherenkov and scintillator detectors are mostly sensitive to electron antineutrinos via inverse beta decay, while the liquid argon technique mainly detects electron neutrinos. While other flavors may also be detected, the two processes above are the dominant ones. Large detector volumes (dozens of kilotons) are required to detect neutrinos from core-collapse supernovae located at $~{O}(10)$ kpc. A convenient way to scale the total number of supernova neutrino events in a detector of given effective mass is Beacom and Vogel (1998); Mena et al. (2007)

$\begin{array}{cc}\begin{array}{r}N=N_0\left(\frac{E_{\text{B}}}{3\times 10^{53}\mathrm{\text{erg}}}\right){\left(\frac{10\mathrm{\text{kpc}}}{D_{\mathrm{\text{OS}}}}\right)}^2.\end{array}& (25)\end{array}$

In the expression above, E_B is the gravitational binding energy of the collapsing star and D_OS the distance between the observer and the supernova. Assuming sensitivity to all reactions, the reference rate is $N_0={O}(10^4)$ for the Super-Kamiokande water Cherenkov detector with 32 kton and 5 MeV energy detection threshold. (Scholberg, 2012, 2018) give an estimate of the number of neutrino events for a number of ongoing and future facilities, based on different detection techniques: water Cherenkov (including also those with long string photosensors in ice, as Icecube and PINGU), liquid argon time projection chambers, and liquid scintillators. Upcoming neutrino detectors, already described in section 6.1 and crucial for oscillation physics measurements, such as the JUNO liquid scintillator (An et al., 2016), the liquid argon DUNE (Acciarri et al., 2015, 2016a,b; Strait et al., 2016) and the water Cherenkov Hyper-Kamiokande (Abe et al., 2015) can lead to a number of 6000, 3000 and 75000 supernova neutrino events respectively, assuming that the explosion occurs at 10 kpc from our position.

Flavor transitions inside a supernova have been carefully reviewed in Refs. Mirizzi et al. (2016); Scholberg (2018) (see also Lunardini and Smirnov, 2001a,b, 2003, 2004; Akhmedov et al., 2002). Here we summarize the most relevant results. As we have seen in section 2, when neutrinos propagate through matter their mixing effects undergo the so-called MSW mechanism, feeling a matter potential which is proportional to the electron number density N_e. If the supernova matter density has a profile which varies slowly, the neutrino matter eigenstates will propagate adiabatically and their final flavor composition will depend on the neutrino mass ordering, which will establish whether or not resonant transitions associated to each neutrino mass squared difference (solar and atmospheric) take place³¹. In the normal ordering case, the neutrino fluxes will have a significantly transformed spectrum, while the electron antineutrino one will only be partially transformed ($F_{{\nu }_e}^{\mathrm{\text{final}}}=F_{{\nu }_x}^{\mathrm{\text{initial}}}$ and $F_{{\bar{\nu }}_e}^{\mathrm{\text{final}}}={cos}^2{\theta }_{12}{F}_{{\bar{\nu }}_e}^{\mathrm{\text{initial}}}+{sin}^2{\theta }_{12}{F}_{{\bar{\nu }}_x}^{\mathrm{\text{initial}}}$). In the inverted ordering case, the effects on the electron neutrino and antineutrino fluxes will be approximately the opposite ones ($F_{{\nu }_e}^{\mathrm{\text{final}}}={sin}^2{\theta }_{12}{F}_{{\nu }_e}^{\mathrm{\text{initial}}}+{cos}^2{\theta }_{12}{F}_{{\nu }_x}^{\mathrm{\text{initial}}}$ and $F_{{\bar{\nu }}_e}^{\mathrm{\text{final}}}=F_{{\bar{\nu }}_x}^{\mathrm{\text{initial}}}$). Once neutrinos exit from supernovae, they can still undergo flavor transitions if they traverse the Earth. Their final flavor composition at the detector location will again depend on the neutrino mass ordering, as matter effects in Earth depend on it (see e.g., Scholberg, 2018) and references therein.

Furthermore, collective effects from neutrino self-interactions, due to ${\nu }_e+{\bar{\nu }}_e\to {\nu }_x+{\bar{\nu }}_x$ flavor processes, can lead to departures from the above summarized three-flavor oscillation picture (Hannestad et al., 2006a; Duan et al., 2007, 2010; Esteban-Pretel et al., 2007, 2008; Raffelt and Sigl, 2007; Mirizzi et al., 2016). The effective potential, proportional to the difference between the electron antineutrino and the muon/tau antineutrino fluxes, and inversely proportional to the supernova radius, should dominate over the standard matter one, leading to spectral swaps or splits (Raffelt and Smirnov, 2007a,b; Dasgupta et al., 2009, 2010). In the early stages, these self-interacting effects are sub-leading for mass ordering signatures, albeit we shall comment on possible non-thermal features in the neutrino or antineutrino spectra which depend on the mass ordering (Choubey et al., 2010).

In the following, we shall summarize the most relevant available methods to extract the neutrino mass ordering using the mentioned fluxes. For a recent and thorough review of the mass ordering signatures from supernovae neutrinos, we refer the reader to Scholberg (2018). The electron neutrinos produced in the neutronization burst undergo the MSW effect being fully (only partially) transformed, i.e., $F_{{\nu }_e}^{\mathrm{\text{final}}}=F_{{\nu }_x}^{\mathrm{\text{initial}}}$ ($F_{{\nu }_e}^{\mathrm{\text{final}}}={sin}^2{\theta }_{12}{F}_{{\nu }_e}^{\mathrm{\text{initial}}}+{cos}^2{\theta }_{12}{F}_{{\nu }_x}^{\mathrm{\text{initial}}}$) if the mass ordering is normal (inverted), respectively. Therefore, detectors with good ν_e tagging, such as liquid argon or water Cherenkov ones, will detect a neutronization burst only in the inverted neutrino mass ordering case. Concerning the accretion phase, and once electron antineutrinos are also produced, as they are almost unchanged in the MSW resonance, the largest signature is expected to occur for the normal ordering case for the three type of aforementioned detector types (liquid argon, water Cherenkov and scintillator), although the Icecube detector, with its excellent capabilities to reconstruct the time dependence of the signal, could also distinguish between the normal and inverted mass orderings (Ott et al., 2013). While a devoted study with precise and accurate mass ordering sensitivities attainable at these three detector types via supernova neutrinos is, to our knowledge, missing in the literature, we exploit the event rates during the accretion phase quoted for normal and inverted orderings in Scholberg (2018) for a supernova located at 10 kpc. For a 40 kton liquid argon detector, 374 kton water Cherenkov and 20 kton scintillator, the normal mass ordering could be extracted with ~ 2, 6 and 2 σ significance, respectively, based on a pure statistical-error analysis.

On the other hand, collective effects, which lead to spectral swaps in the electron (anti)neutrino spectra, show very sharp features at fixed energy values which depend, among other factors, on the neutrino mass ordering. However, these signatures are not as robust as the ones existing in the neutronization and accretion phases. Finally, a very significant imprint of the neutrino mass ordering on the supernovae neutrino fluxes is that due to their propagation through the Earth interior, where the standard MSW effect will induce a few percent-level oscillatory pattern in the 10−60 MeV energy range, in the electron (anti)neutrino spectra in case of (normal) inverted mass ordering. The detection of these wiggles requires however excellent energy resolution.

6.7. Prospects From Relic Neutrino Direct Detection

In the early Universe, neutrinos decoupled from the cosmic plasma during the cool down, in a process similar to the one leading to the formation of the CMB but at an earlier time, when the universe was seconds to minutes old. These neutrinos have been free-streaming for such a long time that they have decohered and are currently propagating as mass eigenstates. The decoupling of neutrinos occurred just before e^± annihilated and reheated photons, leading to the following ratio between the photon (T_γ) and neutrino (T_ν) temperatures, see Equation (15):

$\begin{array}{cc}\begin{array}{r}\frac{T_{\nu }}{T_{\gamma }}={\left(\frac{4}{11}\right)}^{1/3}.\end{array}& (26)\end{array}$

Today, the temperature of the neutrino background is $T_{\nu }^0\simeq 1.6\times 10^{-4}$ eV. Their mean energy is $\langle E_{\nu }\rangle \simeq 3T_{\nu }\simeq 5\times 10^{-4}$ eV, much smaller than the minimal mass of the second-to-lightest neutrino as required by flavor oscillations, so that at least two out of three neutrinos are non-relativistic today. The cosmic neutrino background (CνB) is the only known source of non-relativistic neutrinos and it has never been detected directly.

Apart from the imprints that relic neutrinos leave in the CMB (see section 4.1), which allow to have an indirect probe of their existence through the determination of N_eff, the direct detection of the CνB would offer a good opportunity to test neutrino masses and their ordering. Capturing relic neutrinos is not only rewarding from the point of view of what we can learn about neutrino properties, but also because it would be a further confirmation of the standard Big Bang cosmological model. Different ideas on how to achieve such a detection have been proposed (Weinberg, 1962; Weiler, 1982, 1984; Duda et al., 2001; Eberle et al., 2004; Barenboim et al., 2005; Gelmini, 2005; Ringwald, 2005; Cocco et al., 2007; Li, 2015; Vogel, 2015; Domcke and Spinrath, 2017), ranging from absorption dips in the ultra-high-energy (UHE) neutrino fluxes due to their annihilation with relic neutrinos at the Z boson resonance, to forces generated by coherent scattering of the relic bath on a pendulum and measured by laser interferometers. Most of these proposed methods are impractical from the experimental point of view. The one exploiting UHE neutrinos Weiler (1982, 1984); Eberle et al. (2004); Barenboim et al. (2005) has two problems, one related with the fact that it is difficult to think about a source that produces such UHE neutrinos, of energies

$\begin{array}{cc}\begin{array}{r}{E}_{\nu }^{\text{res}}=\frac{m_Z^2}{2m_i}\simeq 4·10^{22}\left(\frac{0.1\text{eV}}{m_i}\right)\text{eV},\end{array}& (27)\end{array}$

and another one regarding the difficulties of detecting a large enough sample of UHE neutrinos in order to resolve the dips. The method based on interferometers (Domcke and Spinrath, 2017) is even more complicated to address. At interferometers, current sensitivities to accelerations are of the order of a≃10⁻¹⁶cm/s², with an optimistic estimation of a≃3·10⁻¹⁸cm/s² (Domcke and Spinrath, 2017) for the incoming generation. However, expected accelerations due to relic neutrino interactions are of the order of (10⁻²⁷−10⁻³³)cm/s² (Duda et al., 2001; Domcke and Spinrath, 2017), many orders of magnitude below the sensitivity of the next-generation interferometers.

The most promising approach to detect relic neutrinos is to use neutrino capture in a β-decaying nucleus A

$\begin{array}{cc}\begin{array}{r}{\genfrac{}{}{0ex}{}{(-)}{\nu }}_e+A\to e^{\pm }+A^{\prime },\end{array}& (28)\end{array}$

where the signal for a positive detection is a peak located about 2m_ν above the true β-decay endpoint (see below). In particular, tritium is considered as the best candidate since it has a high neutrino capture cross section, low Q-value and it is long-lived (Cocco et al., 2007; Blennow, 2008; Lazauskas et al., 2008; Faessler et al., 2011; Long et al., 2014). The proposal for an experiment chasing this purpose was made in Cocco et al. (2007). Currently, efforts are put for such experiment, the PonTecorvo Observatory for Light Early-Universe Massive-Neutrino Yield (PTOLEMY) (Betts et al., 2013; Baracchini et al., 2018), to be built. The experiment has recently been approved by the Scientific Committee of the Italian National Laboratories of Gran Sasso and, in the following months, the existing prototypes for various components are expected to be moved from Princeton, where the R&D has been performed up to now, to Gran Sasso. The idea is to implant the tritium source on graphene layers, to avoid the problems related to a gaseous source, then collect and measure the energy of the emitted electrons using a combination of MAC-E filter, radio-frequency tracking and micro-calorimetry to obtain a determination of the β-decay and neutrino capture spectrum of tritium with an energy resolution of the order Δ ≃ 0.05−0.1 eV.

The total expected event rate from relic neutrino capture for a PTOLEMY-like experiment, assuming the estimated tritium mass of 100g, is

$\begin{array}{cc}\begin{array}{r}{\text{Γ}}_{\text{C}\nu \text{B}}=\left[n_0({\nu }_{h_R})+n_0({\nu }_{h_L})\right]N_T\bar{\sigma }{\displaystyle \sum _{i=1}^3}|U_{ei}{|}^2{f}_c(m_i),\end{array}& (29)\end{array}$

where n₀(ν_{hR, L}) is the averaged number density of relic neutrinos with right (R) or left (L) helicity, $N_T=M_T/m{(}^3\text{H})$ is the approximated number of tritium atoms in the source, $\bar{\sigma }\simeq 3.834\times 10^{-45}\text{c}{\text{m}}^2$ (Long et al., 2014), and f_c(m_i) is a mass-dependent overdensity factor that accounts for the clustering of relic neutrinos under the gravitational attraction of the matter potential (mostly from the dark matter halo) of our galaxy. This last factor was originally computed in Singh and Ma (2003) and Ringwald and Wong (2004) and later updated in de Salas et al. (2017) (see also Zhang and Zhang, 2018), where smaller masses were considered for the neutrinos, and the treatment of the matter potential of the Milky Way was improved. The values of f_c(m_ν) range from 1.1−1.2 for a neutrino with m_ν = 60 meV to 1.7−2.9 for m_ν = 150 meV (de Salas et al., 2017).

For unclustered neutrinos (i.e., f_c = 1) and 100 g of tritium, the expected number of events per year is Long et al. (2014)

$\begin{array}{cc}\begin{array}{r}{\text{Γ}}_{\text{C}\nu \text{B}}^{\text{D}}\simeq 4\text{yea}{\text{r}}^{-1},{\text{Γ}}_{\text{C}\nu \text{B}}^{\text{M}}=2{\text{Γ}}_{\text{C}\nu \text{B}}^{\text{D}}\simeq 8\text{yea}{\text{r}}^{-1},\end{array}& (30)\end{array}$

where the upperscripts D and M stand for the possible Dirac and Majorana neutrino character. If neutrinos are Majorana particles, the expected number of events is doubled with respect to the Dirac case. The reason is related to the fact that, during the transition from ultra-relativistic to non-relativistic particles, helicity is conserved, but not chirality. The population of relic neutrinos is then composed by left- and right-helical neutrinos in the Majorana case, and only left-helical neutrinos in the Dirac case. Since the neutrino capture can only occur for left-chiral electron neutrinos, the fact that in the Majorana case the right-handed neutrinos can have a left-chiral component leads to a doubled number of possible interactions. While this means that in principle it is possible to distinguish the Dirac or Majorana neutrino nature with a precise determination of the event rate, there are two problems. First of all, even without assuming new physics, the factor of two coming from the neutrino nature is degenerate with the clustering factor, see Equation (29), so that a precise calculation of f_c is required to determine if neutrinos are Dirac or Majorana particles through the direct detection of relic neutrinos (de Salas et al., 2017). Moreover, non-standard interactions can increase the event rate in the Dirac case by a factor larger than two, canceling the difference with Majorana neutrinos in some scenarios (Arteaga et al., 2017).

Let us come back to the PTOLEMY proposal. Instead of considering the total event rate, for this kind of experiment it is much better to study the energy spectrum, as the direct detection of relic neutrinos can only be possible if one can distinguish the signal events due to neutrino capture from the background events due to the β-decay of tritium. A crucial issue for such an experiment, actually more important than the event rate, is therefore the energy resolution. In order to distinguish the peak due to the captured relic neutrinos from the β-decay background, a full-width half maximum (FWHM) energy resolution Δ ≲ 0.7m_ν is needed (Long et al., 2014). If neutrinos are non-degenerate in mass, the neutrino capture signal has a peak for each of the separate neutrino mass eigenstates. The full expression of the energy spectrum of neutrino capture, given an energy resolution $\sigma =\Delta /\sqrt{8ln2}$, can be written as:

$\begin{array}{cc}\begin{array}{l}\frac{d{\tilde{\Gamma }}_{\text{CNB}}}{d{E}_e}(E_e)=\frac{1}{\sqrt{2\pi }\sigma }{n}_0{N}_T\overline{\sigma }\\ {\displaystyle \sum _{i=1}^{N_{\nu }}|}{U}_{ei}{|}^2{f}_{c,i}\times \exp \left\{-\frac{{[E_e-(E_{\text{end}}+m_i+m_{\text{lightest}})]}^2}{2{\sigma }^2}\right\},\end{array}& (31)\end{array}$

where E_end is the energy of the β-decay endpoint, E_end = E_{end, 0}−m_lightest, being E_{end, 0} the endpoint energy when m_lightest = 0. If the energy resolution is good enough, the three peaks coming from the three neutrino mass eigenstates could be resolved, each of them with an expected number of events modulated by $|U_{ei}{|}^2$. This might lead to a positive detection of the neutrino mass ordering, since the electron-flavor component of ν₁ is larger than the one of ν₂ and ν₃, and therefore the furthest peak from the β-decay endpoint (again if neutrinos are non-degenerate) is enhanced if the ordering of neutrino masses is inverted. This can be seen in the three panels of Figure 15, which also show the effect of changing the mass ordering on the β-decay spectrum. Dashed lines represent the spectrum which would be determined by an experiment capable of measuring the β spectrum with zero energy uncertainty, while solid lines represent the shape of the spectrum that one would observe in a real experiment. We plot in red (blue) the spectrum obtained using normal (inverted) ordering, a FWHM resolution Δ = 10 meV (top), Δ = 20 meV (middle), Δ = 50 meV (bottom) and a lightest neutrino mass m_lightest = 10 meV. As we can see from the figure, the kink commented in section 3 is clearly visible when one observes the huge number of events that come from the 100 g of decaying tritium with a sufficient energy resolution. While for distinguishing the relic neutrino events from the β-decay background and for having a direct detection of the CνB the energy resolution is a crucial requirement, in principle even a worse energy resolution may allow to determine the neutrino mass scale and the mass ordering, thanks to the fact that we expect less events near the endpoint when the ordering is inverted. A direct observation of the amplitude of all the CνB peaks, however, would give a much cleaner signal, because the peak corresponding to the heaviest neutrino would be always higher in the inverted ordering case, independently of any other factor.

FIGURE 15

Figure 15. Electron spectrum in a PTOLEMY-like experiment, comparing normal (red) and inverted ordering (blue) with m_lightest = 10 meV and three different energy resolutions: Δ = 10 meV (Top), Δ = 20 meV (Middle), Δ = 50 meV (Bottom). Dashed lines indicate the spectrum as it would be measured by an experiment with perfect energy resolution.

In summary, the CνB capture event rate in a PTOLEMY-like experiment (Equation (31)), even within SM physics and without considering non-standard interactions, depends on several main unknowns: i) the absolute neutrino mass, ii) the matter distribution (especially that of dark matter) in our galaxy, iii) the nature of neutrino masses (whether neutrinos are Dirac or Majorana particles), and iv) the true mass ordering. This last dependence is encoded in the $|U_{ei}{|}^2$ factor in Equation (31) and it is only accessible if neutrinos are non-degenerate. A quantitative study on the PTOLEMY capabilities in determining the mass ordering has not been published yet, but a new Letter of Intent is in preparation (Baracchini et al., 2018)³².

7. Summary

Identifying the neutrino mass ordering is one of the major pending issues to complete our knowledge of masses and mixings in the lepton sector. The two possibilities, normal vs. inverted, may result from very different underlying symmetries and therefore to single out the one realized in nature is a mandatory step to solve the flavor puzzle, i.e., to ensure a full theoretical understanding of the origin of particle masses and mixings. We have presented a comprehensive review on the current status and on future prospects of extracting the neutrino mass ordering via a number of different ongoing and upcoming observations. Furthermore, the most updated and complete result on the preference for a given neutrino mass ordering from a Bayesian global fit to all 2018 publicly available neutrino data has also been presented.

Currently, among the three available methods to extract the neutrino mass ordering (oscillations, neutrinoless double beta decay searches and cosmological observations), the leading probe comes from oscillations in matter, measured at long-baseline accelerator or atmospheric neutrino beams in combination with reactor experiments. The latest frequentists global data analysis results in a preference for normal mass ordering with Δχ² = 11.7 (~ 3.4σ), mostly arising from the combination of the long-baseline T2K and NOνA data with reactor experiments (Daya Bay, RENO and Double Chooz), plus the latest atmospheric neutrino results from Super-Kamiokande. Similar results for the preference in favor of the normal mass ordering arise from other global fit analyses (Capozzi et al., 2018a).

Cosmological measurements are able to set indirect, albeit independent bounds on the neutrino mass ordering. Neutrinos affect Cosmic Microwave Background (CMB) primary anisotropies by changing the gravitational potential at the recombination period when they become non-relativistic. However, for sub-eV neutrino masses this effect is tiny and the most prominent effect on the CMB is via lensing, as neutrinos, having non-zero velocities, will reduce the lensing effect at small scales. Nevertheless, the largest impact of neutrinos in cosmology gets imprinted in the matter power spectrum. Once neutrinos become non-relativistic, their large velocity dispersions will prevent the clustering of matter inhomogeneities at all scales smaller than their free streaming length. At present, the cosmological constraints on the neutrino mass ordering come from the sensitivity to the total neutrino mass ∑m_ν and not via the effects induced in the CMB and matter power spectrum by each of the individual neutrino masses m_i. Within the context of the minimal ΛCDM model with massive neutrinos, current cosmological probes cannot provide odds stronger than ~3:1 in favor of normal ordering.

Neutrinoless double beta decay searches can also test the neutrino mass ordering if neutrinos are Majorana particles. However, present constraints on the so-called effective Majorana mass do not affect the overall Bayesian analyses.

All in all, the 2018 Bayesian global analysis, including all the neutrino oscillation data available before the Neutrino 2018 conference, results in a 3.2σ preference for the normal neutrino mass ordering which, in Bayesian words, implies a strong preference for such a scenario. One can then combine the oscillation data with 0νββ data from KamLAND-Zen, EXO-200 and Gerda and cosmological observations from Planck, SDSS BOSS, 6DF and SDSS DR7 MGS. Using this conservative cosmological data combination, the aforementioned preference becomes 3.4σ, which raises to 3.5σ if a prior on the Hubble parameter H₀ from local measurements is considered in addition. This clearly states the current power of oscillation results when dealing with neutrino mass ordering extractions.

While in the very near perspective an improved sensitivity (i.e., above the 3.5σ level) is expected mostly from more precise measurements of current long-baseline and atmospheric experiments, and, to a minor extent, from cosmological surveys (Planck, DES and eBOSS among others), there will be a number of planned experiments which will be crucial for extracting the neutrino mass ordering in the non-immediate future.

Of particular relevance are the upcoming neutrino oscillation facilities, as they will be able to measure the neutrino mass ordering with astonishing precision without relying on combinations of different data sets. Such is the case of the Deep Underground Neutrino Experiment (DUNE), that will be able to measure the neutrino mass ordering with a significance of 5σ with 7 years of data. Atmospheric neutrino observatories as PINGU or ORCA will also mainly focus on the mass ordering measurement. Some of these future devices could also identify the neutrino mass ordering via the detection of matter effects in the neutrino fluxes emitted at the eventual explosion of a supernova in our galaxy or in its neighborhood. On the other hand, medium baseline reactor neutrino detectors such as JUNO or RENO will also be able to extract the neutrino mass ordering despite matter effects are negligible for these two experiments. They will focus instead on an extremely accurate measurement of the survival electron antineutrino probability.

Improved masses and detection techniques in neutrinoless double beta decay future searches could go down the 10 meV region in the effective Majorana mass m_ββ, and they could be able to discard at some significance level the inverted mass ordering scenario, in the absence of a positive signal. These limits, however, will apply only in case neutrinos have a Majorana nature. Moreover, the determination of the neutrino mass ordering may be complicated by the presence of a light sterile neutrino at the eV scale, as currently suggested by the NEOS and DANSS results.

Concerning future cosmological projects, the combination of different probes will still be required. Near-future CMB and large scale structure surveys will only be sensitive to the neutrino mass ordering via their achieved error on ∑m_ν. Furthermore, the accuracy in the extraction of the neutrino mass ordering will strongly depend on how far ∑m_ν lies from the minimum allowed value from oscillation probes. The future CMB mission CORE plus the DESI galaxy survey could provide odds of 9:1 for normal neutrino mass ordering assuming ∑m_ν = 0.056 eV. Even if very futuristic surveys, based on the observation of the 21 cm redshifted line in neutral hydrogen, may be able to extract the individual values of the neutrino masses, their precision on the m_i values may not be enough to guarantee a direct determination of the neutrino mass ordering by these means, albeit they can achieve an accurate measurement of the ordering thanks to their unprecedented precision on ∑m_ν.

Last, but not least, relic neutrino capture in tritium in a PTOLEMY-like experiment could also establish the neutrino mass ordering via an almost perfect energy reconstruction of the β-decay spectrum, ensured by the extremely large amount of tritium adopted. The detection is possible both from a kink in the β-decay spectrum which only appears if the ordering is inverted and from the peaks due to neutrino capture just above the endpoint.

All these future probes may either confirm or reject the current strong preference (3.5σ) in favor of the normal neutrino mass ordering. Such a preference has kept gaining significance in the recent years, thanks to the fact that current neutrino oscillation experiments have enormously improved our knowledge of neutrino flavor physics.

Author Contributions

PFdS, CT, and MT have contributed mainly to review the current status of neutrino oscillations as well as to the summary of the prospects on the neutrino mass ordering from future neutrino oscillation experiments. SG has contributed to review beta and neutrinoless double beta decay current status and future prospects. SG has also led the 2018 Global Bayesian analysis results. PFdS and SG have also contributed to review the present and future cosmological bounds and have also reviewed the prospects from relic neutrino detection. OM has mainly contributed to review the cosmological bounds on the mass ordering and the perspectives from future 21 cm surveys and core-collapse supernovae.

Conflict of Interest Statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Acknowledgments

We thank C. Giunti for providing us the two panels constituting Figure 7 and M. Hirsch for his suggestions on how to improve the first version of the manuscript. Work supported by the Spanish grants FPA2015-68783-REDT, FPA2017-90566-REDC (Red Consolider MultiDark), FPA2017-85216-P, FPA2017-85985-P and SEV-2014-0398 (AEI/FEDER, UE, MINECO), and PROMETEOII/2014/050, PROMETEO/2018/165 and GV2016-142 (Generalitat Valenciana). SG receives support from the European Union's Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie individual grant agreement No. 796941. OM is also supported by the European Union's Horizon 2020 research and innovation program under the Marie Skłodowska-Curie grant agreements No. 690575 and 674896 and acknowledges the hospitality of the Fermilab Theoretical Physics Department. PFdS and CAT are also supported by the MINECO fellowships FPU13/03729 and BES-2015-073593, respectively. MT acknowledges financial support from MINECO through the Ramón y Cajal contract RYC-2013-12438 as well as from the L'Oréal-UNESCO For Women in Science initiative.

Footnotes

1. ^Valencia-Globalfit, 2018; Available online at: http://globalfit.astroparticles.es/.

2. ^Note that the observation of matter effects in the Sun constrains the product $\Delta m_{21}^{2}cos2{\theta }_{12}$ to be positive. Therefore, depending on the convention chosen to describe solar neutrino oscillations, matter effects either fix the sign of the solar mass splitting $\Delta m_{21}^2$ or the octant of the solar angle θ₁₂, with $\Delta m_{21}^2$ positive by definition.

3. ^See the “July 2017” version in¹.

4. ^A somewhat milder preference in favor of normal mass ordering was obtained in the corresponding version of the analysis in Refs. Esteban et al. (2017)

5. ^NuFIT v3.2, http://www.nu-fit.org/.

6. ^A clarification about the use of “hierarchy” and “ordering” is mandatory. One talks about “hierarchy” when referring to the absolute scales of neutrino masses, in the sense that neutrino masses can be distinguished and ranked from lower to higher. This does not include the possibility that the lightest neutrino mass is much larger than the mass splittings obtained by neutrino oscillation measurements, since in this case the neutrino masses are degenerate. On the other hand, the mass “ordering” is basically defined by the sign of $\Delta m_{31}^2$, or by the fact that the lightest neutrino is the most (least) coupled to the electron neutrino flavor in the normal (inverted) case.

7. ^See also the review Qian and Vogel (2015), focused mostly on neutrino oscillation perspectives.

8. ^For an expansion including also the solar mixing parameters, see Ref. Akhmedov et al. (2004).

9. ^Note that this extra sensitivity comes essentially from Super-Kamiokande, since the effect of IceCube DeepCore and ANTARES is negligible in comparison.

10. ^In the case of quasi-degenerate spectrum, the distortion of the spectrum will consist of just a bending and a shift of the end point, similar to the case of an electron neutrino with a given mass without mixing Farzan et al. (2001), and the ordering cannot be measured. Therefore, for future β-decay searches, measuring the neutrino mass ordering will be practically the same as measuring the neutrino mass hierarchy.

11. ^This is the most constraining 95% CL limit Palanque-Delabrouille et al. (2015) at present, excluding combinations of data sets that are in tension, and we have chosen it as the benchmark value in the following discussions throughout this review.

12. ^Here, σ₈ corresponds to the normalization of the matter power spectrum on scales of 8h⁻¹ Mpc, see Equation (13).

13. ^The thermal SZ thermal effect consists on a spectral distortion on CMB photons which arrive along the line of sight of a cluster.

14. ^The BAO measurements exploited by the Planck collaboration include the 6dF Galaxy Survey (6dFGS) Beutler et al. (2011), the BOSS LOWZ BAO extraction of the spherical averaged D_v/r_s (Anderson et al., 2014; Ross et al., 2015) and the BOSS CMASS-DR11 data of Anderson et al. (2014).

15. ^See e.g., the work of the authors of Simpson et al. (2017) and the explanation of their results in Schwetz et al. (2017) and Gariazzo et al. (2018a). See also Long et al. (2018), Heavens and Sellentin (2018), Handley and Millea (2018) for useful discussions concerning the prior choice on the neutrino mass ordering extraction.

16. ^As stated in Vagnozzi et al. (2017), in the future, a deeper understanding of the non-linear regime of the galaxy power spectrum with massive neutrinos included, plus a better understanding of the galaxy bias could change the constraining power of full-shape analyses vs. BAO ones.

17. ^See Jackson (2007) and Freedman and Madore (2010) for dedicated reviews concerning the different possible local measurements of H₀. Among them, the one based on Cepheid variables.

18. ^The final result of Efstathiou (2014) is however H₀ = (72.5±2.5) km s⁻¹ Mpc⁻¹, when the combination of the H₀ results obtained with three different distance estimators is performed. The value H₀ = (70.6±3.3) km s⁻¹ Mpc⁻¹ is the only one of the three which shows a milder tension with the H₀ estimate from Planck.

19. ^The work of de Salas and Pastor (2016), including three-flavor neutrino oscillations, has revisited previous calculations including all the proper collision integrals for both diagonal and off-diagonal elements in the neutrino density matrix and quotes the value of N_eff = 3.045.

20. ^Interacting dark energy models can also change the neutrino mass constraints (see e.g., Gavela et al., 2009; La Vacca et al., 2009; Lopez Honorez and Mena, 2010; Reid et al., 2010; Guo et al., 2018).

21. ^We also refer the reader to Blennow et al. (2014), which provides a comprehensive study of the sensitivity reach to the mass ordering in the context of the frequentist approach.

22. ^As we are making use of logarithmic priors here, we shall not report the upper limits we obtain on the sum of the neutrino masses, as they will be much smaller than the usually quoted results due to the volume effects associated with the use of the logarithmic prior, that naturally leads to a preference for small neutrino masses.

23. ^We are not aware of any study showing the T2K or SK expectations to the mass ordering in the next few years.

24. ^The effect of statistic and systematic uncertainties on the PINGU sensitivity to the mass ordering has been presented in Capozzi et al. (2015).

25. ^The collaboration does not report the sensitivity in terms of the half-life of the decay.

26. ^For a detailed study on the prospects from pre- and post-2020 CMB experiments on the extraction of cosmological parameters, including the total neutrino mass ∑m_ν, see also (Errard et al., 2016).

27. ^The authors of Amendola et al. (2018) have nonetheless presented constraints for different fiducial models.

28. ^For the CORE CMB mission, data were generated following Refs (Bond et al., 1997, 2000). For DESI, mock r_sH(z) and d_A(z)/r_s data were generated for the three DESI tracers in the 0.15 < z < 1.85 redshift range, accordingly to Font-Ribera et al. (2014b).

29. ^These scenarios differ in the assumptions concerning the power modeling, the prior on the reionization history and the residual foregrounds cutoff scale, among other factors (see Tegmark and Zaldarriaga, 2009).

30. ^More recently, this very important synergy between Euclid and future 21 cm surveys, concretely with the intensity mapping survey SKA1, has been further assessed in Sprenger et al. (2018).

31. ^In case the matter potential inside the supernova suffers from discontinuities, the neutrino transitions will be non-adiabatic and the final flavor composition will depend on the precise matter profile.

32. ^We suggest the interested readers to look forward to the publication of this document, which will describe in more detail the physics reach and the technical characteristics of PTOLEMY.

References

Aalbers, J., Agostinib, F., Alfonsic, M., Amaror, F. D., Amslerd, C., Aprilee, E., et al. (2016). DARWIN: towards the ultimate dark matter detector. JCAP 11:017. doi: 10.1088/1475-7516/2016/11/017

CrossRef Full Text | Google Scholar

Aalseth, C., Berkeley, U. C., and Richland, P. N. L. (2018). Search for Neutrinoless Double-β Decay in ⁷⁶Ge with the Majorana Demonstrator. Phys. Rev. Lett. 120:132502. doi: 10.1103/PhysRevLett.120.132502

CrossRef Full Text | Google Scholar

Aartsen, M., and Adelaide, U (2014). Letter of intent: the precision iceCube next generation upgrade (PINGU). arXiv:1401.2046. 136.

Google Scholar

Aartsen, M. G., Ackermann, M., Adams, J., Aguilar, J. A., Ahlers, M., Ahrens, M., et al. (2015). Determining neutrino oscillation parameters from atmospheric muon neutrino disappearance with three years of IceCube DeepCore data. Phys. Rev. D 91:072004. doi: 10.1103/PhysRevD.91.072004

CrossRef Full Text | Google Scholar

Abazajian, K., Calabrese, E., Cooray, A., De Bernardis, F., Dodelson, S., Friedland, A., et al. (2011). Cosmological and astrophysical neutrino mass measurements. Astropart. Phys. 35, 177–184. doi: 10.1016/j.astropartphys.2011.07.002

CrossRef Full Text | Google Scholar

Abazajian, K. N., Adshead, P., Ahmed, Z., Allen, S. W., Alonso, D., Arnold, K. S., et al. (2016). CMB-S4 Science Book, 1st Edn.

Google Scholar

Abazajian, K. N., and Dodelson, S. (2003). Neutrino mass and dark energy from weak lensing. Phys. Rev. Lett. 91:041301. doi: 10.1103/PhysRevLett.91.041301

PubMed Abstract | CrossRef Full Text | Google Scholar

Abbott, T., Abdalla, F. B., Alarcon, A., Aleksić, J., Allam, S., Allen, S., et al. (2018). Dark energy survey year 1 results: cosmological constraints from galaxy clustering and weak lensing. Phys. Rev. D 98:043526. doi: 10.1103/PhysRevD.98.043526

CrossRef Full Text | Google Scholar

Abbott, T., Abdalla, F. B., Alarcon, A., Allam, S., Andrade-Oliveira, F., Annis, J., et al. (2017). Dark energy survey year 1 results: measurement of the baryon acoustic oscillation Scale in the distribution of galaxies to redshift 1. Mon. Not. R. Astron. Soc. D98:043526.

Google Scholar

Abdurashitov, J. N., Gavrin, V. N., Gorbachev, V. V., Gurkina, P. P., Ibragimova, T. V., Kalikhov, A. V., et al. (2009). Measurement of the solar neutrino capture rate with gallium metal. III: Results for the 2002–2007 data-taking period. Phys. Rev. C 80:015807. doi: 10.1103/PhysRevC.80.015807

CrossRef Full Text | Google Scholar

Abe, K., Abe, Ke., Ahn, S. H., Aihara, H., Aimi, A., Akutsu, R., et al. (2018c). Physics potentials with the second hyper-kamiokande detector in Korea. PTEP 2018:063C01. doi: 10.1093/ptep/pty044

CrossRef Full Text | Google Scholar

Abe, K., Abe, Ke., Aihara, H., Aimi, A., Akutsu, R., Andreopoulos, C., et al. (2018b). Hyper-kamiokande design report. arXiv:1805.04163v1.

Google Scholar

Abe, K., Abgrall, N., Ajima, Y., Aihara, H., Albert, J. B., Andreopoulos, C., et al. (2011a). Indication of electron neutrino appearance from an accelerator-produced Off-axis muon neutrino beam. Phys. Rev. Lett. 107:041801. doi: 10.1103/PhysRevLett.107.041801

PubMed Abstract | CrossRef Full Text | Google Scholar

Abe, K., Aihara, H., Andreopoulos, C., Anghel, I., Ariga, A., Ariga, T., et al. (2015). Physics potential of a long-baseline neutrino oscillation experiment using a J-PARC neutrino beam and Hyper-Kamiokande. Prog. Theor. Exp. Phys. 2015:053C02. doi: 10.1093/ptep/ptv061

CrossRef Full Text | Google Scholar

Abe, K., Bronner, C., Haga, Y., Hayato, Y., Ikeda, M., Iyogi, K., et al. (2018a). Atmospheric neutrino oscillation analysis with external constraints in Super-Kamiokande I-IV. Phys. Rev. D 97:072001. doi: 10.1103/PhysRevD.97.072001

CrossRef Full Text | Google Scholar

Abe, K., Hayato, Y., Iida, T., Ikeda, M., Ishihara, C., Iyogi, K., et al. (2011b). Solar neutrino results in Super-Kamiokande-III. Phys. Rev. D 83:052010. doi: 10.1103/PhysRevD.83.052010

CrossRef Full Text | Google Scholar

Abe, Y., Asano, Y., Haba, N., and Yamada, T. (2017). Heavy neutrino mixing in the T2HK, the T2HKK and an extension of the T2HK with a detector at Oki Islands. Eur. Phys. J. C 77:851. doi: 10.1140/epjc/s10052-017-5294-7

CrossRef Full Text | Google Scholar

Abe, Y., dos Anjos, J. C., Barriere, J. C., Baussan, E., Bekman, I., Bergevin, M., et al. (2014). Improved measurements of the neutrino mixing angle θ₁₃ with the Double Chooz detector. JHEP 10:086. doi: 10.1007/JHEP10(2014)086

CrossRef Full Text | Google Scholar

Abell, P. A., Allison, J., Anderson, S. F., Andrew, J. R., Roger, J., Angel, P., et al. (2009). LSST Science Book, Version 2.0.

Abgrall, N., Abramov, A., Abrosimov, N., Abt, I., Agostini, M., Agartioglu, M., et al. (2017). The large enriched germanium experiment for neutrinoless double beta decay (LEGEND). AIP Conf. Proc. 1894:020027. doi: 10.1063/1.5007652

CrossRef Full Text | Google Scholar

Abrahão, T., Minakata, H., Nunokawa, H., and Quiroga, A. A. (2015). Constraint on Neutrino Decay with Medium-Baseline Reactor Neutrino Oscillation Experiments. J. High Energy Phys. 11:001. doi: 10.1007/JHEP11(2015)001

CrossRef Full Text | Google Scholar

Acciarri, R., Acero, M. A., Adamowski, M., Adams, C., Adamson, P., Adhikari, S., et al. (2016a). Long-baseline neutrino facility (LBNF) and deep underground neutrino experiment (DUNE) Volume 1. arXiv:1601.05471v1.

Google Scholar

Acciarri, R., Acero, M. A., Adamowski, M., Adams, C., Adamson, P., Adhikari, S., et al. (2015). Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE): Conceptual Design Report, Volume 2: The Physics Program for DUNE at LBNF. arXiv:1512.06148.

Google Scholar

Acciarri, R., Acero, M. A., Adamowski, M., Adams, C., Adamson, P., Adhikari, S., et al. (2016b). Long-Baseline Neutrino Facility (LBNF) and Deep Underground Neutrino Experiment (DUNE) : Conceptual Design Report, Volume 4 The DUNE Detectors at LBNF. arXiv:1601.02984.

Google Scholar

Adam, A. (2018). “Recent results from MINOS and MINOS+,” in XXVIII International Conference on Neutrino Physics and Astrophysics (Heidelberg), Available online at: doi: 10.5281/zenodo.1286760

CrossRef Full Text | Google Scholar

Adam, R., Ade, P. A. R., Aghanim, N., Akrami, Y., Alves, M. I. R., Arnaud, M., et al. (2016). Planck 2015 results. I. Overview of products and scientific results. Astron. Astrophys. 594:A1. doi: 10.1051/0004-6361/201527101

CrossRef Full Text | Google Scholar

Adams, D., Adams, Q., Alduino, C., Alfonso, K., Avignone, F. T. III., Azzolini, O., et al. (2018). Update on the recent progress of the CUORE experiment. arXiv:1808.10342v1.

Google Scholar

Adamson, P., Anghel, I., Aurisano, A., Barr, G., Bishai, M., Blake, A., et al. (2014). Combined analysis of ν_μ disappearance and ν_μ → ν_e appearance in MINOS using accelerator and atmospheric neutrinos. Phys. Rev. Lett. 112:191801. doi: 10.1103/PhysRevLett.112.191801

PubMed Abstract | CrossRef Full Text | Google Scholar

Ade, P., Aghanim, N., Arnaud, M., Ashdown, M., Aumont, J., Baccigalupi, C., et al. (2016a). Planck 2015 results. XXVII. The Second Planck Catalogue of Sunyaev-Zeldovich Sources. Astron. Astrophys. 594:A27. doi: 10.1051/0004-6361/201525823

CrossRef Full Text | Google Scholar

Ade, P. A. R., Aghanim, N., Armitage-Caplan, C., Arnaud, M., Ashdown, M., Atrio-Barandela, F., et al. (2014). Planck 2013 results. XVI. Cosmological parameters. Astron. Astrophys. 571:A16. doi: 10.1051/0004-6361/201321591

CrossRef Full Text | Google Scholar

Ade, P. A. R., Aghanim, N., Arnaud, M., Ashdown, M., Aumont, J., Baccigalupi, C., et al. (2016b). Planck 2015 results. XIII. Cosmological parameters. Astron. Astrophys. 594:A13. doi: 10.1051/0004-6361/201525830

CrossRef Full Text | Google Scholar

Adrian-Martinez, S., Ageron, M., Aharonian, F., Aiello, S., Albert, A., Ameli, F., et al. (2016). Letter of intent for KM3NeT 2.0. J. Phys. G 43, 084001. doi: 10.1088/0954-3899/43/8/084001

CrossRef Full Text | Google Scholar

Adrian-Martinez, S., Al Samarai, I., Albert, A., Andre, M., Anghinolfi, M., Anton, G., et al. (2012). Measurement of atmospheric neutrino oscillations with the ANTARES neutrino telescope. Phys. Lett. B714, 224–230. doi: 10.1016/j.physletb.2012.07.002

CrossRef Full Text | Google Scholar

Afshordi, N., Zaldarriaga, M., and Kohri, K. (2005). On the stability of dark energy with mass-varying neutrinos. Phys. Rev. D 72:065024. doi: 10.1103/PhysRevD.72.065024

CrossRef Full Text | Google Scholar

Agarwalla, S. K., Chatterjee, S. S., and Palazzo, A. (2016). Physics Reach of DUNE with a Light Sterile Neutrino. J. High Energy Phys. 09:016. doi: 10.1007/JHEP09(2016)016

CrossRef Full Text | Google Scholar

Agarwalla, S. K., Chatterjee, S. S., and Palazzo, A. (2018a). Signatures of a Light Sterile Neutrino in T2HK. J. High Energy Phys. 04:091. doi: 10.1007/JHEP04(2018)091

CrossRef Full Text | Google Scholar

Agarwalla, S. K., Chatterjee, S. S., Petcov, S., and Titov, A. (2018b). Addressing Neutrino Mixing Models with DUNE and T2HK. Eur. Phys. J. C 78:286. doi: 10.1140/epjc/s10052-018-5772-6

CrossRef Full Text | Google Scholar

Aghamousa, A., Aguilar, J., Ahlen, S., Alam, S., Allen, L. E., Prieto, C. A., et al. (2016). The DESI experiment part I: Science, targeting, and survey design. arXiv:1611.00036v2.

Google Scholar

Aghanim, N., Arnaud, M., Ashdown, M., Aumont, J., Baccigalupi, C., Banday, A. J., et al. (2016a). Planck 2015 results. XI. CMB power spectra, likelihoods, and robustness of parameters. Astron. Astrophys. 594:A11. doi: 10.1051/0004-6361/201526926

CrossRef Full Text | Google Scholar

Aghanim, N., Ashdown, M., Aumont, J., Baccigalupi, C., Ballardini, M., Banday, A. J., et al. (2016b). Planck intermediate results. XLVI. Reduction of large-scale systematic effects in HFI polarization maps and estimation of the reionization optical depth. Astron. Astrophys. 596:A107. doi: 10.1051/0004-6361/201628890

CrossRef Full Text | Google Scholar

Aghanim, N., Majumdar, S., and Silk, J. (2008). Secondary anisotropies of the CMB. Rept. Prog. Phys. 71:066902. doi: 10.1088/0034-4885/71/6/066902

CrossRef Full Text | Google Scholar

Agostini, M., Allardt, M., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., et al. (2017b). Background-free search for neutrinoless double-β decay of ⁷⁶Ge with GERDA. Nature 544, 47–52. doi: 10.1038/nature21717

CrossRef Full Text | Google Scholar

Agostini, M., Bakalyarov, A. M., Balata, M., Barabanov, I., Baudis, L., Bauer, C., et al. (2018). Improved Limit on Neutrinoless Double-β Decay of ⁷⁶Ge from GERDA Phase II. Phys. Rev. Lett. 120:132503. doi: 10.1103/PhysRevLett.120.132503

CrossRef Full Text | Google Scholar

Agostini, M., Benato, G., and Detwiler, J. (2017a). Discovery probability of next-generation neutrinoless double-β decay experiments. Phys. Rev. D 96:053001. doi: 10.1103/PhysRevD.96.053001

CrossRef Full Text | Google Scholar

Aharmim, B., Ahmed, S. N., Amsbaugh, J. F., Anthony, A. E., Banar, J., Barros, N., et al. (2008). An independent measurement of the total active B-8 solar neutrino flux using an array of He-3 proportional counters at the sudbury neutrino observatory. Phys. Rev. Lett. 101:111301. doi: 10.1103/PhysRevLett.101.111301

CrossRef Full Text | Google Scholar

Aharmim, B., Ahmed, S. N., Anthony, A. E., Barros, N., Beier, E. W., Bellerive, A., et al. (2010). Low energy threshold analysis of the Phase I and Phase II data sets of the sudbury neutrino observatory. Phys. Rev. C 81:055504. doi: 10.1103/PhysRevC.81.055504

CrossRef Full Text | Google Scholar

Ahmad, Q. R., Allen, R. C., Andersen, T. C., Anglin, J. D., Bühler, G., Barton, J. C., et al. (2001). Measurement of the rate of ${\nu }_e+d\to p+p+e^{-}$ interactions produced by ⁸B solar neutrinos at the Sudbury Neutrino Observatory. Phys. Rev. Lett. 87:071301. doi: 10.1103/PhysRevLett.87.071301

CrossRef Full Text | Google Scholar

Ahmad, Q. R., Allen, R. C., Andersen, T. C., Anglin, J. D., Bühler, G., Barton, J. C., et al. (2002). Direct evidence for neutrino flavor transformation from neutral current interactions in the Sudbury Neutrino Observatory. Phys. Rev. Lett. 89:011301. doi: 10.1103/PhysRevLett.89.011301

PubMed Abstract | CrossRef Full Text | Google Scholar

Ahmed, S., Sajjad Athar, M., Hasan, R., Salim, M., Singh, S. K., Inbanathan, S. S. R., et al. (2017). Physics Potential of the ICAL detector at the India-based Neutrino Observatory (INO). Pramana 88:79. doi: 10.1007/s12043-017-1373-4

CrossRef Full Text | Google Scholar

Ahmed, Z., Amiri, M., Benton, S. J., Bock, J. J., Bowens-Rubin, R., Buder, I., et al. (2014). BICEP3: a 95GHz refracting telescope for degree-scale CMB polarization. 9153, 91531N. doi: 10.1117/12.2057224

CrossRef Full Text | Google Scholar

Ahn, M. H., Aliu, E., Andringa, S., Aoki, S., Aoyama, Y., Argyriades, J., et al. (2006). Measurement of neutrino oscillation by the K2K experiment. Phys. Rev. D 74:072003. doi: 10.1103/PhysRevD.74.072003

CrossRef Full Text | Google Scholar

Akhmedov, E. K., Johansson, R., Lindner, M., Ohlsson, T., and Schwetz, T. (2004). Series expansions for three flavor neutrino oscillation probabilities in matter. J. High Energy Phys. 04:078. doi: 10.1088/1126-6708/2004/04/078

CrossRef Full Text | Google Scholar

Akhmedov, E. K., Lunardini, C., and Smirnov, A. Y. (2002). Supernova neutrinos: difference of muon-neutrino - tau-neutrino fluxes and conversion effects. Nucl.Phys. B643, 339–366. doi: 10.1016/S0550-3213(02)00692-2

CrossRef Full Text | Google Scholar

Alam, S., Ata, M., Bailey, S., Beutler, F., Bizyaev, D., Blazek, J. A., et al. (2017). The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: cosmological analysis of the DR12 galaxy sample. Mon. Not. Roy. Astron. Soc. 470, 2617–2652. doi: 10.1093/mnras/stx721

CrossRef Full Text | Google Scholar

Albert, J. B., Anton, G., Arnquist, I. J., Badhrees, I., Barbeau, P., Beck, D., et al. (2018). Sensitivity and discovery potential of nEXO to neutrinoless double beta decay. Phys. Rev. C 97:065503. doi: 10.1103/PhysRevC.97.065503

CrossRef Full Text | Google Scholar

Albert, J. B., Auty, D. J., Barbeau, P. S., Beauchamp, E., Beck, D., Belov, V., Benitez-Medina, C., et al. (2014). Search for Majorana neutrinos with the first two years of EXO-200 data. Nature 510, 229–234. doi: 10.1038/nature13432

CrossRef Full Text | Google Scholar

Alduino, C., Alfonso, K., Andreotti, E., Arnaboldi, C., Avignone, F. T. III., Azzolini, O., et al. (2018a). First results from CUORE: a search for lepton number violation via 0νββ Decay of ¹³⁰Te. Phys. Rev. Lett. 120:132501. doi: 10.1103/PhysRevLett.120.132501

CrossRef Full Text | Google Scholar

Alduino, C., Alfonso, K., Artusa, D. R., Avignone, F. T. III., Azzolini, O., Balata, M., et al. (2016). CUORE-0 detector: design, construction and operation. JINST 11:P07009. doi: 10.1088/1748-0221/11/07/P07009

CrossRef Full Text | Google Scholar

Alduino, C., Alfonso, K., Avignone, F. T. III., Azzolini, O., Bari, G., Bellini, F., et al. (2018b). Study of rare nuclear processes with CUORE. Int. J. Mod. Phys. A33:1843002. doi: 10.1142/S0217751X18430029

CrossRef Full Text | Google Scholar

Alekseev, E., Alekseeva, L., Volchenko, V., and Krivosheina, I. (1987). Possible detection of a neutrino signal on 23 february 1987 at the baksan undergroundscintillation telescope of the institute of nuclear research. JETP Lett. 45, 589–592.

Google Scholar

Alekseev, I., Belov, V., Brudanin, V., Danilov, M., Egorov, V., Filosofov, D., et al. (2018). Search for sterile neutrinos at the DANSS experiment. High Energy Phys. Exp. arXiv:1804.04046v2.

Google Scholar

Alenkov, V., Aryal, P., Beyer, J., Boiko, R. S., Boonin, K., Buzanov, O., et al. (2015). Technical design report for the AMoRE 0νββ decay search experiment. arXiv:1512.05957.

Google Scholar

Ali, Z. S., Parsons, A. R., Zheng, H., Pober, J. C., Liu, A., Aguirre, J. E., et al. (2015). PAPER-64 constraints on reionization: the 21cm power spectrum at z = 8.4. Astrophys. J. 809:61. doi: 10.1088/0004-637X/809/1/61

CrossRef Full Text | Google Scholar

Ali-Haimoud, Y., and Bird, S. (2012). An efficient implementation of massive neutrinos in non-linear structure formation simulations. Mon. Not. R. Astron. Soc. 428, 3375–3389. doi: 10.1093/mnras/sts286

CrossRef Full Text | Google Scholar

Allen, S., Schmidt, R., and Bridle, S. (2003). A Preference for a non-zero neutrino mass from cosmological data. Mon.Not.Roy.Astron.Soc., 346:593.

Google Scholar

Allen, S. W., Evrard, A. E., and Mantz, A. B. (2011). Cosmological parameters from observations of galaxy clusters. Ann. Rev. Astron. Astrophys. 49, 409–470. doi: 10.1146/annurev-astro-081710-102514

CrossRef Full Text | Google Scholar

Allison, R., Caucal, P., Calabrese, E., Dunkley, J., and Louis, T. (2015). Towards a cosmological neutrino mass detection. Phys.Rev.D, 92(12):123535.

Google Scholar

Alonso, J., Barros, N., Bergevin, M., Bernstein, A., Bignell, L., Blucher, E., et al. (2014). Advanced scintillator detector concept (ASDC): a Concept Paper on the physics potential of water-based liquid scintillator. e-Print: arXiv:1409.5864.

Google Scholar

Alpert, B., Balata, M., Bennett, D., Biasotti, M., Boragno, C., Brofferio, C., et al. (2015). HOLMES-The electron capture decay of ¹⁶³Ho to measure the electron neutrino mass with Sub-eV sensitivity. Eur. Phys. J. C 75:112. doi: 10.22323/1.244.0066

CrossRef Full Text | Google Scholar

Amendola, L., Appleby, S., Bacon, D., Baker, T., Baldi, M., Bartolo, N., et al. (2018). Cosmology and fundamental physics with the euclid satellite. Living Rev. Rel. 21:2. doi: 10.1007/s41114-017-0010-3

PubMed Abstract | CrossRef Full Text | Google Scholar

An, F., An, G., An, Q., Antonelli, V., Baussan, E., Beacom, J., et al. (2016). Neutrino physics with JUNO. J. Phys. G 43:030401.

Google Scholar

An, F. P., Bai, J. Z., Balantekin, A. B., Band, H. R., Beavis, D., Beriguete, W., et al. (2012). Observation of electron-antineutrino disappearance at Daya Bay. Phys. Rev. Lett. 108:171803. doi: 10.1103/PhysRevLett.108.171803

PubMed Abstract | CrossRef Full Text | Google Scholar

An, F. P., Balantekin, A. B., Band, H. R., Bishai, M., Blyth, S., Cao, D., et al. (2017). Measurement of electron antineutrino oscillation based on 1230 days of operation of the Daya Bay experiment. Phys. Rev. D D 95:072006. doi: 10.1103/PhysRevD.95.072006

CrossRef Full Text | Google Scholar

Ananthakrishnan, S. (1995). The giant meterwave radio telescope/GMRT. J. Astrophys. Astr. Suppl. 16:427.

Google Scholar

Anderson, L., Aubourg, E., Bailey, S., Beutler, F., Bhardwaj, V., Blanton, M., et al. (2014). The clustering of galaxies in the SDSS-III baryon oscillation spectroscopic survey: baryon acoustic oscillations in the Data Releases 10 and 11 Galaxy samples. Mon. Not. R. Astron. Soc., 441, 24–62. doi: 10.1093/mnras/stu523

CrossRef Full Text | Google Scholar

Anderson, L., Aubourg, E., Bailey, S., Bizyaev, D., Blanton, M., Bolton, A. S., et al. (2013). The clustering of galaxies in the SDSS-III baryon oscillation spectroscopic survey: baryon acoustic oscillations in the data release 9 spectroscopic galaxy sample. Mon. Not. R. Astron. Soc. 427, 3435–3467. doi: 10.1111/j.1365-2966.2012.22066.x

CrossRef Full Text | Google Scholar

Andringa, S., Arushanova, E., Asahi, S., Askins, M., Auty, D. J., Back, A. R., et al. (2016). Current status and future prospects of the SNO+ experiment. Adv. High Energy Phys. 2016:6194250. doi: 10.1155/2016/6194250

CrossRef Full Text | Google Scholar

Angrik, J., Armbrust, T., Beglarian, A., Besserer, U., Blumer, J., Bonn, J., et al. (2004). Report NPI ASCR Řež, EXP-01/2005.

Google Scholar

Archidiacono, M., Brinckmann, T., Lesgourgues, J., and Poulin, V. (2017). Physical effects involved in the measurements of neutrino masses with future cosmological data. JCAP 02:052. doi: 10.1088/1475-7516/2017/02/052

CrossRef Full Text | Google Scholar

Archidiacono, M., Giusarma, E., Hannestad, S., and Mena, O. (2013a). Cosmic dark radiation and neutrinos. Adv.High Energy Phys., 2013:191047.

Google Scholar

Archidiacono, M., Giusarma, E., Melchiorri, A., and Mena, O. (2013b). Neutrino and dark radiation properties in light of recent CMB observations. Phys.Rev.D, 87(10):103519.

Google Scholar

Archidiacono, M., and Hannestad, S. (2014). Updated constraints on non-standard neutrino interactions from Planck. JCAP 07:046. doi: 10.1088/1475-7516/2014/07/046

CrossRef Full Text | Google Scholar

Archidiacono, M., and Hannestad, S. (2016). Efficient calculation of cosmological neutrino clustering in the non-linear regime. JCAP 06:018. doi: 10.1088/1475-7516/2016/06/018

CrossRef Full Text | Google Scholar

Archidiacono, M., Hannestad, S., Mirizzi, A., Raffelt, G., and Wong, Y. Y. Y. (2013c). Axion hot dark matter bounds after Planck. JCAP 10:020. doi: 10.1088/1475-7516/2013/10/020

CrossRef Full Text | Google Scholar

Arnold, R., Augier, C., Baker, J., Barabash, A. S., Basharina-Freshville, A., Bongrand, M., et al. (2010). Probing new physics models of neutrinoless double beta decay with superNEMO. Eur. Phys. J. C 70, 927–943. doi: 10.1140/epjc/s10052-010-1481-5

CrossRef Full Text | Google Scholar

Arnold, R., Augier, C., Barabash, A. S., Basharina-Freshville, A., Blondel, S., Blot, S., et al. (2018). Final results on ⁸²Se double beta decay to the ground state of ⁸²Kr from the NEMO-3 experiment. e-Print: arXiv:1806.05553.

Google Scholar

Arteaga, M., Bertuzzo, E., Perez-Gonzalez, Y. F., and Zukanovich Funchal, R. (2017). Impact of beyond the standard model physics in the detection of the cosmic neutrino background. J. High Energy Phys. 09:124. doi: 10.1007/JHEP09(2017)124

CrossRef Full Text | Google Scholar

Artusa, D., Artusa, D. R., Avignone, F. T. III., Azzolini, O., Balata, M., Banks, T. I., et al. (2015). Searching for neutrinoless double-beta decay of ¹³⁰Te with CUORE. Adv. High Energy Phys. 2015:879871. doi: 10.1103/PhysRevLett.115.102502

CrossRef Full Text | Google Scholar

Ascencio-Sosa, M., Calatayud-Cadenillas, A., Gago, A., and Jones-Pérez, J. (2018). Matter effects in neutrino visible decay at future long-baseline experiments. J. High Energy Phys. arXiv:1805.03279.

Google Scholar

Asner, D. M., Bradley, R. F., de Viveiros, L., Doe, P. J., Fernandes, J. L., Fertl, M., et al. (2015). Single electron detection and spectroscopy via relativistic cyclotron radiation. Phys. Rev. Lett. 114:162501. doi: 10.1103/PhysRevLett.114.162501

PubMed Abstract | CrossRef Full Text | Google Scholar

Aubourg, E., Bailey, S., Bautista, J. E., Beutler, F., Bhardwaj, V., Bizyaev, D., et al. (2015). Cosmological implications of baryon acoustic oscillation measurements. Phys. Rev. D 92:123516. doi: 10.1103/PhysRevD.92.123516

CrossRef Full Text | Google Scholar

Audren, B., Lesgourgues, J., Bird, S., Haehnelt, M. G., and Viel, M. (2013). Neutrino masses and cosmological parameters from a Euclid-like survey: markov chain monte carlo forecasts including theoretical errors. JCAP 01:026. doi: 10.1088/1475-7516/2013/01/026

CrossRef Full Text | Google Scholar

Azzolini, O., Barrera, M. T., Beeman, J. W., Bellini, F., Beretta, M., Biassoni, M., et al. (2018). First result on the neutrinoless double beta decay of ⁸²Se with CUPID-0. Phys. Rev. Lett. 120:232502. doi: 10.1103/PhysRevLett.120.232502

CrossRef Full Text | Google Scholar

Bakhti, P., and Farzan, Y. (2014). Shedding light on LMA-Dark solar neutrino solution by medium baseline reactor experiments: JUNO and RENO-50. J. High Energy Phys. 07:064. doi: 10.1007/JHEP07(2014)064

CrossRef Full Text | Google Scholar

Bakhti, P., and Khan, A. N. (2017). Sensitivities to charged-current nonstandard neutrino interactions at DUNE. J. Phys. G 44:125001. doi: 10.1088/1361-6471/aa9098

CrossRef Full Text | Google Scholar

Baldi, M., Villaescusa-Navarro, F., Viel, M., Puchwein, E., Springel, V., and Moscardini, L. (2014). Cosmic degeneracies – I. Joint N-body simulations of modified gravity and massive neutrinos. Mon. Not. R. Astron. Soc. 440, 75–88. doi: 10.1093/mnras/stu259

CrossRef Full Text | Google Scholar

Balieiro Gomes, G., Forero, D., Guzzo, M., De Holanda, P., and Oliveira, R. N. (2018). Quantum decoherence effects in neutrino oscillations at DUNE. High Energy Phys. arXiv:1805.09818.

Google Scholar

Ballett, P., King, S. F., Pascoli, S., Prouse, N. W., and Wang, T. (2017). Sensitivities and synergies of DUNE and T2HK. Phys. Rev. D 96:033003. doi: 10.1103/PhysRevD.96.033003

CrossRef Full Text | Google Scholar

Banerjee, A., and Dalal, N. (2016). Simulating nonlinear cosmological structure formation with massive neutrinos. JCAP 11:015. doi: 10.1088/1475-7516/2016/11/015

CrossRef Full Text | Google Scholar

Banerjee, A., Powell, D., Abel, T., and Villaescusa-Navarro, F. (2018). Reducing noise in cosmological N-body simulations with neutrinos. JCAP arXiv:1801.03906. doi: 10.1088/1475-7516/2018/09/028

CrossRef Full Text | Google Scholar

Baracchini, E. (2018). PTOLEMY: a proposal for thermal relic detection of massive neutrinos and directional detection of MeV dark matter. Cosmol. Nongalact. Astrophys. arXiv:1808.01892.

Google Scholar

Barenboim, G., Masud, M., Ternes, C. A., and Tórtola, M. (2018a). Exploring the intrinsic Lorentz-violating parameters at DUNE. High Energy Phys. arXiv:1805.11094.

Google Scholar

Barenboim, G., Mena Requejo, O., and Quigg, C. (2005). Diagnostic potential of cosmic-neutrino absorption spectroscopy. Phys. Rev. D 71:083002. doi: 10.1103/PhysRevD.71.083002

CrossRef Full Text | Google Scholar

Barenboim, G., Ternes, C. A., and Tórtola, M. (2018b). Neutrinos, DUNE and the world best bound on CPT invariance. Phys. Lett. B780, 631–637. doi: 10.1016/j.physletb.2018.03.060

CrossRef Full Text | Google Scholar

Barenboim, G., Ternes, C. A., and Tórtola, M. (2018c). New physics vs new paradigms: distinguishing CPT violation from NSI. High Energy Phys. arXiv:1804.05842.

Google Scholar

Barger, V., Marfatia, D., and Tregre, A. (2004). Neutrino mass limits from SDSS, 2dFGRS and WMAP. Phys. Lett. B595, 55–59. doi: 10.1016/j.physletb.2004.06.049

CrossRef Full Text | Google Scholar

Barkana, R. (2018). Possible interaction between baryons and dark-matter particles revealed by the first stars. Nature 555, 71–74. doi: 10.1038/nature25791

PubMed Abstract | CrossRef Full Text | Google Scholar

Barkana, R., and Loeb, A. (2005a). A Method for separating the physics from the astrophysics of high-redshift 21 cm fluctuations. Astrophys. J. 624, L65–L68. doi: 10.1086/430599

CrossRef Full Text | Google Scholar

Barkana, R., and Loeb, A. (2005b). Probing the epoch of early baryonic infall through 21cm fluctuations. Mon. Not. R. Astron. Soc. 363, L36–L40. doi: 10.1111/j.1745-3933.2005.00079.x

CrossRef Full Text | Google Scholar

Barkana, R., Outmezguine, N. J., Redigolo, D., and Volansky, T. (2018). Signs of Dark Matter at 21-cm? Cosmol. Nongalact. Astrophy. arXiv:1803.03091.

Google Scholar

Barreira, A., Li, B., Baugh, C., and Pascoli, S. (2014). Modified gravity with massive neutrinos as a testable alternative cosmological model. Phys. Rev. D 90:023528. doi: 10.1103/PhysRevD.90.023528

CrossRef Full Text | Google Scholar

Basse, T., Bjaelde, O. E., Hamann, J., Hannestad, S., and Wong, Y. Y. (2014). Dark energy properties from large future galaxy surveys. JCAP 05:021. doi: 10.1088/1475-7516/2014/05/021

CrossRef Full Text | Google Scholar

Bautista, J. E., Busca, N. G., Guy, J., Rich, J., Blomqvist, M., Bourboux, H. d. M. d., et al. (2017a). Measurement of BAO correlations at z = 2.3 with SDSS DR12 Lyα-Forests. Astron. Astrophys. 603:A12. doi: 10.1051/0004-6361/201730533

CrossRef Full Text | Google Scholar

Bautista, J. E., Vargas-Magańa, M., Dawson, K. S., Percival, W. J., Brinkmann, J., Brownstein, J., et al. (2017b). The SDSS-IV extended baryon oscillation spectroscopic survey: baryon acoustic oscillations at redshift of 0.72 with the DR14 luminous red galaxy sample. Astrophys. J. 863:110. doi: 10.3847/1538-4357/aacea5

CrossRef Full Text | Google Scholar

Beacom, J. F., Bell, N. F., and Dodelson, S. (2004). Neutrinoless universe. Phys. Rev. Lett. 93:121302. doi: 10.1103/PhysRevLett.93.121302

PubMed Abstract | CrossRef Full Text | Google Scholar

Beacom, J. F., and Vogel, P. (1998). Mass signature of supernova muon-neutrino and tau-neutrino neutrinos in Super-Kamiokande. Phys. Rev. D 58:053010. doi: 10.1103/PhysRevD.58.053010

CrossRef Full Text | Google Scholar

Beardsley, A. P., Morales, M. F., Lidz, A., Malloy, M., and Sutter, P. M. (2015). Adding context to james webb space telescope surveys with current and future 21cm radio observations. Astrophys. J. 800:128. doi: 10.1088/0004-637X/800/2/128

CrossRef Full Text | Google Scholar

Behera, S. P., Ghosh, A., Choubey, S., Datar, V. M., Mishra, D. K., and Mohanty, A. K. (2017). Search for the sterile neutrino mixing with the ICAL detector at INO. Eur. Phys. J. C 77:307. doi: 10.1140/epjc/s10052-017-4851-4

CrossRef Full Text | Google Scholar

Bell, N. F., Pierpaoli, E., and Sigurdson, K. (2006). Cosmological signatures of interacting neutrinos. Phys. Rev. D 73:063523. doi: 10.1103/PhysRevD.73.063523

CrossRef Full Text | Google Scholar

Bellini, G., Benziger, J., Bick, D., Bonfini, G., Bravo, D., Avanzini, M. B., et al. (2014). Final results of Borexino Phase-I on low energy solar neutrino spectroscopy. Phys. Rev. D, 89:112007. doi: 10.1103/PhysRevD.89.112007

CrossRef Full Text | Google Scholar

Bellomo, N., Bellini, E., Hu, B., Jimenez, R., Peña-Garay, C., and Verde, L. (2017). Hiding neutrino mass in modified gravity cosmologies. JCAP 02:043. doi: 10.1088/1475-7516/2017/02/043

CrossRef Full Text | Google Scholar

Benson, B., Ade, P. A. R., Ahmed, Z., Allen, S. W., Arnold, K., Austermann, J. E., et al. (2014). “SPT-3G: a next-generation cosmic microwave background polarization experiment on the south pole telescope,” Proceedings Volume 9153, Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy VII (Montréal, QC).

Google Scholar

Berlin, A., Hooper, D., Krnjaic, G., and McDermott, S. D. (2018). Severely constraining dark matter interpretations of the 21-cm anomaly. Phys. Rev. Lett. 121:011102. doi: 10.1103/PhysRevLett.121.011102

PubMed Abstract | CrossRef Full Text | Google Scholar

Berryman, J. M., de Gouvea, A., Kelly, K. J., and Kobach, A. (2015). Sterile neutrino at the deep underground neutrino experiment. Phys. Rev. D 92:073012. doi: 10.1103/PhysRevD.92.073012

CrossRef Full Text | Google Scholar

Berryman, J. M., de Gouvea, A., Kelly, K. J., Peres, O. L. G., and Tabrizi, Z. (2016). Large, extra dimensions at the deep underground neutrino experiment. Phys. Rev. D 94:033006. doi: 10.1103/PhysRevD.94.033006

CrossRef Full Text | Google Scholar

Betoule, M., Kessler, R., Guy, J., Mosher, J., Hardin, D., Biswas, R., et al. (2014). Improved cosmological constraints from a joint analysis of the SDSS-II and SNLS supernova samples. Astron. Astrophys. 568:A22. doi: 10.1051/0004-6361/201423413

CrossRef Full Text | Google Scholar

Betoule, M., Marriner, J., Regnault, N., Cuillandre, J.-C., Astier, P., Guy, J., et al. (2013). Improved photometric calibration of the SNLS and the SDSS supernova surveys. Astron. Astrophys. 552:A124. doi: 10.1051/0004-6361/201220610

CrossRef Full Text | Google Scholar

Betts, S., Blanchard, W. R., Carnevale, R. H., Chang, C., Chen, C., Chidzik, S., et al. (2013). “Development of a Relic Neutrino Detection Experiment at PTOLEMY: Princeton Tritium Observatory for Light, Early-Universe, Massive-Neutrino Yield.” in Proceedings, Community Summer Study 2013: Snowmass on the Mississippi (CSS2013) (Minneapolis, MN).

Google Scholar

Beutler, F., Blake, C., Colless, M., Jones, D. H., Staveley-Smith, L., Campbell, L., Parker, Q., Saunders, W., and Watson, F. (2011). The 6dF galaxy survey: baryon acoustic oscillations and the local hubble constant. Mon. Not. Roy. Astron. Soc. 416, 3017–3032. doi: 10.1111/j.1365-2966.2011.19250.x

CrossRef Full Text | Google Scholar

Beutler, F., Seo, H.-J., Ross, A. J., McDonald, P., Saito, S., Bolton, A. S., et al. (2017b). The clustering of galaxies in the completed SDSS-III Baryon Oscillation spectroscopic survey: baryon acoustic oscillations in Fourier-space. Mon. Not. R. Astron. Soc. 464, 3409–3430. doi: 10.1093/mnras/stw2373

CrossRef Full Text | Google Scholar

Beutler, F., Seo, H.-J., Saito, S., Chuang, C.-H., Cuesta, A. J., Eisenstein, D. J., et al. (2017a). The clustering of galaxies in the completed SDSS-III baryon oscillation spectroscopic survey: anisotropic galaxy clustering in Fourier-space. Mon. Not. R. Astron. Soc. 466, 2242–2260. doi: 10.1093/mnras/stw3298

CrossRef Full Text | Google Scholar

Bionta, R., Blewitt, G., Bratton, C. B., Casper, D., Ciocio, A., Claus, R., Cortez, B., et al. (1987). Observation of a neutrino burst in coincidence with supernova SN 1987a in the large magellanic cloud. Phys. Rev. Lett. 58:1494. doi: 10.1103/PhysRevLett.58.1494

CrossRef Full Text | Google Scholar

Bird, S., Viel, M., and Haehnelt, M. G. (2012). Massive Neutrinos and the Non-linear Matter Power Spectrum. Mon. Not. R. Astron. Soc. 420, 2551–2561. doi: 10.1111/j.1365-2966.2011.20222.x

CrossRef Full Text | Google Scholar

Bjaelde, O. E. (2008). Neutrino dark energy–revisiting the stability issue. JCAP 01:026. doi: 10.1088/1475-7516/2008/01/026

CrossRef Full Text | Google Scholar

Blake, C., Kazin, E., Beutler, F., Davis, T., Parkinson, D., Brough, S., et al. (2011). The WiggleZ Dark Energy Survey: mapping the distance-redshift relation with baryon acoustic oscillations. Mon. Not. R. Astron. Soc. 418, 1707–1724. doi: 10.1111/j.1365-2966.2011.19592.x

CrossRef Full Text | Google Scholar

Blas, D., Lesgourgues, J., and Tram, T. (2011). The cosmic linear anisotropy solving system (CLASS) II: approximation schemes. JCAP 07:034. doi: 10.1088/1475-7516/2011/07/034

CrossRef Full Text | Google Scholar

Blennow, M. (2008). Prospects for cosmic neutrino detection in tritium experiments in the case of hierarchical neutrino masses. Phys. Rev. D 77:113014. doi: 10.1103/PhysRevD.77.113014

CrossRef Full Text | Google Scholar

Blennow, M. (2014). On the Bayesian approach to neutrino mass ordering. J. High Energy Phys. 01:139. doi: 10.1007/JHEP01(2014)139

CrossRef Full Text | Google Scholar

Blennow, M., Coloma, P., Fernandez-Martinez, E., Hernandez-Garcia, J., and Lopez-Pavon, J. (2017). Non-Unitarity, sterile neutrinos, and Non-Standard neutrino Interactions. J. High Energy Phys. 04:153. doi: 10.1007/JHEP04(2017)153

CrossRef Full Text | Google Scholar

Blennow, M., Coloma, P., Huber, P., and Schwetz, T. (2014). Quantifying the sensitivity of oscillation experiments to the neutrino mass ordering. J. High Energy Phys. 03:028. doi: 10.1007/JHEP03(2014)028

CrossRef Full Text | Google Scholar

Blennow, M., and Schwetz, T. (2013). Determination of the neutrino mass ordering by combining PINGU and Daya Bay II. J. High Energy Phys. 09:089. doi: 10.1007/JHEP09(2013)089

CrossRef Full Text | Google Scholar

Blennow, M., and Smirnov, A. Y. (2013). Neutrino propagation in matter. Adv. High Energy Phys. 2013:972485. doi: 10.1155/2013/972485

CrossRef Full Text | Google Scholar

Boehm, C., Dolan, M. J., and McCabe, C. (2012). Increasing Neff with particles in thermal equilibrium with neutrinos. JCAP 12:027. doi: 10.1088/1475-7516/2012/12/027

CrossRef Full Text | Google Scholar

Bond, J., Efstathiou, G., and Tegmark, M. (1997). Forecasting cosmic parameter errors from microwave background anisotropy experiments. Mon. Not. R. Astron. Soc. 291, L33–L41. doi: 10.1093/mnras/291.1.L33

CrossRef Full Text | Google Scholar

Bond, J., Jaffe, A. H., and Knox, L. (2000). Radical compression of cosmic microwave background data. Astrophys. J. 533:19. doi: 10.1086/308625

CrossRef Full Text | Google Scholar

Bond, J. R., Efstathiou, G., and Silk, J. (1980). Massive neutrinos and the large scale structure of the universe. Phys. Rev. Lett. 45, 1980–1984. doi: 10.1103/PhysRevLett.45.1980

CrossRef Full Text | Google Scholar

Bourboux, H. d. M. d., Le Goff, J.-M., Blomqvist, M., Busca, N. G., Guy, J., Rich, J., et al. (2017). Baryon acoustic oscillations from the complete SDSS-III Lyα-quasar cross-correlation function at z = 2.4. Astron. Astrophys. 608:A130. doi: 10.1051/0004-6361/201731731

CrossRef Full Text | Google Scholar

Bowman, J. D., Morales, M. F., and Hewitt, J. N. (2007). Constraints on fundamental cosmological parameters with upcoming epoch of reionization observations. Astrophys. J. 661, 1–9. doi: 10.1086/516560

CrossRef Full Text | Google Scholar

Bowman, J. D., and Rogers, A. E. (2010). A lower limit of dz > 0.06 for the duration of the reionization epoch. Nature 468, 796–798. doi: 10.1038/nature09601

CrossRef Full Text | Google Scholar

Bowman, J. D., Rogers, A. E. E., Monsalve, R. A., Mozdzen, T. J., and Mahesh, N. (2018). An absorption profile centred at 78 megahertz in the sky-averaged spectrum. Nature 555, 67–70. doi: 10.1038/nature25792

PubMed Abstract | CrossRef Full Text | Google Scholar

Brandbyge, J., and Hannestad, S. (2009). Grid based linear neutrino perturbations in cosmological N-body simulations. JCAP 05:002. doi: 10.1088/1475-7516/2009/05/002

CrossRef Full Text | Google Scholar

Brookfield, A., van de Bruck, C., Mota, D., and Tocchini-Valentini, D. (2006a). Cosmology with massive neutrinos coupled to dark energy. Phys. Rev. Lett. 96:061301. doi: 10.1103/PhysRevLett.96.061301

PubMed Abstract | CrossRef Full Text | Google Scholar

Brookfield, A. W., van de Bruck, C., Mota, D., and Tocchini-Valentini, D. (2006b). Cosmology of mass-varying neutrinos driven by quintessence: theory and observations. Phys. Rev. D 73:083515. doi: 10.1103/PhysRevD.73.08351510.1103/PhysRevD.76.049901

CrossRef Full Text | Google Scholar

Bull, P., Ferreira, P. G., Patel, P., and Santos, M. G. (2015). Late-time cosmology with 21cm intensity mapping experiments. Astrophys. J. 803:21. doi: 10.1088/0004-637X/803/1/21

CrossRef Full Text | Google Scholar

Burns, J. O., Lazio, T. J. W., Bale, S. D., Bowman, J. D., Bradley, R. F., Carilli, C. L., et al. (2012). Probing the first stars and black holes in the early universe with the dark ages radio explorer (DARE). Adv. Space Res. 49, 433–450. doi: 10.1016/j.asr.2011.10.014

CrossRef Full Text | Google Scholar

Busca, N. G., Delubac, T., Rich, J., Bailey, S., Font-Ribera, A., Kirkby, D., et al. (2013). Baryon acoustic oscillations in the Ly-α forest of BOSS quasars. Astron. Astrophys. 552:A96. doi: 10.1051/0004-6361/201220724

CrossRef Full Text | Google Scholar

Caldwell, A., Merle, A., Schulz, O., and Totzauer, M. (2017). A global bayesian analysis of neutrino mass data. Phys. Rev. D 96:073001. doi: 10.1103/PhysRevD.96.073001

CrossRef Full Text | Google Scholar

Caldwell, R., Dave, R., and Steinhardt, P. J. (1998). Cosmological imprint of an energy component with general equation of state. Phys. Rev. Lett. 80, 1582–1585. doi: 10.1103/PhysRevLett.80.1582

CrossRef Full Text | Google Scholar

Canac, N., Aslanyan, G., Abazajian, K. N., Easther, R., and Price, L. C. (2016). Testing for new physics: neutrinos and the primordial power spectrum. JCAP 09:022. doi: 10.1088/1475-7516/2016/09/022

CrossRef Full Text | Google Scholar

Capozzi, F., Di Valentino, E., Lisi, E., Marrone, A., Melchiorri, A., and Palazzo, A. (2017). Global constraints on absolute neutrino masses and their ordering. Phys. Rev. D D 95:096014. doi: 10.1103/PhysRevD.95.096014

CrossRef Full Text | Google Scholar

Capozzi, F., Lisi, E., and Marrone, A. (2015). PINGU and the neutrino mass hierarchy: Statistical and systematic aspects. Phys. Rev. D 91:073011. doi: 10.1103/PhysRevD.91.073011

CrossRef Full Text | Google Scholar

Capozzi, F., Lisi, E., Marrone, A., and Palazzo, A. (2018a). Current unknowns in the three neutrino framework. Prog. Part. Nucl. Phys. 102, 48–72. doi: 10.1016/j.ppnp.2018.05.005

CrossRef Full Text | Google Scholar

Capozzi, F., Shoemaker, I. M., and Vecchi, L. (2018b). Neutrino oscillations in dark backgrounds. JCAP 07:004. doi: 10.1088/1475-7516/2018/07/004

CrossRef Full Text | Google Scholar

Carbone, C., Fedeli, C., Moscardini, L., and Cimatti, A. (2012). Measuring the neutrino mass from future wide galaxy cluster catalogues. JCAP 03:023. doi: 10.1088/1475-7516/2012/03/023

CrossRef Full Text | Google Scholar

Carbone, C., Verde, L., Wang, Y., and Cimatti, A. (2011). Neutrino constraints from future nearly all-sky spectroscopic galaxy surveys. JCAP 03:030. doi: 10.1088/1475-7516/2011/03/030

CrossRef Full Text | Google Scholar

Castorina, E., Sefusatti, E., Sheth, R. K., Villaescusa-Navarro, F., and Viel, M. (2014). Cosmology with massive neutrinos II: on the universality of the halo mass function and bias. JCAP 02:049. doi: 10.1088/1475-7516/2014/02/049

CrossRef Full Text | Google Scholar

Chakraborty, K., Deepthi, K., Goswami, S., Joshipura, A. S., and Nath, N. (2018). Partial μ-τ reflection symmetry and its verification at DUNE and hyper-kamiokande. High Energy Phys. arXiv:1804.02022.

Google Scholar

Chang, C., Pujol, A., Gaztanaga, E., Amara, A., Refregier, A., Bacon, D., et al. (2016). Galaxy bias from the dark energy survey science verification data: combining galaxy density maps and weak lensing maps. Mon. Not. R. Astron. Soc. 459, 3203–3216. doi: 10.1093/mnras/stw861

CrossRef Full Text | Google Scholar

Chang, T.-C., Pen, U.-L., Peterson, J. B., and McDonald, P. (2008). Baryon acoustic oscillation intensity mapping as a test of dark energy. Phys. Rev. Lett. 100:091303. doi: 10.1103/PhysRevLett.100.091303

CrossRef Full Text | Google Scholar

Chatterjee, A., Gandhi, R., and Singh, J. (2014). Probing lorentz and CPT violation in a magnetized iron detector using atmospheric neutrinos. J. High Energy Phys. 06:045. doi: 10.1007/JHEP06(2014)045

CrossRef Full Text | Google Scholar

Chatterjee, S. S., Masud, M., Pasquini, P., and Valle, J. (2017a). Cornering the revamped BMV model with neutrino oscillation data. Phys. Lett. B774, 179–182. doi: 10.1016/j.physletb.2017.09.052

CrossRef Full Text | Google Scholar

Chatterjee, S. S., Pasquini, P., and Valle, J. W. F. (2017b). Probing atmospheric mixing and leptonic CP violation in current and future long baseline oscillation experiments. Phys. Lett. B771, 524–531. doi: 10.1016/j.physletb.2017.05.080

CrossRef Full Text | Google Scholar

Chen, C.-S., Lee, F.-F., Lin, G.-L., and Lin, Y.-H. (2014). Probing dark matter self-interaction in the sun with iceCube-PINGU. JCAP 10:049. doi: 10.1088/1475-7516/2014/10/049

CrossRef Full Text | Google Scholar

Chen, X. (2017). PandaX-III: Searching for neutrinoless double beta decay with high pressure¹³⁶Xe gas time projection chambers. Sci. China Phys. Mech. Astron. 60:061011. doi: 10.1007/s11433-017-9028-0

CrossRef Full Text | Google Scholar

Chen, Y., and Xu, L. (2016). Galaxy clustering, CMB and supernova data constraints on ϕ CDM model with massive neutrinos. Phys. Lett. B752, 66–75. doi: 10.1016/j.physletb.2015.11.022

CrossRef Full Text | Google Scholar

Cheung, K., Kuo, J.-L., Ng, K.-W., and Tsai, Y.-L. S. (2018). The impact of EDGES 21-cm data on dark matter interactions. arXiv:1803.09398.

Google Scholar

Chevallier, M., and Polarski, D. (2001). Accelerating universes with scaling dark matter. Int. J. Mod. Phys. D10, 213–224. doi: 10.1142/S0218271801000822

CrossRef Full Text | Google Scholar

Choubey, S., Dasgupta, B., Dighe, A., and Mirizzi, A. (2010). Signatures of collective and matter effects on supernova neutrinos at large detectors. arXiv:1008.0308.

Google Scholar

Choubey, S., Ghosh, A., Ohlsson, T., and Tiwari, D. (2015). Neutrino physics with non-standard interactions at INO. J. High Energy Phys. 12:126. doi: 10.1007/JHEP12(2015)126

CrossRef Full Text | Google Scholar

Choubey, S., Ghosh, A., and Tiwari, D. (2018a). Prospects of Indirect Searches for Dark Matter at INO. JCAP 05:006. doi: 10.1088/1475-7516/2018/05/006

CrossRef Full Text | Google Scholar

Choubey, S., Goswami, S., Gupta, C., Lakshmi, S., and Thakore, T. (2018b). Sensitivity to neutrino decay with atmospheric neutrinos at the INO-ICAL detector. Phys. Rev. D 97:033005. doi: 10.1103/PhysRevD.97.033005

CrossRef Full Text | Google Scholar

Choubey, S., Goswami, S., and Pramanik, D. (2018c). A Study of Invisible Neutrino Decay at DUNE and its Effects on θ₂₃ Measurement. J High Energy Phys. 02:055. doi: 10.1007/JHEP02(2018)055

CrossRef Full Text | Google Scholar

Choubey, S., and Ohlsson, T. (2014). Bounds on non-standard neutrino interactions using PINGU. Phys. Lett. B739, 357–364. doi: 10.1016/j.physletb.2014.11.010

CrossRef Full Text | Google Scholar

Clark, S., Dutta, B., Gao, Y., Ma, Y.-Z., and Strigari, L. E. (2018). 21cm limits on decaying dark matter and primordial black holes. Phys. Rev. D 98:043006. doi: 10.1103/PhysRevD.98.043006

CrossRef Full Text | Google Scholar

Clesse, S., Lopez-Honorez, L., Ringeval, C., Tashiro, H., and Tytgat, M. H. (2012). Background reionization history from omniscopes. Phys. Rev. D 86:123506. doi: 10.1103/PhysRevD.86.123506

CrossRef Full Text | Google Scholar

Cleveland, B., Daily, T., Davis, R. Jr., Distel1, J. R., Lande, K., Lee, C. K., et al. (1998). Measurement of the solar electron neutrino flux with the Homestake chlorine detector. Astrophys. J. 496, 505–526. doi: 10.1086/305343

CrossRef Full Text | Google Scholar

Cocco, A. G., Mangano, G., and Messina, M. (2007). Probing low energy neutrino backgrounds with neutrino capture on beta decaying nuclei. JCAP 06:015. doi: 10.1088/1475-7516/2007/06/015

CrossRef Full Text | Google Scholar

Cole, S., Percival, W. J., Peacock, J. A., Norberg, P., Baugh, C. M., Frenk, C. S., et al. (2005). The 2dF galaxy redshift survey: power-spectrum analysis of the final dataset and Cosmological Implications. Mon. Not. R. Astron. Soc. 362, 505–534. doi: 10.1111/j.1365-2966.2005.09318.x

CrossRef Full Text | Google Scholar

Coloma, P. (2016). Non-standard interactions in propagation at the deep underground neutrino experiment. J. High Energy Phys. 03:016. doi: 10.1007/JHEP03(2016)016

CrossRef Full Text | Google Scholar

Coloma, P., Denton, P. B., Gonzalez-Garcia, M. C., Maltoni, M., and Schwetz, T. (2017). Curtailing the dark side in non-standard neutrino interactions. J. High Energy Phys. 04:116. doi: 10.1007/JHEP04(2017)116

CrossRef Full Text | Google Scholar

Coloma, P., Forero, D. V., and Parke, S. J. (2018). DUNE sensitivities to the mixing between sterile and tau neutrinos. J. High Energ. Phys. 07:079. doi: 10.1007/JHEP07(2018)079

CrossRef Full Text | Google Scholar

Coloma, P., and Peres, O. L. G. (2017). Visible neutrino decay at DUNE. J. High Energy Phys. arXiv:1705.03599.

Google Scholar

Coloma, P., and Schwetz, T. (2016). Generalized mass ordering degeneracy in neutrino oscillation experiments. Phys. Rev. D 94:055005. doi: 10.1103/PhysRevD.95.079903

CrossRef Full Text | Google Scholar

Cooray, A. R. (1999). Weighing neutrinos: weak lensing approach. Astron. Astrophys. 348:31.

Google Scholar

Costa, A. A., Landim, R. C., Wang, B., and Abdalla, E. (2018). Interacting dark energy: possible explanation for 21-cm absorption at cosmic dawn. Eur. Phys. J. C 78:746. doi: 10.1140/epjc/s10052-018-6237-7

CrossRef Full Text | Google Scholar

Costanzi, M., Sartoris, B., Viel, M., and Borgani, S. (2014). Neutrino constraints: what large-scale structure and CMB data are telling us? JCAP 10:081. doi: 10.1088/1475-7516/2014/10/081

CrossRef Full Text | Google Scholar

Costanzi, M., Villaescusa-Navarro, F., Viel, M., Xia, J.-Q., Borgani, S., Castorina, E., et al. (2013). Cosmology with massive neutrinos III: the halo mass function andan application to galaxy clusters. JCAP 12:012. doi: 10.1088/1475-7516/2013/12/012

CrossRef Full Text | Google Scholar

Cravens, J. (2008). Solar neutrino measurements in Super-Kamiokande-II. Phys.Rev.D, 78:032002.

Google Scholar

Croft, R. A., Hu, W., and Dave, R. (1999). Cosmological Limits on the Neutrino Mass from the Lya Forest. Phys. Rev. Lett. 83, 1092–1095. doi: 10.1103/PhysRevLett.83.1092

CrossRef Full Text | Google Scholar

Crotty, P., Lesgourgues, J., and Pastor, S. (2004). Current cosmological bounds on neutrino masses and relativistic relics. Phys. Rev. D 69:123007. doi: 10.1103/PhysRevD.69.123007

CrossRef Full Text | Google Scholar

Cuesta, A. J., Niro, V., and Verde, L. (2016). Neutrino mass limits: robust information from the power spectrum of galaxy surveys. Phys. Dark Univ. 13, 77–86. doi: 10.1016/j.dark.2016.04.005

CrossRef Full Text | Google Scholar

Dakin, J., Brandbyge, J., Hannestad, S., Haugbølle, T., and Tram, T. (2017). νCONCEPT: Cosmological neutrino simulations from the non-linear Boltzmann hierarchy. arXiv:1712.03944.

Google Scholar

D'Amico, G., Panci, P., and Strumia, A. (2018). Bounds on dark matter annihilations from 21 cm data. Phys. Rev. Lett. 121:011103. doi: 10.1103/PhysRevLett.121.011103

PubMed Abstract | CrossRef Full Text | Google Scholar

Dasgupta, B., Dighe, A., Raffelt, G. G., and Smirnov, A. Y. (2009). Multiple spectral splits of supernova neutrinos. Phys. Rev. Lett. 103:051105. doi: 10.1103/PhysRevLett.103.051105

PubMed Abstract | CrossRef Full Text | Google Scholar

Dasgupta, B., Mirizzi, A., Tamborra, I., and Tomas, R. (2010). Neutrino mass hierarchy and three-flavor spectral splits of supernova neutrinos. Phys. Rev. D 81:093008. doi: 10.1103/PhysRevD.81.093008

CrossRef Full Text | Google Scholar

Dash, N., Datar, V., and Majumder, G. (2016). Sensitivity for detection of decay of dark matter particle using ICAL at INO. Pramana 86, 927–937. doi: 10.1007/s12043-015-1094-5

CrossRef Full Text | Google Scholar

Dawson, K. S., Kneib, J.-P., Percival, W. J., Alam, S., Albareti, F. D., Anderson, S. F., et al. (2016). The SDSS-IV extended baryon oscillation spectroscopic survey: overview and early data. Astron. J. 151:44. doi: 10.3847/0004-6256/151/2/44

CrossRef Full Text | Google Scholar

Dawson, K. S., Schlegel, D. J., Ahn, C. P., Anderson, S. F., Aubourg, É., Bailey, S., et al. (2013). The baryon oscillation spectroscopic survey of SDSS-III. Astron. J. 145:10. doi: 10.1088/0004-6256/145/1/10

CrossRef Full Text | Google Scholar

De Bernardis, F., Kitching, T. D., Heavens, A., and Melchiorri, A. (2009). Determining the neutrino mass hierarchy with cosmology. Phys. Rev. D 80:123509. doi: 10.1103/PhysRevD.80.123509

CrossRef Full Text | Google Scholar

De Bernardis, F., Stevens, J. R., Hasselfield, M., Alonso, D., Bond, J. R., Calabrese, E., et al. (2016). “Survey strategy optimization for the atacama Cosmology telescope,” in Proceedings Volume 9910, Observatory Operations: Strategies, Processes, and Systems VI; 991014 (Edinburgh).

Google Scholar

de Gouvêa, A., and Kelly, K. J. (2016). Non-standard neutrino interactions at DUNE. Nucl. Phys. B908, 318–335. doi: 10.1016/j.nuclphysb.2016.03.013

CrossRef Full Text | Google Scholar

de Gouvêa, A., and Kelly, K. J. (2017). Neutrino vs. Antineutrino oscillation parameters at DUNE and hyper-kamiokande. Phys. Rev. D 96:095018. doi: 10.1103/PhysRevD.96.095018

CrossRef Full Text | Google Scholar

de Haan, T., Benson, B. A., Bleem, L. E., Allen, S. W., Applegate, D. E., Ashby, M. L. N., et al. (2016). Cosmological constraints from galaxy clusters in the 2500 square-degree SPT-SZ survey. Astrophys. J. 832:95. doi: 10.3847/0004-637X/832/1/95

CrossRef Full Text | Google Scholar

de Putter, R., Linder, E. V., and Mishra, A. (2014). Inflationary freedom and cosmological neutrino constraints. Phys. Rev. D 89:103502. doi: 10.1103/PhysRevD.89.103502

CrossRef Full Text | Google Scholar

de Putter, R., Mena, O., Giusarma, E., Ho, S., Cuesta, A., Seo, H.-J., et al. (2012). New neutrino mass bounds from sloan digital sky survey III data release 8 photometric luminous galaxies. Astrophys. J. 761:12. doi: 10.1088/0004-637X/761/1/12

CrossRef Full Text | Google Scholar

de Putter, R., Zahn, O., and Linder, E. V. (2009). CMB lensing constraints on neutrinos and dark energy. Phys. Rev. D 79:065033. doi: 10.1103/PhysRevD.79.065033

CrossRef Full Text | Google Scholar

De Romeri, V., Fernandez-Martinez, E., and Sorel, M. (2016). Neutrino oscillations at DUNE with improved energy reconstruction. J. High Energy Phys. 09:030. doi: 10.1007/JHEP09(2016)030

CrossRef Full Text | Google Scholar

De Rujula, A., and Lusignoli, M. (1982). Calorimetric measurements of ¹⁶³Ho decay as tools to determine the electron neutrino mass. Phys. Lett. B118:429. doi: 10.1016/0370-2693(82)90218-0

CrossRef Full Text | Google Scholar

de Salas, P., Forero, D., Ternes, C., Tórtola, M., and Valle, J. (2018). Status of neutrino oscillations 2018: 3 σ hint for normal mass ordering and improved CP sensitivity. Phys. Lett. B782, 633–640. doi: 10.1016/j.physletb.2018.06.019

CrossRef Full Text | Google Scholar

de Salas, P. F., Gariazzo, S., Lesgourgues, J., and Pastor, S. (2017). Calculation of the local density of relic neutrinos. JCAP 09:034. doi: 10.1088/1475-7516/2017/09/034

CrossRef Full Text | Google Scholar

de Salas, P. F., and Pastor, S. (2016). Relic neutrino decoupling with flavour oscillations revisited. JCAP 07:051. doi: 10.1088/1475-7516/2016/07/051

CrossRef Full Text | Google Scholar

Debono, I., Rassat, A., Refregier, A., Amara, A., and Kitching, T. (2010). Weak lensing forecasts for dark energy, neutrinos and initial conditions. Mon. Not. R. Astron. Soc. 404, 110–119. doi: 10.1111/j.1365-2966.2010.16284.x

CrossRef Full Text | Google Scholar

Deepthi, K. N., Goswami, S., and Nath, N. (2017). Nonstandard interactions jeopardizing the hierarchy sensitivity of DUNE. Phys. Rev. D 96:075023. doi: 10.1103/PhysRevD.96.075023

CrossRef Full Text | Google Scholar

Delabrouille, J., de Bernardis, P., Bouchet, F. R., Achúcarro, A., Ade, P. A. R., Allison, R., et al. (2018). Exploring cosmic origins with CORE: survey requirements and mission design. JCAP 04:014. doi: 10.1088/1475-7516/2018/04/014

CrossRef Full Text | Google Scholar

Dell'Oro, S., Marcocci, S., Viel, M., and Vissani, F. (2016). Neutrinoless double beta decay: 2015 review. Adv. High Energy Phys. 2016:2162659. doi: 10.1155/2016/2162659

CrossRef Full Text | Google Scholar

Delubac, T., Bautista, J. E., Busca, N. G., Rich, J., Kirkby, D., Bailey, S., et al. (2015). Baryon acoustic oscillations in the Lyα forest of BOSS DR11 quasars. Astron. Astrophys. 574:A59. doi: 10.1051/0004-6361/201423969

CrossRef Full Text | Google Scholar

Dentler, M., Hernández-Cabezudo, ạ́., Kopp, J., Machado, P. A. N., Maltoni, M., Martinez-Soler, I., et al. (2018). Updated global analysis of neutrino oscillations in the presence of eV-scale sterile neutrinos. J. High Energy Phys. 08:010. doi: 10.1007/JHEP08(2018)010

CrossRef Full Text | Google Scholar

Dentler, M., Hernández-Cabezudo, A., Kopp, J., Maltoni, M., and Schwetz, T. (2017). Sterile neutrinos or flux uncertainties?-status of the reactor anti-neutrino anomaly. J. High Energy Phys. 11:099. doi: 10.1007/JHEP11(2017)099

CrossRef Full Text | Google Scholar

Desjacques, V., Jeong, D., and Schmidt, F. (2018). Large-scale galaxy bias. Phys. Rept. 733:1–193. doi: 10.1016/j.physrep.2017.12.002

CrossRef Full Text | Google Scholar

Dewdney, P., Turner, W., Millenaar, R., McCool, R., Lazio, J., Cornwell, T. J., et al. (2015). SKA Baseline Description. Available online at: https://www.skatelescope.org/wp-content/uploads/2014/03/SKA-TEL-SKO-0000308_SKA1_System_Baseline_v2_DescriptionRev01-part-1-signed.pdf.

Di Valentino, E., Brinckmann, T., Gerbino, M., Poulin, V., Bouchet, F. R., Lesgourgues, J., et al. (2018a). Exploring cosmic origins with cORE: cosmological parameters. JCAP 04:017. doi: 10.1088/1475-7516/2018/04/017

CrossRef Full Text | Google Scholar

Di Valentino, E., Gariazzo, S., Gerbino, M., Giusarma, E., and Mena, O. (2016a). Dark radiation and inflationary freedom after planck 2015. Phys. Rev. D D 93:083523. doi: 10.1103/PhysRevD.93.083523

CrossRef Full Text | Google Scholar

Di Valentino, E., Gariazzo, S., Giusarma, E., and Mena, O. (2015). Robustness of cosmological axion mass limits. Phys. Rev. D D 91:123505. doi: 10.1103/PhysRevD.91.123505

CrossRef Full Text | Google Scholar

Di Valentino, E., Giusarma, E., Lattanzi, M., Mena, O., Melchiorri, A., and Silk, J. (2016b). Cosmological Axion and neutrino mass constraints from Planck 2015 temperature and polarization data. Phys. Lett. B752, 182–185. doi: 10.1016/j.physletb.2015.11.025

CrossRef Full Text | Google Scholar

Di Valentino, E., Giusarma, E., Mena, O., Melchiorri, A., and Silk, J. (2016c). Cosmological limits on neutrino unknowns versus low redshift priors. Phys. Rev. D 93:083527. doi: 10.1103/PhysRevD.93.083527

CrossRef Full Text | Google Scholar

Di Valentino, E., hm, C. B. e., Hivon, E., and Bouchet, F. R. (2018b). Reducing the H₀ and σ₈ tensions with Dark Matter-neutrino interactions. Phys. Rev. D 97:043513. doi: 10.1103/PhysRevD.97.043513

CrossRef Full Text | Google Scholar

Di Valentino, E., Melchiorri, A., and Mena, O. (2013). Dark radiation sterile neutrino candidates after Planck data. JCAP 11:018. doi: 10.1088/1475-7516/2013/11/018

CrossRef Full Text | Google Scholar

Dirian, Y. (2017). Changing the prior: absolute neutrino mass constraints in nonlocal gravity. Phys. Rev. D 96:083513. doi: 10.1103/PhysRevD.96.083513

CrossRef Full Text | Google Scholar

Doe, P., Kofron, J., McBride, E. L., Robertson, R. G. H., Rosenberg, L. J., Rybka, G. S., et al. (2013) Project 8: determining neutrino mass from tritium beta decay using a frequency-based method. Nuclear Exp. arXiv:1309.7093..

Google Scholar

Domcke, V., and Spinrath, M. (2017). Detection prospects for the cosmic neutrino background using laser interferometers. JCAP 06:055. doi: 10.1088/1475-7516/2017/06/055

CrossRef Full Text | Google Scholar

Duan, H., Fuller, G. M., Carlson, J., and Qian, Y.-Z. (2007). Neutrino mass hierarchy and stepwise spectral swapping of supernova neutrino flavors. Phys. Rev. Lett. 99:241802. doi: 10.1103/PhysRevLett.99.241802

PubMed Abstract | CrossRef Full Text | Google Scholar

Duan, H., Fuller, G. M., and Qian, Y.-Z. (2010). Collective neutrino oscillations. Ann. Rev. Nucl. Part. Sci. 60, 569–594. doi: 10.1146/annurev.nucl.012809.104524

CrossRef Full Text | Google Scholar

Duda, G., Gelmini, G., and Nussinov, S. (2001). Expected signals in relic neutrino detectors. Phys. Rev. D 64:122001. doi: 10.1103/PhysRevD.64.122001

CrossRef Full Text | Google Scholar

Dutta, D., Ghoshal, P., and Roy, S. (2017). Effect of non unitarity on neutrino mass hierarchy determination at DUNE, NOνA and T2K. Nucl. Phys. B920, 385–401. doi: 10.1016/j.nuclphysb.2017.04.018

CrossRef Full Text | Google Scholar

Dvali, G., and Funcke, L. (2016). Small neutrino masses from gravitational θ-term. Phys. Rev. D 93:113002. doi: 10.1103/PhysRevD.93.113002

CrossRef Full Text | Google Scholar

Eberle, B., Ringwald, A., Song, L., and Weiler, T. J. (2004). Relic neutrino absorption spectroscopy. Phys. Rev. D 70:023007. doi: 10.1103/PhysRevD.70.023007

CrossRef Full Text | Google Scholar

Efstathiou, G. (2014). H0 revisited. Mon. Not. R. Astron. Soc. 440, 1138–1152. doi: 10.1093/mnras/stu278

CrossRef Full Text | Google Scholar

Eguchi, K., Enomoto, S., Furuno, K., Goldman, J., Hanada, H., Ikeda, H., et al. (2003). First results from KamLAND: evidence for reactor anti-neutrino disappearance. Phys. Rev. Lett. 90:021802. doi: 10.1103/PhysRevLett.90.021802

CrossRef Full Text | Google Scholar

Eisenstein, D. J., Weinberg, D. H., Agol, E., Aihara, H., Prieto, C. A., Anderson, S. F., et al. (2011). SDSS-III: massive spectroscopic surveys of the distant universe, the milky way galaxy, and extra-solar planetary systems. Astron. J. 142:72. doi: 10.1088/0004-6256/142/3/72

CrossRef Full Text | Google Scholar

Eisenstein, D. J., Zehavi, I., Hogg, D. W., Scoccimarro, R., Blanton, M. R., Nichol, R. C., et al. (2005). Detection of the baryon acoustic peak in the large-scale correlation function of SDSS luminous red galaxies. Astrophys. J. 633, 560–574. doi: 10.1086/466512

CrossRef Full Text | Google Scholar

Elgaroy, O., and Lahav, O. (2003). Upper limits on neutrino masses from the 2dFGRS and WMAP: the role of priors. JCAP 04:004. doi: 10.1088/1475-7516/2003/04/004

CrossRef Full Text | Google Scholar

Eliseev, S., Blaum, K., Block, M., Chenmarev, S., Dorrer, H., Düllmann, C. E., et al. (2015). Direct measurement of the mass difference of ¹⁶³Ho and ¹⁶³Dy solves the Q-value puzzle for the neutrino mass determination. Phys. Rev. Lett. 115:062501. doi: 10.1103/PhysRevLett.115.062501

CrossRef Full Text | Google Scholar

Engel, J., and Menéndez, J. (2017). Status and future of nuclear matrix elements for neutrinoless double-beta decay: a review. Rept. Prog. Phys. 80:046301.

PubMed Abstract | Google Scholar

Errard, J., Feeney, S. M., Peiris, H. V., and Jaffe, A. H. (2016). Robust forecasts on fundamental physics from the foreground-obscured, gravitationally-lensed CMB polarization. JCAP 03:052. doi: 10.1088/1475-7516/2016/03/052

CrossRef Full Text | Google Scholar

Escrihuela, F. J., Forero, D. V., Miranda, O. G., Tortola, M., and Valle, J. W. F. (2017). Probing CP violation with non-unitary mixing in long-baseline neutrino oscillation experiments: DUNE as a case study. New J. Phys. 19:093005. doi: 10.1088/1367-2630/aa79ec

CrossRef Full Text | Google Scholar

Esfahani, A. A., Asner, D. M., Böser, S., Cervantes, R., Claessens, C., de Viveiros, L., et al. (2017). Determining the neutrino mass with cyclotron radiation emission spectroscopy-Project 8. J. Phys. G 44:054004. doi: 10.1088/1361-6471/aa5b4f

CrossRef Full Text | Google Scholar

Essinger-Hileman, T., Ali, A., Amiri, M., Appel, J. W., Araujo, D., Bennett, C. L., et al. (2014). “CLASS: the cosmology large angular scale surveyor,” in Proceedings Millimeter, Submillimeter, and Far-Infrared Detectors and Instrumentation for Astronomy VII (Montréal, QC). doi: 10.1117/12.2056701

CrossRef Full Text | Google Scholar

Esteban, I., Gonzalez-Garcia, M. C., Maltoni, M., Martinez-Soler, I., and Schwetz, T. (2017). Updated fit to three neutrino mixing: exploring the accelerator-reactor complementarity. J. High Energy Phys. 01:087. doi: 10.1007/JHEP01(2017)087

CrossRef Full Text | Google Scholar

Esteban-Pretel, A., Mirizzi, A., Pastor, S., Tomas, R., Raffelt, G. G., Serpico, P. D., et al. (2008). Role of dense matter in collective supernova neutrino transformations. Phys. Rev. D 78:085012. doi: 10.1103/PhysRevD.78.085012

CrossRef Full Text | Google Scholar

Esteban-Pretel, A., Pastor, S., Tomas, R., Raffelt, G. G., and Sigl, G. (2007). Decoherence in supernova neutrino transformations suppressed by deleptonization. Phys. Rev. D 76:125018. doi: 10.1103/PhysRevD.76.125018

CrossRef Full Text | Google Scholar

Ewall-Wice, A., Chang, T., Lazio, J., Dore, O., Seiffert, M., and Monsalve, R. (2018). Modeling the radio background from the first black holes at cosmic Dawn: implications for the 21 cm absorption amplitude. arXiv:1803.01815.

Google Scholar

Faessler, A., Hodak, R., Kovalenko, S., and Simkovic, F. (2011). Beta decaying nuclei as a probe of cosmic neutrino background. J. High Energy Phys. arXiv:1102.1799.

Google Scholar

Falkowski, A., and Petraki, K. (2018). 21cm absorption signal from charge sequestration. J. High Energy Phys. arXiv:1803.10096.

Google Scholar

Fardon, R., Nelson, A. E., and Weiner, N. (2004). Dark energy from mass varying neutrinos. JCAP 10:005. doi: 10.1088/1475-7516/2004/10/005

CrossRef Full Text | Google Scholar

Farzan, Y., Peres, O., and Smirnov, A. (2001). Neutrino mass spectrum and future beta decay experiments. Nucl. Phys. B612, 59–97. doi: 10.1016/S0550-3213(01)00361-3

CrossRef Full Text | Google Scholar

Farzan, Y., and Tortola, M. (2018). Neutrino oscillations and Non-Standard Interactions. Front. Phys. 6:10. doi: 10.3389/fphy.2018.00010

CrossRef Full Text | Google Scholar

Feng, C., and Holder, G. (2018). Enhanced global signal of neutral hydrogen due to excess radiation at cosmic dawn. Astrophys. J. 858:L17. doi: 10.3847/2041-8213/aac0fe

CrossRef Full Text | Google Scholar

Fialkov, A., Barkana, R., and Cohen, A. (2018). Constraining baryon–dark matter scattering with the cosmic dawn 21-cm signal. Phys. Rev. Lett. 121:011101. doi: 10.1103/PhysRevLett.121.011101

PubMed Abstract | CrossRef Full Text | Google Scholar

Fogli, G., Lisi, E., Marrone, A., Melchiorri, A., Palazzo, A., Serra, P., Silk, J., et al. (2007). Observables sensitive to absolute neutrino masses: a Reappraisal after WMAP-3y and first MINOS results. Phys. Rev. D 75:053001. doi: 10.1103/PhysRevD.75.053001

CrossRef Full Text | Google Scholar

Fogli, G., Lisi, E., Marrone, A., Melchiorri, A., Palazzo, A., Serra, P., Silk, J., et al. (2008). Observables sensitive to absolute neutrino masses. 2. Phys. Rev. D 78:033010. doi: 10.1103/PhysRevD.78.033010

CrossRef Full Text | Google Scholar

Font-Ribera, A., Kirkby, D., Busca, N., Miralda-Escudé, J., Ross, N. P., Slosar, A., et al. (2014a). Quasar-lyman α forest cross-correlation from bOSS DR11 : baryon acoustic oscillations. JCAP 05:027. doi: 10.1088/1475-7516/2014/05/027

CrossRef Full Text | Google Scholar

Font-Ribera, A., McDonald, P., Mostek, N., Reid, B. A., Seo, H.-J., and Slosar, A. (2014b). DESI and other dark energy experiments in the era of neutrino mass measurements. JCAP 05:023. doi: 10.1088/1475-7516/2014/05/023

CrossRef Full Text | Google Scholar

Forero, D. V., and Huang, W.-C. (2017). Sizable NSI from the SU(2)_L scalar doublet-singlet mixing and the implications in DUNE. J. High Energy Phys. 03:018. doi: 10.1007/JHEP03(2017)018

CrossRef Full Text | Google Scholar

Forero, D. V., and Huber, P. (2016). Hints for leptonic CP violation or New Physics? Phys. Rev. Lett. 117:031801. doi: 10.1103/PhysRevLett.117.031801

CrossRef Full Text | Google Scholar

Forero, D. V., Tortola, M., and Valle, J. W. F. (2014). Neutrino oscillations refitted. Phys. Rev. D 90:093006. doi: 10.1103/PhysRevD.90.093006

CrossRef Full Text | Google Scholar

Fraser, S., Hektor, A., Hütsi, G., Kannike, K., Marzo, C., Marzola, L., et al. (2018). The EDGES 21 cm anomaly and properties of dark matter. Phys. Lett. B 785, 159–164. doi: 10.1016/j.physletb.2018.08.035

CrossRef Full Text | Google Scholar

Freedman, W. L., and Madore, B. F. (2010). The hubble constant. Ann. Rev. Astron. Astrophys. 48, 673–710. doi: 10.1146/annurev-astro-082708-101829

CrossRef Full Text | Google Scholar

Fukuda, Y., Hayakawa, T., Ichihara, E., Inoue, K., Ishihara, K., Ishino, H., et al. (1998). Evidence for oscillation of atmospheric neutrinos. Phys. Rev. Lett. 81, 1562–1567. doi: 10.1103/PhysRevLett.81.1562

CrossRef Full Text | Google Scholar

Furlanetto, S., Oh, S., and Briggs, F. (2006). Cosmology at low frequencies: the 21 cm transition and the high-redshift universe. Phys. Rept. 433, 181–301. doi: 10.1016/j.physrep.2006.08.002

CrossRef Full Text | Google Scholar

Furlanetto, S. R. (2015). “The 21-cm line as a probe of reionization,” in UUnderstanding the Epoch of Cosmic Reionization. Astrophysics and Space Science Library, Vol 423, ed A. Mesinger (Cham: Springer), 247–280.

Google Scholar

Gando, A., Gando, Y., Ichimura, K., Ikeda, H., Kibe, Y., Kishimoto, Y., et al. (2011). Constraints on θ₁₃ from a three-flavor oscillation analysis of reactor antineutrinos at KamLAND. Phys. Rev. D 83:052002. doi: 10.1103/PhysRevD.83.052002

CrossRef Full Text | Google Scholar

Gando, A., Gando, Y., Ichimura, K., Ikeda, H., Kibe, Y., Kishimoto, Y., et al. (2016). Search for majorana neutrinos near the inverted mass hierarchy region with KamLAND-Zen. Phys. Rev. Lett. 117:082503. doi: 10.1103/PhysRevLett.117.082503

CrossRef Full Text | Google Scholar

Gando, A. “KamLAND-Zen,” in XXVIII International Conference on Neutrino Physics Astrophysics, 4–9 June (2018), (Heidelberg). Available online at: URL: http://doi.org/10.5281/zenodo.1286895.,

Gariazzo, S., Archidiacono, M., de Salas, P. F., Mena, O., Ternes, C. A., and Tórtola, M. (2018a). Neutrino masses and their ordering: global data, priors and models. JCAP 03:011. doi: 10.1088/1475-7516/2018/03/011

CrossRef Full Text | Google Scholar

Gariazzo, S., Giunti, C., Laveder, M., and Li, Y. F. (2017). Updated global 3+1 analysis of short-baseLine neutrino oscillations. J. High Energy Phys. 06:135. doi: 10.1007/JHEP06(2017)135

CrossRef Full Text | Google Scholar

Gariazzo, S., Giunti, C., Laveder, M., and Li, Y. F. (2018b). Model-independent ${\bar{\nu }}_e$ short-baseline oscillations from reactor spectral ratios. Phys. Lett. B782, 13–21. doi: 10.1016/j.physletb.2018.04.057

CrossRef Full Text | Google Scholar

Gariazzo, S., Giunti, C., Laveder, M., Li, Y. F., and Zavanin, E. M. (2016). Light sterile neutrinos. J. Phys. G, 43:033001.

Google Scholar

Gastaldo, L. (2018) “Determining the electron neutrino mass with Ho-163,” in XXVIII International Conference on Neutrino Physics and Astrophysics (Heidelberg). Available online at: https://doi.org/10.5281/zenodo.1286950.,

Google Scholar

Gavela, M. B., Hernandez, D., Lopez Honorez, L., Mena, O., and Rigolin, S. (2009). Dark coupling. JCAP 07:034. doi: 10.1088/1475-7516/2009/07/034

CrossRef Full Text | Google Scholar

Ge, S.-F., Lindner, M., and Rodejohann, W. (2017). New physics and atmospheric neutrino trident production with PINGU and ORCA. Phys. Lett. B772, 164–168. doi: 10.1016/j.physletb.2017.06.020

CrossRef Full Text | Google Scholar

Gelmini, G. B. (2005). Prospect for relic neutrino searches. Phys. Scripta T121, 131–136. doi: 10.1088/0031-8949/2005/T121/019

CrossRef Full Text | Google Scholar

Gerbino, M., Freese, K., Vagnozzi, S., Lattanzi, M., Mena, O., Giusarma, E., and Ho, S. (2017a). Impact of neutrino properties on the estimation of inflationary parameters from current and future observations. Phys. Rev. D 95:043512. doi: 10.1103/PhysRevD.95.043512

CrossRef Full Text | Google Scholar

Gerbino, M., Lattanzi, M., Mena, O., and Freese, K. (2017b). A novel approach to quantifying the sensitivity of current and future cosmological datasets to the neutrino mass ordering through Bayesian hierarchical modeling. Phys. Lett. B775, 239–250. doi: 10.1016/j.physletb.2017.10.052

CrossRef Full Text | Google Scholar

Ghosh, A., Thakore, T., and Choubey, S. (2013). Determining the neutrino mass hierarchy with INO, T2K, NOvA and reactor Experiments. J. High Energy Phys. 04:009. doi: 10.1007/JHEP04(2013)009

CrossRef Full Text | Google Scholar

Giachero, A., Alpert, B., Becker, D., Bennett, D., Biasotti, M., Brofferio, C., et al. (2017). Measuring the electron neutrino mass with improved sensitivity: the HOLMES experiment. JINST 12:C02046. doi: 10.1088/1748-0221/12/02/C02046

CrossRef Full Text | Google Scholar

Girardi, I., Meloni, D., Ohlsson, T., Zhang, H., and Zhou, S. (2014). Constraining sterile neutrinos using reactor neutrino experiments. J. High Energy Phys. 08:057. doi: 10.1007/JHEP08(2014)057

CrossRef Full Text | Google Scholar

Giuliani, A. (2018) “The mid and long term future of neutrinoless double beta decay,” in XXVIII International Conference on Neutrino Physics and Astrophysics (Heidelberg) Avaialable online at : http://doi.org/10.5281/zenodo.1286915.,

Google Scholar

Giuliani, A., and Poves, A. (2012). Neutrinoless double-beta decay. Adv. High Energy Phys. 2012:857016.

Google Scholar

Giunti, C. (2017). “Light sterile neutrinos and neutrinoless double-beta decay,” in Proceedings, Matrix Elements for the Double beta decay Experiments (MEDEX'17) (Prague) Vol. 1894, 020009.

Google Scholar

Giunti, C., and Kim, C. W. (2007). Fundamentals of Neutrino Physics and Astrophysics. Oxford: Oxford University Press.

Google Scholar

Giunti, C., and Zavanin, E. M. (2015). Predictions for neutrinoless double-beta decay in the 3+1 sterile neutrino scenario. J. High Energy Phys. 07:171. doi: 10.1007/JHEP07(2015)171

CrossRef Full Text | Google Scholar

Giusarma, E., Corsi, M., Archidiacono, M., de Putter, R., Melchiorri, A., Mena, O., et al. (2011). Constraints on massive sterile neutrino species from current and future cosmological data. Phys. Rev. D 83:115023. doi: 10.1103/PhysRevD.83.115023

CrossRef Full Text | Google Scholar

Giusarma, E., de Putter, R., Ho, S., and Mena, O. (2013a). Constraints on neutrino masses from Planck and Galaxy Clustering data. Phys. Rev. D 88:063515. doi: 10.1103/PhysRevD.88.063515

CrossRef Full Text | Google Scholar

Giusarma, E., De Putter, R., and Mena, O. (2013b). Testing standard and nonstandard neutrino physics with cosmological data. Phys. Rev. D 87:043515. doi: 10.1103/PhysRevD.87.043515

CrossRef Full Text | Google Scholar

Giusarma, E., Di Valentino, E., Lattanzi, M., Melchiorri, A., and Mena, O. (2014). Relic neutrinos, thermal axions and cosmology in early 2014. Phys. Rev. D 90:043507. doi: 10.1103/PhysRevD.90.043507

CrossRef Full Text | Google Scholar

Giusarma, E., Gerbino, M., Mena, O., Vagnozzi, S., Ho, S., and Freese, K. (2016). Improvement of cosmological neutrino mass bounds. Phys. Rev. D 94:083522. doi: 10.1103/PhysRevD.94.083522

CrossRef Full Text | Google Scholar

Giusarma, E., Vagnozzi, S., Ho, S., Ferraro, S., Freese, K., Kamen-Rubio, R., et al. (2018). Scale-dependent galaxy bias, CMB lensing-galaxy cross-correlation, and neutrino masses. arXiv:1802.08694.

Google Scholar

Gomez-Cadenas, J. J., Martin-Albo, J., Mezzetto, M., Monrabal, F., and Sorel, M. (2012). The Search for neutrinoless double beta decay. Riv. Nuovo Cim. 35, 29–98. doi: 10.1393/ncr/i2012-10074-9

CrossRef Full Text | Google Scholar

Goobar, A., Hannestad, S., Mortsell, E., and Tu, H. (2006). A new bound on the neutrino mass from the sdss baryon acoustic peak. JCAP 06:019. doi: 10.1088/1475-7516/2006/06/019

CrossRef Full Text | Google Scholar

Gratton, S., Lewis, A., and Efstathiou, G. (2008). Prospects for constraining neutrino mass using planck and lyman-alpha forest data. Phys. Rev. D 77:083507. doi: 10.1103/PhysRevD.77.083507

CrossRef Full Text | Google Scholar

Greenhill, L., and Bernardi, G. (2012). HI epoch of reionization arrays. arXiv:1201.1700.

Google Scholar

Guo, R.-Y., Zhang, J.-F., and Zhang, X. (2018). Exploring neutrino mass and mass hierarchy in the scenario of vacuum energy interacting with cold dark matter. Chin. Phys. C 42:095103. doi: 10.1088/1674-1137/42/9/095103

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Lesgourgues, J., Rampf, C., and Wong, Y. Y. Y. (2010a). Cosmological parameters from large scale structure - geometric versus shape information. JCAP 07:022. doi: 10.1088/1475-7516/2010/07/022

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Melchiorri, A., and Wong, Y. Y. (2008). Nonlinear corrections to the cosmological matter power spectrum and scale-dependent galaxy bias: implications for parameter estimation. JCAP 07:017. doi: 10.1088/1475-7516/2008/07/017

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Raffelt, G., and Wong, Y. Y. (2007a). Observational bounds on the cosmic radiation density. JCAP 08:021. doi: 10.1088/1475-7516/2007/08/021

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Raffelt, G. G., Tamborra, I., and Wong, Y. Y. (2010b). Cosmology seeking friendship with sterile neutrinos. Phys. Rev. Lett. 105:181301. doi: 10.1103/PhysRevLett.105.181301

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Raffelt, G. G., and Wong, Y. Y. Y. (2011). Sterile neutrinos with eV masses in cosmology: how disfavoured exactly? JCAP 09:034. doi: 10.1088/1475-7516/2011/09/034

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., Sloth, M. S., and Wong, Y. Y. (2007b). How robust are inflation model and dark matter constraints from cosmological data? Phys. Rev. D 75:023522. doi: 10.1103/PhysRevD.75.023522

CrossRef Full Text | Google Scholar

Hamann, J., Hannestad, S., and Wong, Y. Y. Y. (2012). Measuring neutrino masses with a future galaxy survey. JCAP 11:052. doi: 10.1088/1475-7516/2012/11/052

CrossRef Full Text | Google Scholar

Handley, W., and Millea, M. (2018). Maximum entropy priors with derived parameters in a specified distribution. e-Print: arXiv:1804.08143.

Google Scholar

Handley, W. J., Hobson, M. P., and Lasenby, A. N. (2015a). PolyChord: nested sampling for cosmology. Mon. Not. R. Astron. Soc. 450, L61–L65. doi: 10.1093/mnrasl/slv047

CrossRef Full Text | Google Scholar

Handley, W. J., Hobson, M. P., and Lasenby, A. N. (2015b). PolyChord: next-generation nested sampling. Mon. Not. R. Astron.Soc. 453:4384. doi: 10.1093/mnras/stv1911

CrossRef Full Text | Google Scholar

Hannestad, S. (2003). Neutrino masses and the number of neutrino species from WMAP and 2dFGRS. JCAP 05:004. doi: 10.1088/1475-7516/2003/05/004

CrossRef Full Text | Google Scholar

Hannestad, S. (2005a). Neutrino masses and the dark energy equation of state - Relaxing the cosmological neutrino mass bound. Phys. Rev. Lett. 95:221301. doi: 10.1103/PhysRevLett.95.221301

PubMed Abstract | CrossRef Full Text | Google Scholar

Hannestad, S. (2005b). Structure formation with strongly interacting neutrinos - Implications for the cosmological neutrino mass bound. JCAP 02:011.

Google Scholar

Hannestad, S., Mirizzi, A., Raffelt, G. G., and Wong, Y. Y. (2008). Cosmological constraints on neutrino plus axion hot dark matter: Update after WMAP-5. JCAP 04:019. doi: 10.1088/1475-7516/2008/04/019

CrossRef Full Text | Google Scholar

Hannestad, S., Mirizzi, A., Raffelt, G. G., and Wong, Y. Y. Y. (2007). Cosmological constraints on neutrino plus axion hot dark matter. JCAP 08:015. doi: 10.1088/1475-7516/2007/08/015

CrossRef Full Text | Google Scholar

Hannestad, S., Mirizzi, A., Raffelt, G. G., and Wong, Y. Y. Y. (2010). Neutrino and axion hot dark matter bounds after WMAP-7. JCAP 08:001. doi: 10.1088/1475-7516/2010/08/001

CrossRef Full Text | Google Scholar

Hannestad, S., and Raffelt, G. (2004). Cosmological mass limits on neutrinos, axions, and other light particles. JCAP 04:008. doi: 10.1088/1475-7516/2004/04/008

CrossRef Full Text | Google Scholar

Hannestad, S., Raffelt, G. G., Sigl, G., and Wong, Y. Y. (2006a). Self-induced conversion in dense neutrino gases: pendulum in flavour space. Phys. Rev. D 74:105010. doi: 10.1103/PhysRevD.74.105010

CrossRef Full Text | Google Scholar

Hannestad, S., and Schwetz, T. (2016). Cosmology and the neutrino mass ordering. JCAP 11:035. doi: 10.1088/1475-7516/2016/11/035

CrossRef Full Text | Google Scholar

Hannestad, S., Tu, H., and Wong, Y. Y. (2006b). Measuring neutrino masses and dark energy with weak lensing tomography. JCAP 06:025. doi: 10.1088/1475-7516/2006/06/025

CrossRef Full Text | Google Scholar

Hartz, M. (2017). T2K NEUTRINO OSCILLATION RESULTS WITH DATA UP TO 2017 SUMMER. Available online at: http://www.t2k.org/docs/talk/282

Heavens, A. F., and Sellentin, E. (2018). Objective Bayesian analysis of neutrino masses and hierarchy. JCAP 04:047. doi: 10.1088/1475-7516/2018/04/047

CrossRef Full Text | Google Scholar

Heitmann, K., Lawrence, E., Kwan, J., Habib, S., and Higdon, D. (2014). The coyote universe extended: precision emulation of the matter power spectrum. Astrophys. J., 780:111. doi: 10.1088/0004-637X/780/1/111

CrossRef Full Text | Google Scholar

Hektor, A., Hütsi, G., Marzola, L., Raidal, M., Vaskonen, V., and Veermäe, H. (2018). Constraining primordial black holes with the EDGES 21-cm absorption signal. Phys. Rev. D 98:023503. doi: 10.1103/PhysRevD.98.023503

CrossRef Full Text | Google Scholar

Hildebrandt, H., Viola, M., Heymans, C., Joudaki, S., Kuijken, K., Blake, C., et al. (2017). KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing. Mon. Not. R. Astron. Soc. 465:1454. doi: 10.1093/mnras/stw2805

CrossRef Full Text | Google Scholar

Hill, J. C., and Baxter, E. J. (2018). Can early dark energy explain EDGES? JCAP 08:037. doi: 10.1088/1475-7516/2018/08/037

CrossRef Full Text | Google Scholar

Hilton, M., Hasselfield, M., Sifón, C., Battaglia, N., Aiola, S., Bharadwaj, V., et al. (2018). The atacama cosmology telescope: the two-season ACTPol Sunyaev-Zel'dovich effect selected cluster catalog. Astrophys. J. Suppl. 235:20. doi: 10.3847/1538-4365/aaa6cb

CrossRef Full Text | Google Scholar

Himmel, A. (2018). First Oscillation Results With Neutrino and Antineutrino Beams in NOvA. Available online at: http://nova-docdb.fnal.gov/cgi-bin/ShowDocument?docid=30273

Hirano, S., and Bromm, V. (2018). Baryon-dark matter scattering and first star formation. Mon. Not. R. Astron. Soc. 480:L85. doi: 10.1093/mnrasl/sly132

CrossRef Full Text | Google Scholar

Hirata, K., Kajita, T., Koshiba, M., Nakahata, M., Oyama, Y., Sato, N., et al. (1987). Observation of a Neutrino Burst from the Supernova SN 1987a. Phys. Rev. Lett. 58, 1490–1493. doi: 10.1103/PhysRevLett.58.1490

CrossRef Full Text | Google Scholar

Horiuchi, S., and Kneller, J. P. (2018). What can be learned from a future supernova neutrino detection? J. Phys. G 45:043002. doi: 10.1088/1361-6471/aaa90a

CrossRef Full Text | Google Scholar

Hosaka, J. (2006). Solar neutrino measurements in super-Kamiokande-I. Phys. Rev. D 73:112001. doi: 10.1103/PhysRevD.73.112001

CrossRef Full Text | Google Scholar

Hu, B., Raveri, M., Silvestri, A., and Frusciante, N. (2015). Exploring massive neutrinos in dark cosmologies with EFTCAMB/ EFTCosmoMC. Phys. Rev. D 91:063524. doi: 10.1103/PhysRevD.91.063524

CrossRef Full Text | Google Scholar

Hu, W., Eisenstein, D. J., and Tegmark, M. (1998). Weighing neutrinos with galaxy surveys. Phys. Rev. Lett. 80, 5255–5258. doi: 10.1103/PhysRevLett.80.5255

CrossRef Full Text | Google Scholar

Humphreys, E. M. L., Reid, M. J., Moran, J. M., Greenhill, L. J., and Argon, A. L. (2013). Toward a new geometric distance to the active galaxy NGC 4258. III. Final results and the hubble constant. Astrophys. J. 775:13. doi: 10.1088/0004-637X/775/1/13

CrossRef Full Text | Google Scholar

Huterer, D., and Linder, E. V. (2007). Separating dark physics from physical darkness: minimalist modified gravity vs. dark energy. Phys. Rev. D 75:023519. doi: 10.1103/PhysRevD.75.023519

CrossRef Full Text | Google Scholar

Ichiki, K., and Keum, Y.-Y. (2008). Neutrino masses from cosmological probes in interacting neutrino dark-energy models. J. High Energy Phys. 06:058. doi: 10.1088/1126-6708/2008/06/058

CrossRef Full Text | Google Scholar

Ichiki, K., Takada, M., and Takahashi, T. (2009). Constraints on Neutrino Masses from Weak Lensing. Phys. Rev. D 79:023520. doi: 10.1103/PhysRevD.79.023520

CrossRef Full Text | Google Scholar

Iliev, I. T., Shapiro, P. R., Ferrara, A., and Martel, H. (2002). On the direct detectability of the cosmic dark ages: 21-cm emission from minihalos. Astrophys. J. 572:123. doi: 10.1086/341869

CrossRef Full Text | Google Scholar

Inman, D., Emberson, J. D., Pen, U.-L., Farchi, A., Yu, H.-R., and Harnois-Déraps, J. (2015). Precision reconstruction of the cold dark matter-neutrino relative velocity from N-body simulations. Phys. Rev. D 92:023502. doi: 10.1103/PhysRevD.92.023502

CrossRef Full Text | Google Scholar

Ivezic, Z., Tyson, J., Allsman, R., Andrew, J., and Angel, R. (2008). LSST: from science drivers to reference design and anticipated data products. Astrophysics arXiv:0805.2366.

Google Scholar

Jackson, N. (2007). The hubble constant. Living Rev. Rel. 10:4. doi: 10.12942/lrr-2007-4

PubMed Abstract | CrossRef Full Text | Google Scholar

Jain, B., Spergel, D., Bean, R., Connolly, A., Dell'antonio, I., Frieman, J., et al. (2015). The whole is greater than the sum of the parts: optimizing the joint science return from LSST, Euclid and WFIRST. arXiv:1501.07897.

Google Scholar

Janka, H.-T. (2012). Explosion mechanisms of core-collapse supernovae. Ann. Rev. Nucl. Part. Sci. 62, 407–451. doi: 10.1146/annurev-nucl-102711-094901

CrossRef Full Text | Google Scholar

Jeffreys, H. (1961). Theory of Probability. The International series of monographs on physics. Clarendon Press.

Google Scholar

Jimenez, R., Kitching, T., Peña-Garay, C., and Verde, L. (2010). Can we measure the neutrino mass hierarchy in the sky? JCAP 05:035. doi: 10.1088/1475-7516/2010/05/035

CrossRef Full Text | Google Scholar

Joudaki, S. (2013). Constraints on neutrino mass and light degrees of freedom in extended cosmological parameter spaces. Phys. Rev. D 87:083523. doi: 10.1103/PhysRevD.87.083523

CrossRef Full Text | Google Scholar

Joudaki, S., Mead, A., Blake, C., Choi, A., de Jong, J., Erben, T., et al. (2017). KiDS-450: testing extensions to the standard cosmological model. Mon. Not. R. Astron. Soc. 471, 1259–1279. doi: 10.1093/mnras/stx998

CrossRef Full Text | Google Scholar

Jurkovich, H., Ferreira, C., and Pasquini, P. (2018). Shadowing neutrino mass hierarchy with lorentz invariance violation High Energy Phys. arXiv:1806.08752.

Google Scholar

Kaether, F., Hampel, W., Heusser, G., Kiko, J., and Kirsten, T. (2010). Reanalysis of the GALLEX solar neutrino flux and source experiments. Phys. Lett. B685, 47–54. doi: 10.1016/j.physletb.2010.01.030

CrossRef Full Text | Google Scholar

Kang, Z. (2018). Post-recombination dark matter for the 21-cm signal. arXiv:1803.04928.

Google Scholar

Kaplinghat, M., Knox, L., and Song, Y.-S. (2003). Determining neutrino mass from the CMB alone. Phys. Rev. Lett. 91:241301. doi: 10.1103/PhysRevLett.91.241301

CrossRef Full Text | Google Scholar

Kazin, E. A., Koda, J., Blake, C., Padmanabhan, N., Brough, S., Colless, M., et al. (2014). The wiggleZ dark energy survey: improved distance measurements to z = 1 with reconstruction of the baryonic acoustic feature. Mon. Not. R. Astron. Soc. 441, 3524–3542. doi: 10.1093/mnras/stu778

CrossRef Full Text | Google Scholar

Khan, A. N., McKay, D. W., and Tahir, F. (2013). Sensitivity of medium-baseline reactor neutrino mass-hierarchy experiments to nonstandard interactions. Phys. Rev. D 88:113006. doi: 10.1103/PhysRevD.88.113006

CrossRef Full Text | Google Scholar

Kharusi, S. A., Alamre, A., Albert, J. B., Alfaris, M., Anton, G., Arnquist, I. J., et al. (2018). nEXO Pre-Conceptual Design Report. arXiv:1805.11142.

Google Scholar

Kilbinger, M. (2015). Cosmology with cosmic shear observations: a review. Rept. Prog. Phys. 78:086901. doi: 10.1088/0034-4885/78/8/086901

PubMed Abstract | CrossRef Full Text | Google Scholar

Kim, S.-B. (2015). New results from RENO and prospects with RENO-50. Nucl. Part. Phys. Proc. 265–266, 93–98. doi: 10.1016/j.nuclphysbps.2015.06.024

CrossRef Full Text | Google Scholar

Kitching, T., Heavens, A., Verde, L., Serra, P., and Melchiorri, A. (2008). Finding evidence for massive neutrinos using 3D weak lensing. Phys. Rev. D 77:103008. doi: 10.1103/PhysRevD.77.103008

CrossRef Full Text | Google Scholar

Ko, Y. J., Kim, B. R., Kim, J. Y., Han, B. Y., Jang, C. H., Jeon, E. J., et al. (2017). Sterile neutrino search at the NEOS experiment. Phys. Rev. Lett. 118:121802. doi: 10.1103/PhysRevLett.118.121802

PubMed Abstract | CrossRef Full Text | Google Scholar

Köhlinger, F., Viola, M., Joachimi, B., Hoekstra, H., van Uitert, E., Hildebrandt, H., et al. (2017). KiDS-450: the tomographic weak lensing power spectrum and constraints on cosmological parameters. Mon. Not. R. Astron. Soc. 471:4412. doi: 10.1093/mnras/stx1820

CrossRef Full Text | Google Scholar

Krnjaic, G., Machado, P. A. N., and Necib, L. (2018). Distorted neutrino oscillations from ultralight scalar dark matter. Phys. Rev. D 97:075017. doi: 10.1103/PhysRevD.97.075017

CrossRef Full Text | Google Scholar

La Vacca, G., Bonometto, S., and Colombo, L. (2009). Higher neutrino mass allowed if DM and DE are coupled. New Astron. 14, 435–442. doi: 10.1016/j.newast.2008.12.004

CrossRef Full Text | Google Scholar

La Vacca, G., and Kristiansen, J. (2009). Dynamical dark energy model parameters with or without massive neutrinos. JCAP 07:036. doi: 10.1088/1475-7516/2009/07/036

CrossRef Full Text | Google Scholar

Lattanzi, M., and Gerbino, M. (2018). Status of neutrino properties and future prospects - Cosmological and astrophysical constraints. Front. Phys. 5:70. doi: 10.3389/fphy.2017.00070

CrossRef Full Text | Google Scholar

Lazauskas, R., Vogel, P., and Volpe, C. (2008). Charged current cross section for massive cosmological neutrinos impinging on radioactive nuclei. J. Phys. G 35:025001. doi: 10.1088/0954-3899/35/2/025001

CrossRef Full Text | Google Scholar

Lesgourgues, J. (2011a). The cosmic linear anisotropy solving system (CLASS) I: overview. arXiv:1104.2932 .

Google Scholar

Lesgourgues, J. (2011b). The cosmic linear anisotropy solving system (CLASS) III: comparision with CAMB for lambdaCDM. arXiv:1104.2934.

Google Scholar

Lesgourgues, J., Mangano, G., Miele, G., and Pastor, S. (2013). Neutrino Cosmology. Cambridge, UK: Cambridge University Press. doi: 10.1017/CBO9781139012874

CrossRef Full Text | Google Scholar

Lesgourgues, J., and Pastor, S. (2006). Massive neutrinos and cosmology. Phys. Rept. 429, 307–379. doi: 10.1016/j.physrep.2006.04.001

CrossRef Full Text | Google Scholar

Lesgourgues, J., and Pastor, S. (2012). Neutrino mass from Cosmology. Adv. High Energy Phys. 2012:608515. doi: 10.1155/2012/608515

CrossRef Full Text | Google Scholar

Lesgourgues, J., and Pastor, S. (2014). Neutrino cosmology and Planck. New J. Phys. 16:065002. doi: 10.1088/1367-2630/16/6/065002

CrossRef Full Text | Google Scholar

Lesgourgues, J., Pastor, S., and Perotto, L. (2004). Probing neutrino masses with future galaxy redshift surveys. Phys. Rev. D 70:045016. doi: 10.1103/PhysRevD.70.045016

CrossRef Full Text | Google Scholar

Lesgourgues, J., Perotto, L., Pastor, S., and Piat, M. (2006). Probing neutrino masses with cmb lensing extraction. Phys. Rev. D, 73:045021. doi: 10.1103/PhysRevD.73.045021

CrossRef Full Text | Google Scholar

Lesgourgues, J., and Tram, T. (2014). Fast and accurate CMB computations in non-flat FLRW universes. JCAP 09, 032. doi: 10.1088/1475-7516/2014/09/032

CrossRef Full Text | Google Scholar

Levi, M., Bebek, C., Beers, T., Blum, R., Cahn, R., Eisenstein, D., et al. (2013). The DESI experiment, a Whitepaper for snowmass 2013. arXiv:1308.0847.

Google Scholar

Lewis, A., and Bridle, S. (2002). Cosmological parameters from CMB and other data: a monte carlo approach. Phys. Rev. D 66:103511. doi: 10.1103/PhysRevD.66.103511

CrossRef Full Text | Google Scholar

Lewis, A., Challinor, A., and Lasenby, A. (2000). Efficient computation of CMB anisotropies in closed FRW models. Astrophys. J. 538, 473–476. doi: 10.1086/309179

CrossRef Full Text | Google Scholar

Li, Y.-F. (2015). Detection prospects of the cosmic neutrino background. Int. J. Mod. Phys. A30:1530031. doi: 10.1142/9789814704779_0025

CrossRef Full Text | Google Scholar

Li, Y.-F.m and Zhao, Z.-h. (2014). Tests of lorentz and CPT violation in the medium baseline reactor antineutrino experiment. Phys. Rev. D 90:113014. doi: 10.1103/PhysRevD.90.113014

CrossRef Full Text | Google Scholar

Liao, J., Marfatia, D., and Whisnant, K. (2017). Nonstandard interactions in solar neutrino oscillations with Hyper-Kamiokande and JUNO. Phys. Lett. B771, 247–253. doi: 10.1016/j.physletb.2017.05.054

CrossRef Full Text | Google Scholar

Linder, E. V. (2003). Exploring the expansion history of the universe. Phys. Rev. Lett. 90:091301. doi: 10.1103/PhysRevLett.90.091301

PubMed Abstract | CrossRef Full Text | Google Scholar

Liu, A., and Parsons, A. R. (2016). Constraining cosmology and ionization history with combined 21 cm power spectrum and global signal measurements. Mon. Not. R. Astron. Soc. 457, 1864–1877. doi: 10.1093/mnras/stw071

CrossRef Full Text | Google Scholar

Liu, A., Pritchard, J. R., Allison, R., Parsons, A. R., Seljak, U., and Sherwin, B. D. (2016). Eliminating the optical depth nuisance from the CMB with 21 cm cosmology. Phys. Rev. D 93:043013. doi: 10.1103/PhysRevD.93.043013

CrossRef Full Text | Google Scholar

Liu, H., and Slatyer, T. R. (2018). Too hot, too cold or just right? Implications of a 21-cm signal for dark matter annihilation and decay. Phys. Rev. D 98:023501. doi: 10.1103/PhysRevD.98.023501

CrossRef Full Text | Google Scholar

Liu, J., Bird, S., Matilla, J. M. Z., Hill, J. C., Haiman, Z., Madhavacheril, M. S., et al. (2018). MassiveNuS: cosmological massive neutrino simulations. JCAP 03:049. doi: 10.1088/1475-7516/2018/03/049

CrossRef Full Text | Google Scholar

Loeb, A., and Wyithe, S. (2008). Precise measurement of the cosmological power spectrum with a dedicated 21cm survey after reionization. Phys. Rev. Lett. 100:161301. doi: 10.1103/PhysRevLett.100.161301

PubMed Abstract | CrossRef Full Text | Google Scholar

Long, A. J., Lunardini, C., and Sabancilar, E. (2014). Detecting non-relativistic cosmic neutrinos by capture on tritium: phenomenology and physics potential. JCAP 08:038. doi: 10.1088/1475-7516/2014/08/038

CrossRef Full Text | Google Scholar

Long, A. J., Raveri, M., Hu, W., and Dodelson, S. (2018). Neutrino mass priors for cosmology from random matrices. Phys. Rev. D 97:043510. doi: 10.1103/PhysRevD.97.043510

CrossRef Full Text | Google Scholar

Lopez Honorez, L., and Mena, O. (2010). Instabilities in dark coupled models and constraints from cosmological data. AIP Conf. Proc. 1241, 1016–1024. doi: 10.1063/1.3462595

CrossRef Full Text | Google Scholar

Lorenz, C. S., Calabrese, E., and Alonso, D. (2017). Distinguishing between Neutrinos and time-varying Dark Energy through Cosmic Time. Phys. Rev. D 96:043510. doi: 10.1103/PhysRevD.96.043510

CrossRef Full Text | Google Scholar

LoVerde, M., and Zaldarriaga, M. (2014). Neutrino clustering around spherical dark matter halos. Phys. Rev. D 89:063502. doi: 10.1103/PhysRevD.89.063502

CrossRef Full Text | Google Scholar

Lunardini, C., and Smirnov, A. (2001a). Neutrinos from SN1987A, earth matter effects and the LMA solution of the solar neutrino problem. Phys. Rev. D 63:073009. doi: 10.1103/PhysRevD.63.073009

CrossRef Full Text | Google Scholar

Lunardini, C., and Smirnov, A. (2001b). Supernova neutrinos: earth matter effects and neutrino mass spectrum. Nucl. Phys. B616:307–348.

Google Scholar

Lunardini, C., and Smirnov, A. Y. (2003). Probing the neutrino mass hierarchy and the 13 mixing with supernovae. JCAP 06:009. doi: 10.1088/1475-7516/2003/06/009

CrossRef Full Text | Google Scholar

Lunardini, C., and Smirnov, A. Y. (2004). Neutrinos from SN1987A: flavor conversion and interpretation of results. Astropart. Phys. 21, 703–720. doi: 10.1016/j.astropartphys.2004.05.005

CrossRef Full Text | Google Scholar

Madau, P., Meiksin, A., and Rees, M. J. (1997). 21-CM tomography of the intergalactic medium at high redshift. Astrophys. J. 475:429. doi: 10.1086/303549

CrossRef Full Text | Google Scholar

Mahdawi, M. S., and Farrar, G. R. (2018). Constraints on dark matter with a moderately large and velocity-dependent DM-Nucleon cross-section. arXiv:1804.03073.

Google Scholar

Mangano, G., Miele, G., Pastor, S., Pinto, T., Pisanti, O., and Serpico, P. D. (2005). Relic neutrino decoupling including flavor oscillations. Nucl. Phys. B729, 221–234. doi: 10.1016/j.nuclphysb.2005.09.041

CrossRef Full Text | Google Scholar

Mao, Y., Tegmark, M., McQuinn, M., Zaldarriaga, M., and Zahn, O. (2008). How accurately can 21 cm tomography constrain cosmology? Phys. Rev. D 78:023529. doi: 10.1103/PhysRevD.78.023529

CrossRef Full Text | Google Scholar

Martín-Albo, J., Muñ~oz Vidal, J., Ferrario, P., Nebot-Guinot, M., Gómez-Cadenas, J. J., Álvarez, V., et al. (2016). Sensitivity of NEXT-100 to neutrinoless double beta decay. J. High Energy Phys. 05:159. doi: 10.1007/JHEP05(2016)159

CrossRef Full Text | Google Scholar

Masud, M., and Mehta, P. (2016). Nonstandard interactions and resolving the ordering of neutrino masses at DUNE and other long baseline experiments. Phys. Rev. D 94:053007. doi: 10.1103/PhysRevD.94.053007

CrossRef Full Text | Google Scholar

McGaugh, S. (2018). Strong hydrogen absorption at cosmic Dawn: the signature of a baryonic universe. Res. Notes AAS 2:37. doi: 10.3847/2515-5172/aab497

CrossRef Full Text | Google Scholar

McQuinn, M., Zahn, O., Zaldarriaga, M., Hernquist, L., and Furlanetto, S. R. (2006). Cosmological parameter estimation using 21 cm radiation from the epoch of reionization. Astrophys. J. 653, 815–830. doi: 10.1086/505167

CrossRef Full Text | Google Scholar

Melchiorri, A., Mena, O., and Slosar, A. (2007). An improved cosmological bound on the thermal axion mass. Phys. Rev. D 76:041303. doi: 10.1103/PhysRevD.76.041303

CrossRef Full Text | Google Scholar

Mellema, G., Koopmans, L., Abdalla, F., Bernardi, G., Ciardi, B., Daiboo, S., et al. (2013). Reionization and the cosmic dawn with the square kilometre array. Exper. Astron. 36, 235–318. doi: 10.1007/s10686-013-9334-5

CrossRef Full Text | Google Scholar

Mena, O., Mocioiu, I., and Quigg, C. (2007). Gravitational lensing of supernova neutrinos. Astropart. Phys. 28, 348–356. doi: 10.1016/j.astropartphys.2007.07.002

CrossRef Full Text | Google Scholar

Mena, O., and Parke, S. J. (2004). Unified graphical summary of neutrino mixing parameters. Phys. Rev. D 69:117301.

Google Scholar

Mikheev, S. P., and Smirnov, A. Yu. (1985). Resonance amplification of oscillations in matter and spectroscopy of solar neutrinos. Sov. J. Nucl. Phys. 42:913–917. doi: 10.1103/PhysRevD.69.117301

CrossRef Full Text | Google Scholar

Mikheev, S. P., and Smirnov, A. Yu. (1986). Resonant amplification of neutrino oscillations in matter and solar neutrino spectroscopy. Nuovo Cim. C9, 17–26. doi: 10.1007/BF02508049

CrossRef Full Text | Google Scholar

Miranda, O., Tortola, M., and Valle, J. (2006). Are solar neutrino oscillations robust? J. Health Energy Phys. 10:008. doi: 10.1088/1126-6708/2006/10/008

CrossRef Full Text | Google Scholar

Mirizzi, A., Tamborra, I., Janka, H.-T., Saviano, N., Scholberg, K., Bollig, R., et al. (2016). Supernova neutrinos: production, oscillations and detection. Riv. Nuovo Cim. 39, 1–112. doi: 10.1393/ncr/i2016-10120-8

CrossRef Full Text | Google Scholar

Mitridate, A., and Podo, A. (2018). Bounds on dark matter decay from 21 cm line. JCAP 05:069. doi: 10.1088/1475-7516/2018/05/069

CrossRef Full Text | Google Scholar

Mosher, J. (2014). Cosmological parameter uncertainties from SALT-II type Ia supernova light curve models. Astrophys. J. 793:16. doi: 10.1088/0004-637X/793/1/16

CrossRef Full Text | Google Scholar

Mota, D., Pettorino, V., Robbers, G., and Wetterich, C. (2008). Neutrino clustering in growing neutrino quintessence. Phys. Lett. B663:160–164. doi: 10.1016/j.physletb.2008.03.060

CrossRef Full Text | Google Scholar

Muñ~oz, J. B., and Dvorkin, C. (2018). Efficient computation of galaxy bias with neutrinos and other relics. Phys. Rev. D 98:043503. doi: 10.1103/PhysRevD.98.043503

CrossRef Full Text | Google Scholar

Muñoz, J. B., Dvorkin, C., and Loeb, A. (2018). 21-cm fluctuations from charged dark matter. arXiv:1804.01092.

Google Scholar

Muñoz, J. B., and Loeb, A. (2018). A small amount of mini-charged dark matter could cool the baryons in the early Universe. Nature 557:684. doi: 10.1038/s41586-018-0151-x

PubMed Abstract | CrossRef Full Text | Google Scholar

Munshi, D., Valageas, P., Van Waerbeke, L., and Heavens, A. (2008). Cosmology with weak lensing surveys. Phys. Rept. 462, 67–121. doi: 10.1016/j.physrep.2008.02.003

CrossRef Full Text | Google Scholar

Murase, K. (2018). New prospects for detecting high-energy neutrinos from nearby Supernovae. Phys. Rev. D 97:081301. doi: 10.1103/PhysRevD.97.081301

CrossRef Full Text | Google Scholar

Nakano, Y. (2016). Ph.D. Thesis, University of Tokyo. Available online at: http://www-sk.icrr.u-tokyo.ac.jp/sk/_pdf/articles/2016/doc_thesis_naknao.pdf

Newburgh, L. B., Addison, G. E., Amiri, M., Bandura, K., Bond, J. R., Connor, L., et al. (2014). Calibrating CHIME, a new radio interferometer to probe dark energy. Proc. SPIE Int. Soc. Opt. Eng. 9145:4V. doi: 10.1117/12.2056962

CrossRef Full Text | Google Scholar

Ohlsson, T., Zhang, H., and Zhou, S. (2014). Nonstandard interaction effects on neutrino parameters at medium-baseline reactor antineutrino experiments. Phys. Lett. B728, 148–155. doi: 10.1016/j.physletb.2013.11.052

CrossRef Full Text | Google Scholar

Orebi Gann, G. (2018) “SNO+,” in XXVIII International Conference on Neutrino Physics and Astrophysics (Heidelberg) Available online at: http://doi.org/10.5281/zenodo.1286908.,

Google Scholar

Orebi Gann, G. D. (2015). Physics potential of an advanced scintillation detector: introducing THEIA arXiv:1504.08284.

Google Scholar

Ott, C., O'Connor, E., Gossan, S., Abdikamalov, E., Gamma, U., and Drasco, S. (2013). Core-collapse supernovae, neutrinos, and gravitational waves. Nuclear Phys. B 235-236, 381–387. doi: 10.1016/j.nuclphysbps.2013.04.036

CrossRef Full Text | Google Scholar

Ouellet, J. (2018) “Latest results from the CUORE experiment,” in XXVIII International Conference on Neutrino Physics and Astrophysics, 4–9 June 2018, (Heidelberg) Available online at: URL: http://doi.org/10.5281/zenodo.1286904.,

Oyama, Y., Kohri, K., and Hazumi, M. (2016). Constraints on the neutrino parameters by future cosmological 21 cm line and precise CMB polarization observations. JCAP 02:008. doi: 10.1088/1475-7516/2016/02/008

CrossRef Full Text | Google Scholar

Oyama, Y., Shimizu, A., and Kohri, K. (2013). Determination of neutrino mass hierarchy by 21 cm line and CMB B-mode polarization observations. Phys. Lett. B718, 1186–1193. doi: 10.1016/j.physletb.2012.12.053

CrossRef Full Text | Google Scholar

Pac, M. Y. (2018). Recent results from RENO. PoS NuFact2017:038. doi: 10.22323/1.295.003

CrossRef Full Text | Google Scholar

Paciga, G., Chang, T.-C., Gupta, Y., Nityanada, R., Odegova, J., Pen, U.-L., et al. (2011). The GMRT epoch of reionization experiment: a new upper limit on the neutral hydrogen power spectrum at z 8.6. Mon. Not. R. Astron. Soc. 413, 1174–1183. doi: 10.1111/j.1365-2966.2011.18208.x

CrossRef Full Text | Google Scholar

Palanque-Delabrouille, N., Yeche, C., Baur, J., Magneville, C., Rossi, G., Lesgourgues, J., et al. (2015). Neutrino masses and cosmology with Lyman-alpha forest power spectrum. JCAP 11:011. doi: 10.1088/1475-7516/2015/11/011

CrossRef Full Text | Google Scholar

Palanque-Delabrouille, N., Yèche, C., Borde, A., Le Goff, J.-M., Rossi, G., Viel, M., et al. (2013). The one-dimensional Ly-alpha forest power spectrum from BOSS. Astron. Astrophys. 559:A85. doi: 10.1051/0004-6361/201322130

CrossRef Full Text | Google Scholar

Parno, D. (2018) “KATRIN: toward a high-precision neutrino-mass determination with tritium,” in XXVIII International Conference on Neutrino Physics and Astrophysics, 4–9 June 2018, (Heidelberg). Available online at: http://doi.org/10.5281/zenodo.1287933.,

Parsons, A. R., Backer, D. C., Bradley, R. F., Aguirre, J. E., Benoit, E. E., Carilli, C. L., et al. (2010). The precision array for probing the epoch of reionization: 8 station results. Astron. J. 139:1468. doi: 10.1088/0004-6256/139/4/1468

CrossRef Full Text | Google Scholar

Pascoli, S., and Petcov, S. (2002). The SNO solar neutrino data, neutrinoless double beta decay and neutrino mass spectrum. Phys. Lett. B544, 239–250. doi: 10.1016/S0370-2693(02)02510-8

CrossRef Full Text | Google Scholar

Pasquini, P., Chulia, S. C., and Valle, J. W. F. (2017). Neutrino oscillations from warped flavor symmetry: predictions for long baseline experiments T2K, NOvA and DUNE. Phys. Rev. D 95:095030. doi: 10.1103/PhysRevD.95.095030

CrossRef Full Text | Google Scholar

Patrick, C., and Xie, F. (2017). Status of the superNEMO 0νββ Experiment. arXiv:1704.06670.

Google Scholar

Peccei, R. D., and Quinn, H. R. (1977a). Constraints imposed by CP conservation in the presence of instantons. Phys. Rev. D 16, 1791–1797.

Google Scholar

Peccei, R. D., and Quinn, H. R. (1977b). CP Conservation in the Presence of Instantons. Phys. Rev. Lett. 38, 1440–1443.

Google Scholar

Peebles, P., and Ratra, B. (1988). Cosmology with a Time Variable Cosmological Constant. Astrophys. J. 325:L17. doi: 10.1086/185100

CrossRef Full Text | Google Scholar

Peirone, S., Frusciante, N., Hu, B., Raveri, M., and Silvestri, A. (2018). Do current cosmological observations rule out all Covariant Galileons? Phys. Rev. D 97:063518. doi: 10.1103/PhysRevD.97.063518

CrossRef Full Text | Google Scholar

Percival, W. J., Baugh, C. M., Bland-Hawthorn, J., Bridges, T., Cannon, R., Cole, S., et al. (2001). The 2dF galaxy redshift survey: the power spectrum and the matter content of the Universe. Mon. Not. R. Astron. Soc. 327:1297. doi: 10.1046/j.1365-8711.2001.04827.x

CrossRef Full Text | Google Scholar

Petcov, S., and Piai, M. (2002). The LMA MSW solution of the solar neutrino problem, inverted neutrino mass hierarchy and reactor neutrino experiments. Phys. Lett. B533, 94–106. doi: 10.1016/S0370-2693(02)01591-5

CrossRef Full Text | Google Scholar

Pober, J. C., Ali, Z. S., Parsons, A. R., McQuinn, M., Aguirre, J. E., Bernardi, G., et al. (2015). PAPER-64 constraints on reionization II: the temperature of the z = 8.4 intergalactic medium. Astrophys. J. 809:62. doi: 10.1088/0004-637X/809/1/62

CrossRef Full Text | Google Scholar

Pospelov, M., Pradler, J., Ruderman, J. T., and Urbano, A. (2018). Room for new physics in the rayleigh-jeans tail of the cosmic microwave background. Phys. Rev. Lett. 121:031103. doi: 10.1103/PhysRevLett.121.031103

PubMed Abstract | CrossRef Full Text | Google Scholar

Pritchard, J. R., and Loeb, A. (2012). 21-cm cosmology. Rept. Prog. Phys. 75:086901. doi: 10.1088/0034-4885/75/8/086901

PubMed Abstract | CrossRef Full Text | Google Scholar

Pritchard, J. R., and Pierpaoli, E. (2008). Constraining massive neutrinos using cosmological 21 cm observations. Phys. Rev. D 78:065009. doi: 10.1103/PhysRevD.78.065009

CrossRef Full Text | Google Scholar

Qian, X., Tan, A., Wang, W., Ling, J., McKeown, R., and Zhang, C. (2012). Statistical evaluation of experimental determinations of neutrino mass hierarchy. Phys. Rev. D 86:113011. doi: 10.1103/PhysRevD.86.113011

CrossRef Full Text | Google Scholar

Qian, X., and Vogel, P. (2015). Neutrino mass hierarchy. Prog. Part. Nucl. Phys. 83, 1–30. doi: 10.1016/j.ppnp.2015.05.002

CrossRef Full Text | Google Scholar

Radovic, A. (2018). JETP January 2018, NOvA Oscillation Results. Available online at: http://nova-docdb.fnal.gov/cgi-bin/ShowDocument?docid=25938

Raffelt, G. (1999). Stars as particle-physics laboratories. AIP Conf. Proc. 490, 125–162.

Google Scholar

Raffelt, G., and Sigl, G. (2007). Self-induced decoherence in dense neutrino gases. Phys. Rev. D 75:083002. doi: 10.1103/PhysRevD.75.083002

CrossRef Full Text | Google Scholar

Raffelt, G. G., and Smirnov, A. Y. (2007a). Adiabaticity and spectral splits in collective neutrino transformations. Phys. Rev. D 76:125008. doi: 10.1103/PhysRevD.76.125008

CrossRef Full Text | Google Scholar

Raffelt, G. G., and Smirnov, A. Y. (2007b). Self-induced spectral splits in supernova neutrino fluxes. Phys. Rev. D 76:081301. doi: 10.1103/PhysRevD.76.081301

CrossRef Full Text | Google Scholar

Ratra, B., and Peebles, P. (1988). Cosmological consequences of a rolling homogeneous scalar field. Phys. Rev. D 37:3406.

PubMed Abstract | Google Scholar

Reid, B. A., Verde, L., Jimenez, R., and Mena, O. (2010). Robust neutrino constraints by combining low redshift observations with the CMB. JCAP 01:003. doi: 10.1088/1475-7516/2010/01/003

CrossRef Full Text | Google Scholar

Renk, J., Zumalacárregui, M., Montanari, F., and Barreira, A. (2017). Galileon gravity in light of ISW, CMB, BAO and H₀ data. JCAP 10:020. doi: 10.1088/1475-7516/2017/10/020

CrossRef Full Text | Google Scholar

Ribordy, M., and Smirnov, A. Y. (2013). Improving the neutrino mass hierarchy identification with inelasticity measurement in PINGU and ORCA. Phys. Rev. D 87:113007. doi: 10.1103/PhysRevD.87.113007

CrossRef Full Text | Google Scholar

Riemer-Sorensen, S. (2012). The wiggleZ dark energy survey: cosmological neutrino mass constraint from blue high-redshift galaxies. Phys. Rev. D 85:081101. doi: 10.1103/PhysRevD.85.081101

CrossRef Full Text | Google Scholar

Riemer-Sorensen, S., Parkinson, D., and Davis, T. M. (2014). Combining Planck data with large scale structure information gives a strong neutrino mass constraint. Phys. Rev. D 89:103505. doi: 10.1103/PhysRevD.89.103505

CrossRef Full Text | Google Scholar

Riemer-Sorensen, S., Parkinson, D., Davis, T. M., and Blake, C. (2013). Simultaneous constraints on the number and mass of relativistic species. Astrophys. J. 763:89. doi: 10.1088/0004-637X/763/2/89

CrossRef Full Text | Google Scholar

Riess, A. G., Macri, L., Casertano, S., Lampeitl, H., Ferguson, H. C., Filippenko, A. V., et al. (2011). A 3% solution: determination of the hubble constant with the hubble space telescope and wide field camera 3. Astrophys. J. 730:119. doi: 10.1088/0004-637X/730/2/119

CrossRef Full Text | Google Scholar

Riess, A. G., Macri, L. M., Hoffmann, S. L., Scolnic, D., Casertano, S., Filippenko, A. V., et al. (2016). A 2.4% determination of the local value of the hubble constant. Astrophys. J. 826:56. doi: 10.3847/0004-637X/826/1/56

CrossRef Full Text | Google Scholar

Ringwald, A. (2005). How to detect big bang relic neutrinos? High Energy Phys. 473–491.

Google Scholar

Ringwald, A., and Wong, Y. Y. Y. (2004). Gravitational clustering of relic neutrinos and implications for their detection. JCAP 12:005. doi: 10.1088/1475-7516/2004/12/005

CrossRef Full Text | Google Scholar

Robertson, D. S., and Albuquerque, I. F. M. (2018). Probing velocity dependent self-interacting dark matter with neutrino telescopes. JCAP 02:056. doi: 10.1088/1475-7516/2018/02/056

CrossRef Full Text | Google Scholar

Rodejohann, W. (2011). Neutrino-less double beta decay and particle physics. Int. J. Mod. Phys. E20, 1833–1930. doi: 10.1142/S0218301311020186

CrossRef Full Text | Google Scholar

Ross, A. J., Beutler, F., Chuang, C.-H., Pellejero-Ibanez, M., Seo, H.-J., Vargas-Magana, M., et al. (2017). The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: observational systematics and baryon acoustic oscillations in the correlation function. Mon. Not. R. Astron. Soc. 464, 1168–1191. doi: 10.1093/mnras/stw2372

CrossRef Full Text | Google Scholar

Ross, A. J., Samushia, L., Howlett, C., Percival, W. J., Burden, A., and Manera, M. (2015). The clustering of the SDSS DR7 main Galaxy sample - I. A 4 per cent distance measure at z = 0.15. Mon. Not. R. Astron. Soc. 449, 835–847. doi: 10.1093/mnras/stv154

CrossRef Full Text | Google Scholar

Rozo, E., and Rykoff, E. S. (2014). redMaPPer II: X-ray and SZ performance benchmarks for the SDSS catalog. Astrophys. J., 783:80. doi: 10.1088/0004-637X/783/2/80

CrossRef Full Text | Google Scholar

Rozo, E., Rykoff, E. S., Bartlett, J. G., and Melin, J. B. (2015). redMaPPer – III. A detailed comparison of the Planck 2013 and SDSS DR8 redMaPPer cluster catalogues. Mon. Not. R. Astron. Soc. 450, 592–605. doi: 10.1093/mnras/stv605

CrossRef Full Text | Google Scholar

Rybka, G. (2018). “Project 8: progress towards using cyclotron radiation emission spectroscopy on atomic tritium for a neutrino mass measurement, ” in XXVIII International Conference on Neutrino Physics and Astrophysics, 4–9 June 2018 (Heidelberg). Avilable online at: http://doi.org/10.5281/zenodo.1286954

Google Scholar

Rykoff, E., Rozo, E., Busha, M. T., Cunha, C. E., Finoguenov, A., Evrard, A., et al. (2014). redMaPPer I: algorithm and SDSS DR8 catalog. Astrophys. J. 785, 104. doi: 10.1088/0004-637X/785/2/104

CrossRef Full Text | Google Scholar

Safarzadeh, M., Scannapieco, E., and Babul, A. (2018). A limit on the warm dark matter particle mass from the redshifted 21 cm absorption line. Astrophys. J. 859:L18. doi: 10.3847/2041-8213/aac5e0

CrossRef Full Text | Google Scholar

Saito, S., Takada, M., and Taruya, A. (2008). Impact of massive neutrinos on nonlinear matter power spectrum. Phys. Rev. Lett. 100:191301. doi: 10.1103/PhysRevLett.100.191301

PubMed Abstract | CrossRef Full Text | Google Scholar

Sanchez, A. G. (2017). The clustering of galaxies in the completed SDSS-III Baryon oscillation spectroscopic survey: cosmological implications of the configuration-space clustering wedges. Mon. Not. R. Astron. Soc. 464, 1640–1658. doi: 10.1093/mnras/stw2443

CrossRef Full Text | Google Scholar

Santos, M. G., and Cooray, A. (2006). Cosmological and astrophysical parameter measurements with 21-cm anisotropies during the era of reionization. Phys. Rev. D 74:083517. doi: 10.1103/PhysRevD.74.083517

CrossRef Full Text | Google Scholar

Satpathy, S., Alam, S., Ho, S., White, M., Bahcall, N. A., Beutler, F., et al. (2016). BOSS DR12 combined galaxy sample: The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: On the measurement of growth rate using galaxy correlation functions. Mon. Not. R. Astron. Soc. doi: 10.1093/mnras/stx883

CrossRef Full Text | Google Scholar

Schechter, J., and Valle, J. W. F. (1982). Neutrinoless Double beta Decay in SU(2) x U(1) Theories. Phys. Rev. D 25:2951. doi: 10.1103/PhysRevD.25.2951

CrossRef Full Text | Google Scholar

Scholberg, K. (2012). Supernova neutrino detection. Ann. Rev. Nucl. Part. Sci. 62, 81–103. doi: 10.1146/annurev-nucl-102711-095006

CrossRef Full Text | Google Scholar

Scholberg, K. (2018). Supernova signatures of neutrino mass ordering. J. Phys. G 45:014002. doi: 10.1088/1361-6471/aa97be

CrossRef Full Text | Google Scholar

Schramm, D., and Truran, J. (1990). New physics from supernova SN1987A. Phys. Rept. 189, 89–126. doi: 10.1016/0370-1573(90)90020-3

CrossRef Full Text | Google Scholar

Schwetz, T., Freese, K., Gerbino, M., Giusarma, E., Hannestad, S., Lattanzi, M., et al. (2017). Comment on “strong evidence for the normal neutrino hierarchy”. arXiv:1703.04585.

Google Scholar

Scott, D., and Rees, M. J. (1990). The 21-cm line at high redshift: a diagnostic for the origin of large scale structure. Mon. Not. R. Astron. Soc. 247:510.

Google Scholar

Sejersen Riis, A., Hannestad, S., and Weinheimer, C. (2011). Analysis of simulated data for the KArlsruhe TRItium Neutrino experiment using Bayesian inference. Phys. Rev. C 84:045503. doi: 10.1103/PhysRevC.84.045503

CrossRef Full Text | Google Scholar

Seljak, U., Makarov, A., McDonald, P., Anderson, S., Bahcall, N., Brinkmann, J., et al. (2005). Cosmological parameter analysis including SDSS Ly-alpha forest and galaxy bias: Constraints on the primordial spectrum of fluctuations, neutrino mass, and dark energy. Phys. Rev. D 71:103515. doi: 10.1103/PhysRevD.71.103515

CrossRef Full Text | Google Scholar

Seljak, U., Slosar, A., and McDonald, P. (2006). Cosmological parameters from combining the Lyman-alpha forest with CMB, galaxy clustering and SN constraints. JCAP 10:014. doi: 10.1088/1475-7516/2006/10/014

CrossRef Full Text | Google Scholar

Senatore, L., and Zaldarriaga, M. (2017). The effective field theory of large-Scale structure in the presence of massive neutrinos. arXiv:1707.04698.

Google Scholar

Shim, J., Lee, J., and Baldi, M. (2014). Breaking the cosmic degeneracy between modified gravity and massive neutrinos with the cosmic web. arXiv:1404.3639.

Google Scholar

Shimabukuro, H., Ichiki, K., Inoue, S., and Yokoyama, S. (2014). Probing small-scale cosmological fluctuations with the 21 cm forest: Effects of neutrino mass, running spectral index, and warm dark matter. Phys. Rev. D 90:083003. doi: 10.1103/PhysRevD.90.083003

CrossRef Full Text | Google Scholar

Shirai, J. (2017). Results and future plans for the KamLAND-Zen experiment. J. Phys. 888, 012031. doi: 10.1088/1742-6596/888/1/012031

CrossRef Full Text | Google Scholar

Shoji, M., and Komatsu, E. (2010). Massive neutrinos in cosmology: analytic solutions and fluid approximation. Phys. Rev. D 81:123516. doi: 10.1103/PhysRevD.81.123516

CrossRef Full Text | Google Scholar

Simpson, F., Jimenez, R., Peña-Garay, C., and Verde, L. (2017). Strong evidence for the normal neutrino hierarchy. JCAP 06:029. doi: 10.1088/1475-7516/2017/06/029

CrossRef Full Text | Google Scholar

Singh, S., and Ma, C.-P. (2003). Neutrino clustering in cold dark matter halos : implications for ultrahigh-energy cosmic rays. Phys. Rev. D 67:023506. doi: 10.1103/PhysRevD.67.023506

CrossRef Full Text | Google Scholar

Slatyer, T. R., and Wu, C.-L. (2018). Early-universe constraints on dark matter-baryon scattering and their implications for a global 21cm signal. Phys. Rev. D 98:023013. doi: 10.1103/PhysRevD.98.023013

CrossRef Full Text | Google Scholar

Slosar, A., Irˇšiˇc,, V., Kirkby, D., Bailey, S., Busca, N. G., Delubac, T., et al. (2013). Measurement of baryon acoustic oscillations in the lyman-alpha forest fluctuations in boss data release 9. JCAP 04:026. doi: 10.1088/1475-7516/2013/04/026

CrossRef Full Text | Google Scholar

Smith, K. M., Hu, W., and Kaplinghat, M. (2006). Cosmological Information from Lensed CMB Power Spectra. Phys. Rev. D 74:123002. doi: 10.1103/PhysRevD.74.123002

CrossRef Full Text | Google Scholar

Smith, R. E., Peacock, J. A., Jenkins, A., White, S. D. M., Frenk, C. S., Pearce, F. R., et al. (2003). Stable clustering, the halo model and nonlinear cosmological power spectra. Mon. Not. R. Astron. Soc. 341:1311. doi: 10.1046/j.1365-8711.2003.06503.x

CrossRef Full Text | Google Scholar

Sohn, J., Chon, G., Böhringer, H., Geller, M. J., Diaferio, A., Hwang, H. S., et al. (2018). The hectoMAP cluster survey - II. X-ray clusters. Astrophys. J. 855:100. doi: 10.3847/1538-4357/aaac7a

CrossRef Full Text | Google Scholar

Song, Y.-S., and Knox, L. (2004). Determination of cosmological parameters from cosmic shear data. Phys. Rev.D 70:063510. doi: 10.1103/PhysRevD.70.063510

CrossRef Full Text | Google Scholar

Spergel, D., Gehrels, N., Baltay, C., Bennett, D., Breckinridge, J., Donahue, M., et al. (2015). Wide-Field infrarRed Survey telescope-astrophysics focused telescope assets WFIRST-AFTA 2015 Report. arXiv:1503.03757.

Google Scholar

Spergel, D., Gehrels, N., Breckinridge, J., Donahue, M., Dressler, A., Gaudi, B. S., et al. (2013). Wide-field infraRed survey telescope-astrophysics focused telescope assets WFIRST-AFTA Final Report. arXiv:1305.5422.

Google Scholar

Spergel, D., Verde, L., Peiris, H. V., Komatsu, E., Nolta, M. R., Bennett, C. L., et al. (2003). First year wilkinson microwave anisotropy probe (WMAP) observations: determination of cosmological parameters. Astrophys. J. Suppl. 148, 175–194. doi: 10.1086/377226

CrossRef Full Text | Google Scholar

Sprenger, T., Archidiacono, M., Brinckmann, T., Clesse, S., and Lesgourgues, J. (2018). Cosmology in the era of Euclid and the Square Kilometre Array. arXiv:1801.08331.

Google Scholar

Springer, P., Bennett, C., and Baisden, P. (1987). Measurement of the neutrino mass using the Inner Bremsstrahlung Emitted in the Electron-Capture Decay og 163Ho. Phys. Rev. A 35, 679–689. doi: 10.1103/PhysRevA.35.679

CrossRef Full Text | Google Scholar

Srivastava, R., Ternes, C. A., Tórtola, M., and Valle, J. W. F. (2018a). Testing a lepton quarticity flavor theory of neutrino oscillations with the DUNE experiment. Phys. Lett. B778, 459–463. doi: 10.1016/j.physletb.2018.01.014

CrossRef Full Text | Google Scholar

Srivastava, R., Ternes, C. A., Tórtola, M., and Valle, J. W. F. (2018b). Zooming in on neutrino oscillations with DUNE. Phys. Rev. D 97:095025. doi: 10.1103/PhysRevD.97.095025

CrossRef Full Text | Google Scholar

Stanco, L., Salamanna, G., Sawy, F., and Sirignano, C. (2017). A new way to determine the neutrino mass hierarchy at reactors. arXiv:1707.07651.

Google Scholar

Strait, J. (2016). Long-baseline neutrino facility (LBNF) and deep underground neutrino experiment (DUNE). arXiv: 1601.05823.

Google Scholar

Sutherland, W. (2018). The CMB neutrino mass/vacuum energy degeneracy: a simple derivation of the degeneracy slopes. Mon. Not. R. Astron. Soc. 477, 1913–1920. doi: 10.1093/mnras/sty687

CrossRef Full Text | Google Scholar

Suzuki, A. (2016). The POLARBEAR-2 and the Simons Array Experiment. J. Low. Temp. Phys. 184, 805–810. doi: 10.1007/s10909-015-1425-4

CrossRef Full Text | Google Scholar

Takahashi, R., Sato, M., Nishimichi, T., Taruya, A., and Oguri, M. (2012). Revising the halofit model for the nonlinear matter power spectrum. Astrophys. J. 761:152. doi: 10.1088/0004-637X/761/2/152

CrossRef Full Text | Google Scholar

Tegmark, M., Eisenstein, D., Strauss, M., Weinberg, D., Blanton, M., Frieman, J., et al. (2006). Cosmological constraints from the SDSS luminous red galaxies. Phys. Rev. D 74:123507. doi: 10.1103/PhysRevD.74.123507

CrossRef Full Text | Google Scholar

Tegmark, M., Strauss, M., Blanton, M., Abazajian, K., Dodelson, S., Sandvik, H., et al. (2004). Cosmological parameters from SDSS and WMAP. Phys. Rev. D 69:103501. doi: 10.1103/PhysRevD.69.103501

CrossRef Full Text | Google Scholar

Tegmark, M., and Zaldarriaga, M. (2009). The fast fourier transform telescope. Phys. Rev. D 79:083530. doi: 10.1103/PhysRevD.79.083530

CrossRef Full Text | Google Scholar

Tereno, I., Schimd, C., Uzan, J.-P., Kilbinger, M., Vincent, F. H., and Fu, L. (2009). CFHTLS weak-lensing constraints on the neutrino masses. Astron. Astrophys. 500, 657–665. doi: 10.1051/0004-6361/200811077

CrossRef Full Text | Google Scholar

Thakore, T., Devi, M. M., Kumar Agarwalla, S., and Dighe, A. (2018). Active-sterile neutrino oscillations at INO-ICAL over a wide mass-squared range. J. High Energy Phys. 08:022. doi: 10.1007/JHEP08(2018)022

CrossRef Full Text | Google Scholar

Tingay, S., Goeke, R., Bowman, J. D., Emrich, D., Ord, S. M., Mitchell, D. A., et al. (2013). The murchison widefield array: the square kilometre array precursor at low radio frequencies. Publ. Astron. Soc. Austral. 30:7. doi: 10.1017/pasa.2012.007

CrossRef Full Text | Google Scholar

Tinker, J. L., Kravtsov, A. V., Klypin, A., Abazajian, K., Warren, M. S., Yepes, G., et al. (2008). Toward a halo mass function for precision cosmology: the Limits of universality. Astrophys. J. 688, 709–728. doi: 10.1086/591439

CrossRef Full Text | Google Scholar

Tojeiro, R., Ross, A. J., Burden, A., Samushia, L., Manera, M., Percival, W. J., et al. (2014). The clustering of galaxies in the SDSS-III baryon oscillation spectroscopic survey: galaxy clustering measurements in the low redshift sample of data release 11. Mon. Not. R. Astron. Soc. 440, 2222–2237. doi: 10.1093/mnras/stu371

CrossRef Full Text | Google Scholar

Tozzi, P., Madau, P., Meiksin, A., and Rees, M. J. (2000). Radio signatures of hi at high redshift: mapping the end of the “dark ages”. Astrophys. J. 528:597. doi: 10.1086/308196

CrossRef Full Text | Google Scholar

Trotta, R. (2008). Bayes in the sky: bayesian inference and model selection in cosmology. Contemp. Phys., 49, 71–104. doi: 10.1080/00107510802066753

CrossRef Full Text | Google Scholar

Upadhye, A., Kwan, J., Pope, A., Heitmann, K., Habib, S., Finkel, H., and Frontiere, N. (2016). Redshift-space distortions in massive neutrino and evolving dark energy cosmologies. Phys. Rev. D 93:063515. doi: 10.1103/PhysRevD.93.063515

CrossRef Full Text | Google Scholar

Vagnozzi, S., Dhawan, S., Gerbino, M., Freese, K., Goobar, A., and Mena, O. (2018). Constraints on the sum of the neutrino masses in dynamical dark energy models with w(z)≥−1 are tighter than those obtained in ΛCDM. arXiv:1801.08553.

Google Scholar

Vagnozzi, S., Giusarma, E., Mena, O., Freese, K., Gerbino, M., Ho, S., and Lattanzi, M. (2017). Unveiling ν secrets with cosmological data: neutrino masses and mass hierarchy. Phys. Rev. D 96:123503. doi: 10.1103/PhysRevD.96.123503

CrossRef Full Text | Google Scholar

van Haarlem, M., Wise, M. W., Gunst, A. W., Heald, G., McKean, J. P., Hessels, J. W. T., et al. (2013). LOFAR: the low-frequency ARray. Astron. Astrophys. 556:A2. doi: 10.1051/0004-6361/201220873

CrossRef Full Text | Google Scholar

Vargas-Magaña, M. (2018). The clustering of galaxies in the completed SDSS-III Baryon Oscillation Spectroscopic Survey: theoretical systematics and Baryon Acoustic Oscillations in the galaxy correlation function. Mon. Not. R. Astron. Soc. 477, 1153–1188. doi: 10.1093/mnras/sty571

CrossRef Full Text | Google Scholar

Vergados, J., Ejiri, H., and Simkovic, F. (2012). Theory of neutrinoless double beta decay. Rept. Prog. Phys. 75:106301. doi: 10.1088/0034-4885/75/10/106301

PubMed Abstract | CrossRef Full Text | Google Scholar

Vergados, J., Ejiri, H., and Šimkovic, F. (2016). Neutrinoless double beta decay and neutrino mass. Int. J. Mod. Phys. E25:1630007. doi: 10.1142/S0218301316300071

CrossRef Full Text | Google Scholar

Viel, M., Becker, G. D., Bolton, J. S., and Haehnelt, M. G. (2013). Warm dark matter as a solution to the small scale crisis: new constraints from high redshift Lyman-α forest data. Phys. Rev. D 88:043502. doi: 10.1103/PhysRevD.88.043502

CrossRef Full Text | Google Scholar

Viel, M., Haehnelt, M. G., and Springel, V. (2010). The effect of neutrinos on the matter distribution as probed by the intergalactic medium. JCAP 06:015. doi: 10.1088/1475-7516/2010/06/015

CrossRef Full Text | Google Scholar

Villaescusa-Navarro, F. (2014a). Cosmology with massive neutrinos I: towards a realistic modeling of the relation between matter, haloes and galaxies. JCAP 03:011. doi: 10.1088/1475-7516/2014/03/011

CrossRef Full Text | Google Scholar

Villaescusa-Navarro, F., Bull, P., and Viel, M. (2015). Weighing neutrinos with cosmic neutral hydrogen. Astrophys. J. 814:146. doi: 10.1088/0004-637X/814/2/146

CrossRef Full Text | Google Scholar

Villaescusa-Navarro, F., Viel, M., Datta, K. K., and Choudhury, T. R. (2014b). Modeling the neutral hydrogen distribution in the post-reionization Universe: intensity mapping. JCAP 09:050. doi: 10.1088/1475-7516/2014/09/050

CrossRef Full Text | Google Scholar

Villaescusa-Navarro, F., Vogelsberger, M., Viel, M., and Loeb, A. (2013). Neutrino signatures on the high transmission regions of the lyman-alpha forest. Mon. Not. R. Astron. Soc. 431:3670. doi: 10.1093/mnras/stt452

CrossRef Full Text | Google Scholar

Visbal, E., Loeb, A., and Wyithe, J. B. (2009). Cosmological constraints from 21cm surveys after reionization. JCAP 10:030. doi: 10.1088/1475-7516/2009/10/030

CrossRef Full Text | Google Scholar

Vogel, P. (2015). How difficult it would be to detect cosmic neutrino background? AIP Conf. Proc. 1666, 140003. doi: 10.1063/1.4915587

CrossRef Full Text | Google Scholar

Wang, G., Chang, C. L., Yefremenko, V., Ding, J., Novosad, V., Bucci, C., et al. (2015). CUPID: CUORE (Cryogenic underground observatory for rare events) upgrade with particle IDentification. arXiv:1504.03599.

Google Scholar

Wang, L.-M., Caldwell, R., Ostriker, J., and Steinhardt, P. J. (2000). Cosmic concordance and quintessence. Astrophys. J. 530, 17–35. doi: 10.1086/308331

CrossRef Full Text | Google Scholar

Wang, S., and Xia, D.-M. (2018). Constraints on the sum of neutrino masses from Bayesian analysis of the latest cosmological data. Chin. Phys. C 42:065103.

Google Scholar

Weiler, T. J. (1982). Resonant absorption of cosmic ray neutrinos by the relic neutrino background. Phys. Rev. Lett. 49:234. doi: 10.1103/PhysRevLett.49.234

CrossRef Full Text | Google Scholar

Weiler, T. J. (1984). Big bang cosmology, relic neutrinos, and absorption of neutrino cosmic rays. Astrophys. J. 285:495. doi: 10.1086/162524

CrossRef Full Text | Google Scholar

Weinberg, D. H., Mortonson, M. J., Eisenstein, D. J., Hirata, C., Riess, A. G., and Rozo, E. (2013). Observational probes of cosmic acceleration. Phys. Rept. 530, 87–255. doi: 10.1016/j.physrep.2013.05.001

CrossRef Full Text | Google Scholar

Weinberg, S. (1962). Universal neutrino degeneracy. Phys. Rev. 128, 1457–1473. doi: 10.1103/PhysRev.128.1457

CrossRef Full Text | Google Scholar

Weinberg, S. (1978). A new light boson? Phys. Rev. Lett. 40, 223–226. doi: 10.1103/PhysRevLett.40.223

CrossRef Full Text | Google Scholar

Wetterich, C. (1995). The Cosmon model for an asymptotically vanishing time dependent cosmological 'constant'. Astron.Astrophys., 301:321–328.

Google Scholar

Wilczek, F. (1978). Problem of strong p and t invariance in the presence of instantons. Phys. Rev. Lett. 40, 279–282. doi: 10.1103/PhysRevLett.40.279

CrossRef Full Text | Google Scholar

Winter, W. (2016). Atmospheric neutrino oscillations for earth tomography. Nucl. Phys. B908, 250–267. doi: 10.1016/j.nuclphysb.2016.03.033

CrossRef Full Text | Google Scholar

Witte, S., Villanueva-Domingo, P., Gariazzo, S., Mena, O., and Palomares-Ruiz, S. (2018). EDGES result versus CMB and low-redshift constraints on ionization histories. Phys. Rev. D, 97:103533. doi: 10.1103/PhysRevD.97.103533

CrossRef Full Text | Google Scholar

Wolfenstein, L. (1978). Neutrino oscillations in matter. Phys. Rev. D 17, 2369–2374. doi: 10.1103/PhysRevD.17.2369

CrossRef Full Text | Google Scholar

Wyithe, S., Loeb, A., and Geil, P. (2008). Baryonic acoustic oscillations in 21cm emission: a probe of dark energy out to high redshifts. Mon. Not. R. Astron. Soc., 383:1195. doi: 10.1111/j.1365-2966.2007.12631.x

CrossRef Full Text | Google Scholar

Yañez, J., and Kouchner, A. (2015). Measurement of atmospheric neutrino oscillations with very large volume neutrino telescopes. Adv. High Energy Phys., 2015:271968. doi: 10.1155/2015/271968

CrossRef Full Text | Google Scholar

Yang, Y. (2018). The contributions of dark matter annihilation to the global 21cm spectrum observed by the EDGES experiment. arXiv:1803.05803.

Google Scholar

Yeche, C., Palanque-Delabrouille, N., Baur, J. ., and BourBoux, H. d. M. d. (2017). Constraints on neutrino masses from Lyman-alpha forest power spectrum with bOSS and XQ-100. JCAP 06:047. doi: 10.1088/1475-7516/2017/06/047

CrossRef Full Text | Google Scholar

Zhang, J., and Zhang, X. (2018). Gravitational clustering of cosmic relic neutrinos in the milky way. Nat. Commun. 9:1833. doi: 10.1038/s41467-018-04264-y

PubMed Abstract | CrossRef Full Text | Google Scholar

Zhao, G.-B., Saito, S., Percival, W. J., Ross, A. J., Montesano, F., Viel, M., et al. (2013). The clustering of galaxies in the SDSS-III Baryon Oscillation Spectroscopic Survey: weighing the neutrino mass using the galaxy power spectrum of the CMASS sample. Mon. Not. R. Astron. Soc. 436, 2038–2053. doi: 10.1093/mnras/stt1710

CrossRef Full Text | Google Scholar

Zhao, J., Wen, L.-J., Wang, Y.-F., and Cao, J. (2017). Physics potential of searching for 0νββ decays in JUNO. Chin. Phys. C 41:053001. doi: 10.1088/1674-1137/41/5/053001

CrossRef Full Text | Google Scholar

Zlatev, I., Wang, L.-M., and Steinhardt, P. J. (1999). Quintessence, cosmic coincidence, and the cosmological constant. Phys. Rev. Lett. 82, 896–899. doi: 10.1103/PhysRevLett.82.896

CrossRef Full Text | Google Scholar