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        <title>Frontiers in Astronomy and Space Sciences | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/astronomy-and-space-sciences</link>
        <description>RSS Feed for Frontiers in Astronomy and Space Sciences | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-05-12T22:36:06.731+00:00</pubDate>
        <ttl>60</ttl>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1742823</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1742823</link>
        <title><![CDATA[A giant solution to the disk mass budget problem of planet formation]]></title>
        <pubdate>2026-05-12T00:00:00Z</pubdate>
        <category>Brief Research Report</category>
        <author>Sofia Savvidou</author>
        <description><![CDATA[Understanding how dust evolves in protoplanetary disks is crucial to constraining the initial conditions of planet formation. The apparent “mass budget problem”, which stems from the comparison of the observed disk masses to the ones inferred for exoplanets, remains debated, as it is unclear whether the discrepancy arises from limitations in interpreting disk observations, from evolutionary processes that rapidly deplete dust, or from incorrect assumptions about the initial disk mass distribution. This work is built on the previously published population synthesis models by separating here the cumulative distribution functions of dust masses at different evolutionary stages into different populations according to the initial disk masses and embryo injection times. The best match to observations comes from disks with intermediate initial disk masses around 4%–7% M⊙. The largest discrepancy between the total dust mass in the models and the estimated through an “optically thin” approximation comes from the models that have the most favorable conditions for giant planet formation and thus contain a large fraction of giants and subsequently trapped “optically thick” dust mass because of the pressure bumps they generate. However, the final dust masses remain higher compared to the estimates from the observed evolved disks. Example cases in this work including planetesimal formation show that the pressure bumps that giant planets form can be prime locations for planetesimal formation and the conversion to planetesimals significantly decreases the dust mass, as expected. However, (giant) planet formation is not influenced showing that the mass in evolved protoplanetary disks can be estimated to be quite low but it can be a natural consequence of planetesimal and planet formation along with depletion due to radial drift.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1695325</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1695325</link>
        <title><![CDATA[Detecting signs of life in biotic–abiotic mixtures using pyrolysis–gas chromatography–mass spectrometry and machine learning]]></title>
        <pubdate>2026-05-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Emersyn Slaughter</author><author>Grethe Hystad</author><author>George Cody</author><author>Anirudh Prabhu</author><author>H. James Cleaves</author><author>Robert M. Hazen</author><author>Michael L. Wong</author>
        <description><![CDATA[Biosignature detection is at the forefront of modern astrobiology and paleobiology research. Previous studies have demonstrated that machine learning models trained on data from pyrolysis–gas chromatography–mass spectrometry (py–GC–MS) can distinguish purely biotic and abiotic specimens from one another, as well as identify differences among contemporary biotic and ancient biotic samples. However, if life exists beyond Earth, its organics may be mixed with abiotic organics from, e.g., those derived from meteoritic infall. Thus, it is critical to test whether mixtures containing both biotic and abiotic components can be accurately characterized by machine learning–based techniques. Here, we investigate whether machine learning models can accurately determine the biogenicity of mixed biotic-abiotic samples. We used py–GC–MS to analyze the organic content of 61 mixtures, which included various combinations of living organisms, fossilized organics, carbonaceous meteorites, and laboratory-synthesized organics. Different ratios of the components in each mixture are used to examine how much biological organic materials can be detected in a sample. The ratios (% component 1:% component 2) include 90:10, 66:33, 50:50, 33:66, and 10:90. The data from the chromatographic and mass peaks produced by the mixed samples were then analyzed by a random forest model trained on purely biotic and purely abiotic samples. This method was able to correctly identify 87% of the mixtures that contain contemporary/modern biotic components as living, with a limit of detection between about 1% and 10% biotic material. Mixtures containing ancient/old biotics were correctly identified 60% of the time, with a limit of detection between about 33% and 50% biotic material.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1809225</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1809225</link>
        <title><![CDATA[Plasma instabilities of blazar-induced pair beams: a mini-review of current understanding]]></title>
        <pubdate>2026-05-07T00:00:00Z</pubdate>
        <category>Mini Review</category>
        <author>Mahmoud Alawashra</author><author>Martin Pohl</author>
        <description><![CDATA[TeV blazars emit very high-energy gamma rays that interact with the extragalactic background light, producing relativistic electron–positron pair beams. These beams are expected to initiate electromagnetic cascades that give observable GeV-scale emission. Yet, for many blazars, this cascade component is absent in the observed spectra. One possible explanation attributes this suppression to weak intergalactic magnetic fields that deflect the pairs out of the line of sight. An alternative scenario proposes that beam–plasma instabilities efficiently dissipate the energy of the pairs before the cascade can fully develop. In this mini review, we present an overview of the theoretical understanding of the plasma instabilities of TeV pair beams and examine their implications for GeV-scale cascade signatures. We start with early studies of the linear growth phase of the instability, discuss different nonlinear-saturation scenarios, and finish with recent investigations of the instability feedback on the pair beams that are based on a Fokker–Planck approach.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1797886</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1797886</link>
        <title><![CDATA[Characterizing solar cycle influence on long-term orbital deterioration of low-earth orbiting space debris]]></title>
        <pubdate>2026-05-06T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ayisha M. Ashruf</author><author>Ankush Bhaskar</author><author>C. Vineeth</author><author>Tarun Kumar Pant</author>
        <description><![CDATA[The rapid increase in space debris poses a major threat to sustainable space operations and underscores the importance of understanding long-term drivers of orbital decay. Because debris objects do not perform station-keeping maneuvers, their orbital evolution directly reflects variations in thermospheric density, unlike that of operational satellites. This makes space debris an effective natural testbed for examining the long-term influence of solar activity on atmospheric drag. This study analyzes the impact of solar activity on the decay of 17 LEO debris objects across solar cycles 22, 23, and 24 using Two-Line Element (TLE) data. TLE-derived decay profiles, combined with sunspot numbers (SSN) and the F10.7 index, reveal a threshold: decay rates rise sharply when SSN exceeds ∼67%–75% of its cycle peak, corresponding to increased Extreme Ultraviolet (EUV) fluxes, thermospheric density and atmospheric drag. Peak decay rates declined progressively from cycle 22 to 24, reflecting reduced solar activity. Decay profiles for cycle 24 - predicted using ballistic coefficients from earlier cycles and MSIS 2.0 atmospheric densities - match observations well after applying a scaling factor. However, two high-inclination objects showed significant deviations, suggesting possible MSIS limitations at high latitudes, while lower-inclination objects aligned closely. Moreover, geomagnetic activity indices such as AE and Dst show little correlation with long-term orbital decay rates, suggesting a comparatively weaker role at the timescales examined, for Joule heating and particle precipitation than for solar EUV forcing in driving sustained orbital decay. Overall, the findings support solar EUV-driven thermospheric variability as a primary factor influencing long-term orbital decay and emphasize the need to refine atmospheric models, particularly for polar regions, to improve reentry predictions and satellite mission planning.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1853179</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1853179</link>
        <title><![CDATA[Correction: Numerical integration and analysis of mars orbital dynamics]]></title>
        <pubdate>2026-05-06T00:00:00Z</pubdate>
        <category>Correction</category>
        <author>Shuhao Feng</author><author>Yilong Han</author><author>Shanhong Liu</author><author>Kai Tang</author><author>Jianguo Yan</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1800321</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1800321</link>
        <title><![CDATA[Detection of exoplanets from TESS imaging data using unsupervised machine learning techniques]]></title>
        <pubdate>2026-05-01T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Abisa Sinha Adhikary</author><author>Sourav Chakraborty</author>
        <description><![CDATA[The identification of exoplanets within habitable zones remains a central objective in modern astrophysics, particularly with the availability of large-scale photometric datasets from space-based missions such as the Transiting Exoplanet Survey Satellite (TESS). This study investigates the effectiveness of unsupervised machine learning techniques–specifically k-means and k-medians clustering–for analyzing and classifying light curves derived from galactic stellar populations. By extracting both basic and extended statistical features, dimensionality reduction methods including t-distributed Stochastic Neighbor Embedding (t-SNE) and Uniform Manifold Approximation and Projection (UMAP) are employed to project high-dimensional data into interpretable low-dimensional spaces. To evaluate the relevance of the identified clusters, the results are systematically compared with the TESS Objects of Interest (TOI) catalog, incorporating information on confirmed planets and candidate signals. This comparison reveals that clusters containing known TOIs often include additional unlabeled objects, suggesting the presence of potentially undiscovered exoplanet candidates. Moreover, the clustering framework effectively distinguishes between transit-like signals and noise-dominated light curves, even in sectors with few or no known TOIs. These findings highlight the capability of unsupervised learning to recover known exoplanetary signals while simultaneously identifying new candidate-rich regions within the data. The proposed framework offers a scalable and data-driven approach for prioritizing targets in large survey datasets, contributing to the advancement of automated exoplanet detection pipelines.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1816412</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1816412</link>
        <title><![CDATA[Fast acquisition of weak eLoran signals via a uniform partitioned overlap-save algorithm exploiting temporal sparsity]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Qian Liu</author><author>Jianfeng Wu</author><author>Yan Xing</author><author>Ying Wang</author><author>Junliang Liu</author>
        <description><![CDATA[Enhanced Loran (eLoran) provides resilient, wide-area positioning, navigation, and timing (PNT) services in the low-frequency band. However, receiver acquisition remains computationally demanding because of the long group repetition intervals (GRIs) and high sampling rates required for signal processing. Although the uniform partitioned overlap-save (UPOLS) algorithm has potential for matched filtering, its application to eLoran acquisition has not yet been explored. In this study, we propose the first UPOLS-based acquisition scheme tailored for eLoran signals. To address the computational bottleneck, we exploit the inherent temporal sparsity of eLoran pulses and develop a sparsity-aware acquisition method, termed the sparsity partitioned overlap-save (SPOLS) algorithm. Extensive simulations were conducted under additive white Gaussian noise (AWGN) and mixed noise-interference conditions, and performance was evaluated in terms of peak detection probability, root-mean-square error (RMSE), runtime, and memory footprint. Under AWGN conditions, SPOLS consistently detected the correlation peak at or near the true time of arrival (TOA) over a wide range of signal-to-noise ratios (SNRs), whereas the envelope delay correlation (EDC) method degraded rapidly as noise increased, showing peak shifts and spurious detections. At a fixed SNR with decreasing signal-to-interference ratio (SIR) from 10 to -25 dB, SPOLS maintained reliable detection with minimal bias, while EDC exhibited progressively distorted results. RMSE analysis showed that SPOLS achieved accuracy comparable to UPOLS and substantially outperformed EDC under moderate-to-low SNR and interference conditions. In addition, SPOLS reduced normalized runtime by approximately 45% relative to UPOLS and required less memory. These results demonstrate that SPOLS provides an effective balance among estimation accuracy, robustness, and computational complexity, making it well suited for TOA-based positioning and ranging in low-SNR and interference-prone environments, particularly in resource-constrained embedded systems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1791135</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1791135</link>
        <title><![CDATA[Multi-scale GNSS-TEC and GIM investigation of ionospheric perturbations triggered by the 28 March 2025 Myanmar earthquake preceded by geomagnetic storm]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Paul Obasanjo</author><author>Daniel Okoh</author><author>Adero Awuor</author><author>Paul Baki</author><author>George Ochieng</author>
        <description><![CDATA[This study investigates variability in ionospheric Total Electron Content (TEC) associated with the 28 March 2025 moment magnitude (Mw) 7.7 Sagaing (Myanmar) earthquake within the low-latitude environment of Southeast Asia. A primary challenge in this region is identifying seismogenic perturbations during the residual recovery phase of two successive geomagnetic storms (25–26 March), which produced large-scale TEC fluctuations of ±35 TEC units (TECU). To isolate potential seismic signatures, we implemented a multi-scale “Filter-to-Focus” framework. This approach uses regional Center for Orbit Determination in Europe (CODE) Global Ionospheric Maps (GIMs) as a spatial filter to separate broad storm-driven trends from localized lithospheric forcing. Subsequently, localized Global Navigation Satellite System (GNSS) TEC time series from station CMUM (located 390 km from the epicenter) were analyzed to provide high-resolution spectral focus. Statistical rigor was established using a non-parametric 1.5× interquartile range (IQR) threshold combined with control-day validation, confirming that differential TEC (dTEC) remained within stable limits prior to the seismic event. Despite the dominant storm-time background, distinct localized perturbations were detected. These included an observed pre-event enhancement of +3.2 TECU 8–12 h prior to the mainshock—though definitively isolating this from late-stage storm dynamics remains complex—and significant coseismic enhancements of 15–25 TECU occurring approximately 18 min after rupture. Continuous Wavelet Transform (CWT) analysis confirmed that these coseismic perturbations exhibited wave-like oscillations within the 10–25 min period range (∼0.7–1.7 mHz), consistent with the internal gravity wave component of the acoustic-gravity wave (AGW) spectrum. Importantly, the CWT distinguished these specific seismogenic signatures from the broader, lower-frequency fluctuations typical of the geomagnetic recovery phase. These results demonstrate that seismogenic signals can be retrieved from geophysically noisy environments using combined spatial and frequency-domain filtering. This study provides a robust methodology for investigating lithosphere–atmosphere–ionosphere (LAI) coupling, offering a significant refinement for anomaly detection within the highly dynamic crest of the Equatorial Ionization Anomaly (EIA).]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1756599</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1756599</link>
        <title><![CDATA[Evolution of density structures in the inner magnetosphere using coordinated Van Allen probe observations]]></title>
        <pubdate>2026-04-30T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Tyler Bishop</author><author>Lauren Blum</author>
        <description><![CDATA[The plasmasphere contains rich small-scale structure that plays a key role in regulating wave propagation and mass transport in the inner magnetosphere, yet the evolution of plasmaspheric density ducts remains poorly understood. We use joint observations from the Van Allen Probes to investigate how density structures change over time by identifying matched structures observed by both spacecraft during the years 2013 and 2014. For each structure, we quantify changes in density, width, and location, and assess whether the structure satisfies theoretical criteria for whistler-mode ducting. We identify 167 density structures and find that structures are usually largest and most dynamic near the plasmapause and are associated with slightly increased levels of geomagnetic activity. Although some structures exhibit minimal evolution over the spacecraft separation interval, many undergo substantial changes in both density and width, with no clear systematic trends, suggesting largely stochastic evolution. The motion of these density structures includes both outward and inward radial shifts. The vast majority of structures remain capable of ducting whistler-mode waves throughout the observation period. These results provide new insights on plasmaspheric substructure evolution and highlight the importance of multi-point measurements for understanding ionosphere-magnetosphere coupling.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1788224</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1788224</link>
        <title><![CDATA[Evaluation of lunar soil sampling disturbance based on penetration resistance method]]></title>
        <pubdate>2026-04-28T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Lan-Lan Xie</author><author>Qian Li</author><author>Ding-Kun Hu</author><author>Jia-Hang Lv</author>
        <description><![CDATA[IntroductionTo investigate the impact of surface sampling operations on the physical and mechanical properties of lunar soil—defined as the granular, sub-centimeter-sized fraction of the lunar regolith—and to mitigate design errors in sampling missions that arise from neglecting such disturbance, we conducted sampling disturbance experiments using the CUG-1A lunar soil simulant.MethodsThe degree of lunar soil disturbance was evaluated based on the change in penetration resistance of a standard probe inserted into the soil before and after sampling.ResultsThe experimental results indicate that the bucket width, sampling depth, sampling speed, and (for shovelling) the entry angle all significantly affect the disturbance degree.DiscussionThe shovelling action, a linear penetration-and-lift operation, predominantly induces a compaction effect on the lunar soil simulant. In contrast, the digging action, an arcuate scooping operation, causes compaction during the initial phase but generates a distinct loosening effect at the motion endpoint. The parameter combination that minimizes disturbance for the shovelling experiment is a bucket width of 4 cm, sampling depth of 2 cm, speed of 50 mm/s, and entry angle of 45°. For the digging experiment, the optimal combination is a bucket width of 4 cm, sampling depth of 3.5 cm, and speed of 50 mm/s.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1786844</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1786844</link>
        <title><![CDATA[A hidden pattern? Common polyextremophilic microbial adaptations in Icy Moon analog environments]]></title>
        <pubdate>2026-04-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sandra Gusi-Martínez</author><author>Alberto G. Fairén</author><author>Miguel Ángel Fernández-Martínez</author>
        <description><![CDATA[The search for life signatures beyond Earth is one of the main objectives of space exploration. Studies of analogous terrestrial ecosystems have shed light on the limits of life and on the adaptations of microbial communities to thrive in these extreme environments resembling Icy Moons. However, their findings tend to be compartmentalized, which hinders the drawing of broad conclusions about the drivers and challenges for life. This study aims to identify general characteristics of microbial communities inhabiting terrestrial analogs of Icy Moons, applying a novel meta-analysis on publicly available 16S rRNA amplicon sequencing data. We also seek to apply our findings to a new fundamental approach in the search for life in Europa and Enceladus, locations where life may exist. Our results suggest that depth, pH and hypersalinity are the key environmental drivers for microbial taxa distribution and molecular adaptations, with halophilic archaea showing ubiquitous presence. Integrating diverse datasets into a single meta-analysis allowed us to infer statistically significant microbial patterns related to adaptation to the Icy Moons’ analog conditions, notably that osmolytes and modified lipids emerged as a shared adaptive strategy, regardless of depth. Our findings are aimed to helping guide future life detection efforts in these extraterrestrial environments.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1784533</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1784533</link>
        <title><![CDATA[Selection of beneficial fungi for plants with the potential to metabolize lunar and Martian regolith]]></title>
        <pubdate>2026-04-17T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Jéssica Carneiro Oliveira</author><author>Rafael Loureiro</author><author>Andrew Palmer</author><author>Camila Maistro Patreze</author>
        <description><![CDATA[The establishment of sustainable agriculture on extraterrestrial bodies (the Moon, Mars, etc.) depends on transforming regolith, an unconsolidated, microbiota-free, mineral substrate, into a functional soil-like material with numerous beneficial properties including as a growth substrate for plants. Lunar and Martian regolith present physicochemical challenges, including alkaline pH, high concentrations of toxic elements (e.g., aluminum, manganese, perchlorates), and limited bioavailability of essential nutrients such as nitrogen, phosphorus, and potassium. This review explores the potential of beneficial fungi to support regolith-based agriculture (RBA) through biomineralization, nutrient mobilization, and bioremediation. We present fungal species capable of solubilizing phosphates, chelating metals via siderophores, and metabolizing iron and aluminum oxides, thereby enhancing nutrient accessibility. While some highlighted genera, such as Trichoderma, Penicillium, and Aspergillus, include well-known pathogenic species, they also encompass strains with potential applications for promoting plant growth under abiotic stress. Extremophilic fungi like Cryomyces antarcticus are also noted for their resilience. Furthermore, we discuss the potential role of arbuscular mycorrhizal fungi (AMF) from the phylum Glomeromycota in promoting plant growth under harsh conditions. On Earth, these fungi are known to enhance iron uptake, mitigate oxidative stress, and improve soil structure via glomalin-mediated aggregation, mechanisms that may be applicable to regolith systems. We also examine fungal strains isolated from the International Space Station which may possess pre-adapted traits suitable for these off-world environments. While knowledge gaps remain, particularly regarding biosafety, strain selection, and performance validation under simulated extraterrestrial conditions, including radiation exposure, we contend that fungi are essential biotechnological allies for ISRU (In Situ Resource Utilization), contributing to sustainable agriculture in both extraterrestrial habitats and degraded ecosystems on Earth. We emphasize the need for interdisciplinary research integrating astrobiology, microbial ecology, and space agriculture in preparation for future crewed missions to the Moon and Mars.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1821037</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1821037</link>
        <title><![CDATA[Refining relative tropospheric delay modeling of GPT3 for large-height-difference RTK positioning]]></title>
        <pubdate>2026-04-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Peida Wu</author><author>Weixing Zhang</author><author>Yidong Lou</author><author>Mengjie Liu</author><author>Wanke Liu</author><author>Hong Chen</author><author>Zhizhao Liu</author>
        <description><![CDATA[Real-Time Kinematic (RTK) positioning technique, with centimeter-level accuracy, is widely used in landslide deformation and building structural health monitoring. However, in large-height-difference scenarios where the height difference between the base and rover station is generally over 100 m, RTK positioning performance experiences a significant decline, mainly due to the deficiency in tropospheric delay modeling. In this study, we proposed a new method to refine the modeling of relative tropospheric delay corrections for the widely-used GPT3 by using ERA5 reanalysis data. The refined model, referred to as GPT3-e, shows an improvement of ∼33% for relative tropospheric modeling on a global scale compared to GPT3. Large-height-difference RTK positioning experiments further show that the vertical errors were reduced by 2.9 cm in January and 2.4 cm in July, with corresponding accuracy improvements of 64% and 57%, respectively, and slightly improves the ambiguity-fixing rate. As the refined model does not rely on external real-time products, it is compatible with the current RTK devices which makes the model easy to implement and will not significantly increase the cost.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1797722</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1797722</link>
        <title><![CDATA[Assessment of DKIST/VTF capabilities for the detection of local acoustic source wavefronts]]></title>
        <pubdate>2026-04-15T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Corinne Morrell</author><author>Mark P. Rast</author><author>Shah Mohammad Bahauddin</author><author>Ivan Milić</author>
        <description><![CDATA[IntroductionRecent studies have demonstrated that temporal filtering can successfully identify local acoustic source wavefronts in radiative magnetohydrodynamic simulations of the solar photosphere. Extending this capability to observations promises new insight into the stochastic excitation of solar p-modes, the source depth distribution below the photosphere, and the dominant physical processes underlying acoustic wave excitation. Such measurements would also enable improved characterization of the complex wavefield in the lower chromosphere and open the possibility of ultra-local helioseismic diagnostics.MethodsIn this work, we assess an observational strategy for the detection of local acoustic wavefronts on the Sun using the Visible Tunable Filter (VTF) instrument on the National Science Foundation’s Daniel K. Inouye Solar Telescope (DKIST). Because wavefront identification requires high spatial and temporal resolution and is limited by the small amplitudes of the wave perturbations, we focus on identifying specific wavelength combinations within photospheric spectral lines that maximize the sensitivity to the wave signal.ResultsUnder the cadence and spectral resolution constraints of DKIST/VTF observations and for the particular simulated wavefront we examine, this approach suggests two possible strategies: fast monochromatic imaging at 6302.425 Å, or ordered interleaved observations in the blue wing of either the Fe I 6302.5 Å or Fe I 5250.6 Å line (between 6302.419 Å and 6302.465 Å, or between 5250.579 Å and 5250.607 Å respectively).DiscussionThe observational capabilities of DKIST/VTF satisfy the stringent spatial, spectral, and temporal resolution requirements of the methods suggested here. Thus, DKIST/VTF presents an opportunity to detect local acoustic wavefronts in the photosphere at their intrinsic temporal and spatial scales for the first time.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1788081</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1788081</link>
        <title><![CDATA[Turbulence properties and kinetic signatures of electrons in Kelvin-Helmholtz waves during a geomagnetic storm]]></title>
        <pubdate>2026-04-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Harsha Gurram</author><author>Jason R. Shuster</author><author>Li-Jen Chen</author><author>Richard E. Denton</author><author>Matthew R. Argall</author><author>Subash Adhikari</author><author>Rachel C. Rice</author><author>Brandon L. Burkholder</author><author>Daniel J. Gershman</author>
        <description><![CDATA[The Kelvin–Helmholtz instability (KHI), in its nonlinear phase, plays a significant role in transporting solar-wind plasma into Earth’s magnetosphere. This study investigates the turbulence properties and reconnection signatures observed at the edges of Kelvin–Helmholtz vortices during a geomagnetic storm. Temporal spectra of the magnetic field, electric field, and bulk ion velocity exhibit power-law behavior with slope changes near the ion gyrofrequency, as well as a distinct spectral knee near 0.14 Hz in the inertial range. The nonlinear KH vortices exhibit an alignment between the magnetic field and plasma velocity at large scales, which progressively weakens toward kinetic scales, consistent with trend in the magnetosheath. These inertial-scale properties indicate that KH vortices host strong turbulence and coherent structures even during their early nonlinear phase. In addition, MMS observes a reconnecting current sheet characterized by intense electron jets and signatures consistent with strong guide-field asymmetric reconnection at the magnetopause. Significant agyrotropy in the electron velocity distribution functions is detected both within the reconnecting current sheet and along the edges of the KH vortices. Together, these observations provide a multi-scale view of KH-driven turbulence and reconnection under strongly driven storm-time conditions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1736938</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1736938</link>
        <title><![CDATA[Planet formation constraints from exoplanet population synthesis and simulation based inference]]></title>
        <pubdate>2026-04-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jason Ran</author><author>Mihkel Kama</author><author>Anna Sommerville-Thomas</author>
        <description><![CDATA[This work introduces a statistical framework to obtain Bayesian constraints on planet formation parameters, which offers a probabilistic interpretation of uncertainties and degeneracies contained within planet formation models. The model likelihood, or the probability distribution of observations conditioned on a set of formation parameters, is intractable for planet formation theories due to the high degrees of complexity involved. Furthermore, traditional likelihood estimation techniques scale poorly high to dimensional parameter spaces, and begin to require an excessive number of samples. Instead, this work utilizes neural density estimation to directly learn the posterior distribution. This is a data driven simulation-based inference approach based on simulations from an exoplanet population synthesis model. This work focuses on understanding the degeneracies found within the parameters of disk mass, disk radius, MHD-wind parameters, mid-plane temperature, and planet birth location. The information within these degeneracies are captured in posterior distributions conditioned on observables of planet mass, orbital period, and atmospheric C/O ratio. As a realized demonstration, inference is performed on the hot Jupiter HD 209458b. The inferred posterior distribution is re-sampled as parameter inputs for the population synthesis model to re-simulate formation tracks of HD 209458b. These tracks reveal two distinct scenarios where the planet formation begins either side of the CO2 ice line. This highlights the ability to both infer formation parameters, and study the interactions between physical processes involved in planet formation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1810495</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1810495</link>
        <title><![CDATA[Radial evolution of the solar wind electron heat flux in the inner heliosphere]]></title>
        <pubdate>2026-04-10T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Bofeng Tang</author><author>Laxman Adhikari</author><author>Gary P. Zank</author><author>Fang Shen</author>
        <description><![CDATA[The electron heat flux plays a important role in the expansion of the solar corona and solar wind. The electron heat flux of the solar wind is fully described by the electron velocity distribution function as it evolves with heliocentric distance. We investigate the characteristics of the radial evolution of the electron heat flux in the inner heliosphere from 0.2 to 2.2 au. The electron Fokker-Planck form of the kinetic transport equation is solved numerically in the presence of the magnetic field, the ambipolar electric field, and appropriate scattering mechanisms. The electron heat flux is calculated from the numerical solutions of the electron velocity distribution function. Our numerical simulations reveal that the radial evolution of the heat flux can be approximated by multiple power laws, with the rate of decrease gradually slowing with increasing heliocentric distance. However, introducing suprathermal electrons, ambipolar electric field, and scattering mechanisms mitigate this property and allow for a single power-law approximation for the radial evolution of the electron heat flux. Suprathermal electrons cause the heat flux to decrease more slowly with heliocentric distance, i.e., a larger power law index, and this results in fewer variations of the index of the radial evolution of electron heat flux. The ambipolar electric fields accelerate the decrease of the electron heat flux. In contrast, suprathermal electrons and scattering mechanisms slow down the decrease of the heat flux with heliocentric distance. The stronger the scattering experienced by electrons, the slower the radial evolution of electron heat flux and the larger the index of the radial evolution of the electron heat flux.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1817245</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1817245</link>
        <title><![CDATA[Oxygen torus and warm plasma cloak: a review]]></title>
        <pubdate>2026-04-09T00:00:00Z</pubdate>
        <category>Review</category>
        <author>Masahito Nosé</author><author>Naomi Maruyama</author>
        <description><![CDATA[This paper reviews past observational studies of low-energy ion populations in the Earth’s magnetosphere, known as the oxygen torus and the warm plasma cloak. These populations have been investigated since the early 1980s and have recently regained attention. The oxygen torus is characterized by enhanced O+ ions at energies below several tens of eV near the plasmapause (L = 3–5), with a magnetic local time distribution skewed toward the dawn sector, whereas the warm plasma cloak consists primarily of field-aligned H+ and O+ ions with energies from ∼10 eV to ∼3 keV, extending from the nightside through dawn to the dayside at L = 4–12. Several formation mechanisms have been proposed for the oxygen torus, including ionospheric heating due to ring current–plasmasphere interactions, the geomagnetic mass spectrometer effect, and direct supply of low-energy O+ ions from the nightside ionosphere followed by eastward drift. Recent observations favor the latter mechanism, although the relative importance of each process remains uncertain. The formation of the warm plasma cloak is generally attributed to ionospheric outflow transported through the magnetotail and subsequently convected earthward. Considering their energy and spatial distributions as well as plausible generation mechanisms, the oxygen torus and the warm plasma cloak appear to be distinct plasma populations. Their mutual relationship and the dominant formation process of the oxygen torus remain open questions, motivating future observations with improved ion composition measurements across a wide energy range.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1774478</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1774478</link>
        <title><![CDATA[Gaia DR3 supervised classification of asteroid reflectance spectra]]></title>
        <pubdate>2026-04-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Marco Delbo</author><author>Thomas Dyer</author><author>Ullas Bhat</author><author>Chrysa Avdellidou</author><author>Laurent Galluccio</author><author>Amelia Milton</author>
        <description><![CDATA[We present a supervised, probabilistic taxonomic classification of asteroid reflectance spectra from Gaia Data Release 3 (DR3). Using high-quality Gaia DR3 spectra and a reference set of spectra from the literature consisting exclusively of asteroids with robust spectroscopic taxonomic types, we construct a principal-component (PC) representation of the Gaia reflectances. For each major spectral complex (C, S, X) and several end-member classes (B, D, A, L, K, V), we model the distribution of reference objects in PC space using multivariate kernel density estimation (KDE). This yields likelihoods for each spectral class and provides a quantitative measure of classification confidence. Validation against a sample of objects with known spectral classes demonstrates good performance for classes with distinctive reflectance signatures, including the S-complex, D, V, and A types. Spectrally continuous classes (B-C-complex, K-L-S-complex, and X-complex) show the expected degrees of mixing given the limited wavelength range of Gaia’s spectrophotometry. We further explore the compositional structure of six major asteroid collisional families using our Gaia-derived spectral classes, finding excellent agreement with ground-based spectroscopy and revealing enhanced detections of olivine-rich A type material in the Flora and Eunomia families, as well as new insights into the spectral diversity of the Tirela family. The resulting catalogue constitutes a fully probabilistic taxonomic classification for the full Gaia DR3 asteroid sample. It offers a resource for studying the compositional structure of the main belt, identifying family interlopers, and linking asteroid populations to meteorite groups, and establishes a methodological framework for future Gaia releases, in particular for the validation of the Gaia DR4, expected by the end of 2026.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fspas.2026.1786771</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fspas.2026.1786771</link>
        <title><![CDATA[Explainable machine learning of the MCP dark count observed by Earth-orbiting space telescope]]></title>
        <pubdate>2026-04-08T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Ryoichi Koga</author><author>Satoshi Oyama</author><author>Masahito Nosé</author><author>Kazuo Yoshioka</author>
        <description><![CDATA[Radiation in low Earth orbit (LEO) poses a critical risk to satellite electronics and optics, and clarifying the causes of sudden variations in Earth’s inner radiation belt is therefore essential. Using the dark count rates on the micro-channel plate (MCP) detector of the Hisaki space telescope collected over the period 2013–2018, we identified several enhancement events with amplitudes of a factor of 2–5. A two-stage regression analysis with model training on 2013–2016 and detailed event analysis in 2017–2018, combining satellite orbital parameters with Geostationary Operational Environmental Satellite (GOES) measurements (X-rays, magnetic fields, protons, and electrons) and the Symmetric-H component (SYM-H) index, detected events in August 2018 and September 2017, as well as precursor variations occurring about 2 days earlier. While such events are expected to be attributed to coronal mass ejections, SHapley Additive exPlanations (SHAP) analysis revealed an unexpected contribution from non-delayed X-ray variations, suggesting that solar flares may directly affect detectors within minutes. This finding indicates that non-delayed X-ray variations can act as a distinct, event-specific driver of transient dark count enhancements, highlighting the event-to-event variability of radiation-induced detector responses in LEO.]]></description>
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