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        <title>Frontiers in Physics | New and Recent Articles</title>
        <link>https://www.frontiersin.org/journals/physics</link>
        <description>RSS Feed for Frontiers in Physics | New and Recent Articles</description>
        <language>en-us</language>
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        <pubDate>2026-08-24T23:04:16.975+00:00</pubDate>
        <ttl>60</ttl>
        <item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1899557</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1899557</link>
        <title><![CDATA[Residual-certified super-clocks for a time-forced Kawahara equation with Caputo-Katugampola memory]]></title>
        <pubdate>2026-08-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Weaam Alhejaili</author><author>Alvaro H. Salas</author><author>Samir A. El-Tantawy</author>
        <description><![CDATA[In this investigation, a residual-certified construction is developed for analyzing a time-forced Kawahara equation with Caputo-Katugampola memory. The main point is that the external forcing is not inserted through a classical primitive. Instead, the forced fractional background is taken to be the Caputo-Katugampola fractional integral of the forcing. A classical sech-fourth Kawahara model is then placed on this memory background and transported by a normalized (α,ρ)-super-clock. The clock coefficients are determined by minimizing the strict fractional residual over a prescribed space-time domain. The fractional forcing response is evaluated after analytically removing the endpoint singularity; the resulting regular integral is computed using a fixed Gauss-Legendre rule. The Caputo-Katugampola derivative in the residual is evaluated using an incomplete beta function formula, avoiding adaptive integration and any fractional chain rule assumption. For a representative non-Caputo case (α,ρ)=(0.85,1.1), the method gives a nontrivial forced coherent profile with a monotone optimized clock and a residual defect suitable for benchmarking nonlinear fractional dispersive solvers. Because a small residual alone does not guarantee a physically meaningful memory-time deformation, the optimized clock is further subjected to an explicit monotonicity (admissibility) test, and only clocks that pass this test are retained as physical propagation histories.]]></description>
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        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1897453</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1897453</link>
        <title><![CDATA[Corruption as a self-sustained collective state in political systems]]></title>
        <pubdate>2026-08-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Nuno Crokidakis</author><author>Jaime L. C. da C. Filho</author>
        <description><![CDATA[Political corruption is often interpreted as the result of individual misconduct or isolated institutional failures. However, persistent corruption patterns observed in real-world political systems suggest that systemic corruption may instead emerge as a self-sustaining governance arrangement supported by reinforcing interaction structures. In this work, we introduce a minimal compartmental model for the dynamics of systemic political corruption and the formation of corruption-supporting relational structures. The concentration of political power is treated as an emergent macroscopic observable arising from these coupled dynamics. Despite its simplicity and mean-field character, the model exhibits a nontrivial phase transition separating regimes of low corruption from structurally captured states sustained by self-reinforcing interaction mechanisms. Analytical expressions for the stationary states, the critical threshold and the stability conditions are obtained, revealing how the formation of corruption-supporting structures competes with institutional dissipation mechanisms. The model predicts that, above a critical interaction strength, the captured state becomes dynamically stable, with small perturbations of the macroscopic variables naturally relaxing back to the stationary state. We argue that this mechanism provides a possible explanation for the persistence of corruption across successive electoral cycles and institutional crises. In particular, the political dynamics observed in the state of Rio de Janeiro, Brazil, provide a qualitative illustrative example of several mechanisms discussed by the proposed framework rather than a quantitative application of the model. More broadly, the results suggest that long-term political capture may emerge spontaneously from reinforcing interactions between systemic corruption and the relational structures that sustain it, without requiring centralized coordination or complex strategic behavior.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1916832</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1916832</link>
        <title><![CDATA[Optimal dissipative pathways in open quantum systems: a variational framework for environmental heat dissipation minimization]]></title>
        <pubdate>2026-08-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Sonet Daniel Thomas</author><author>Aparna Rajan</author><author>Naveen Joy</author><author>Lijin Varghese</author><author>Aswathi Balakrishnan</author><author>Ivin Shajan</author><author>Muhammed Shahul</author><author>Suhail Subair</author><author>Somasundaram R</author><author>Neena Xavier</author><author>Amogh V. Itagi</author><author>Rajesh Raju</author>
        <description><![CDATA[Optimal control in open quantum systems is considered, with a focus on a two-level logical qubit system whose time evolution is governed by Markovian dynamics described within the Lindblad (GKSL) formalism. The objective is to minimize the net heat transferred to the environment during the transition while explicitly accounting for the work performed by the external control field. In this context, we formulate a variational optimal control framework for minimizing dissipated heat under fidelity constraints, which establishes existence under standard assumptions of bounded controls and lower semi-continuity of at least one bounded control that minimizes the environmental heat dissipation functional while maintaining the final-state fidelity above a designated threshold. The analysis combines the direct method of the calculus of variations with the Pontryagin Maximum Principle. The direct method in the calculus of variations (in L ∞ spaces) guarantees existence by demonstrating the compactness of admissible controls and the lower semi-continuity of the cost functional. Second, the Pontryagin Maximum Principle for open quantum systems establishes essential optimality conditions, resulting in coupled state–costate equations and switching functions that define optimal controls. We establish a physical foundation for the optimization problem by defining internal energy, heat flow, and work within the Lindblad framework, resulting in a thermodynamically coherent expression for dissipated energy. This formulation allows for both analytical understanding together with a practical numerical approximation based on the MDR-GRAPE algorithm. To demonstrate numerical consistency, we present MDR-GRAPE, a modified gradient-based algorithm that extends GRAPE to dissipative environments, integrating positivity-preserving techniques for density matrices. Numerical experiments demonstrate reproducible convergence across the five independent initializations considered in this study, providing empirical evidence of consistent convergence toward feasible low-dissipation solutions.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1751961</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1751961</link>
        <title><![CDATA[Covariant laws of reflection and refraction at relativistically moving interfaces]]></title>
        <pubdate>2026-08-24T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>J. Sumaya-Martinez</author><author>J. S. Stabler</author><author>M. A. Ortiz-Ferreyro</author>
        <description><![CDATA[IntroductionLight interacting with moving optical interfaces exhibits relativistic aberration and Doppler effects that modify reflection, refraction, frequency conversion, and momentum exchange beyond the static-interface limit. These effects are relevant to plasma mirrors, refractive fronts, attosecond sources, and precision interferometry.MethodsWe develop a covariant, self-contained treatment of planar interfaces in uniform motion with arbitrary obliquity. For reflection, we derive closed-form laboratory-frame expressions for the reflected angle, reflected frequency, and radiation pressure. For refraction, we obtain a relativistic Snell’s law by aberrating to the comoving frame, applying the classical Snell condition, and aberrating back to the laboratory frame. We further analyze limiting cases and construct numerical design maps.ResultsThe formulation recovers the classical limit as β → 0, identifies a kinematic grazing-reflection threshold, and clarifies the role of the normal velocity component in controlling angular and spectral shifts. For refraction, the theory quantifies the relativistic correction to the transmitted angle and identifies operational regions where |Δθ2| is appreciable. Numerical examples, comparison tables, and parameter maps summarize application-relevant regimes for up-conversion, low-backaction operation, and motion sensitivity.DiscussionThe results provide experimentally testable relations for moving interfaces and connect naturally to plasma-mirror experiments, including attosecond pulse generation, relativistic beam steering, and precision metrology. The framework also offers practical guidance for future studies of partially reflecting and dispersive moving media.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1860207</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1860207</link>
        <title><![CDATA[SO(3)-based and structure-guided deformable registration for respiratory motion correction in thoracic PET]]></title>
        <pubdate>2026-08-20T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Hui Zhou</author><author>Longxi He</author><author>Siyu Wang</author><author>Jianfeng He</author>
        <description><![CDATA[Respiratory motion in thoracic positron emission tomography (PET) introduces spatially heterogeneous non-rigid deformation that can blur lesions, weaken local boundary definition, and reduce structural fidelity. To address this problem, we developed TLCE-morph, a Tri-Path Lie Convolution Encoder-based learning framework for deformable respiratory motion correction in thoracic PET. The framework combines an SO(3)-based group-aware convolution module with a Tri-Path Fusion Encoder to couple orientation-aware geometric modeling with structurally guided feature encoding at local, global, and cross-scale levels. TLCE-morph was evaluated on simulated respiratory motion datasets and a two-center clinical gated PET cohort using Dice, correlation coefficient, and 95th percentile Hausdorff distance. Additional analyses included lesion-level normalized PET uptake consistency, local line-profile and full width at half maximum measurements in motion-sensitive regions, architectural ablation, group-representation comparison, and computational profiling. Across the simulated datasets, TLCE-morph remained comparatively stable as deformation increased from relatively regular displacement to more heterogeneous and coupled motion. In the clinical gated PET cohort, it achieved the most favorable overall quantitative performance among the evaluated methods and showed more consistent local structural recovery in representative motion-sensitive regions. Additional comparisons of group representations and architectural ablation indicated that the observed advantage was associated with the joint contribution of 3D orientation-aware feature modeling and complementary structural constraints rather than with any single component alone. These findings suggest that stable respiratory motion correction in thoracic PET may benefit from coupling geometric sensitivity with structurally guided feature encoding under heterogeneous deformation, rather than relying on appearance matching alone.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1951889</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1951889</link>
        <title><![CDATA[Editorial: Beta decay: current theoretical and experimental challenges]]></title>
        <pubdate>2026-08-19T00:00:00Z</pubdate>
        <category>Editorial</category>
        <author>Alejandro Algora</author><author>Pedro Sarriguren</author><author>Gábor Gyula Kiss</author><author>Muriel Fallot</author>
        <description></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1926250</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1926250</link>
        <title><![CDATA[Enhanced erosion resistance of seawater-based bio-cemented sand via soybean hull-derived EICP]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Xin Hu</author><author>Gaoqun Chu</author><author>Huiming Tan</author>
        <description><![CDATA[Coastal erosion severely threatens the stability of sandy shorelines, necessitating low-cost and sustainable bio-mediated treatment methods for shoreline protection. This study investigates an enzyme-induced carbonate precipitation (EICP) approach utilizing crude urease extracted from soybean hulls and concentrated seawater as an ionic source to enhance the erosion resistance of sand. The joint effects of urease activity, solution volume, treatment cycles, seawater concentration, and curing time were systematically evaluated through penetration strength, wind erosion, and hydraulic erosion tests, complemented by carbonate content measurements. Testing results indicate that the urease activity of the soybean hull extract scaled with the dosage, reaching a maximum of 2.27 mmol L-1·min-1. The seawater-based EICP treatment successfully formed a hardened surface crust, increasing the surface penetration strength to 0.841 MPa, while the critical wind velocity and critical flow velocity increased by up to 7.2 and 6.4 times, respectively, compared with untreated sand. Notably, multi-cycle spraying proved superior to a single application with the same total solution volume. While urease activity was the dominant factor governing carbonate production under relatively low-activity conditions, the number of treatment cycles exerted the strongest influence on hydraulic erosion resistance. Furthermore, power-law relationships were established between erosion-resistance indices and both carbonate content and penetration strength. Carbonate content showed consistently stronger correlations with erosion resistance than penetration strength, indicating that it provides a practical and reliable indicator for evaluating the erosion resistance of seawater-based EICP-treated sand. These findings demonstrate the feasibility of coupling agricultural by-product-derived urease with seawater-based EICP for cost-effective and sustainable stabilization of coastal sandy soils.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1896122</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1896122</link>
        <title><![CDATA[Reinforcement learning-driven adaptive rewiring modulates fragmentation depth in bounded-confidence opinion dynamics]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Quang Nguyen</author><author>Nha Binh Truong</author>
        <description><![CDATA[The structure of an interaction network strongly shapes opinion clustering and the emergence of echo chambers in bounded-confidence (BC) models. We ask whether a controller can steer this clustering by rewiring edges adaptively and how a learned policy compares with hand-designed heuristics. We train a dueling double deep Q-network (DQN) with a candidate-aware state to select degree-preserving edge swaps in a Deffuant model on a sparse Erdős–Rényi (ER) graph (N=500, ⟨k⟩=7.8). Augmenting the state with the signed discord change of each candidate is essential: without it, the agent fails to learn. With it, training reward saturates within ∼200 episodes. Pooling over 10 independent graph realizations and 25 opinion initializations per graph (250 trials per strategy), the learned heterophilic policy reaches a median cluster count C=7.0 at ε=0.18, significantly above the no-rewiring baseline (C=3.0, p<10−3) and the greedy heterophilic oracle (C=6.0). The RL benefit is mode-asymmetric: reinforcement learning (RL) exceeds greedy heterophilic rewiring in 9/10 graphs (Cliff’s δ=+0.26, small effect) but is exceeded by greedy homophilic rewiring in 9/10 graphs (Cliff’s δ=−0.21, small effect). A sweep over ε∈[0.12,0.30] reveals a sigmoidal nucleation barrier for reaching C≥6, with directed strategies giving up to 2.5× speedup over random rewiring. Interpretation: at intermediate ε, the natural attractor is bipolar, so homophilic and heterophilic rewiring amplifies fragmentation; what they control is the depth, not the sign. This finding delimits what rewiring-based interventions can and cannot achieve within the abstract BC framework and identifies the regimes where multistep planning outperforms myopic heuristics.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1881118</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1881118</link>
        <title><![CDATA[Penta band terahertz metamaterial absorber for cancer detection using deep learning]]></title>
        <pubdate>2026-08-18T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Santosh Kumar Mishra</author><author>Bhargav Appasani</author><author>Amitkumar V. Jha</author><author>Wriddhi Bhowmik</author><author>Yadgar I. Abdulkarim</author><author>Avireni Srinivasulu</author><author>Bharati Ainapure</author><author>Omprakash Acharya</author><author>Nicu Bizon</author>
        <description><![CDATA[This paper presents a novel approach to skin, blood, and breast cancer detection using a penta-band Terahertz (THz) metamaterial absorber and deep learning. The proposed absorber, designed on a Gallium Arsenide substrate, exhibits high absorption peaks of 99.37%, 99.11%, 99.25%, 91.95%, and 99.37% at 0.541 THz, 2.904 THz, 3.291 THz, 3.423 THz, and 3.661 THz, respectively. Cancerous and non-cancerous breast, blood, and skin cells of varying thicknesses are placed on top of the absorber, and the corresponding absorption spectra are obtained under different incident and polarization angles of THz radiation. The underlying principle is that the absorption spectrum varies with the refractive index of the tissue. A dataset of 252 unique absorption spectra is generated for each cell type. Three different deep neural networks have been built, one for each of the following applications: breast cancer detection (Model I), blood cancer detection (Model II), and skin cancer detection (Model III). Model I achieved 100% training accuracy and 94.4% validation accuracy, while Models II and III both achieved perfect accuracy on both training and validation sets (100% and 100%, respectively). On the unseen test data, Model I achieves an accuracy of 100%, Model II achieves an accuracy of 93.88%, and Model III achieves an accuracy of 100%. The results confirm the potential of integrating THz absorption spectroscopy with machine learning for cancer diagnosis. This research offers significant advancements in diagnostic technology, paving the way for more efficient, cancer detection methods.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1927967</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1927967</link>
        <title><![CDATA[A side-channel attack for recovering keys in HMAC-SM3 algorithm]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhen Wu</author><author>Zhiguang Qin</author><author>Kai Wang</author>
        <description><![CDATA[Cyber-Physical-Social Systems (CPSS) face escalating side-channel threats that undermine secure data transmission and authentication. As China’s national cryptographic hash standard, SM3 is widely deployed in CPSS-integrated social network ecosystems for identity authentication, API signing, and cross-platform data integrity verification—yet its key-dependent input vulnerabilities against side-channel attacks remain inadequately addressed. This study tackles two critical limitations of traditional side-channel attacks for HMAC-SM3 key recovery: non-profiling methods fail due to absent plaintext correlations, while profiling-based approaches suffer from error accumulation and near-zero success rates in single-trace scenarios. We propose a self-calibrating side-channel attack (SC-SCA) that enables high-accuracy HMAC-SM3 key recovery using only a single power trace during the attack phase. The method constructs a Bayesian network to integrate power trace statistics with prior knowledge of input dependencies, then performs joint probabilistic inference via belief propagation. Experimental results demonstrate 100% key recovery success under simulated noiseless conditions, 91.45% success on a real smart card system, and 73% effectiveness at a 10 dB signal-to-noise ratio. Crucially, this work exposes a previously overlooked attack surface in CPSS-based social networks: a single compromised HMAC-SM3 key can enable forged device control commands, large-scale privacy breaches, and cascading identity theft across linked social platforms. Our findings provide both a practical security benchmark for CPSS edge devices and theoretical foundations for designing side-channel-resistant cryptographic implementations.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1868616</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1868616</link>
        <title><![CDATA[Energy efficiency of a GPU-based computing system for high energy physics experiments]]></title>
        <pubdate>2026-08-17T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Jiahui Zhuo</author><author>Arantza Oyanguren</author><author>Álvaro Fernández Casani</author><author>Luca Fiorini</author><author>Valerii Kholoimov</author>
        <description><![CDATA[In this paper we introduce the energy efficiency as a new metric for evaluating both hardware platforms based on Graphic Processor Units (GPU), and algorithm optimisations at High Energy Physics (HEP) experiments. We develop a method to compute the energy efficiency for the case of the first high level trigger (HLT1) of the LHCb experiment, relating the throughput with GPU specifications such as the number of cores, clock frequency, memory bandwidth and thermal design power. The model can be extended to other HEP experiments to make decisions and reach sustainable computing ecosystems.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1857070</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1857070</link>
        <title><![CDATA[Interdisciplinarity as a centripetal force: physics-based methods for complex systems to artificial intelligence]]></title>
        <pubdate>2026-08-14T00:00:00Z</pubdate>
        <category>Perspective</category>
        <author>Giovanna Zimatore</author><author>Piercesare Grimaldi</author><author>Stavros Hatzopoulos</author><author>Piotr Henryk Skarzynski</author>
        <description><![CDATA[Analytical tools derived from nonlinear dynamics and dynamical systems theory, such as phase-space reconstruction and Recurrence Quantification Analysis (RQA), provide a powerful framework for investigating complex systems across different scientific domains. These methods allow the identification of dynamical structures, including recurrence, nonlinearity, and transitions between states, in time series data originating from diverse contexts. Scientific research is often shaped by two opposing forces that resemble the dynamics of physics: a centrifugal force, associated with increasing specialization, and a centripetal force, associated with interdisciplinarity. The rapid development of technologies and analytical methods has led to highly specialized languages and frameworks, which, while enabling scientific progress, can also generate fragmentation and communication barriers between disciplines. In contrast, interdisciplinarity emerges as a centripetal force that promotes the identification of shared analytical frameworks across domains. In this context, the transfer of methods is not merely a consequence of mathematical convenience but reflects the presence of common dynamical properties governed by similar physical principles. Artificial intelligence, integrated within physics-informed computational frameworks, provides a powerful tool for analyzing complex, high-dimensional, and heterogeneous datasets while preserving the dynamical structure of the underlying system. This convergence is not merely technical: the same nonlinear dynamical principles that govern physiological and cognitive systems appear to operate within artificial ones, suggesting that AI is not external to the phenomena this manuscript addresses but continuous with them. This inherent interdisciplinarity positions AI as a centripetal force, drawing together methods, languages, and findings from otherwise distant disciplines around a shared dynamical core.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1930892</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1930892</link>
        <title><![CDATA[Construction and fitting of an infectious disease propagation network based on age stratification and family hyperedges]]></title>
        <pubdate>2026-08-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Zhijia Liu</author><author>Xiujuan Ma</author><author>Fuxiang Ma</author><author>Jun Yin</author><author>Xin Yang</author>
        <description><![CDATA[BackgroundAge-dependent social activity and household contact patterns can substantially influence infectious disease transmission. This study aims to develop a network framework that jointly represents age stratification and household contact structures.MethodsThe population was divided into youth, middle-aged, and elderly groups, and family hyperedges were used to represent household membership and generate cross-age household contacts. An Age Family Hyperedge Multilayer Network (AFHMN) was constructed using differentiated intra-layer topologies. Eight simulation scenarios were examined under the SIR and SIRS frameworks, with BA and ER networks used as benchmarks. The models were further evaluated using four empirical infectious disease datasets and the RMSE, MAE, MAPE, R2, and DTW metrics.ResultsThe mixed topology, in which the youth and middle-aged layers use BA networks and the elderly layer uses an ER network, showed the closest agreement with the social characteristics of the three age groups. AFHMN achieved lower RMSE and MAE and higher R² values than the benchmark networks across the four empirical datasets and showed more stable overall agreement with infection peaks and temporal transmission patterns.ConclusionAFHMN provides a practical multilayer modeling framework for investigating how age-dependent social structures and household contacts jointly regulate infectious disease transmission.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1896756</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1896756</link>
        <title><![CDATA[High-performance void-core photonic crystal fiber biosensor for terahertz detection of illicit drugs]]></title>
        <pubdate>2026-08-13T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Kabeer Usman Abdulrazaq</author><author>Jacob Wekalao</author>
        <description><![CDATA[IntroductionThe terahertz (THz) band enables non-destructive molecular sensing of controlled substances including amphetamine, cocaine, and ketamine, which possess characteristic THz absorption fingerprints. Existing THz photonic crystal fiber (PCF) biosensors frequently achieve relative sensitivity below 80% with high confinement losses, limiting their practical utility.MethodsA seven-hexagon void-core photonic crystal fiber biosensor (VCPCFB) was designed in a Zeonex substrate (n = 1.53, α = 0.2 cm−1) with a 10 μm pitch and 700 μm core radius. Full-vector finite element method (FEM) simulations were performed in COMSOL Multiphysics over 1.0–3.0 THz with perfectly matched layer boundaries. Amphetamine (n = 1.518), cocaine (n = 1.5022), and ketamine (n = 1.562) were represented as frequency-independent homogeneous bulk analytes fully occupying the hollow core.ResultsAt 3 THz, relative sensitivity reaches 99.95% for ketamine, 99.84% for amphetamine, and 99.78% for cocaine. Power confinement exceeds 99% for all analytes. Effective material loss reduces to 5.98 × 10−4 cm−1 for ketamine. Confinement loss approaches 0 cm⁻¹ for ketamine at the operating point. Chromatic dispersion ranges between +0.097 and +0.149 ps/THz/cm at 3 THz, with group velocity dispersion below 0.05 ps²/cm. The nonlinear coefficient ranges from 1.87–1.91 × 10−3 W−1cm−1 and self-phase modulation length exceeds 5 × 105 cm at 1 mW. Differential group delay enables ketamine–cocaine separation over ~16.1 cm fiber lengths. Beat lengths exceed 2,353 cm, confirming negligible polarization evolution.DiscussionThe proposed seven-hexagon void-core architecture simultaneously achieves near-unity relative sensitivity, ultra-low propagation loss, flat dispersion, negligible nonlinear effects, and excellent fabrication tolerance. Pitch is identified as the most sensitive structural parameter. The design outperforms all previously reported THz PCF biosensors included in the benchmark comparison, with the proposed maximum sensitivity of 99.95% exceeding the nearest competitor by 7.75 percentage points.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1878327</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1878327</link>
        <title><![CDATA[From key distribution to direct transmission: a comprehensive review of quantum image security via QKD and QSDC]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Review</category>
        <author>S. Deepika</author><author>N. Jeyanthi</author>
        <description><![CDATA[In the rapidly evolving landscape of cybersecurity, traditional cryptographic systems are increasingly vulnerable to attacks, including brute-force, side-channel, man-in-the-middle, replay, and ransomware attacks, highlight the limitations of classical encryption techniques. Quantum cryptography leverages the no-cloning theorem and the properties of quantum states to establish fundamentally secure communication protocols with intrinsic eavesdropping detection capabilities. This security framework provides information-theoretic protection beyond the mathematical assumptions underlying conventional cryptographic systems. Quantum image security has evolved into two major paradigms: Quantum Key Distribution (QKD) and Quantum Secure Direct Communication (QSDC). Although recent surveys have reviewed both approaches chronologically, they have not systematically analysed their security thresholds The objective of this paper proposes a three-axis taxonomy of QSDC protocols, classifying them by quantum resource type, physical transmission channel, and device trust model. Furthermore, it presents a comparative performance analysis of QKD employing a hyperchaotic cipher over QSDC channels across seven quantum image representations, including FRQI, NEQR, GQIR, and MCQI. The analysis shows that QKD-seeded schemes achieve efficient key distribution, whereas pixel-level security remains dependent on cipher complexity. In contrast, QSDC provides end-to-end security governed by quantum mechanical principles; hyperentangled carriers achieve an eavesdropping detection probability of 0.875 compared with 0.5 for conventional two-step protocols, although communication throughput remains a limiting factor. Based on these findings, this review outlines future research directions, including QSDC-specific quantum repeaters for continental-scale deployment, hyperentangled carriers supporting up to 12 bits per photon pair compatible with NEQR’s 8-bit encoding, and machine-learning-assisted management of hybrid fiber–free-space quantum communication networks.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1849102</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1849102</link>
        <title><![CDATA[Effects of strategy-relationship coevolution on the emergence of cooperation in multilayer networks]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Mengmeng Liu</author>
        <description><![CDATA[Since social interactions are inherently embedded in multiple relational contexts, single-network models often fall short in explaining the evolution of cooperation. This study develop a two-layer coevolutionary model where behavioral strategies in the upper interaction layer are coupled with the lower signed emotional layer, representing friendly or hostile ties. The framework of this study allows behavioral strategies, emotional attitudes, and the network structure to coevolve dynamically. It found that the dynamics of the emotional layer influence the evolutionary outcomes. Counterintuitively, a relatively low cross-layer coupling strength proves more favorable for sustaining cooperation. It also showed that stochasticity is crucial for breaking the monostability of the defection-dominated state. It provides the necessary conditions for the system to enter another stable cooperative state or mixed strategy, effectively leading to the existence of system bistability. In the end, although the evolution of emotions changes the distribution of the final probability of cooperation, it is more like a regulator of cooperation frequency and cannot significantly improve the overall level of cooperation. This highlights how the constantly evolving relationship environment affects the trajectory of social cooperation.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1897232</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1897232</link>
        <title><![CDATA[Nonlinear responses of station-area functional vitality to the built environment in urban rail transit networks: an interpretable machine learning approach]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Weixin Zhu</author><author>Zhengyang Fang</author>
        <description><![CDATA[Functional vitality in urban rail transit station areas reflects the concentration of services and urban functions around stations. This study examines 170 operational stations on Lines 1–8 of the Ningbo rail transit network. Using point-of-interest (POI), bus stop, street network, station attribute, and rail network data within 800 m catchments, we constructed a station-area functional vitality index and investigated its built-environment determinants using XGBoost, SHapley Additive exPlanations (SHAP), and partial dependence plots (PDPs). XGBoost outperformed the comparison models, with an R2 value of 0.7213, a root mean square error (RMSE) of 0.0801, and a mean absolute error (MAE) of 0.0589. Distance to the city center, intersection density, and the number of bus stops were the dominant predictors, together accounting for 71.55% of total importance. One-dimensional PDPs revealed marked nonlinear responses: predicted vitality increased at approximately 105–113 intersections/km2 and around 16–17 bus stops but declined rapidly as distance from the city center increased within the first 4 km. Two-dimensional PDPs further suggested that central location conditions the effects of other built-environment factors, while strong street connectivity combined with sufficient bus stop provision corresponds to higher predicted vitality. These findings provide evidence for station-area functional planning and bus–rail integration.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1890771</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1890771</link>
        <title><![CDATA[Innovative applications of visualization technologies for scientists and the public in magnetic confinement fusion]]></title>
        <pubdate>2026-08-12T00:00:00Z</pubdate>
        <category>Technology and Code</category>
        <author>Yuxin Chen</author><author>Haoxi Zhong</author><author>Zixi Liu</author><author>J. P. Tang</author><author>Dakai Wang</author><author>Jianyuan Xiao</author><author>Yuanfan Yang</author><author>Yate Wu</author><author>Hong Yu</author><author>Xinke Ding</author><author>Yihan Wang</author><author>T. Y. Xia</author><author>H. Q. Liu</author><author>Kangning Yang</author><author>G. Zhuang</author><author>W. D. Liu</author><author>X. Gao</author><author>J. G. Li</author>
        <description><![CDATA[Magnetic confinement fusion research heavily relies on massive data generated by large-scale experimental facilities. Researchers need to process experimental data and interpret theoretical results using complex mathematical and physical tools; however, the intuitive presentation of internal physical processes within these devices remains challenging. To address these challenges, this study focuses on innovative visualization technologies for magnetic confinement fusion. Based on high spatiotemporal resolution physical simulation data from the Experimental Advanced Superconducting Tokamak tokamak device, we constructed a dynamic presentation of tokamak edge instability evolution processes with cinematic visual effects. Furthermore, we developed three-dimensional reconstruction algorithms for parallel computing results, effectively extracting structural characteristics of Weakly Coherent Modes (WCM) in I-mode and filamentary structures of Edge Localized Modes (ELM) in H-mode. Through key information-preserving mapping and dimensionality reduction, we achieved model visualization in Extended Reality (XR) head-mounted displays, enabling researchers to intuitively compare the differences between these two instability structures and gain deeper understanding of simulation results. Furthermore, taking the “Keda Torus eXperiment” (KTX) device as the research object, we established an intelligent conversion system from CAD models to lightweight 3D models, employing adaptive mesh simplification algorithms based on geometric feature recognition. Under the premise of ensuring key geometric feature precision, the model face count is compressed to 1% of the original scale; we further developed a cross-platform multimodal interaction system supporting Apple Vision Pro and Meta Quest 3 devices. Meanwhile, through 3D Gaussian Splatting technology, we constructed a laboratory-level digital twin system that high-fidelity reconstructs the “Keda Torus eXperiment” laboratory in virtual space, providing a high-precision virtual platform for remote experimental rehearsal.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1817906</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1817906</link>
        <title><![CDATA[Design and characterization of high-efficiency 2D-material-based MOS-HEMTs for next-generation sustainable electronics]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author> Neelu</author><author>Kaushik Mazumdar</author>
        <description><![CDATA[The noteworthy, astonishing, and remarkable electronic properties of graphene make it a reliable material for the fabrication of downscaled and high-frequency devices in the next and future generations. In this research work, the design approach of a graphene-based metal-oxide semiconductor high-electron-mobility transistor (MOS-HEMT) using the Silvaco ATLAS simulation tool is demonstrated, in which undoped graphene is used as the channel material, and graphene oxide (GO) functions as the oxide layer. It is investigated that at a particular threshold voltage VT = 1 V, the value of drain current (Id) is 1,280 mA, which demonstrates a twofold enhancement compared to GaN-based MOS-HEMTs. Several appealing characteristics, such as transconductance variation vs. change in gate-to-source voltage (Vgs), carrier mobility variation with different operating temperatures, and device transfer characteristics, are also explored. Accordingly, the obtained and accomplished technical evaluation and assessment of the outcomes validate that graphene could be most suitable for designing next-generation power electronics devices.]]></description>
      </item><item>
        <guid isPermaLink="true">https://www.frontiersin.org/articles/10.3389/fphy.2026.1886901</guid>
        <link>https://www.frontiersin.org/articles/10.3389/fphy.2026.1886901</link>
        <title><![CDATA[Quantification of the effects of Si3N4 gate thickness on the enhancement of a-Si:H thin film transistor performances]]></title>
        <pubdate>2026-08-11T00:00:00Z</pubdate>
        <category>Original Research</category>
        <author>Djemâa Ben Othmane</author><author>Houssem Eddine Doghmane</author><author>Elfahem Sakher</author><author>Nozha El Ahlem Doghmane</author><author>Cristian Vacacela Gomez</author><author>Abdellaziz Doghmane</author>
        <description><![CDATA[To improve the performance of hydrogenated amorphous silicon thin-film transistors (a-Si:H TFTs), which are used in flat-panel displays and related electronic devices, we investigated the effect of reducing the Si3N4 gate-insulator thickness (di) on selected transistor parameters (P). Two-dimensional numerical simulations were performed using Atlas-Silvaco. As di decreased from 300 to 15 nm, the a-Si:H TFTs showed sharper switching behavior, with the drain current increasing from an off-state current (Ioff) of 1.4 × 10−12 A to an on-state current (Ion) of approximately 1.8 × 10−5 A at low operating voltages. For di = 15 nm, the extracted parameters were a threshold voltage (Vth) of 3.06 V, field-effect mobility (μFE) of approximately 0.037 cm2 V−1 s-1, subthreshold swing (SS) of 0.10 V dec−1, gate capacitance per unit area (Ci) of 44.25 × 10−8 F cm-2, and maximum electric field (Emax) of 1.65 × 105 V cm-1. As di decreased, Ci, Ion, Ion/Ioff, and Emax increased, whereas Vth, μFE, Ioff, and SS decreased. These trends were quantified by curve fitting to obtain empirical P = f (di) relations for each parameter. The fitted relations provide a practical basis for estimating the Si3N4 gate-insulator thickness required to target specific electrical parameters in a-Si:H TFT design.]]></description>
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