Published: 2026-02-25 18:15:31
Authors: John M. Mehlhaff, Alexander Y. Chen, Martin Luepker, Yajie Yuan
Categories: astro-ph.HE
Abstract:
In low-luminosity active galactic nuclei like M87* and Sgr A*, the accretion disk around the central supermassive black hole is tenuous and collisionless. As a result, the usual ideal magnetohydrodynamics (MHD) approximation may not be applicable. In this Letter, we report on the first fully kinetic simulations of the accretion process where the plasma initially has finite angular momentum. The simulated accretion flow behaves remarkably similarly to the magnetically arrested disk (MAD) regime of ideal MHD, reproducing episodes of magnetic flux saturation and eruption typical of MADs. The resemblance to fluid models owes largely to kinetic instabilities, which regulate pressure anisotropy in the disk, allowing fluid terms to dominate the angular momentum transfer. In addition, by handling vacuum regions effectively, our kinetic approach probes the matter supply to the jet funnel. We observe no efficient penetration of the accreting material into this region, which suggests that a pair discharge may be required to sustain the Blandford-Znajek process.
Published: 2026-02-25 17:04:50
Authors: Raquel Garcia Belles, Alexander Anferov, Lukas F. Deeg, Loris Colicchio, Arianne Brooks, Tom Schatteburg, Maxwell Drimmer, Ines C. Rodrigues, Rodrigo Benevides, Marco Liffredo, Jyotish Patidar, Oleksandr Pshyk, Matteo Fadel, Luis Guillermo Villanueva, Sebastian Siol, Gerhard Kirchmair, Yiwen Chu
Categories: quant-ph, cond-mat.mes-hall, cond-mat.mtrl-sci
Abstract:
Circuit quantum acoustodynamics (cQAD) devices have a wide range of applications in quantum science, all of which depend crucially on the quantum coherence of the mechanical subsystem. In this context, high-overtone bulk acoustic-wave resonators (HBARs) are particularly promising, since they have shown very high quality factors with negligible dephasing. However, the introduction of piezoelectric films, which are necessary for coupling to a superconducting circuit, can lead to additional loss channels, such as surface scattering and two-level systems (TLS). Here, we study the acoustic dissipation of HBAR resonators in cQAD systems and find that the defect density of the piezoelectric material and its interface with the bulk are limiting factors for the coherence. We measure acoustic modes with phonon lifetimes up to 400 $μ$s and lifetime-limited coherence times approaching one millisecond in the quantum regime. When coupled to a superconducting qubit, this leads to a hybrid system with a large quantum coherence cooperativity of $C_{T_2}=1.1\times10^5$. These results represent a new milestone for the performance of cQAD devices and offer concrete paths forward for further improvements.
Published: 2026-02-25 16:36:52
Authors: Robert Brignall, Michal Opler, Vincent Vatter
Categories: math.CO
Abstract:
A hereditary class of graphs has bounded clique-width if and only if its prime members do, but this lifting property fails for linear clique-width. We prove that a hereditary class has bounded linear clique-width if and only if its prime members do and it contains neither all quasi-threshold graphs nor all complements of quasi-threshold graphs. This generalizes a result of Brignall, Korpelainen, and Vatter, who established the result for cographs.
Published: 2026-02-25 16:05:49
Authors: Mathieu Ladouce, Pablo Marin-Palomo, Martin Virte
Categories: physics.optics
Abstract:
We investigate discrete wavelength switching in single-gain-section multi-wavelength lasers monolithically integrated on InP with phase-controlled optical-feedback. By modulating the feedback phase, nanosecond-scale wavelength switching is experimentally demonstrated with transition times below 2.5 ns. Measurements consistently show that the switching time decreases with stronger optical feedback and larger phase-modulation amplitudes. Transitions from lower to higher modal gain are faster. We support the experimental observations with a multi-mode extension of the Lang-Kobayashi rate-equation model. We analyze the influence of laser, feedback-cavity, and modulation parameters on the switching dynamics, and highlight the role of mode coupling. These results highlight the potential of integrated multi-wavelength lasers for compact and high-speed all-optical networking systems.
Published: 2026-02-25 15:55:55
Authors: Ansgar Denner, Daniele Lombardi, Mathieu Pellen, Giovanni Pelliccioli
Categories: hep-ph
Abstract:
We present full off-shell NLO corrections in QCD obtained with the MoCaNLO code matched to parton shower. A resonance-aware matching procedure has been devised for the MC@NLO method tuned to the Catani-Seymour dipole subtraction. Specifically, we consider the off-shell production of a top-antitop pair in the semi-leptonic decay channel in electron-positron collisions and match it to the final-state QCD parton shower of PYTHIA8. Distortions of resonances' line shapes are avoided by providing the details of the resonance-cascade chain on an event-by-event basis to the parton shower and by adapting the matching accordingly through the introduction of dedicated counterterms.
Published: 2026-02-25 15:47:34
Authors: Cheng-Yeh Yang, Chien-Chun Wang, Li-Wei Chen, Hung-Shin Lee, Hsin-Min Wang, Berlin Chen
Categories: eess.AS, cs.AI, cs.CL, cs.SD
Abstract:
Low-resource automatic speech recognition (ASR) continues to pose significant challenges, primarily due to the limited availability of transcribed data for numerous languages. While a wealth of spoken content is accessible in television dramas and online videos, Taiwanese Hokkien exemplifies this issue, with transcriptions often being scarce and the majority of available subtitles provided only in Mandarin. To address this deficiency, we introduce TG-ASR for Taiwanese Hokkien drama speech recognition, a translation-guided ASR framework that utilizes multilingual translation embeddings to enhance recognition performance in low-resource environments. The framework is centered around the parallel gated cross-attention (PGCA) mechanism, which adaptively integrates embeddings from various auxiliary languages into the ASR decoder. This mechanism facilitates robust cross-linguistic semantic guidance while ensuring stable optimization and minimizing interference between languages. To support ongoing research initiatives, we present YT-THDC, a 30-hour corpus of Taiwanese Hokkien drama speech with aligned Mandarin subtitles and manually verified Taiwanese Hokkien transcriptions. Comprehensive experiments and analyses identify the auxiliary languages that most effectively enhance ASR performance, achieving a 14.77% relative reduction in character error rate and demonstrating the efficacy of translation-guided learning for underrepresented languages in practical applications.
Published: 2026-02-25 15:37:24
Authors: Pepijn Demol, Urban Vernik, Thomas Duguet, Alexander Tichai
Categories: nucl-th, nucl-ex
Abstract:
Charge radii are investigated along the Tin isotopic chain via ab initio Bogoliubov coupled cluster calculations at the singles and doubles level. In addition to the reproduction of absolute radii, the parabolic behavior of isotopic shifts between the N = 50 and N = 82 magic numbers and the kink through ${}^{132}$Sn are shown to provide stringent tests for state-of-the-art chiral effective field theory ($χ$EFT) inter-nucleon interactions. Indeed, none of the employed fine-tuned interactions can capture all such key characteristics. Eventually, the pronounced sensitivity of the results to the employed Hamiltonian beyond ${}^{132}$Sn provides a unique playground to pin down critical attributes of $χ$EFT inter-nucleon interactions in the future. This calls for measuring isotopic shifts both towards ${}^{100}$Sn and beyond ${}^{134}$Sn, as well as for performing high-accuracy ab initio calculations of mean-square radii in heavy open-shell nuclei by adding both triples corrections to the many-body wave function and the two-body charge density correction to the operator
Published: 2026-02-25 15:16:36
Authors: Lisa Kühn, Jacopo Bonari, Max von Danwitz, Alexander Popp
Categories: cs.CE
Abstract:
Numerical simulations of contaminant dispersion, as after a gas leakage incident on a chemical plant, can provide valuable insights for both emergency response and preparedness. Simulation approaches combine incompressible Navier-Stokes (INS) equations with advection-diffusion (AD) processes to model wind and concentration field. However, the computational cost of such high-fidelity simulations increases rapidly for complex geometries like urban environments, making them unfeasible in time-critical or multi-query "what-if" scenarios. Therefore, this study focuses on the application of model order reduction (MOR) techniques enabling fast yet accurate predictions. To this end, a thorough comparison of intrusive and non-intrusive MOR methods is performed for the computationally more demanding parametric INS problem with varying wind velocities. Based on these insights, a non-intrusive reduced-order model (ROM) is constructed accounting for both wind velocity and direction. The study is conducted on a two-dimensional domain derived from real-world building footprints, preserving key features for analyzing the dispersion of, for instance, denser contaminants. The resulting ROM enables faster than real-time predictions of spatio-temporal contaminant dispersion from an instantaneous source under varying wind conditions. This capability allows assessing wind measurement uncertainties through a Monte Carlo analysis. To demonstrate the practical applicability, an interactive dashboard provides intuitive access to simulation results.
Published: 2026-02-25 14:52:45
Authors: Nabaneet Das, Thorsten Dickhaus
Categories: stat.ME
Abstract:
The proportion of edges in a Gaussian graphical model (GGM) characterizes the complexity of its conditional dependence structure. Since edge presence corresponds to a nonzero entry of the precision matrix, estimation of this proportion can be formulated as a large-scale multiple testing problem. We propose an estimator that combines p-values from simultaneous edge-wise tests, conducted under false discovery rate control, with Storey's estimator of the proportion of true null hypotheses. We establish weak dependence conditions on the precision matrix under which the empirical cumulative distribution function of the p-values converges to its population counterpart. These conditions cover high-dimensional regimes, including those arising in genetic association studies. Under such dependence, we characterize the asymptotic bias of the Schweder--Spjøtvoll estimator, showing that it is upward biased and thus slightly underestimates the true edge proportion. Simulation studies across a variety of models confirm accurate recovery of graph complexity.
Published: 2026-02-25 12:59:31
Authors: Dimitrios Apostolakis, Georgios Angelidis, Vasileios Argyriou, Panagiotis Sarigiannidis, Georgios Th. Papadopoulos
Categories: cs.HC
Abstract:
A user-centered AR interface for disaster response is presented in this work that uses 3D Gaussian Splatting (3DGS) to visualize detailed scene reconstructions, while maintaining situational awareness and keeping cognitive load low. The interface relies on a lightweight interaction approach, combining World-in-Miniature (WIM) navigation with semantic Points of Interest (POIs) that can be filtered as needed, and it is supported by an architecture designed to stream updates as reconstructions evolve. User feedback from a preliminary evaluation indicates that this design is easy to use and supports real-time coordination, with participants highlighting the value of interaction and POIs for fast decision-making in context. Thorough user-centric performance evaluation demonstrates strong usability of the developed interface and high acceptance ratios.
Published: 2026-02-25 12:38:06
Authors: Giorgio Navone, Katerina Santicola, Harry C. Shaw, Haowen Zhang
Categories: math.NT, math.AG
Abstract:
We construct an infinite family of quartic del Pezzo surfaces over $\mathbb{F}_p(t)$ with no quadratic points, for all primes $p\neq 2$. This answers a question of Colliot--Thélène, Creutz and Viray in the negative, which asks whether every quartic del Pezzo surface has quadratic points over $C_2$ fields. We exhibit a Brauer--Manin obstruction on the variety parametrising lines associated to the quartic del Pezzo surface.
Published: 2026-02-25 12:20:12
Authors: Alejandra Alcantarilla Sánchez, Jolijn Cottaar, Tanja Lange, Benne de Weger
Categories: math.NT
Abstract:
In this paper we show that a certain subset of the Carmichael numbers contains good Euler pseudoprimes, composite numbers that for many bases survive the Solovay-Strassen primality test. We present a classification of Carmichael numbers, and use the knowledge gained from this to create a fast algorithm to compute new Euler pseudoprimes, by multiplying already found Euler pseudoprimes. We use this algorithm to find many Euler pseudoprimes that are pseudoprimes for several consecutive prime bases starting at 2, hence for all integer bases up to that number. The best Euler pseudoprime we find survives up to 211, i.e., survives the first 47 prime bases.
Published: 2026-02-25 11:48:58
Authors: Alessandro Ignesti, Francesca Loi, Antonino Marasco, Benedetta Vulcani, Bianca M. Poggianti, Christoph Pfrommer, Marco Gullieuszik, Alessia Moretti, Paolo Serra, Stephanie Tonnesen, Rory Smith, Cecilia Bacchini, Marc A. W. Verheijen, Myriam Gitti, Anna Wolter, Koshy George, Yara Jaffe, Rosita Paladino, Giorgia Peluso, Mario Radovich, Augusto E. Lassen, Neven Tomicic, Peter Kamphuis
Categories: astro-ph.GA, astro-ph.CO
Abstract:
All gas-rich galaxies in cluster environments are expected to experience ram-pressure stripping from the intra-cluster medium. However, only a fraction of these develop ongoing star-formation in their stripped tail, becoming the so-called ``jellyfish'' galaxies. In this work we provide observational evidence that magnetic fields can signal differences in the extraplanar star formation and explore what are the physical conditions that lead to the formation of a jellyfish galaxy. We first focus on JO147, a jellyfish galaxy that features weak star formation activity in its tail. Using MeerKAT radio continuum observations, we discover polarized emission only in a small fraction of its tail, with an average fraction of $~10\%$, and a low Mach number $\mathcal{M}=1.3-1.6$, which suggests a possible association between magnetic field draping, shock-compression of the gas, and extraplanar star formation activity. Then, we test this scenario in a sample of 17 jellyfish galaxies from the GASP project. We combine dynamical models for their orbits within the host clusters with realistic cluster temperature profiles to infer their Mach number, and we find a positive correlation between it and the star formation activity in their tail. We conclude that supersonic motion is a necessary condition for triggering star formation in the stripped tails of jellyfish galaxies. Our findings provide empirical evidence that the critical factor preventing the stripped gas evaporation is the shock compression induced by the supersonic motion through the cluster. This process likely enhances the magnetic field surrounding the galaxy and the properties of the stripped material.
Published: 2026-02-25 09:16:28
Authors: Håkon Næss Sandum, Hans Ole Ørka, Oliver Tomic, Terje Gobakken
Categories: cs.CV
Abstract:
Accurate forest stand delineation is essential for forest inventory and management but remains a largely manual and subjective process. A recent study has shown that deep learning can produce stand delineations comparable to expert interpreters when combining aerial imagery and airborne laser scanning (ALS) data. However, temporal misalignment between data sources limits operational scalability. Canopy height models (CHMs) derived from digital photogrammetry (DAP) offer better temporal alignment but may smoothen canopy surface and canopy gaps, raising the question of whether they can reliably replace ALS-derived CHMs. Similarly, the inclusion of a digital terrain model (DTM) has been suggested to improve delineation performance, but has remained untested in published literature. Using expert-delineated forest stands as reference data, we assessed a U-Net-based semantic segmentation framework with municipality-level cross-validation across six municipalities in southeastern Norway. We compared multispectral aerial imagery combined with (i) an ALS-derived CHM, (ii) a DAP-derived CHM, and (iii) a DAP-derived CHM in combination with a DTM. Results showed comparable performance across all data combinations, reaching overall accuracy values between 0.90-0.91. Agreement between model predictions was substantially larger than agreement with the reference data, highlighting both model consistency and the inherent subjectivity of stand delineation. The similar performance of DAP-CHMs, despite the reduced structural detail, and the lack of improvements of the DTM indicate that the framework is resilient to variations in input data. These findings indicate that large datasets for deep learning-based stand delineations can be assembled using projects including temporally aligned ALS data and DAP point clouds.
Published: 2026-02-25 08:50:37
Authors: K. Pomorski, A. Augustyn, T. Cap, Y. J. Chen, M. Kowal, B. Nerlo-Pomorska, M. Warda, Z. G. Xiao
Categories: nucl-th
Abstract:
Isotope-resolved post-neutron fission yields in the Ba and Xe chains are calculated and benchmarked against evaluated reference data, with emphasis on element-resolved isotopic chains $Y(N_f)$ at fixed fragment charge $Z$ and on the consistency of heavy--light fragment correlations. Calculations are performed within a four-dimensional (4D) Langevin framework employing Fourier-over-Spheroid shape parametrization. The benchmark covers spontaneous fission of selected Cm and Cf isotopes (including $^{244,246}$Cm and $^{250}$Cf) as well as neutron-induced fission at thermal and 14-MeV energies for representative actinides in the Th--Pu region (including $^{229}$Th, $^{235}$U, $^{239}$Pu, and $^{249}$Cf). The dominant neutron-number maxima are reproduced for a large fraction of the isotopic chains considered, indicating that the mean charge partition and the average neutron content of the main fission channels are described consistently. A systematic residual discrepancy is observed in the isotopic widths: the calculated yields often fall off too rapidly on the distribution tails, producing distributions that are narrower than the evaluated data, most notably for heavy-fragment chains.
Published: 2026-02-25 05:04:43
Authors: Naomi Ota, Angie Veronica, Jakob Dietl, Anri Yanagawa, Thomas H. Reiprich, Veronica Biffi, Klaus Dolag, Marcus Brüggen, Esra Bulbul, Florian Pacaud, Yoshiki Toba
Categories: astro-ph.CO, astro-ph.GA
Abstract:
We investigate the gas motions in the core region of the Abell~3395 South subcluster (A3395S) using high-resolution X-ray spectroscopy with XRISM/Resolve. By analyzing the Fe~XXV He$α$ emission line, we directly measure the line-of-sight bulk and turbulent velocities of the intracluster medium. We find that the one-dimensional turbulent velocity is low, at the level of $124\pm21~{\rm km\,s^{-1}}$, while a significant line-of-sight bulk velocity of $263\pm23~{\rm km\,s^{-1}}$ is detected. The coexistence of low turbulence and finite bulk motion suggests that A3395S has not yet reached a dynamically relaxed state. These results are consistent with the non-detection of a radio halo in A3395S, implying that turbulent particle reacceleration is currently inefficient in the cluster core. This study demonstrates that high-resolution X-ray spectroscopy with XRISM provides a powerful means to directly constrain intracluster medium dynamics in merging galaxy clusters, and it provides a reference for future comparative studies of A3395N and A3391 within the same large-scale structure.
Published: 2026-02-24 22:49:36
Authors: Nick Williams, Alessandro De Rosis, Alex Skillen
Categories: physics.plasm-ph, physics.flu-dyn
Abstract:
Magnetic reconnection and turbulence are deeply intertwined in magnetohydrodynamic flows, yet how reconnection self-generates turbulence remains unclear. Using an ensemble of high-resolution three-dimensional direct numerical simulations of an unstable magnetised jet with an initially weak mean field, we demonstrate a self-sustained transition from laminar reconnection to fully developed turbulence in the absence of external forcing. We show that a three-dimensional current-sheet instability triggers stochastic reconnection, leading to persistent turbulent energy injection. Energy-budget analysis reveals that the coupling between the turbulent electromotive force and the magnetic mean shear dominates turbulent production, with magnetic fluctuations subsequently transferring energy to the kinetic field through a nonlinear cascade.
Published: 2026-02-24 19:00:05
Authors: Tetyana Pitik, David Radice, Daniel Kasen, Fabio Magistrelli, Patrick Chi-Kit Cheong, Sebastiano Bernuzzi
Categories: astro-ph.HE, nucl-th
Abstract:
We present the first end-to-end calculation connecting the accretion-induced collapse (AIC) of a magnetized, rapidly rotating white dwarf to observable kilonova signatures, combining 2D general-relativistic neutrino-magnetohydrodynamic simulations, followed by radiation hydrodynamics with in-situ nuclear network and 2D Monte Carlo radiative transfer with spatially resolved heating rates. Unlike all previous unmagnetized AIC models - which predicted proton-rich, $^{56}$Ni-dominated ejecta - strong magnetic fields eject ${\sim 0.2 M_\odot}$ of neutron-rich material $(\langle Y_e \rangle \sim 0.24)$ on dynamical timescales, before neutrino irradiation can raise the electron fraction, enabling strong $r$-process nucleosynthesis up to and beyond the third peak. The resulting kilonova is lanthanide-rich $(X_{\rm lan} \approx 6\%)$ and dominated by near-infrared emission. We compute synthetic light curves in the LSST and JWST bands and find striking agreement, without parameter tuning, between the observations of AT 2023vfi/GRB 230307A and our broadband light curves for polar viewing angles. These results establish magnetized AIC as a viable channel for heavy $r$-process element production and a compelling progenitor candidate for long-duration gamma-ray bursts with kilonova signatures.
Published: 2026-02-24 16:46:01
Authors: El Mehdi Cherradi
Categories: math.CT, math.AT
Abstract:
We introduce a general notion of $J$-tribe, and construct the $J$-tribe of $J$-frames in a given tribe $\mathcal{T}$, where $J$ a suitable generalized direct category. This construction applies to semi-cubical diagrams for a category of semi-cubes with symmetries and reversals.
Published: 2026-02-24 16:44:24
Authors: Pedro M. Prado, Lucas A. M. Rattighieri, Rafael Simões do Carmo, Giovanni S. Franco, Guilherme E. L. Pexe, Alexandre Drinko, Erick G. Dorlass, Tatiana F. de Almeida, Felipe F. Fanchini
Categories: quant-ph
Abstract:
Reconstructing DNA sequences without a reference, known as de novo assembly, is a complex computational task involving the alignment of overlapping fragments. To address this problem, a usual strategy is to map the assembly to a Quadratic Unconstrained Binary Optimization (QUBO) formulation, which can be solved by different quantum algorithms. In this work, we focus on three versions of the Feedback-based Algorithm, a protocol that eliminates classical optimization loops via measurement feedback. We analyze long-read DNA fragments from SARS-CoV-2 and human mitochondrial DNA using standard FALQON, second-order FALQON (SO-FALQON), and time-rescaled FALQON (TR-FALQON). Numerical results show that both variants improve convergence to the ground state and increase success probabilities at reduced circuit depths. These findings indicate that enhanced feedback-driven dynamics are effective for solving combinatorial problems on near-term quantum hardware.
Published: 2026-02-24 16:39:14
Authors: Wayne M. Witzel, Anand Ganti, Tzvetan S. Metodi
Categories: quant-ph
Abstract:
The performance of a given quantum error correction (QEC) code depends upon the noise model that is assumed. Independent Pauli noise, applied after each quantum operation, is a simplistic noise model that is easy to simulate and understand in the context of stabilizer codes. Although such a noise model is artificial, it is equivalent to independent, random, unbiased qubit rotations. What about spatially or temporally correlated qubit rotations? Such a noise model is applicable to global operations (e.g., NMR or ESR), common control sources (e.g., lasers), or slow drift (e.g., charge or magnetic noise) in various qubit technologies. In the worst case, such errors can combine constructively and result in a post-correction failure rate that increases with the number of error correction cycles. However, we show that this worst case does not generally arise unless taking active corrective actions while performing QEC. That is, by employing virtual Pauli frame updates ("passive" error correction) rather than physical corrections ("active" error correction), coherent errors do not compound appreciably. Starting in a random Pauli frame is also advantageous. In fact, through perturbation theory arguments and supporting numerical simulations, we show that the logical qubit performance beyond distance 3 for correlated single-qubit Hamiltonian noise models (i.e., global errant qubit rotations), when employing these "lazy" strategies, essentially matches the performance of Pauli noise model with the same process fidelity (fidelity after one application). In a more general circuit model of noise, correlations may add constructively within syndrome extraction rounds but Pauli frame randomization from passive error correction mitigates this effect across multiple rounds.
Published: 2026-02-24 16:37:20
Authors: Maria Andrade
Categories: math.DG
Abstract:
In this work, we study compact Riemannian manifolds with boundary satisfying V-static-type equations. By combining a generalized Reilly formula with Steklov-type boundary value problems, we derive integral inequalities for geometric quantities associated with the boundary. These inequalities lead to rigidity results, including characterizations of geodesic balls in space forms. In particular, our results offer new insights into several known rigidity theorems in the literature.
Published: 2026-02-24 16:24:49
Authors: Yiqin He
Categories: math.NT
Abstract:
Let $p$ be a prime number, $n$ an integer $\geq 2$, and $L$ a finite extension of $\mathrm{Q}_p$. Let $ρ_L$ be an $n$-dimensional (non-critical but not necessary generic) potentially crystalline $p$-adic Galois representation of the absolute Galois groups of $L$ of regular Hodge-Tate weights. By generalizing the previous results and strategy for the crystabelline case of Ding and the recent work of Breuil-Ding, we construct an explicit locally analytic representation $π_{1}(ρ_L)$, and describe explicitly the information of Hodge filtration of $ρ_L$ it determines. When $ρ_L$ comes from a patched $p$-adic automorphic representation, we show that $π_{1}(ρ_L)$ is a subrepresentation of the $\mathrm{GL}_n(L)$-representation globally associated to $ρ_L$, under some mild hypothesis.
Published: 2026-02-24 16:16:44
Authors: Anna Martin-Boyle, William Humphreys, Martha Brown, Cara Leckey, Harmanpreet Kaur
Categories: cs.HC, cs.CL
Abstract:
Large Language Models (LLMs) are transforming scholarly tasks like search and summarization, but their reliability remains uncertain. Current evaluation metrics for testing LLM reliability are primarily automated approaches that prioritize efficiency and scalability, but lack contextual nuance and fail to reflect how scientific domain experts assess LLM outputs in practice. We developed and validated a schema for evaluating LLM errors in scholarly question-answering systems that reflects the assessment strategies of practicing scientists. In collaboration with domain experts, we identified 20 error patterns across seven categories through thematic analysis of 68 question-answer pairs. We validated this schema through contextual inquiries with 10 additional scientists, which showed not only which errors experts naturally identify but also how structured evaluation schemas can help them detect previously overlooked issues. Domain experts use systematic assessment strategies, including technical precision testing, value-based evaluation, and meta-evaluation of their own practices. We discuss implications for supporting expert evaluation of LLM outputs, including opportunities for personalized, schema-driven tools that adapt to individual evaluation patterns and expertise levels.
Published: 2026-02-24 16:14:42
Authors: Oliver Schnetz
Categories: hep-th, hep-ph
Abstract:
We prove that massless scalar three-point amplitudes are self-dual under Fourier transformation. This implies that the momentum space amplitude can be expressed as the position space amplitude of the same graph with transformed edge-weights (not the dual graph) if external vertices are labeled accordingly. In particular, a massless scalar three-point integral can be expressed as a graphical function. The result follows immediately from a theorem by M. Golz, E. Panzer and the author on parametric representations of position space integrals (2015), but it was only observed by X. Jiang in 2025 in the context of four-dimensional Super-Yang-Mills theory. We generalize Jiang's result and discuss the consequences of the self-duality in the context of graphical functions. In particular, we derive a new identity for graphical functions and a new twist relation for scalar integrals (Feynman periods) in $φ^4$ theory.
Published: 2026-02-24 16:04:26
Authors: Yanrui Wu, Lingling Zhang, Xinyu Zhang, Jiayu Chang, Pengyu Li, Xu Jiang, Jingtao Hu, Jun Liu
Categories: cs.AI
Abstract:
Evaluations of large language models (LLMs) primarily emphasize convergent logical reasoning, where success is defined by producing a single correct proof. However, many real-world reasoning problems admit multiple valid derivations, requiring models to explore diverse logical paths rather than committing to one route. To address this limitation, we introduce LogicGraph, the first benchmark aimed to systematically evaluate multi-path logical reasoning, constructed via a neuro-symbolic framework that leverages backward logic generation and semantic instantiation. This pipeline yields solver-verified reasoning problems formalized by high-depth multi-path reasoning and inherent logical distractions, where each instance is associated with an exhaustive set of minimal proofs. We further propose a reference-free evaluation framework to rigorously assess model performance in both convergent and divergent regimes. Experiments on state-of-the-art language models reveal a common limitation: models tend to commit early to a single route and fail to explore alternatives, and the coverage gap grows substantially with reasoning depth. LogicGraph exposes this divergence gap and provides actionable insights to motivate future improvements. Our code and data will be released at https://github.com/kkkkarry/LogicGraph.
Published: 2026-02-24 16:00:15
Authors: Rafael Hanashiro, Abhishek Shetty, Patrick Jaillet
Categories: stat.ML, cs.LG
Abstract:
Towards understanding the statistical complexity of learning from heterogeneous sources, we study the problem of multi-distribution learning. Given $k$ data sources, the goal is to output a classifier for each source by exploiting shared structure to reduce sample complexity. We focus on the bounded label noise setting to determine whether the fast $1/ε$ rates achievable in single-task learning extend to this regime with minimal dependence on $k$. Surprisingly, we show that this is not the case. We demonstrate that learning across $k$ distributions inherently incurs slow rates scaling with $k/ε^2$, even under constant noise levels, unless each distribution is learned separately. A key technical contribution is a structured hypothesis-testing framework that captures the statistical cost of certifying near-optimality under bounded noise-a cost we show is unavoidable in the multi-distribution setting.
Finally, we prove that when competing with the stronger benchmark of each distribution's optimal Bayes error, the sample complexity incurs a \textit{multiplicative} penalty in $k$. This establishes a \textit{statistical} separation between random classification noise and Massart noise, highlighting a fundamental barrier unique to learning from multiple sources.
Published: 2026-02-24 15:55:39
Authors: Jakub Železný
Categories: cond-mat.mtrl-sci
Abstract:
Condensed matter compounds typically form crystals, which break the rotational and translational invariance of space but remain invariant under a discrete set of symmetry operations. Understanding the effects allowed by this symmetry breaking, as well as the constraints imposed by the crystal structure, is a crucial problem in condensed matter physics. Here, we present a Python package for determining the symmetry-restricted forms of tensors describing physical properties of crystals, focusing particularly on magnetic materials. The primary focus is on response tensors; however, the program can also describe equilibrium properties and other physical properties, such as magnetic interactions. The program can describe the symmetry using the conventional magnetic space groups, as well as using the spin groups that describe the non-relativistic limit. Additional functionality includes the treatment of quantities projected onto a particular site and expansions in the magnetic order parameter. The code can be used either from the command line or via a Python API.
Published: 2026-02-24 15:52:54
Authors: Hayk Gevorgyan, Konstantinos Kalogeropoulos, Angelos Alexopoulos
Categories: stat.ME, stat.ML
Abstract:
We study the use of exchangeable multi-task Gaussian processes (GPs) for causal inference in panel data, applying the framework to two settings: one with a single treated unit subject to a once-and-for-all treatment and another with multiple treated units and staggered treatment adoption. Our approach models the joint evolution of outcomes for treated and control units through a GP prior that ensures exchangeability across units while allowing for flexible nonlinear trends over time. The resulting posterior predictive distribution for the untreated potential outcomes of the treated unit provides a counterfactual path, from which we derive pointwise and cumulative treatment effects, along with credible intervals to quantify uncertainty. We implement several variations of the exchangeable GP model using different kernel functions. To assess prediction accuracy, we conduct a placebo-style validation within the pre-intervention window by selecting a ``fake'' intervention date. Ultimately, this study illustrates how exchangeable GPs serve as a flexible tool for policy evaluation in panel data settings and proposes a novel approach to staggered-adoption designs with a large number of treated and control units.
Published: 2026-02-24 15:50:44
Authors: Saeed Razavikia, Deniz Gündüz, Carlo Fischione
Categories: eess.SP, cs.IT
Abstract:
Over-the-air computation (OAC) enables low-latency aggregation over multiple-access channels (MACs) by exploiting the superposition property of the wireless medium to compute functions efficiently in distributed networks. A critical but often overlooked challenge is that electromagnetic interference in practical radio channels frequently exhibits heavy-tailed behavior, causing strong impulsive noise that severely degrades computation performance. This work studies digital OAC with QAM-based signaling under heavy-tailed interference modeled by a Cauchy distribution (lacking a finite second moment). We seek QAM-like constellations that minimize the mean-squared error (MSE) of sum aggregation subject to an average-power constraint. The problem is formulated as a constrained optimization, whose solution yields unique optimality conditions. Numerical results confirm the effectiveness of the proposed design. Notably, the framework extends naturally to nomographic functions, broader constellation families, and alternative noise models.
Published: 2026-02-24 15:48:39
Authors: David Heddle
Categories: cs.SE, physics.comp-ph
Abstract:
This paper presents the design and implementation of a modular multi-document interface (MDI) framework for scientific visualization and simulation in the Java Virtual Machine (JVM) ecosystem. The framework emphasizes architectural separation between visualization layers, simulation engines, and optional hardware-accelerated 3D rendering. 3D functionality is isolated into a separate module to prevent unnecessary dependency coupling in 2D-only applications. We describe the core abstractions, threading model, simulation integration strategy, and dependency isolation approach. A case study involving a real-time 3D gas expansion simulation integrated with synchronized 2D entropy plotting demonstrates architectural cohesion. The framework is publicly available via Maven Central and targets long-lived scientific and engineering desktop applications.
Published: 2026-02-24 15:46:43
Authors: Olivier Benoist, James Hotchkiss
Categories: math.AG, math.CV
Abstract:
We investigate the Brauer group of the ring $\mathcal{O}(S)$ of holomorphic functions on a finite-dimensional Stein space S. We provide a purely topological computation of this group and deduce a comparison theorem between the étale cohomology of $\textrm{Spec}(\mathcal{O}(S))$ and the singular cohomology of S in degree 2. Furthermore, we prove a purity theorem when S is nonsingular and study the index of classes in the Brauer group of $\mathcal{O}(S)$.
Published: 2026-02-24 15:43:51
Authors: Francisco Arrepol, Mauricio Soto-Gomez, Christopher Thraves Caro
Categories: math.CO
Abstract:
Robinson spaces are structures equipped with a total order that encodes comparative dissimilarity relationships.
We study the problem of representing Robinson dissimilarity spaces into low-dimensional metric spaces. These representations aim to preserve the relative dissimilarity relationships between elements rather than their exact values. While low dimensional Euclidean spaces such as $\mathbb{R}^1$ and $\mathbb{R}^2$ are natural candidates for such embeddings, previous work has shown that not all Robinson spaces admit a valid embedding in the real line that respects their structural constraints. Motivated by this limitation, we explore the broader class of real trees, which retain low-dimensional interpretability while allowing greater flexibility.
To address the embedding problem, we develop two key tools: a combinatorial representation of Robinson spaces and a topological characterization of caterpillars, a restricted class of real trees. These tools enable a formulation of the embedding problem as a linear program, providing both computational and theoretical insights. We prove that some subclasses of Robinson spaces always admit embeddings in a caterpillar, and we establish the existence of Robinson spaces that cannot be embedded in any real tree. These results clarify the geometric limitations of representing ordered dissimilarity structures and open new directions for studying the interaction between dissimilarity, order, and metric geometry.
Published: 2026-02-24 15:30:29
Authors: Yoshua Bengio, Stephen Clare, Carina Prunkl, Maksym Andriushchenko, Ben Bucknall, Malcolm Murray, Rishi Bommasani, Stephen Casper, Tom Davidson, Raymond Douglas, David Duvenaud, Philip Fox, Usman Gohar, Rose Hadshar, Anson Ho, Tiancheng Hu, Cameron Jones, Sayash Kapoor, Atoosa Kasirzadeh, Sam Manning, Nestor Maslej, Vasilios Mavroudis, Conor McGlynn, Richard Moulange, Jessica Newman, Kwan Yee Ng, Patricia Paskov, Shalaleh Rismani, Girish Sastry, Elizabeth Seger, Scott Singer, Charlotte Stix, Lucia Velasco, Nicole Wheeler, Daron Acemoglu, Vincent Conitzer, Thomas G. Dietterich, Fredrik Heintz, Geoffrey Hinton, Nick Jennings, Susan Leavy, Teresa Ludermir, Vidushi Marda, Helen Margetts, John McDermid, Jane Munga, Arvind Narayanan, Alondra Nelson, Clara Neppel, Sarvapali D. Ramchurn, Stuart Russell, Marietje Schaake, Bernhard Schölkopf, Alvaro Soto, Lee Tiedrich, Gaël Varoquaux, Andrew Yao, Ya-Qin Zhang, Leandro Angelo Aguirre, Olubunmi Ajala, Fahad Albalawi, Noora AlMalek, Christian Busch, Jonathan Collas, André Carlos Ponce de Leon Ferreira de Carvalho, Amandeep Gill, Ahmet Halit Hatip, Juha Heikkilä, Chris Johnson, Gill Jolly, Ziv Katzir, Mary N. Kerema, Hiroaki Kitano, Antonio Krüger, Kyoung Mu Lee, José Ramón López Portillo, Aoife McLysaght, Oleksii Molchanovskyi, Andrea Monti, Mona Nemer, Nuria Oliver, Raquel Pezoa, Audrey Plonk, Balaraman Ravindran, Hammam Riza, Crystal Rugege, Haroon Sheikh, Denise Wong, Yi Zeng, Liming Zhu, Daniel Privitera, Sören Mindermann
Categories: cs.CY
Abstract:
The International AI Safety Report 2026 synthesises the current scientific evidence on the capabilities, emerging risks, and safety of general-purpose AI systems. The report series was mandated by the nations attending the AI Safety Summit in Bletchley, UK. 29 nations, the UN, the OECD, and the EU each nominated a representative to the report's Expert Advisory Panel. Over 100 AI experts contributed, representing diverse perspectives and disciplines. Led by the Report's Chair, these independent experts collectively had full discretion over the report's content.
Published: 2026-02-24 15:25:55
Authors: Masaki Nagai, Hideaki Kawaguchi, Shin Nishio, Takahiko Satoh
Categories: quant-ph, cs.NI
Abstract:
The Quantum Internet will allow clients to delegate quantum workloads to remote servers over heterogeneous networks, but choosing the server that minimizes end-to-end execution time is difficult because server processing, feedforward classical communication, and entanglement distribution can overlap in protocol-dependent ways and shift the runtime bottleneck. We propose $T_{\max}$, a lightweight runtime score that sums coarse telemetry from multiple layers to obtain a conservative ranking for online server selection without calibrating weights for each deployment. Using NetSquid discrete-event simulations of a modified parameter-blind VQE (PB-VQE) workload, we evaluate $T_{\max}$ on pools of 10,000 heterogeneous candidates (selecting among up to 100 per decision) across crossover and bottleneck-dominated regimes, including temporal jitter scenarios and jobs with multiple shots. $T_{\max}$ achieves single-digit mean regret normalized by the oracle (below 10%) in both regimes and remains in the single-digit range under classical communication latency jitter for multi-shot jobs, while performance degrades for single-shot jobs under severe jitter. To connect performance to deployment planning, we derive an operating map based on requirements relating distance and entanglement rate requirements to protocol level counts, quantify how simple multiuser contention shifts the crossover, and use Sobol global sensitivity analysis to identify regime-dependent bottlenecks. These findings suggest that simple cross-layer telemetry can enable practical server selection while providing actionable provisioning guidance for emerging Quantum Internet services.
Published: 2026-02-24 15:25:38
Authors: Sofia Sartore, Daniel Nagel, Georg Diez, Gerhard Stock
Categories: cond-mat.soft, physics.bio-ph, physics.comp-ph, physics.data-an
Abstract:
To interpret molecular dynamics (MD) simulations, it is common practice to reduce the dimensionality of the molecular coordinates to a low-dimensional collective variable $x$. Projecting the high-dimensional MD data onto $x$ yields a free energy landscape $ΔG(x)$, which highlights low-energy regions corresponding to conformational states. The accurate definition of these states, however, is often impeded by projection artifacts, resulting in artificially shortened state lifetimes or even the complete disappearance of states from the analysis. As demonstrated for a two-dimensional toy model, Gaussian low-pass filtering of the high-dimensional MD coordinates can restore the underlying free energy landscape, allowing to recover previously hidden states. When applied to an all-atom folding trajectory of HP35, the number of microstates increases by an order of magnitude, which leads to metastable states that are long-lived and much better defined structurally, even compared to dynamically cored state trajectories.
Published: 2026-02-24 15:10:18
Authors: Prakhar Maheshwari, Mayukh Pahari, Anish Sarkar, Saurabh Sharma
Categories: astro-ph.HE
Abstract:
In this study, we analysed about $\sim$13 years of publicly available data from MAXI and Swift/BAT to examine the long-term source evolution of 42 transient low-mass X-ray binaries. The sample consists of 11 confirmed black hole X-ray binaries (BHXBs), 10 black hole candidates (BHC), and 21 neutron star X-ray binaries (NSXBs). Outbursts and flaring activities studied over 13 years show that 19/21 NSXBs spend significantly longer time in the hard state (observations for which hardness ratio is $\geq$ 0.2) while 15/21 BHXB+XRC spend substantially longer time in the soft state (observations for which hardness ratio is $<$ 0.2). The frequency distribution of the hardness ratio clearly shows two distinct distributions for BHXBs and NSXBs, with their peaks separated: NSXBs prefer harder values, while BHXBs prefer softer values of hardness. Our model-independent analysis for 42 transient sources shows that statistically NSXBs do not prefer to show a canonical high soft state as observed in BHXBs. Additionally, the probability distribution of the duration of the 2-20 keV X-ray outburst is observed to peak at a significantly longer duration ($>$100 days) for BHXBs than for NSXBs (15-60 days). Our analysis shows that among candidate sources, Swift J1728.9-3613, MAXI J1535-571, MAXI J1659-152, EXO 1846-031 show a `q' diagram in the HID and prefer to align with the HID frequency distribution of BHXBs that show `q' diagram, MAXI J1305-704 and MAXI J1836-194 align with frequency distribution of black hole sources without `q' diagram while MAXI J1848-015 shows the HID distribution similar to NSXBs, indicating a neutron star accretor. Therefore, a long-term statistical study of MAXI and Swift/BAT X-ray outbursts from a large sample of transient sources may be used to distinguish BHXB from NSXB.
Published: 2026-02-24 15:01:30
Authors: Yang Zhang, Danyang Li, Yuxuan Li, Xin Zhang, Tianyu Xie, Mingming Cheng, Xiang Li
Categories: cs.CV, cs.AI
Abstract:
Multimodal Large Language Models (MLLMs) have achieved remarkable performance by integrating powerful language backbones with large-scale visual encoders. Among these, latent Chain-of-Thought (CoT) methods enable implicit reasoning in continuous hidden states, facilitating seamless vision-language integration and faster inference. However, existing heuristically predefined supervision signals in latent CoT provide limited guidance for preserving critical visual information in intermediate latent states. To address this limitation, we propose CrystaL (Crystallized Latent Reasoning), a single-stage framework with two paths to process intact and corrupted images, respectively. By explicitly aligning the attention patterns and prediction distributions across the two paths, CrystaL crystallizes latent representations into task-relevant visual semantics, without relying on auxiliary annotations or external modules. Extensive experiments on perception-intensive benchmarks demonstrate that CrystaL consistently outperforms state-of-the-art baselines, achieving substantial gains in fine-grained visual understanding while maintaining robust reasoning capabilities.
Published: 2026-02-24 15:01:29
Authors: Mark Marron
Categories: cs.SE, cs.AI, cs.PL
Abstract:
Fully leveraging the capabilities of AI agents in software development requires a rethinking of the software ecosystem itself. To this end, this paper outlines the creation of an Agentic Infused Software Ecosystem (AISE), that rests on three pillars. The first, of course, is the AI agents themselves, which in the past 5 years have moved from simple code completion and toward sophisticated independent development tasks, a trend which will only continue. The second pillar is the programming language and APIs (or tools) that these agents use to accomplish tasks, and increasingly, serve as the communication substrate that humans and AI agents interact and collaborate through. The final pillar is the runtime environment and ecosystem that agents operate within, and which provide the capabilities that programmatic agents use to interface with (and effect actions in) the external world. To realize the vision of AISE, all three pillars must be advanced in a holistic manner, and critically, in a manner that is synergistic for AI agents as they exist today, those that will exist in the future, and for the human developers that work alongside them.
Published: 2026-02-24 15:00:29
Authors: Sara C. Debón
Categories: math.GR, math.RT
Abstract:
A famous result of P. Hegedüs describes the structure of finite rational $\{2,5\}$-groups. In this paper, we show how Hegedüs' proof can be used to obtain a similar result for the more general situation of a finite rational $2$-group acting faithfully and with the eigenvector property on a f.d $\mathbb{F}_p$-vector space with $p\geq 5$.
Published: 2026-02-24 14:57:49
Authors: Benjamin Miquel, Abram Ellison, Michael A. Calkins, Keith Julien, Edgar Knobloch
Categories: physics.flu-dyn
Abstract:
Rapidly rotating Rayleigh-Bénard convection on a $f$-plane at colatitude $\vartheta_f$ is investigated numerically using an asymptotically reduced equation set valid in the limit of very rapid rotation. The equations provide a non-hydrostatic but quasi-geostrophic description in a non-orthogonal coordinate system. The tilt changes the structure of the large-scale barotropic condensate from large-scale vortices to zonal flows as the colatitude of the $f$-plane increases, with bistable states present for certain parameter ranges, extending prior work to a geophysically significant parameter regime. This behaviour is understood through the impact of broken rotation symmetry on the barotropic source terms resulting from baroclinic vortical stresses and baroclinic torque. As the tilt angle $\vartheta_f$ increases, global heat and momentum transport is reduced relative to upright-polar convection, a result that is explained through linear theory and nonlinear power maps both of which demonstrate increased attenuation of the domain of dynamically active spatial scales as the convective modes depart from a North-South alignment in the horizontal plane. A key finding is that the predominance of lateral thermal mixing allows for the maintenance of a persistent unstable mean temperature gradient that saturates at increasing forcing levels and remains insensitive to the colatitude.
Published: 2026-02-24 14:48:47
Authors: Maxim Gritskov, Andrey Losev, Saveliy Timchenko
Categories: math-ph, hep-th
Abstract:
In this work, we propose a cohomological approach to studying perturbative anomalies in quantum mechanics. The Hamiltonian $\hat{H}$ together with the symmetry generator $\hat{S}$ forms a unitary representation of the two-dimensional Abelian Lie algebra $g\cong \mathbb{R}^{2}$ on the Hilbert space $V$. We show that perturbations of such a system are related to the first Chevalley-Eilenberg cohomology group $H^{1}_{CE}(\mathbb{R}^{2},\mathfrak{u}(V))$. In turn, the perturbative anomalies of the symmetry $\hat{S}$ are related to the second cohomology group $H^{2}_{CE}(\mathbb{R}^{2},\mathfrak{u}(V))$.
Published: 2026-02-24 14:39:32
Authors: Ian Slagle, Faisal Alamgir, Victor Fung
Categories: cond-mat.mtrl-sci
Abstract:
Determining atomic structure from spectroscopic data is central to materials science but remains restricted to a limited set of techniques and material classes, largely due to the computational cost and complexity of structural refinement. Here we introduce ActiveStructOpt, a general framework that integrates graph neural network surrogate models with active learning to efficiently determine candidate structures that reproduce target spectra with minimal computational expenditure. Benchmarking with X-ray pair distribution function data, and with the more computationally demanding simulations of X-ray absorption near-edge spectra (XANES) and extended X-ray absorption fine structure (EXAFS), demonstrate that ActiveStructOpt reliably determines structures that match closely in spectra across diverse materials classes. Under equivalent computational budgets, ActiveStructOpt outperforms existing structure determination methods. By enabling data-efficient, multi-objective structural refinement across a broad range of computable spectroscopic techniques, ActiveStructOpt provides a flexible and extensible approach to atomic structure determination in complex materials.
Published: 2026-02-24 14:37:36
Authors: Luka Šiktar, Branimir Ćaran, Bojan Šekoranja, Marko Švaco
Categories: cs.RO, cs.AI
Abstract:
Search and rescue (SAR) operations require rapid responses to save lives or property. Unmanned Aerial Vehicles (UAVs) equipped with vision-based systems support these missions through prior terrain investigation or real-time assistance during the mission itself. Vision-based UAV frameworks aid human search tasks by detecting and recognizing specific individuals, then tracking and following them while maintaining a safe distance. A key safety requirement for UAV following is the accurate estimation of the distance between camera and target object under real-world conditions, achieved by fusing multiple image modalities. UAVs with deep learning-based vision systems offer a new approach to the planning and execution of SAR operations. As part of the system for automatic people detection and face recognition using deep learning, in this paper we present the fusion of depth camera measurements and monocular camera-to-body distance estimation for robust tracking and following. Deep learning-based filtering of depth camera data and estimation of camera-to-body distance from a monocular camera are achieved with YOLO-pose, enabling real-time fusion of depth information using the Extended Kalman Filter (EKF) algorithm. The proposed subsystem, designed for use in drones, estimates and measures the distance between the depth camera and the human body keypoints, to maintain the safe distance between the drone and the human target. Our system provides an accurate estimated distance, which has been validated against motion capture ground truth data. The system has been tested in real time indoors, where it reduces the average errors, root mean square error (RMSE) and standard deviations of distance estimation up to 15,3\% in three tested scenarios.
Published: 2026-02-24 14:31:39
Authors: Angelo A. Casulli, Daniel Kressner, Nian Shao
Categories: math.NA
Abstract:
The Lanczos method with implicit restarting is one of the most popular methods for finding a few exterior eigenpairs of a large symmetric matrix $A$. Usually based on polynomial filtering, restarting is crucial to limit memory and the cost of orthogonalization. In this work, we propose a novel strategy for the same purpose, called Lanczos with compression. Unlike polynomial filtering, our approach compresses the Krylov subspace using rational approximation and, in doing so, it sacrifices the structure of the associated Krylov decomposition. Nevertheless, it remains compatible with subsequent Lanczos steps and the overall algorithm is still solely based on matrix-vector products with $A$. On the theoretical side, we show that compression introduces only a small error compared to standard (unrestarted) Lanczos and therefore has only a negligible impact on convergence. Comparable guarantees are not available for commonly used implicit restarting strategies, including the Krylov--Schur method. On the practical side, our numerical experiments demonstrate that compression often outperforms the Krylov--Schur method in terms of matrix-vector products.
Published: 2026-02-24 14:22:56
Authors: Khwahish Kushwah, Gabriel Silveria Denicol
Categories: astro-ph.HE, hep-th
Abstract:
We derive the equations of motion of relativistic magnetohydrodynamics from the Boltzmann equation using the method of moments. We consider a locally electrically neutral system composed of two particle species with opposite charges, with vanishing dipole moment or spin, so that the fluid has vanishing magnetization and polarization. We find that the dynamics of this fluid changes dramatically in the presence of a magnetic field. The shear stress tensor no longer adheres to a single differential equation; instead, it splits into three non-degenerate components, each evolving according to distinct dynamical equations. Exploring these equations in a Bjorken flow scenario, we find that for large magnetic fields, our theory predicts oscillatory behavior beyond the scope of an Israel-Stewart-like theory.
Published: 2026-02-24 14:20:22
Authors: Sofia Ferreira-Teixeira, Daniel Tezze, Maria Ramos, Covadonga Álvarez-García, Bertuğ Bayındır, Junhyeon Jo, Beatriz Martín-García, Maider Ormaza, Fèlix Casanova, Samuel Mañas-Valero, Eugenio Coronado, Hasan Sahin, Luis E. Hueso, Marco Gobbi
Categories: cond-mat.mtrl-sci
Abstract:
CrSBr is a van der Waals magnetic semiconductor exhibiting antiferromagnetic order below 140 K. It has emerged as a promising platform for engineering 2D magnetism because its intertwined electronic, optical, and magnetic properties can be profoundly modified via external stimuli such as electrical gating or magnetic fields. However, other strategies for tuning magnetism in layered materials, such as molecular intercalation, remain largely unexplored for CrSBr. Here, we demonstrate that the intercalation of tetramethylammonium (TMA) and tetrapropylammonium (TPA) ions into CrSBr induces a transition from antiferromagnetic to ferromagnetic order, while significantly enhancing the magnetic transition temperature to 190 K (TMA) and 230 K (TPA). The resulting intercalates are air-stable and exhibit large, hysteretic magnetoresistance exceeding 60% at 50 K in the TPA case. Besides, intercalation introduces symmetry-breaking structural changes in each CrSBr plane, revealed by Raman microscopy and corroborated by density functional theory (DFT) calculations. These findings highlight molecular intercalation as a powerful and versatile route to tailor the magnetic properties of CrSBr and unlock its potential to fabricate robust, high-temperature 2D magnetic devices.
Published: 2026-02-24 14:11:56
Authors: Shuangkang Fang, I-Chao Shen, Xuanyang Zhang, Zesheng Wang, Yufeng Wang, Wenrui Ding, Gang Yu, Takeo Igarashi
Categories: cs.CV
Abstract:
Recent 3D Gaussian Splatting (3DGS) Dropout methods address overfitting under sparse-view conditions by randomly nullifying Gaussian opacities. However, we identify a neighbor compensation effect in these approaches: dropped Gaussians are often compensated by their neighbors, weakening the intended regularization. Moreover, these methods overlook the contribution of high-degree spherical harmonic coefficients (SH) to overfitting. To address these issues, we propose DropAnSH-GS, a novel anchor-based Dropout strategy. Rather than dropping Gaussians independently, our method randomly selects certain Gaussians as anchors and simultaneously removes their spatial neighbors. This effectively disrupts local redundancies near anchors and encourages the model to learn more robust, globally informed representations. Furthermore, we extend the Dropout to color attributes by randomly dropping higher-degree SH to concentrate appearance information in lower-degree SH. This strategy further mitigates overfitting and enables flexible post-training model compression via SH truncation. Experimental results demonstrate that DropAnSH-GS substantially outperforms existing Dropout methods with negligible computational overhead, and can be readily integrated into various 3DGS variants to enhance their performances. Project Website: https://sk-fun.fun/DropAnSH-GS
Published: 2026-02-24 14:09:59
Authors: O. P. Ferreira, D. S. Gonçalves, M. S. Louzeiro, S. Z. Németh, J. Zhu
Categories: math.OC
Abstract:
This paper investigates the properties of Busemann functions on Hadamard manifolds and their use in optimization algorithms in Riemannian settings. We present a new Busemann-based characterization of the subdifferential, which is particularly well suited to Riemannian optimization. In the classical Hadamard manifold framework, a subgradient provides a global lower model of a convex function expressed through the inverse exponential map. However, this model may fail to exhibit a useful convexity or concavity structure. By contrast, our characterization yields a concave bounding function by exploiting key properties of Busemann functions. We use this concavity to design and analyze difference-of-convex (DC) optimization methods on Hadamard manifolds. In particular, we reformulate the classical DC algorithm (DCA) for Riemannian contexts and study its convergence properties. We also report preliminary numerical experiments comparing the proposed Busemann DCA, which leads to geodesically convex subproblems, with the classical Riemannian DCA.
Published: 2026-02-24 14:08:12
Authors: Cristian Valero-Abundio, Emilio Sansano-Sansano, Raúl Montoliu, Marina Martínez García
Categories: cs.CV
Abstract:
Handling geometric transformations, particularly rotations, remains a challenge in deep learning for computer vision. Standard neural networks lack inherent rotation invariance and typically rely on data augmentation or architectural modifications to improve robustness. Although effective, these approaches increase computational demands, require specialised implementations, or alter network structures, limiting their applicability. This paper introduces General Intensity Direction (GID), a preprocessing method that improves rotation robustness without modifying the network architecture. The method estimates a global orientation for each image and aligns it to a canonical reference frame, allowing standard models to process inputs more consistently across different rotations. Unlike moment-based approaches that extract invariant descriptors, this method directly transforms the image while preserving spatial structure, making it compatible with convolutional networks. Experimental evaluation on the rotated MNIST dataset shows that the proposed method achieves higher accuracy than state-of-the-art rotation-invariant architectures. Additional experiments on the CIFAR-10 dataset, confirm that the method remains effective under more complex conditions.