April 2026 arXiv papers — page 24

H. Tang, A. Picksley, C. Benedetti, R. Li

Guiding relativistically intense laser pulses in low-density plasmas enables extended acceleration lengths in laser-plasma accelerators (LPAs), allowing for the production of multi-GeV electron beams. Quantitative interpretation of such experiments is often limited by substantial uncertainties in key plasma parameters, particularly the transverse density pro

Zeev Dvir

In this note we prove an upper bound on the $\mathbb F_p$-rank of the incidence matrix of points and hyperplanes in $(\mathbb Z/p^k \mathbb Z)^n$, improving a recent bound of Laba and Trainer when $k$ is large.

Qiang Jia, Ran Luo, Jiahua Tian, Yi-Nan Wang

We propose that the symmetry category associated to a 2D quantum field theory with 0-form $G$-symmetry with 't Hooft anomaly $k\in H^4(BG,\mathbb{Z})$ for a large class of Lie groups $G$ is the category of twisted measurable fields of Hilbert spaces over $G$ denoted by $\mathrm{Hilb}^k(G)$, which is equivalent to the category of unitary representations of $C

Qiang Jia, Cheng Ma, Jiahua Tian

Different gaugings of the global symmetry of a quantum field theory are closely related to its various phases. In this work, we study candidate gaugeable symmetries by analyzing candidate Lagrangian algebra data in the Drinfeld center of a symmetry category $\mathscr{C}^k(G)$ associated to a QFT with continuous global $G$-symmetry and possible 't Hooft anoma

Yupeng Zhou, Lianghua Huang, Zhifan Wu, Jiabao Wang

In this work, we propose Mutual Forcing, a framework for fast autoregressive audio-video generation with long-horizon audio-video synchronization. Our approach addresses two key challenges: joint audio-video modeling and fast autoregressive generation. To ease joint audio-video optimization, we adopt a two-stage training strategy: we first train uni-modal ge

Michael Correll, Jay Broccolo, Drew Bush

Mount Washington is home to extreme, and extremely volatile, weather conditions. Consulting a weather forecast of conditions at the summit is vital for making one's visit as safe as possible. Using the discussion and suggestions arising from a participatory workshop as input, we test a design intervention employing color-coded hazard icons to function as vis

Ifeanyi Ezuma, Olusiji Medaiyese

Magnification shift is a major obstacle to robust histopathology classification, because models trained on one imaging scale often generalize poorly to another. Here, we evaluated this problem on the BreaKHis dataset using a strict patient-disjoint leave-one-magnification-out protocol, comparing supervised baseline, baseline augmented with DCGAN-generated pa

S. Mal, D. K. Nandy, B. K. Sahoo

Although random matrix theory provides a fundamental framework for characterizing quantum chaos, encompassing both ergodic and localized phases, a comprehensive understanding of the universal features governing the critical transition remains elusive in many disordered and quasi-random systems. In this study, we explore the ergodic-to-many-body localization

Mohamed Camil Belhadjoudja, Kirsten A. Morris

We consider the one-dimensional quasilinear heat equation with state-dependent heat capacity and thermal conductivity, and design a boundary-output observer based on the backstepping design for a linear heat equation with constant coefficients. Viewing the quasilinear system as a perturbation of the linear one, we establish exponential stability of the origi

Jaime Banks, Nicholas David Bowman, Roman Saladino

Anthropomorphic language describing artificial intelligence (AI) is widespread in media, policy, and everyday discourse; so too are discussions of AI bad behavior, from hallucinations to inappropriate comments. How does humanizing language about AI shape moral judgments when AI behaves badly? Across four experiments (total N = 1,020), we tested whether lexic

Davide Pedrotti

I perform a model-independent reconstruction of the background pre-recombination expansion history of the Universe. I find that purely early-time resolutions to the Hubble tension, satisfying the geometric CMB constraints, exist at the background level. This class of solutions requires a smooth transition around matter-radiation equality, characterized by a

Hala ElAarag, Anas Gamal Aly

Parallel and Distributed Computing (PDC) is a critical yet conceptually challenging area of the undergraduate computer science curriculum. While students often encounter these concepts in theory, few gain exposure to experience in real high-performance computing (HPC) environments. Research shows that when students are engaged in project-based learning they

John M. Campbell, Narad Rampersad

Defant and Kravitz introduced generalizations of West's stack-sorting map $s$ from permutations to finite words. This raises questions as to how such generalizations could be applied in the field of combinatorics on words. The Defant-Kravitz generalizations of $s$ depend on how repeated occurrences of the same character within a word may be repositioned, acc

Tereza Constantinou, Oliver Shorttle, Harrison Nicholls

While Earth locks much of its carbon in its crust as carbonates, Venus retains a comparable carbon inventory almost entirely in its atmosphere as CO$_2$. On Earth, the geological carbon cycle that has produced this vast crustal carbonate inventory is regulated by biology, liquid water, and plate tectonics, which together have stabilised climate over geologic

Yashwant Pravinrao Bangde, Debaditya Roy

Vision-Language Models (VLMs) exhibit strong performance in instruction following and open-ended vision-language reasoning, yet they frequently generate fluent outputs that are weakly grounded in visual evidence. Prior works have shown that instruction prompting further worsens this issue by amplifying language priors, especially when the visual signal is un

Owen Lailey, Dusan Sarenac, David G. Cory, Michael G. Huber

The theory of dynamical diffraction (DD) in perfect crystals is the backbone of high-precision neutron and X-ray diffraction experiments, enabling accurate determination of crystal structure factors and the realization of perfect crystal interferometers. In practice, however, real crystals exhibit deformations and imperfections, including surface roughness,

Domenico D'Alessandro, Phattharaporn Singkanipa, Daniel Lidar

Universally robust dynamical decoupling (UR$n$) sequences were proposed to compensate pulse imperfections arising from arbitrary experimental parameters while achieving high-order error suppression with only a linear increase in the number of pulses. Although their performance was supported by analytical arguments, numerical simulations, and experiments, a c

Shangqing Tu, Yanjia Li, Keyu Chen, Sichen Zhang

Creating interactive STEM courseware traditionally requires HTML/CSS/JavaScript expertise, leaving barriers for educators. While generative AI can produce HTML codes, existing tools generate static presentations rather than interactive simulations, struggle with long documents, and lack pedagogical accuracy mechanisms. Furthermore, full regeneration for modi

Yi Zhou

At LaAlO$_3$/KTaO$_3$ interfaces, the superconducting $T_c$ exhibits a striking quasi-linear dependence on crystallographic orientation, coexisting with switchable polar nanoregions (PNRs). We propose an effective minimal Eliashberg framework in which overdamped PNR fluctuations provide the pairing glue, while geometric Rashba coupling controls its angular d

Xiaozhou Li, Nariman Mani, Jose Sosa Rodriguez, Tomas Cerny

Microservice-based systems impose significant organizational coordination challenges, yet the role of individual developers in shaping organizational coupling (OC) remains underexplored. Prior work largely focuses on structural architectural aspects, leaving gaps in understanding how developer roles influence coordination dynamics over time. This study inves

Caleb Jonker, Julian Kupka, Ingmar Saberi, Charles Strickland-Constable

We give an explicit description (in component fields) of a holomorphic theory associated to a general supersymmetric background of $\mathcal N=1$ supergravity in ten dimensions. Conjecturally, this provides a sought-for holomorphic realisation of the supergravity twist in such backgrounds, generalising the minimal type I BCOV theory for Calabi-Yau manifolds.

Hao-Fei Gao, Xue-Ying Han, Jun Hua, Xiangdong Ji

We present a first-principles determination of heavy meson light-cone distribution amplitudes (LCDAs) from lattice QCD in the continuum limit, improving substantially on our previous pioneering study. Within the heavy-quark large-momentum effective theory (HQLaMET) framework, supplemented by lattice QCD calculations of the OPE moments, we analyze six ensembl

Kejun Liu

The Jaynes-Cummings (JC) model, introduced in 1963 and central to cavity quantum electrodynamics, describes a two-level system coupled to a single bosonic mode under the rotating-wave approximation. When the mode is projected out via the Nakajima-Zwanzig (NZ) formalism, the memory-kernel generator QLQ is manifestly non-Hermitian -- yet we prove analytically

Oliver Kraus, Yash Sarrof, Yuekun Yao, Alexander Koller

Chain-of-Thought (CoT) has been shown to empirically improve Transformers' performance, and theoretically increase their expressivity to Turing completeness. However, whether Transformers can learn to generalize to CoT traces longer than those seen during training is understudied. We use recent theoretical frameworks for Transformer length generalization

Kazi Mohammad Abidur Rahman, Davis Rakhshan, Philipp Lütke, Laura Harms

The convergence of accelerating human spaceflight ambitions and critical terrestrial health monitoring demands is driving unprecedented requirements for reliable, real-time feature extraction on extremely resource-constrained wearable health sensors. We present an ultra-low-power (ULP) Field-Programmable Gate Array (FPGA) based solution for real-time Seismoc

Jan Meibohm, Samuel Monter, Sarah A. M. Loos, Clemens Bechinger

We theoretically and experimentally study finite-time optimal control of a colloidal particle steered through a spatially inhomogeneous environment, modeled by a position-dependent energetic cost at the final state. The competition between this state-dependent penalty and path-dependent dissipation gives rise to a sharp transition in the control strategy at

Jan Niklas Schmäke, Martin Ruess

Localized features such as singularities, sharp gradients, discontinuities, and moving sources require adaptive finite element discretizations. Conventional refinement strategies introduce significant computational overhead through mesh-topology modifications, constraint handling for non-matching interfaces, and repeated remeshing with state transfer. This w

Andy Caen, Mark H. M. Winands, Dennis J. N. J. Soemers

We present StratFormer, a transformer-based meta-agent that learns to simultaneously model and exploit opponents in imperfect-information games through a two-phase curriculum. The first phase trains an opponent modeling head to identify behavioral patterns from action histories while the agent plays a game-theoretic optimal (GTO) policy. The second phase pro

Tri-Nhan Vo, Dang Nguyen, Kien Do, Sunil Gupta

Knowledge distillation (KD) is a well-known technique to effectively compress a large network (teacher) to a smaller network (student) with little sacrifice in performance. However, most KD methods require a large training set and internal access to the teacher, which are rarely available due to various restrictions. These challenges have originated a more p

Tri-Nhan Vo, Dang Nguyen, Trung Le, Kien Do

Knowledge distillation (KD) represents a vital mechanism to transfer expertise from complex teacher networks to efficient student models. However, in decentralized or secure AI ecosystems, privacy regulations and proprietary interests often restrict access to the teacher's interface and original datasets. These constraints define a challenging black-box data

L. G. Pereira

The relation between uniformly accelerated laboratories and laboratories supported in a gravitational field lies at the conceptual core of the Equivalence Principle, yet its precise kinematical content beyond strictly local considerations remains subtle. In this work we develop a unified metric description of these configurations using the standard Arnowitt-

Sven Heihoff, Arseniy A. Filin, Evgeny Epelbaum

Effective field theories have established themselves as key pillars of modern nuclear physics. They enable a quantitative understanding of the strong nuclear force, provided low-energy constants that parametrize short-distance physics can be determined from experimental data. This, however, often becomes prohibitively expensive due to a significant computati

Chen Ma, Bin Wu, Zhen-Ming Xu

In this study, by utilizing the constructed generalized free energy alongside the Mean First-Passage Time and the Kramers escape rate from stochastic dynamics, we have obtained a comprehensive landscape of the phase transitions for the Bardeen-AdS-class black hole. This black hole model admits two distinct categories of solutions. Type I black holes feature

David González-Lociga, Simeon Ball

As emerging quantum architectures evolve into heterogeneous networks combining different physical substrates, such as qubits for logic and higher-dimensional qudits for robust communication, the traditional scalar metrics of quantum error correction become insufficient. To address this, we introduce a mathematical framework based on dimension multisets to ch

Ido Efrat

We prove a criterion for the mildness of a finitely presented pro-$p$ group $G$. It implies as a special case a cohomological mildness criterion via Massey products, generalizing results due to Schmidt and G\"artner. It subsumes Labute's non-singular circuit criterion. We further show connections with the triangle condition for the mildness of pro-$p$ right-

Yixuan Huang, Bowen Li, Vaibhav Saxena, Yichao Liang

Robotic systems that interact with the physical world must reason about kinematic and dynamic constraints imposed by their own embodiment, their environment, and the task at hand. We introduce KinDER, a benchmark for Kinematic and Dynamic Embodied Reasoning that targets physical reasoning challenges arising in robot learning and planning. KinDER comprises 25

Yu Liu, Jiangxia Cao

Generative recommender systems have recently emerged as a promising paradigm by formulating next-item prediction as an auto-regressive semantic IDs generation, such as OneRec series works. However, with the next-item-agnostic prediction paradigm, its could beam out some next potential items via Semantic IDs but hard to estimate which items are better from th

Jeff Shen, Joshua S. Speagle, Shirley Ho

Large-scale spectroscopic surveys have collectively observed millions of stars across the Milky Way, but each derives stellar labels using independent pipelines with distinct modelling assumptions, introducing systematic offsets that obscure signals in chemical space and hinder large-scale Galactic archaeology. We present a unified deep-learning framework th

B. Shapiro

We study the asymptotic distribution of level crossings for random matrix pencils A_n+λB_n in several ensembles, including complex and real i.i.d. matrices and Gaussian/Hermitian settings. We derive a representation of the normalized log-discriminant in terms of pairwise eigenvalue interactions and formulate conditions under which its limit is governed by a

Michael Greinecker, Martin Meier, Konrad Podczeck

Sequential equilibrium is one of the most fundamental refinements of Nash equilibrium for games in extensive form. However, it is not defined for extensive-form games in which a player can choose among a continuum of actions. We define a class of infinite extensive form games in which information behaves continuously as a function of past actions and define

George Morgulis, John Hewitt

Subliminal learning describes a student language model inheriting a behavioral bias by fine-tuning on seemingly innocuous data generated by a biased teacher model. Prior work has begun to characterize this phenomenon but leaves open questions about the scope of signals it can transfer, the mechanisms that explain it, and the precision with which a bias can b

Ciprian Manolescu, Nick Rozenblyum

We prove that the stable tame isomorphism, quasi-isomorphism, and derived Morita equivalence problems for semifree noncommutative differential graded algebras (DGAs) are all undecidable. This resolves half of Problem 5.16 from the K3 Problem List in Low-Dimensional Topology. We present two solutions, both obtained (essentially autonomously) by Gemini Deep Th

Qian Yin, Jiaxing Li, Jiaqi Cheng, Qizhang Luo

Earth observation satellite imaging scheduling is a challenging NP-hard combinatorial optimisation problem central to space mission operations. While next-generation agile Earth observation satellites (EOS) increase operational flexibility, they also significantly raise scheduling complexity. The lack of a unified, open-source benchmark makes it difficult to

Marta Ziosi, Miro Plueckebaum, Stephen Casper, Henry Papadatos

Frontier AI both amplifies existing risks and introduces qualitatively novel challenges. Not only is there a notable lack of stable scientific consensus resulting from the rapid pace of technological change, but emerging frontier AI safety practices are often misaligned with, or may undermine, established risk management frameworks. To address these challeng

Haruka Kogure, Taishi Kurahashi

In this paper, we investigate arithmetical completeness with respect to finite Kripke models of quantified modal logic. We adapt the finite-model embedding techniques of Artemov and Japaridze to two settings involving finite Kripke models. First, for conversely well-founded finite Kripke models of quantified modal logic, we construct a $\Sigma_2$ Fefermanian

Chayanon Kitkana, Shivam Arora

In the MNIST auxiliary logit distillation experiment, a student can acquire an unintended teacher trait despite distilling only on no-class logits through a phenomenon called subliminal learning. Under a single-step gradient descent assumption, subliminal learning theory attributes this effect to alignment between the trait and distillation gradients, but do

Fahad Ebrahim, Mike Joy

Source Code Plagiarism Detection (SCPD) plays an important role in maintaining fairness and academic integrity in software engineering education. Code Evaluation Metrics (CEMs) are developed for assessing code generation tasks. However, it remains unclear whether such metrics can reliably detect plagiarism across different levels of modification (L1-L6), inc

Michel Bataille, Robert Frontczak

From an identity connecting a combinatorial sum and Legendre polynomials, we derive closed forms for a number of combinatorial sums. Some of them are obtained via results about the integrals of functions associated with Legendre polynomials.

Taryn Wong, Zeerak Talat, Hanan Aldarmaki, Anjalie Field

Critical analyses of emotion recognition technology have raised ethical concerns around task validity and potential downstream impacts, urging researchers to ensure alignment between their stated motivations and practice. However, these discussions have not adequately influenced or drawn from research on speech emotion recognition (SER). We address this gap

Yuntian Gu, Zeyao Han, Wenrui Li, Zhiyu Xiao

Neural Quantum States (NQS) are now among the most accurate methods for studying strongly correlated many-fermion systems, outperforming existing many-body approaches for large systems. However, NQS calculations remain extremely resource-intensive. Here, we introduce a new Pareto frontier of efficiency and accuracy for NQS in simulating strongly correlated l

Samuel Carlos S. Ferreira, Bruno R. Freitas, João Carlos R. Medrado

We analyze a three-dimensional discontinuous piecewise linear system \(Z=(X,Y)\) whose switching manifold \(\Sigma\) contains visible-visible two-fold intersection lines. Assuming that the matrices \(DX\) and \(DY\) each have one nonzero real eigenvalue and one pair of complex conjugate eigenvalues, we reduce the system to a canonical form. Under a resonant

Jan Peleska, Felix Brüning, Wen-Ling Huang, Anne E. Haxthausen

We present the SCenario Specification Language (SCSL) for automated generation and execution of system-level tests. SCSL targets complex distributed systems (e.g., collaborating autonomous robots) where classical model-based testing becomes impractical because (1) the overall system complexity is too high for a single monolithic model, (2) test behaviour can

Hao Sun, Tuo Tan, Jiang-Hao Yu

We present a systematic technique for constructing the Lorentz-covariant structures of hadronic matrix elements of local operators. The spinor Young tableaux of the Lorentz group is employed to construct all possible structures for the matrix elements of arbitrary operators, using the relativistic wave functions and momenta of the initial and final state par

R. Tuomainen, A. Finoguenov, J. Comparat, L. Doubrawa

We statistically quantified the prevalence and properties of substructure in optical galaxy clusters and directly investigated its impact on X-ray morphology and scaling relations, leveraging new data from the DECaLS Legacy Survey and the SRG/eROSITA all-sky survey. We applied the hierarchical density-based clustering algorithm HDBSCAN to the redMaPPer galax

Jason Miller, Yi Tian

The Brownian tree, also known as the continuum random tree, is a canonical random compact, geodesic $\mathbf R$-tree that arises as the universal scaling limit for numerous models of discrete random trees. A key quasisymmetric invariant of a metric space is its conformal dimension, defined as the infimum of the Hausdorff dimensions over all quasisymmetricall

Dylan Lewis, Roeland Wiersema

Quantum optimal control methods are widely used to design experimental control pulses such as laser amplitudes, phases, or detunings, that implement a target unitary evolution. In practice, what makes a pulse "good" depends not only on its fidelity, but also on the experimental setting and the relevant hardware constraints. Here, we introduce geometric quant

Laura Caron

Between 1949 and 1980, every U.S. state mandated public schools to provide educational services for disabled students. This is one of the largest education reforms in U.S. history, but little is known about its impacts. Given scarce data in this period, I compile survey and administrative datasets and set up a difference-in-difference design using variation

Yongtao Yao, Wenjing Xiao, Miaojiang Chen, Anfeng Liu

In the context of quantum secure scenarios, existing research on mobile edge devices and intelligent computing and edge (ICE) systems based on the Non-Orthogonal Multiple Access (NOMA) communication model have overlooked the energy consumption overhead of Post-Quantum Cryptography (PQC) modules, and the high complexity of traditional resource allocation algo

Andrea Maurino

The quality of training data is critical to the performance of machine learning models. In this paper, the Error Sensitivity Profile (ESP) is proposed. It quantifies the sensitivity of model performance to errors in a single feature or in multiple features. By leveraging ESP, data-cleaning efforts can be prioritized based on error types and features most lik

Tim Donkiewicz, Oliver Gaul

Many large-scale optimization problems decompose into a master problem and scenario subproblems, a structure that can be exploited by Benders decomposition. In Benders decomposition, each iteration may generate many cuts from scenario subproblems, and adding all of them as constraints then causes the master problem to grow rapidly. These are constraints that

Lennart Ronge

We describe various ways of obtaining the Hadamard coefficients associated to a normally hyperbolic operator from the corresponding Green's operators. As the Hadamard expansion on its own is not enough for this, we include additional information either by considering something like a resolvent or powers of Green's operators or by looking at a product of the

Euclid Collaboration, E. Tsaprazi, A. Fumagalli, F. Marulli

The Euclid satellite will deliver a catalogue of optically selected galaxy clusters spanning from around 2000 deg$^2$ in Data Release (DR) 1 to around $14\,000$ deg$^2$ in DR3. In this work, we assess the validity of cluster clustering (CC) models for template-fitting, which complements the full-shape methodology by providing cosmological information from th

Gabriel Roberto Silva de Lima, Carla Silva Oliveira, João Domingos Gomes da Silva Junior

Let $G$ be a simple graph, $A(G)$ its adjacency matrix, and $D(G)$ its diagonal degree matrix. In 2022, \citeauthor{Wang2020} (\cite{Wang2020}) defined the family of matrices $L_\alpha$ as the convex linear combination: \[ L_\alpha(G) = \alpha D(G) + (\alpha - 1)A(G), \] where $\alpha \in [0,1]$. The study of the spectrum of this family of matrices may provi

Michael Greinecker, Konrad Podczeck

An economy, large or small, has traditionally been defined in terms of an explicit set of agents and an assignment of characteristics to each agent. But when individual agents are negligible, most economically relevant properties of an economy can be defined in terms of the distribution of characteristics alone. Agents need not be specified. It has been freq

Kenta Yoshimura

We propose a neural-network-based variational framework for nuclear Density Functional Theory based on the extended Thomas--Fermi (ETF) model, in which proton and neutron number densities are represented by multilayer perceptrons and determined by direct minimization of a Skyrme-type energy density functional. We clarify the mathematical connection to the co

Sanskar Sharma, Ipsita Mandal

We investigate the transport signatures of pseudo-Landau levels (PLLs) in two-dimensional anisotropic Dirac systems with tilted cones, whose effective bandstructure results from strain-induced pseudogauge fields. In contrast to conventional Landau quantisation, the PLLs exhibit explicit momentum-dependence by being dispersive, leading to finite longitudinal

Thomas J. Neubert, Laxima Niure Kandel, Berker Peköz

Open, unclassified research on secure autonomy is constrained by limited access to operational platforms, contested communications infrastructure, and representative adversarial test conditions. This paper presents a threat-oriented digital twinning methodology for cybersecurity evaluation of learning-enabled autonomous platforms. The approach is instantiate

Lorenzo Bastonero, Gabriel Joalland, Chiara Cignarella, Lorenzo Monacelli

Materials underpin modern technologies, from energy harvesting, storage, and conversion to information and communication technologies. Their functionality is often governed by the interplay between competing phases, as thermodynamic behavior shapes microscopic properties and ultimately determines technological performance; for instance, the light absorption

Ruqian Zhang, Juan Shen, Yijiao Zhang

The availability of data from multiple heterogeneous environments has motivated methods that remain reliable under distributional shifts. When the joint distribution of response and predictors varies across environments, the response may still depend on a subset of predictors through an invariant mechanism. Existing methods typically assess candidate invaria

Yi-Xuan Yao, Hao-Yue Zhang, Cheng-Ge Liu, Rong-Hang Chen

Two-dimensional spectroscopy (2DS) is a powerful ultrafast technique for probing electronic and vibrational dynamics in complex microscopic systems. Extracting detailed information on system dynamics and system-bath interactions from 2DS experiments requires precise theoretical simulations for comparison, which motivates the development of numerically-exact

Dileep Singh, Riley W. Hooper, Christoph Findler, Utsab Banerjee

Nuclear magnetic resonance (NMR) spectroscopy provides unparalleled access to molecular structure and dynamics but is traditionally limited by weak signal strength, requiring large sample volumes and high magnetic fields. Here, we demonstrate nanoscale deuterium (2H) NMR spectroscopy using nitrogen vacancy (NV) centers in diamond, reproducing the characteris

Nidhi Gahlian

In this paper, we analyze the solutions of the following non-linear differential-difference equations f^n(z) +\omega f^(n-1)f'(z) +p(z)f(z+c) = p_1e^{\alpha}_1z +p_2e^{\alpha}_2z and f^n(z)f'(z) +q(z)e^Q(z)f(z+c) = p_1e^{\alpha}_1z +p_2e^{\alpha}_2z, where n is a positive integer,\omega, p1, p2,{\alpha}1 & {\alpha}2 are non-zero constants satisfying {\alpha}

Léa Loisel, Sandie Arnoux, Gaël Beaunée, Pauline Ezanno

Dengue virus transmission models commonly assume an exponential distribution for the mosquito extrinsic incubation period (EIP), potentially oversimplifying biological variability. We developed a stochastic mechanistic dengue transmission model comparing epidemic dynamics under commonly assumed exponential (EXP) versus experimentally derived (ED) EIP distrib

E. Sánchez García, Y. Shi, N. Ackermann, H. Bonet

The CONUS+ experiment has recently reported the first detection of coherent elastic neutrino-nucleus scattering (CEvNS) of reactor antineutrinos on germanium nuclei and is now entering a precision phase. The dominant uncertainty in the first measurement was the energy scale, which contributed 14% to the uncertainty of the prediction of the combined signal. W

Chiyi Luo, Dawei Yang

We prove that for $C^{1+\beta}$ flows whose generating vector fields may have singularities, every weakly mixing hyperbolic SRB measure is Bernoullian.

Adrià Garcés, Ueli Töpfer, Lucio Isa, Demian Levis

We experimentally, numerically and analytically explore the diffusive transport of active colloidal particles with sensory delay, navigating motility landscapes in which the self-propulsion speed depends on space. We show how the transport properties can be obtained by replacing the space dependence of the self-propulsion speed by a dynamical stochastic swit

Alex Stringer, Jeffrey Negrea

We test the hypothesis that simulataneous linear contrasts of multiple variance components equal zero in a Gaussian variance components model via a parametric bootstrap. Applications include but are not limited to nested and crossed designs. The main technical contributions are a computationally efficient decomposition of the normalized residual log-likeliho

I. Smirnov, S. Alyatkin, P. G. Lagoudakis

Temporal coherence of driven-dissipative condensates is limited by phase noise. We show that mirror-mediated time-delayed self-feedback enables control of coherence in a trapped exciton-polariton condensate. Reinjecting a small fraction of the emitted light with a tunable delay reveals two regimes set by the ratio of delay time to intrinsic coherence time. L

Marie Schölch, Óscar Jiménez-Arranz, Mercè Romero-Gómez, Xavier Luri

The interaction between the LMC and SMC (the Clouds) has resulted in prominent tidal features, including an extended bridge of gas and stars connecting the two galaxies. This Bridge has likely formed during the most recent interaction between the Clouds, about 150-250 Myr ago. While some young stars observed in the Bridge have formed in-situ from the tidally

Yongtao Yao, Yao Yang, Haorui Shi, Canglu Zhu

With the rapid advancement of artificial intelligence (AI) and intelligent science, intelligent edge computing has been widely adopted. However, the limitations of traditional methods, such as poor adaptability and the slow convergence of heuristic algorithms, are becoming increasingly evident. To enable sustainable and resource-efficient edge applications,

Mrigankamauli Chakraborty, Marco Klann, Sven-Olaf Moch, Pooja Mukherjee

Graphical functions have emerged as a powerful framework for evaluating multi-loop Feynman integrals in perturbative quantum field theory. Defined as massless three-point position-space integrals, they reveal rich analytic structures and have enabled major advances, including the highest-loop results currently known in several quantum field theories. Their r

Noam Tarshish, Nofar Selouk, Daniel Hodisan, Bar Ezra Gafniel

Instructed code editing is a significant challenge for large language models (LLMs). On the EditBench benchmark, 39 of 40 evaluated models obtain a task success rate (TSR) below 60 percent, highlighting a gap between general code generation and the ability to perform instruction-driven editing under executable test constraints. To address this, we propose SA

S. A. Andreeva, A. A. Gavrilov, K. R. Dzhikirba, A. S. Astrakhantseva

We investigate the effect of inter-disk coupling on the magnetoplasmon dispersion in a square lattice of two-dimensional electron system (2DES) disks etched from a GaAs quantum well. Using magneto-optical terahertz (THz) spectroscopy, we track the evolution of the collective modes as disk lattice period is systematically reduced, thereby increasing the coupl

Thomas Gawne, Jan Vorberger, Zhandos Moldabekov, Hannah Bellenbaum

X-ray Thomson scattering (XRTS) has emerged as a widely used diagnostics for extreme states of matter in a great variety of situations, and over a broad range of parameters. The standard approach for the interpretation of XRTS measurements is given by the forward modeling approach, where the electronic dynamic structure factor $S_{ee}(\mathbf{q},\omega)$ is

Tian Bai, Fedor V. Fomin, Petr A. Golovach, Yash Hiren More

Rank aggregation seeks a representative permutation for a collection of rankings and plays a central role in areas such as social choice, information retrieval, and computational biology. Two fundamental aggregation tasks are the center and median problems, which minimize the maximum and the total distance to the input permutations, respectively. While these

Benedikt Bollig

These lecture notes provide an introduction to the verification of neural networks from a theoretical perspective. We discuss feed-forward neural networks, recurrent neural networks, attention mechanisms, and transformers, together with specification languages and algorithmic verification techniques.

Xiaodong Li, Jiawei Sheng, Jiangxia Cao, Xinghua Zhang

Cross-domain recommendation (CDR) has demonstrated to be an effective solution for alleviating the user cold-start issue. By leveraging rich user-item interactions available in a richly informative source domain, CDR could improve the recommendation performance for cold-start users in the target domain. Previous CDR approaches mostly adhere the Embedding and

Konstantinos Dialektopoulos, Theodoros Papanikolaou, Vasilios Zarikas

We review a new natural inflationary mechanism operated by repulsive-like primordial black holes (PBHs). In particular, working within the ``Swiss - Cheese" cosmological framework, we find that a Universe filled with PBHs, whose spacetime metric presents a repulsive-like behaviour, is characterised by an early quasi-de-Sitter cosmic expansion phase. Notably,

Yu Hin Au, Murray R. Bremner

We study enumeration problems for multi-operator monomials generated from one indeterminate by an associative multiplication together with finitely many unary operators. We consider four regimes, according to whether multiplication is commutative and whether the unary operators commute. In the case where the unary operators do not commute, we obtain explicit

Matteo Biassoni, Andrea Nava, Oscar Azzolini, Mattia Beretta

The Neganov-Trofimov-Luke (NTL) effect is used by experiments based on cryogenic detectors to boost the sensitivity of light-sensitive devices down to a few optical photons. In this work we introduce a silicon light-detector technology that implements NTL amplification at millikelvin temperatures using transparent indium-tin-oxide (ITO) electrodes. The ITO e

Hiromu Nakano

We construct derivations on the triplet $W$-algebras $\mathcal{W}_{p_+,p_-}$ by refining the Frobenius homomorphisms of Tsuchiya-Wood and show that the property of the Adamovi\'{c}-Milas derivation for $\mathcal{W}_{2,p}$ extends to our derivations. As an application, we show that the $\mathfrak{sl}_2$-symmetry of $\mathcal{W}_{p_+,p_-}$ arises naturally fro

Junpeng Ma, Yuke Li, Junbo Wang, Yongxing Zhou

Designing Doppler-resilient unimodular discrete phase-coded waveforms (DPWs) with low delay-Doppler sidelobes is critical for multiple-input multiple-output (MIMO) radar. Existing block coordinate descent (BCD) methods suffer from high computational cost for designing long sequences or large waveform sets. Meanwhile, learning-based alternatives such as the s

Zhiyuan Fan, Tinghao Yu, Yuanjun Cai, Jiangtao Guan

Terminal agents have demonstrated strong potential for autonomous command-line execution, yet their training remains constrained by the scarcity of high-quality and diverse execution trajectories. Existing approaches mitigate this bottleneck by synthesizing large-scale terminal task instances for trajectory sampling. However, they primarily focus on scaling

Rishav Roshan

Domain wall annihilation can leave a distinctive imprint on the induced gravitational wave spectrum. During annihilation, most of the domain wall energy transforms into the scalar field responsible for the initial $\mathbb{Z}_2$ symmetry breaking that created the walls, along with any coupled species. If the produced scalar is sufficiently long-lived, its de

Louigi Addario-Berry, Bruce Reed, Dao Chen Yuan

An $n$-tuple $D=(d(1),\dots,d(n))$ is a \emph{feasible degree sequence} if there is a graph on $\{1,\dots,n\}$ such that $i$ has degree $d(i)$. Any such graph will have $m=\sum_{i=1}^n d(i)/2$ edges. Letting $G(D)$ be a graph chosen uniformly from those with the given degree sequence, we upper-bound the probability that $G(D)$ is disconnected based on the nu

Srikanta Prasad S, Utkarsh Arora

Modern enterprise AI applications increasingly rely on compound AI systems - architectures that compose multiple models, retrievers, and tools to accomplish complex tasks. Deploying such systems in production demands inference infrastructure that can efficiently serve concurrent, heterogeneous model invocations while maintaining cost-effectiveness and low la

Biqiang Zhao

In this paper, we establish Liouville-type theorems for parabolic differential inequalities with $(p,q)-$Laplacian operator on Riemannian manifolds. By a test function argument, we establish nonexistence results under suitable weighted volume growth assumptions involving potential. In particular, we can obtain nonexistence results for a wider class of parabo

P. N. Vabishchevich

The work is devoted to the development and computational implementation of the homogenization method for modeling unsteady flows of a viscous incompressible fluid in periodic porous media taking into account memory effects. At the macrolevel, the flow is described by an integro-differential Darcy law with a tensor memory kernel determined by solving unsteady

Meng Xia, Yan Chen, Qiao Jin, Yang Shi

This workshop addresses this gap by bringing together researchers and practitioners from AI, HCI, and the learning sciences to explore how interactive systems can better support learning. We focus on the design and evaluation of human-AI collaborative learning interfaces that are technically robust, human-centered, and pedagogically grounded. By fostering in

Ran Gu, Benjamin Hou, Mélanie Hébert, Asmita Indurkar

Despite strong performance of deep learning models in retinal disease detection, most systems produce static predictions without clinical reasoning or interactive explanation. Recent advances in multimodal large language models (MLLMs) integrate diagnostic predictions with clinically meaningful dialogue to support clinical decision-making and patient counsel