April 2026 arXiv papers — page 3

Sriram Narayanan, Ziyu Jiang, Srinivasa Narasimhan, Manmohan Chandraker

Modern video diffusion models excel at appearance synthesis but still struggle with physical consistency: objects drift, collisions lack realistic rebound, and material responses seldom match their underlying properties. We present PhyCo, a framework that introduces continuous, interpretable, and physically grounded control into video generation. Our approac

Lautaro Giordano, Sebastian Gonçalves, José Roberto Iglesias, María Fabiana Laguna

We present a minimal agent-based model of interacting agents characterized by their wealth to study taxation and inequality in a non-conservative economy. Wealth evolves through an extremal stochastic replacement process in which the poorest agent has its wealth replaced by a new random value, financed through a collective taxation mechanism. We explore taxa

Ryan John Oommen, Tanusree Sharma

Identity verification is a critical gateway to accessing government services and public benefits, yet contemporary systems are typically designed around visual interaction, leaving blind and low vision (BLV) individuals disproportionately burdened. In this work, we examine how BLV users navigate identity verification in government services and how current de

Ramesh Sasmal, Supratik Banerjee

Finite Larmor radius magnetohydrodynamics (FLR-MHD) provides a hybrid model of plasma that explains how turbulent energy cascade extends to sufficiently small parallel length scales, potentially leading to perpendicular heating of the ions in the solar corona and the solar wind. In this work, we derive exact laws for the cascades of energy and generalized he

Daniel Waxman, Fernando Llorente, Petar M. Djurić

The proliferation of capable and efficient machine learning (ML) models marks one of the strongest methodological shifts in signal processing (SP) in its nearly 100-year history. ML models support the development of SP systems that represent complex, nonlinear relationships with high predictive accuracy. Adapting these models often requires sequential infere

Tim Missal, Lucas Domingues, Berk Guler, Simon Manschitz

The robotic manipulation of Deformable Linear Objects (DLOs) is a fundamental challenge due to the high-dimensional, non-linear dynamics of flexible structures and the complexity of maintaining topological integrity during contact-rich tasks. While recent data-driven methods have utilized Recurrent and Graph Neural Networks for dynamics modeling, they often

Wenxiao Li, Faqiang Wang, Yuping Duan, Li Cui

Topological features play an essential role in ensuring geometric plausibility and structural consistency in image analysis tasks such as segmentation and skeletonization. However, integrating topology-preserving learning based on simple points into deep learning tasks remains challenging, as existing simple point detection methods are confined to binary ima

Yujun Wu, Dongxu Zhang, Xinchen Li, Jinhang Xu

Existing research infrastructure is fundamentally document-centric, providing citation links between papers but lacking explicit representations of methodological evolution. In particular, it does not capture the structured relationships that explain how and why research methods emerge, adapt, and build upon one another. With the rise of AI-driven research a

Yanting Wang, Chenlong Yin, Ying Chen, Jinyuan Jia

Long-context large language models (LLMs)-for example, Gemini-3.1-Pro and Qwen-3.5-are widely used to empower many real-world applications, such as retrieval-augmented generation, autonomous agents, and AI assistants. However, security remains a major concern for their widespread deployment, with threats such as prompt injection and knowledge corruption. To

Binghao Huang, Yunzhu Li

We present FlexiTac, a low-cost, open-source, and scalable piezoresistive tactile sensing solution designed for robotic end-effectors. FlexiTac is a practical "plug-in" module consisting of (i) thin, flexible tactile sensor pads that provide dense tactile signals and (ii) a compact multi-channel readout board that streams synchronized measurements for real-t

Sindre Brattegard, Stephanie Matern, Mark T. Mitchison, Saulo V. Moreira

In realistic nanoscale transport set-ups, electron-phonon coupling leads to the exchange of heat between phonon baths and electronic reservoirs with finite heat capacities. Such exchange affects the finite reservoir's temperature. However, this sensitivity of the finite reservoir temperature to the exchange of heat with the finite reservoir has remained unex

Richard Whitehill

Global QCD analyses provide the primary framework for extracting hadron structure from experimental data, yet the mechanisms by which data constrain non-perturbative functions remain difficult to interpret due to the high dimensionality and complexity of these fits. Here we develop a framework based on linear response and influence functions, which are gradi

Lukas Taus, Richard Tsai, Jeffrey G. Andrews

In a wireless network, the spatial location of the transmitters has a large impact on the achievable rate at each user location. The optimal placement of -- for example -- cellular base stations is a difficult non-convex problem, and is usually addressed with simplified propagation models and simplified heuristics that may account for specifics such as the s

Diederik Beckers, H. Jane Bae, Andres Goza

We introduce a refined immersed boundary (IB) methodology that is better-than-first-order accurate in practice, while preserving key properties of "continuous-forcing" IB approaches that retain a singular source term in the governing equations. Our method leverages a smoothed indicator (Heaviside) function, following ideas from multiphase flow and immersed l

Phuc Lam, Oanh Nguyen

We study how long the SIRS process persists or how quickly it reaches extinction across various network topologies. Our results provide a three-part characterization of this process: In finite sparse graphs, we prove the existence of a regime where the process survives for an exponentially long time. In heavy-tailed networks with power-law-like exponents, we

Zhuoyao Xin, Yiren Zhang, Christopher Wu, Dong Liu

Accurate synthesis of computed tomography (CT) images from magnetic resonance imaging (MRI) is clinically valuable for cranial applications such as attenuation correction, radiotherapy planning, and image-guided interventions. However, heterogeneity across MRI field strengths and acquisition protocols limits the generalizability of existing methods. In this

Matthias Hertel, Alexandra Nikoltchovska, Sebastian Pütz, Ralf Mikut

Time Series Foundation Models (TSFMs) have recently emerged as general-purpose forecasting models and show considerable potential for applications in energy systems. However, applications in critical infrastructure like power grids require transparency to ensure trust and reliability and cannot rely on pure black-box models. To enhance the transparency of TS

Sajjad Boorghan Farahan, Ahmed Alajlouni, Jingzhou Zhao

This work presents ThermoMesh, a passive thin-film thermoelectric mesh sensor designed to detect and characterize spatio-temporally sparse heat sources through conduction-based thermal imaging. The device integrates thermoelectric junctions with linear or nonlinear interlayer resistive elements to perform simultaneous sensing and in-sensor compression. We fo

Samuel Kiegeland, Vésteinn Snæbjarnarson, Tim Vieira, Ryan Cotterell

Surprisal theory links human processing effort to the predictability of an upcoming linguistic unit, but empirical work often leaves the notion of a unit underspecified. In practice, experimental stimuli are segmented into linguistically motivated units (e.g., words), while pretrained language models assign probability mass to a fixed token alphabet that typ

Brandon Keller, Kaitlin Yandik, Angela Ngo, Andy Meneely

Filenames are a concise means of conveying information about source code to fellow developers. One such convention is util. Commonly understood to stand for "utility", filenames with the letters util are often an indication that the file contains code that may be broadly useful or reusable. Some projects use this convention heavily, for example, the Apache T

Seth W. Kurfman, Philipp Geyer, Anoop Kamalasanan, Karl Heimrich

Strong-coupling experiments based on magnons enable the exploration into on-chip demonstrations involving numerous long-lived excitations. Yttrium iron garnet (YIG) has been considered for decades as a gold standard material for magnonics due to its low-loss magnonic properties. While YIG has successfully demonstrated strong-coupling in macroscopic device ge

Florian Wolf, Ilyas Fatkhullin, Niao He

Efficient exploration is a central problem in reinforcement learning and is often formalized as maximizing the entropy of the state-action occupancy measure. While unconstrained maximum-entropy exploration is relatively well understood, real-world exploration is often constrained by safety, resource, or imitation requirements. This constrained setting is par

Rafael R. Del Grande, David A. Strubbe

Exciton-phonon interactions in transition metal dichalcogenides (TMD) are strong and lead to phenomena such as coherent phonon generation. When stacked and twisted, their properties can be tuned by the twisting angle. In experiments with 1.1$^\circ$ twisted 2L WSe$_2$, a change of 0.1 {\AA} in the interlayer distance was observed when light was shone on this

Silvio Martinico, Franco Maria Nardini, Cosimo Rulli, Rossano Venturini

Multivector retrieval models achieve state-of-the-art effectiveness through fine-grained token-level representations, but their deployment incurs substantial computational and memory costs. Current solutions, based on the well-known k-means clustering algorithm, group similar vectors together to enable both effective compression and efficient retrieval. Howe

José Geraldo Telles Ribeiro, Americo Cunha

Asymmetric damping is widely used in passive vehicle suspensions, with rebound damping often recommended to exceed compression damping by a factor of two to three. Despite its prevalence, this guideline remains largely empirical and lacks a systematic derivation based on vehicle dynamics and excitation conditions. This paper presents a scenario-driven optimi

Yunnan Yu, Zhuoyue Zhao

Ad-hoc queries over frequently updated data in a flat schema are common in real-time data analysis applications and often require very low latency. Online aggregation can achieve so by providing approximate aggregation answers with confidence bound guarantees. It relies on the ability to draw samples online in a linear time to sample size rather than databas

Francisco M. Blanco

We study geodesic motion of a test particle in Schwarzschild spacetime. Bound and scattering geodesics are commonly described using Darwin variables, which provide a convenient parametrization of the radial motion. However, this description breaks down at the separatrix and does not extend straightforwardly to plunging trajectories. We construct an analytic

Chenxin Li, Zhengyang Tang, Mingxin Huang, Yunlong Lin

LLM agents are expected to complete end-to-end units of work across software tools, business services, and local workspaces. Yet many agent benchmarks freeze a curated task set at release time and grade mainly the final response, making it difficult to evaluate agents against evolving workflow demand or verify whether a task was executed. We introduce Claw-E

Tianyuan Wu, Chaokun Chang, Lunxi Cao, Wei Gao

Autonomous agents act through sandboxed containers and microVMs whose state spans filesystems, processes, and runtime artifacts. Checkpoint and restore (C/R) of this state is needed for fault tolerance, spot execution, RL rollout branching, and safe rollback-yet existing approaches fall into two extremes: application-level recovery preserves chat history but

Marcos V. S. Lima, Carlos H. S. Vieira, Irismar G. da Paz, Pedro R. Dieguez

Quantum measurement is physically realized through a finite dynamical interaction between a system and a measuring apparatus, giving rise to a continuous transition from weak to strong regimes. While this crossover is well understood under ideal conditions, the combined role of thermal instabilities and pre- and post-selection open dynamics has not been syst

Furkan Kınlı

Night Photography Rendering (NPR) poses a significant challenge due to the extreme contrast between dark and illuminated areas in scenes, stemming from concurrent capture of severely dark regions alongside intense point light sources. Existing methods, which are mainly tailored for fidelity metrics, reveal considerable perceptual gaps and often detract from

Katja Karhu, Kari Smolander, Jussi Kasurinen

There has been intense debate among qualitative researchers about whether generative AI is suitable for qualitative research. In this paper, we summarize the broader ongoing discussion of generative AI in qualitative research and its implications for software engineering researchers. The qualitative research approach, small-q (positivist or post-positivist)

Prithak Bhattarai, Andrew Brandt, Alan Bross, Bradley Brown

DAMSA (DArk Messenger Searches at an Accelerator) is a novel short-baseline accelerator/beam dump experiment aimed at probing short-lived physics processes, including searches for evidence of a dark sector of particle physics and well-motivated rare Standard Model signals. Motivated by open questions in neutrino physics and the absence of conclusive evidence

Zhong-Bo Kang, Andreas Metz, Daniel Pitonyak, Congyue Zhang

We develop a novel strategy for accessing the transversity parton distribution function (PDF) of the nucleon within collinear factorization using near-side energy-energy correlators in the dihadron fragmentation framework. We show how this removes the complications of previous approaches that must model either intrinsic parton transverse momentum or resonanc

Prashant Kulkarni

Multi-turn prompt injection follows a known attack path -- trust-building, pivoting, escalation but text-level defenses miss covert attacks where individual turns appear benign. We show this attack path leaves an activation-level signature in the model's residual stream: each phase shift moves the activation, producing a total path length far exceeding benig

M. Balli, L. Attou, S-E. Bouzarmine, S. Oubad

The RPO4 orthophosphates (R = rare earth element) have recently attracted a wide interest due to the strong coupling between their electronic, orbital and structural ordering parameters resulting in a variety of functional properties. Herein, we demonstrate that NdPO4 phases synthesized via a facile precipitation growth process unveil promise in low-temperat

C A Escobar Ruiz, H Olivares-Pilon, A M Escobar-Ruiz

Degenerate quantum eigenspaces can support substantial changes in nodal geometry at fixed energy. We show that, for the two-dimensional isotropic harmonic oscillator, this restructuring is organized by the Hermite-constrained algebraic curve \(P_N(x,y)=0\) associated with each real shell state, $\psi_N(x,y)=e^{-\alpha r^2/2}P_N(x,y)$. Finite singularities, \

Nina Seron-Abouelfadil, Poppy Fynes

Sign languages, of any geographical or accentual variation, understandably face continuous scrutiny under the ever present popularity of verbal dictation and audism. Through this, many potential problems arise with the current lack of accessible communication for those who rely on such sign languages for essential conversation. Such AI systems regularly take

Pierpaolo Uberti

In this research, starting from a widely accepted definition of risk, we support the idea that risk reduction is a more realistic objective than risk minimization, which represents a theoretical utopia. Furthermore, significant risk reduction can be achieved without relying on risk measurement and risk minimization. To this end, we propose a generalization o

Andrew Bond, Ilkin Umut Melanlioglu, Erkut Erdem, Aykut Erdem

Modern visual world modeling systems increasingly rely on high-capacity architectures and large-scale data to produce plausible motion, yet they often fail to preserve underlying 3D geometry or physically consistent camera dynamics. A key limitation lies not only in model capacity, but in the latent representations used to encode geometric structure. We prop

Sayonee Ray, Jezer Jojo, Jason Iaconis, Abeynaya Gnanasekaran

The Quantum Lattice Boltzmann Method (QLBM) has emerged as one of the most promising quantum computing approaches for the numerical simulation of problems in computational fluid dynamics (CFD). The dynamics is formulated in terms of mesoscopic particle distribution functions governed by a discrete Boltzmann transport equation, comprising local streaming and

Rahil Haria, Noah Schnitzer, T. Ben Britton, Yaqi Li

Polar metals, materials in which electric polarisation and metallicity coexist, are exceptionally rare because itinerant electrons screen long-range dipoles and favour centrosymmetric structures. Engineering polar textures in a conducting magnet holds promise for reconfigurable spin orbit coupling and magnetoelectric functionality. Here we show that releasin

Usha Bhalla, Thomas Fel, Can Rager, Sheridan Feucht

Sparse autoencoders (SAEs) are widely used to extract interpretable features from neural network representations, often under the implicit assumption that concepts correspond to independent linear directions. However, a growing body of evidence suggests that many concepts are instead organized along low-dimensional manifolds encoding continuous geometric rel

Kristian Blom, Doron Benyamin, Uwe Thiele, Oren Raz

We investigate temperature quenches across the reentrant phase transition of the antiferromagnetic Ising model in a magnetic field and show that the strong direct and inverse Mpemba effects arise when quenches terminate in the paramagnetic phase. These anomalous relaxation phenomena originate from the selective excitation of the slowest relaxation mode, whic

Ben Green, Mehtaab Sawhney

Denote by $p(k)$ the limit, as $n \rightarrow \infty$, of the probability that a random permutation on a set of size $n$ has an invariant set of size $k$. We give an asymptotic formula for $p(k)$, showing that it is asymptotically $f(\{\log_2 k\}) k^{-\delta} (\log k)^{-3/2}$ where $\delta = 1 - \frac{1 + \log \log 2}{\log 2} \approx 0.086$ and $f$ is a smoo

Zeyu Jiang, Changqing Zhou, Xingxing Zuo, Changhao Chen

Existing learning-based occupancy prediction methods rely on large-scale 3D annotations and generalize poorly across environments. We present FreeOcc, a training-free framework for open-vocabulary occupancy prediction from monocular or RGB-D sequences. Unlike prior approaches that require voxel-level supervision and ground-truth camera poses, FreeOcc operate

Djordje Bogdanović, Marija Dimitrijević Ćirić, Stefan Djordjević, Richard J. Szabo

We review the quantization of scalar field theory on $\lambda$-Minkowski space using the Batalin--Vilkovisky (BV) formalism. We consider $\phi^3$-theory in two different quantization schemes: standard and braided. While standard BV quantization is based on an ordinary $L_\infty$-algebra, braided BV quantization is based on a braided $L_\infty$-algebra. We co

Matti Berthold, Lydia Blümel, Giovanni Buraglio, Anna Rapberger

This work proposes novel splitting techniques for argumentation formalisms that incorporate supports between defeasible elements. We base our studies on bipolar set-based argumentation frameworks (BSAFs) which generalize argumentation frameworks with collective attacks (SETAFs), as well as bipolar argumentation frameworks (BAFs), by incorporating both collec

Qamrul Hasan Ansari, Feeroz Babu, D. R. Sahu, Jen Chih Yao

In this paper, we propose a scaled gradient modified non-monotone line search method for solving constrained minimization problems, and explore several specific properties of this method, namely, its convergence analysis. We discuss the linear convergence rate of the sequence generated by the proposed algorithm to a solution of the constrained minimization p

Junqi Gao, Dazhi Zhang, Zhichang Guo, Biqing Qi

Model merging has attracted attention as an effective path toward multi-task adaptation by integrating knowledge from multiple task-specific models. Among existing approaches, dynamic merging mitigates performance degradation caused by conflicting parameter updates across tasks by flexibly combining task-specific parameters at inference time, thereby maintai

Zhiyuan Huang, Shuo Li, Murat Arcak, Majid Zamani

This paper introduces a general approximate alternating simulation relation (\emph{$\varepsilon$-gAAS relation}) for continuous-time systems, which relaxes existing simulation relations to tolerate larger mismatches between abstract and concrete models. The definition of gAAS for continuous-time systems is first proposed, and its properties are investigated.

Akhil Gupta, Erhan Guven

Accurate state estimation of nonlinear dynamical systems is fundamental to modern aerospace operations across air, sea, and space domains. Online tracking of adversarial unmanned aerial vehicles (UAVs) is especially challenging due to agile nonlinear motion, noisy and sparse sensor measurements, and unknown control inputs; conditions that violate key assumpt

Emilio Méndez, Rocio Semino

Zn(imidazolate)$_2$ metal-organic frameworks (MOFs) exhibit a remarkable degree of polymorphism. Because of their promising industrial applications, many research groups have investigated phase transitions, phase diagram and relative stability of these polymorphs. There is now wide consensus in the research community that these MOFs are solvothermally formed

R. Mathew Roy, M. Povolotskiy, J. Kirschke, C. Prange

The realization of bulk metallic altermagnetism has remained elusive despite the growing number of candidate materials. Here, we present evidence that moderate cobalt substitution ($\sim$15%) drives the correlated narrow-gap semiconductor FeSb$_2$ into a metallic altermagnetic state persisting up to room temperature. The infrared optical conductivity reveals

Daniel Diz-Castro, Manuel Febrero-Bande, Wenceslao González-Manteiga

We provide a unified framework for independence and mean independence tests based on the Hilbert-Schmidt independence criterion, extending some previous results in the literature to hold in general topological spaces. We also present a complete theoretical analysis of the test statistic asymptotic behavior when the observed sample corresponds to a partial sa

Alexandre Ern, Johnny Guzmán, Pratyush Potu

We construct bounded, commuting projections for the three-dimensional de Rham complex with the additional property that the projections preserve the trace of functions/fields if the latter is a piecewise polynomial in the appropriate trace space. The projections are locally defined and stable in the graph norm. More precisely, the part of the graph norm invo

Arthur Corrêa, Paulo Nascimento, Samuel Moniz

Solving practical multi-depot vehicle routing problems (MDVRP) is a challenging optimization task central to modern logistics, increasingly driven by e-commerce. To address the MDVRP's computational complexity, neural-based combinatorial optimization methods offer a promising scalable alternative to traditional approaches. However, neural-based methods typic

Israely Lima, Lucas Moura Lourenço, Márcio Ribeiro, Ivan Machado

Software development is a sociotechnical and human-centered endeavor in which human factors directly influence quality, productivity, and innovation capacity. In this context, career development in computing goes beyond technical mastery, requiring competencies that enable professionals to deal with continuous change and collaborative demands. Among these, n

Ang Liu, Jingsong Shang, Jiangang J. Du, Shyamsunder Erramilli

Sensitive biomarker detection in physiological fluids is often limited by Debye screening, which suppresses electrostatic signals at sensor surfaces. Here we report a sensing approach based on flexoelectric resonance in silicon nanowire field-effect transistors. An applied radiofrequency field induces strain gradients in the nanowires, generating flexoelectr

Michael L. Whittaker, Pan Wang, Chunhui Li, Naman Katyal

The bond-valence model is a standard way to estimate bond strengths in crystals, but its exponential dependence on bond length has lacked a derivation from a specific physical interaction. We show that this form emerges as the leading-order limit of screened Coulomb electrostatics and that the fitted bond-valence softness can be interpreted in terms of an el

Dorottya Demszky, Edith Bouton, Alison Twiner, Sara Hennessy

Research on classroom interaction has long been divided between large-scale observation and in-depth ethnographic work. We propose a framework mapping this methodological space along three dimensions--scale, duration, and modality--where a study's position shapes what it reveals and obscures. We illustrate it through contrasting studies of dialogic teaching-

Doa Hashemi Asl, Kai Schmitz

Metastable cosmic strings are a common prediction of grand unified theories and act as a source of a gravitational-wave background (GWB) that can explain the 2023 pulsar timing array (PTA) signal. In this paper, we revisit the GWB signal from metastable strings, emphasizing the need to carefully distinguish between two different time scales: (i) t_LB, the ti

Ahammed Ullah, Alex Pothen

We propose new graph representations that exploit dense local structure to improve time and space simultaneously. Given an undirected graph $G$, we define a dual clique cover (DCC) representation of $G$ to be the pair $(C, L)$, where $C$ is a collection of cliques that covers the edges of $G$ and $L$ is the incidence dual of $C$. We identify classes of polyn

Johannes Dittloff, Lukas M. Wolz, Matthias U. Quintern, Laura I. Wagner

Ta$_{3}$N$_{5}$ is among the most intensively studied photoanode materials for solar-driven water oxidation, yet its performance often remains limited by short carrier lifetimes and defect mediated recombination. Although transient absorption spectroscopy is widely used to probe carrier dynamics in photoelectrodes, spectral assignments are frequently ambiguo

Arturo Tozzi

Percolation theory from statistical physics has been applied to several aspects of tumor progression. Tumor growth on percolation clusters has been used to model spatial expansion, vascular percolation to describe nutrient supply and transport related percolation to investigate drug and gene delivery. At the molecular level, mutational percolation has been e

Ivan Bercovich

Terminal-agent benchmarks have become a primary signal for measuring the coding and system-administration capabilities of large language models. As the market for evaluation environments grows, so does the pressure to ship tasks quickly, often without thorough adversarial review of the verification logic. This paper is a guideline for writing good benchmark

Nathan Carlson

In 1967 Hajnal and Juh{\'a}sz showed that the cardinality of a first-countable Hausdorff space with the countable chain condition has cardinality at most $\mathfrak{c}$, the cardinality of the real line. We give an improvement of this celebrated theorem by replacing ``first-countable" with the weaker condition ``each point has a countable centered local $\pi

Heda Zhang, Nikolai Peshcherenko, Ning Mao, Nianlong Zou

The nonlinear Hall effect (NLHE) connects crystalline symmetry to quantum geometry, offering a probe of band topology beyond linear transport. While most studies have focused on the Berry curvature dipole in low-symmetry crystals, mechanisms that directly probe Berry monopoles in higher-symmetry chiral lattices remain unexplored. Here, we report the observat

Yudong Cui, Tianchang Lu, Yusheng Zhang, Dong Mao

This article presents a systematic review of theoretical and experimental findings for bound states of two and several dissipative solitons in fiber lasers. The theoretical basis underlying the formation and stabilization of soliton molecules in the fibers, which is provided by the complex Ginzburg-Landau equations and bound states of such equations, is pres

Neelanjan Chakraborti, Sudeep Kumar Ghosh, Snehasish Nandy

Altermagnets host spin-split band structures while exhibiting vanishing equilibrium spin magnetization, making field-induced responses a direct probe of their quantum geometry. A central question, in this regard, is which quantum-geometric mechanism can generate a linear spin magnetization in centrosymmetric systems. Here we develop a unified framework based

Zainab Rehan, Christian Medeiros Adriano, Sona Ghahremani, Holger Giese

Rule-based systems remain central in safety-critical domains but often struggle with scalability, brittleness, and goal misspecification. These limitations can lead to reward hacking and failures in formal verification, as AI systems tend to optimize for narrow objectives. In previous research, we developed a neuro-symbolic causal framework that integrates f

G. Diaz, J. I. Dıaz

This paper investigates the existence and uniqueness of solutions for a nonlinear evolution equation governed by an m-accretive operator A in a Banach space, presenting a perturbation term that does not satisfy the Lipschitz condition.

Swapnajit Das

In this article we show that the semi log canonical abundance for compact K\"ahler varieties fails in dimension $3$. More specifically we construct a counterexample of a compact K\"ahler (irreducible) slc threefold $(X, 0)$ such that $K_X$ is nef and $\kappa(\tilde X, K_{\tilde X}+\tilde D)=0$, where $\mu:(\tilde X, \tilde D)\to X$ is the normalization morph

Mahuizi Lu, Kelin Jia, Rajib Goswami, Yukun Hu

The rapid electrification and intelligence of modern transportation systems place stringent demands on the electromagnetic compatibility, reliability, and adaptability of automotive power electronics. In electric and autonomous vehicles, electromagnetic interference (EMI) generated by high-frequency switching power converters can compromise safety-critical f

Doolos Aibek Uulu, Meruyert Khamitova, Rui Chen, Liang Chen

Semiconductor-based plasmonic nanostructures support localized surface plasmon modes in the infrared region. Unlike metallic nanostructures, they support both free electrons and holes, requiring a two-fluid hydrodynamic Drude equation (HDE) to accurately capture spatial dispersion effects and low-frequency acoustic plasmon modes that cannot be described by s

Anietta Weckauff, Yuchen Zhang, Maksym Andriushchenko

Fine-tuning large language models (LLMs) on narrowly misaligned data generalizes to broadly misaligned behavior, a phenomenon termed emergent misalignment (EM). While prior work has found a correlation between harmful behavior and self-assessment in emergently misaligned models, it remains unclear how consistent this correspondence is across tasks and whethe

Aram Shojaei, Edmondo Valvo, Maximilian Rimbach-Russ, Eliska Greplova

Planar germanium heterostructures hosting hole-spin qubits are among the leading platforms for scalable semiconductor-based quantum computing. Yet, device performance is hindered by significant quantum dot variability, which leads to uncertainty in qubit energy levels and random orientations of the spin quantization axis. Tailored control of the g-tensor off

Shudi Weng, Ming Xiao, Mikael Skoglund

This paper studies a key research question: how to achieve perfect privacy in over-the-air computation (AirComp)? The problem is particularly intriguing due to a dilemma. Real-field operations can ensure invertibility but generally introduce statistical dependence, resulting in inevitable privacy leakage. In contrast, modulo operations can decorrelate the ou

Yujin Han, Yujie Wei, Yefei He, Xinyu Liu

Despite rapid advances in photorealistic video generation, real-world applications such as filmmaking require video aesthetics, e.g., harmonious colors and cinematic lighting, beyond visual fidelity. Prior work on visual aesthetics largely focuses on images, often reducing aesthetics to coarse definitions, e.g., visual pleasure, without a rigorous and system

Dilek Yildiz, Sungmin Kim, Dengyu Yang, Muqing Yu

Superconductivity in strontium titanate has remained enigmatic for more than 50 years. The LaAlO$_3$/SrTiO$_3$ (LAO/STO) heterointerface enables systematic dimensional confinement, from a two-dimensional electron gas to quasi-one-dimensional nanostructures, providing access to this quantum state. Transport measurements in patterned devices reveal puzzling ph

Ansar Aynetdinov, Patrick Haller, Alan Akbik

Recent research has shown that filtering massive English web corpora into high-quality subsets significantly improves training efficiency. However, for high-resource non-English languages like German, French, or Japanese, aggressive filtering creates a strategic dilemma: should practitioners prioritize diversity by training once on large amounts of lightly f

A. M. Carulli, F. L. Vieyro, M. M. Reynoso, E. J. Marchesini

The WISE source, J141046.00+740511.2, has been recently observed from radio to $\gamma$ rays. Although the optical spectrum is consistent with a BL Lacertae (BL Lac) object, the source displays unusually weak radio emission, which challenges standard interpretations. Our aim is to understand the origin of the broadband emission from J141046.00+740511.2, usin

René Peschmann

Building on the genus-3 reduction $C_A : w^2 = \lambda^8 + A \lambda^4 + 1$ established in our companion paper (arXiv:2604.09328), we give an unconditional proof of the perfect-cuboid conjecture ("Conjecture B") on $1{,}072$ explicit master-tuple fibers, excluding all rational $(a,b)$-specialisations on each such fiber. Our three main contributions are: (i)

Nazar Pyvovar, Hao Li, Zhaowei Dai, Owen D. Miller

To couple many independent modes from free space to on chip, the key challenge is not enhancing the many necessary coupling rates (scattering-matrix elements) between targeted mode pairs. Instead, the key is to avoid additional cross-couplings to undesired modes, due to the presence of multiple simultaneously satisfied phase-matching conditions. With this pr

Sofía Pérez Casulo, Marcelo Fiori, Bernardo Marenco, Federico Larroca

Hyperbolic geometry has emerged as an effective latent space for representing complex networks, owing to its ability to capture hierarchical organization and heterogeneous connectivity patterns using low-dimensional embeddings. As a result, numerous hyperbolic graph representation learning methods have been proposed in recent years. However, their practical

C. Kelly, G. J. Lord, M. Ptashnyk, S. Sonner

We investigate the dynamics of dissipative systems with stochastic forcing and focus in particular on mean-square stability. First we show, under a natural condition on the drift and diffusion, that the stochastic system is mean-square dissipative. Next we examine the linearised system and state conditions ensuring that perturbations of a linear system with

Takuma Imamura

The impossibility of eliminating hallucination, understood here as incorrect definite answers, in sufficiently expressive yes-or-no formal domains is an immediate consequence of classical undecidability theorems. This note does not revisit that forced-answer obstruction as its main claim. Instead, it attempts to formally describe the corresponding limitation

Sahan Sanjaya, Hari Krishna Parvatham, Emma Andrews, Prabhat Mishra

Quantum machine learning (QML) provides a promising framework for leveraging quantum-mechanical effects in learning tasks. However, its vulnerability to adversarial perturbations remains a major challenge for practical deployment. In QML systems, small perturbations applied to classical inputs can propagate through the quantum encoding stage and distort the

Seyyed Jabbar Mousavi, Vivek Unikandanunni, Niccolo Sellati, Paolo Barone

In ferroelastic materials, spontaneous symmetry breaking leads to the formation of twin domains. Although the bulk crystal typically remains centrosymmetric, inversion symmetry can be locally broken at the domain walls, potentially changing phonon selection rules and enabling local anharmonic phonon coupling. Here we report direct evidence of such anharmonic

Chialoon Cheng, Kaijun liu, Zhiyang Liu, Marcelo H Ang

This comprehensive review examines the evolution and the current state of the art in three-dimensional (3D) reconstruction techniques in manufacturing applications. The analysis covers both traditional approaches and emerging deep learning methods, showing a critical research gap in unified 3d reconstruction frameworks. Through systematic review of 106 recen

K. E. S. Mendes, D. T da Silva, M. L. L. da Silva

We investigate the photoproduction of the tensor meson $f_2(1270)$ on the proton within a Regge-based framework, focusing on the reaction $\gamma p \to p f_2(1270)$ in the few-GeV energy region. The production mechanism is modeled through the exchange of vector-meson Regge trajectories in the $t$-channel, including both $\rho$ and $\omega$ exchanges with phe

Arpan Chatterjee, Stefan Groote

Baryons, as three-quark bound states, require a covariant treatment in the intermediate-energy regime where perturbative QCD is no longer applicable and where nonperturbative correlations dominate. This article reformulates the content of the CERN Baltic Conference 2025 presentation on baryonic bound states in the non-local Nambu--Jona-Lasinio (NJL) model. W

Ana Luisa Foguel, Eduardo S. Fraga

Core-collapse supernovae provide natural laboratories for the production of new light particles. In particular, axion-like particles (ALPs) can be constrained via SN1987A cooling arguments. However, significant astrophysical and nuclear uncertainties imply that such bounds may vary strongly depending on modeling choices, even when expensive simulations are e

Zhen He, Nika Salia, Casey Tompkins, Xiutao Zhu

We study Tur\'an-type extremal problems for distance graphs, motivated by work of Csikv\'ari, Bollob\'as, Tyomkyn, and Uzzell. We determine the maximum number of vertex pairs at distance three in an $n$-vertex graph with no triangle formed by these pairs, resolving the first case of a conjecture of Tyomkyn and Uzzell. We also determine the maximum number of

Hao Li, Nazar Pyvovar, Zhaowei Dai, Owen D. Miller

We apply a systematic inverse design approach to discover foundry-compliant, multilayer grating couplers that can efficiently couple a number of independent waves from free space to on-chip propagating modes. For visible- and near-infrared couplers, we find that minimum feature sizes are by far the most important constraint to tailor the design algorithms ar

James O'Hara, Karl Wunderlich, Gregory Stevens

As autonomous vehicles slowly deploy into urban roads for limited use cases with significant edge case issues, closed facilities like marshaling yards provide a ripe case for combining lower-level vehicle autonomy with fixed infrastructure to create full autonomy without similar edge case concerns. Within a delivery marshaling yard, electric fleet vehicles c

Feiyu Wu, Xu Zheng, Zhuocheng Wang, Yi ming Dai

Large language models (LLMs) make reward design in reinforcement learning substantially more scalable, but generated rewards are not automatically reliable training objectives. Existing work has focused primarily on generating, evolving, or selecting reward candidates, while paying less attention to when such candidates can be verified and deployed during po

Qing Lyu, Jeremy Hudson, Mohammad Kawas, Yuming Jiang

Individualized Alzheimer's disease (AD) progression prediction requires models that use irregular visits, account for censoring, avoid diagnostic leakage, and provide calibrated horizon risks. We propose PROgression-aware MultI-horizon Survival Estimation for Alzheimer's Disease (PROMISE-AD), a leakage-safe survival framework for predicting conversion from c

B-A. Courchene, A. Hampel, S. Beck, J. R. Paudel

Emergent magnetic states at oxide interfaces arise from the interplay of charge transfer, orbital reconstruction, and dimensional confinement, offering a route to engineered correlated-electron behavior in nanoscale spintronic materials. Here, we combine in situ synthesis, polarization-dependent angle-resolved photoelectron spectroscopy, X-ray magnetic circu

Shreya Chappidi, Jatinder Singh

Responsible AI research typically focuses on examining the use and impacts of deployed AI systems. Yet, there is currently limited visibility into the pre-deployment decisions to pursue building such systems in the first place. Decisions taken in the earlier stages of development shape which systems are ultimately released, and therefore represent potential,