April 2026 arXiv papers — page 6

Ramanpreet Kaur

In \cite{Bedford}, the dynamics of a particular polynomial diffeomorphism of $\mathbb{C}^N$, called a polynomial shift-like map of type $\nu$, has been studied as a higher dimensional analog of H\'enon maps. In this note, we prove that the Julia set of their transcendental counterpart is non-empty. In addition, an example of a transcendental shift-like map w

Maryna Prus, Lenka Filová, Hans-Peter Piepho, Waqas Ahmed Malik

Plant breeding and variety trials are usually conducted in multiple environments sampled from a defined target population of environments in order to characterize the performance of breeding lines or varieties. When the population is large and heterogeneous, it may be sub-divided into sub-regions or zones according to administrative and agro-ecological crite

Simon Althaus, Nikolaos Alexopoulos, Max Mühlhäuser, Christian Reuter

System auditing on Android faces two problems. First, existing syscall tracers lose events under load, silently overwriting entries faster than a user space reader can drain them. Second, security-relevant application behavior is mediated through Binder, Android's kernel IPC mechanism, and is therefore hidden from the syscall layer. The Binder parcels that t

Kh. P. Gnatenko

We propose a method for constructing multi-qubit entangled quantum states representing weighted tripartite graphs. An expression for the entanglement distance for multi-qubit states corresponding to arbitrary tripartite graph structures is obtained. The entanglement of a qubit with the rest of the system in a quantum graph state is determined by the weights

Madeline Howell, Jennifer A. Johnson, Marc H. Pinsonneault, Leslie M. Morales

Open clusters are fundamental laboratories for investigating stellar and Galactic evolution, and serve as important benchmarks for asteroseismic analyses. Using a boutique method to analyze TESS photometry, we study red giants in two old metal-rich open clusters: NGC 188 & NGC 6791. By comparing Kepler and TESS observations for NGC 6791, similar oscillation

Albert Jiménez-Ramos, Juan J. Hidalgo

We analyze the mixing, migration and spreading of a gravity current in a heterogeneous porous medium using high-fidelity numerical simulations. Heterogeneity is represented by log-normal permeability fields of varying correlation lengths and variance. Stable and unstable density stratification scenarios are considered through linear and non-monotonic density

Ravi Kumar, Saksham Mahajan, Felix Donaldson, Leonardo Santoni

Degradation of near surface nitrogen vacancy (NV) centers in diamond under optical illumination has restricted their deployment in applications such as scanning NV magnetomety, particularly under harsh environment such as low temperatures and vacuum. Previously, alumina passivation of planar diamond samples has been shown to reduce the degradation of near su

Hina Saeeda, Soniya Abraham

AI integration in automotive perception systems shifts requirements from static specifications to continuously evolving entities shaped by data, models, and operating contexts. When such changes are not consistently documented, validated, and traced, they accumulate as Requirements Debt (ReD), an underexplored but critical subtype of technical debt. This stu

Farrokh Labib, David Nicholaeff, Vincent Russo, William J. Zeng

Accurately characterizing multipartite entangled states is a critical challenge in quantum information processing. In this work, we focus on applying compressed sensing techniques to efficiently estimate the fidelity of Greenberger-Horne-Zeilinger (GHZ) states. By exploiting the inherent sparsity of these states, our compressed sensing protocol drastically r

Gergely Csáji, Zhaohong Sun

Stable matching theory is the foundation of centralized clearinghouses worldwide, from school choice programs to medical residency allocations. However, incorporating complex distributional goals-such as multi-dimensional diversity quotas or sibling co-assignment guarantees-often compromises stability or renders the problem computationally intractable. The e

V. I. Kuznetsov, O. V. Trofimov

We measured the critical temperatures and critical switching and retrapping currents of wide and narrow thin-film quasi-one-dimensional superconducting aluminum structures of the same thickness in zero magnetic field. For the first time, we found that the narrower the structure, the lower the critical temperature and critical current density in the structure

Nimrod Millenium Ndulue, Jose Andres Millan-Romera, Matteo Giorgi, Holger Voos

Accurate localization is a fundamental requirement for autonomous robots operating in indoor environments. Scene graphs encode the spatial structure of an environment as a hierarchy of semantic entities and their relationships, and can be constructed both online from robot sensor data and offline from architectural priors such as Building Information Models

Mohit Dubey, Open Gigantic

Every document format in existence was designed for a human reader moving linearly through text. Autonomous LLM agents do not read - they retrieve. This fundamental mismatch forces agents to inject entire documents into their context window, wasting tokens on irrelevant content, compounding state across multi-turn loops, and broadcasting information indiscri

Haonan Li, Tianjun Sun, Yongqing Wang, Qisheng Zhang

Multi-server MCP agents create an information-flow control problem: faithful tool composition can turn individually benign read/write permissions into cross-boundary credential propagation -- a structural side effect of workflow topology, not necessarily malicious model behavior. We present MCPHunt, to our knowledge the first controlled benchmark that isolat

Jona te Lintelo, Lichao Wu, Marina Krček, Sengim Karayalçin

Mixture-of-Experts (MoE) architectures in Large Language Models (LLMs) have significantly reduced inference costs through sparse activation. However, this sparse activation paradigm also introduces new safety challenges. Since only a subset of experts is engaged for each input, model behavior becomes coupled to routing decisions, yielding a difficult-to-cont

Koki Okada, Kenta Kasai

We study square-base Calderbank--Shor--Steane (CSS) hypergraph-product codes as a finite-length class for regular high-girth quantum low-density parity-check (LDPC) design. For base matrices of small column weight, we give checkable conditions for regularity, rank deficiency, and short-cycle exclusion, and we present explicit column-weight-three and column-w

Ebru Nayir, Melissa Özsahakyan

We show that the VC-density in certain theories of oriented abelian groups is at most the size of parameter variables, which yields dp-minimality. We further prove that the VC-density of formulas in pairs of such models is bounded by twice the size of parameter variables. This uniform upper bound is shown to be sharp, and as a consequence, we show that such

Mohammad Akhond, Massimo Bianchi, Antonio Cristofaro, Fabio Riccioni

An asymptotically flat spacetime in $D=4$ can be mapped via Couch-Torrence conformal inversion to the geometry around an extremal non-expanding and non-rotating horizon. At the linearized level, an infinite tower of conserved Newman-Penrose charges can be found at null-infinity, while infinitely many Aretakis charges are conserved in the near-horizon. Couch-

Christian Klötergens, Vijaya Krishna Yalavarthi, Lars Schmidt-Thieme

Joint probabilistic modeling is essential for forecasting irregular multivariate time series (IMTS) to accurately quantify uncertainty. Existing approaches often struggle to balance model expressivity with consistent marginalization, frequently leading to unreliable or contradictory forecasts. To address this, we propose CircuITS, a novel architecture for pr

Jonathan B. Hill

We construct a block bootstrap max-test for detecting the presence of significant predictors in a high dimensional setting, allowing for weakly dependent and heterogeneous (possibly non-stationary) data. The number of covariates to be screened may be large $p$ $>>$ $n$, and growing at an exponential rate, provided $\ln (p)$ $=$ $o(n^{a})$ for some $a$ $>$ $0

Andrea Bardin, Francesco Lorenzi, Luca Salasnich

We investigate the superfluid dynamics of a Josephson junction beyond the mean-field description, incorporating the role of thermal fluctuations as well as quantum fluctuations. Using a formalism that accounts for the fluctuations in a homogeneous gas, and under the assumption that the transport of the non-condensed component is negligible, we derive a corre

Emanuele Venieri, Simone Manoni, Alberto Florian, Jaehyun Park

High Bandwidth Memory with Processing-in-Memory (HBM-PIM) offers an opportunity to reduce data movement by executing computation directly inside memory, but current commercial platforms expose limited instruction sets and require specialized software stacks. In this work, we investigate whether HBM-PIM can serve as a backend for ISA-level matrix acceleration

Behnaz Ranjbar, Kirankumar Raveendiran, Sudeep Pasricha, Samarjit Chakraborty

The design of embedded safety-critical systems such as those used in next-generation automotive and autonomous platforms, is increasingly challenged by escalating system complexity, hardware-software heterogeneity, and the integration of intelligent, data-driven components. Ensuring dependability in such systems requires a holistic approach that spans multip

Sam Blake

We give a self-contained, modern exposition of \'Edouard Goursat's 1887 theorem on pseudo-elliptic integrals -- those integrals of the form $\int F(t)\,\d t/\sqrt{R(t)}$ with $R$ a cubic or quartic polynomial that, despite living on a genus-$1$ algebraic curve, admit elementary antiderivatives. After reviewing integration in finite terms and Liouville's theo

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li

Cross-chain NFT migration refers to the process of transferring digital assets along with their associated functionalities and guarantees between distinct blockchain platforms. However, architectural divergences among these platforms introduce critical challenges, often resulting in features that fail to behave as intended. While protocol-level mechanisms ca

Ishrak Hamim Mahi, Siam Ferdous, Md Sakib Sadman Badhon, Nabid Hasan Omi

The rapid proliferation of image generation models and other artificial intelligence (AI) systems has intensified concerns regarding data privacy and user consent. As the availability of public datasets declines, major technology companies increasingly rely on proprietary or private user data for model training, raising ethical and legal challenges when user

Krzysztof Siwek, Tran Hoai Linh, Tomasz Gryczka, Maciej Stodolski

The verification of bullion coin authenticity is essential for maintaining integrity within the precious metals market; however, the increasing sophistication of counterfeits has rendered traditional inspection methods insufficient. This paper proposes a non-destructive verification framework based on acoustic frequency analysis and deep neural networks. The

Hanno von Bergen, Larissa Fastenau, Enna Gerhard, Nicola Lorenz

We study solution discovery, where the goal is to obtain a feasible solution to a problem from an initial configuration by a bounded sequence of local moves. In many applications, however, the graph that defines which vertex sets are feasible is not the same as the graph that governs how tokens, agents, or resources may move. Existing models such as token sl

Javier Blanco-Romero, Florina Almenares Mendoza

Lattice reduction smooths the Gram-Schmidt profile, and we use majorization to describe the local swap mechanism behind that smoothing. In this language, each non-degenerate Lov\'asz swap acts as a T-transform on the log-norm profile. As a consequence, every strictly Schur-convex measure of profile spread decreases at such a swap. Two structural consequences

Ajit Kumar Kushwaha, Dinkar Mishra, Shivani Aggarwal, Saumya Singh

The excitation of plasma wakefields driven by chirped laser pulses is investigated using a reduced relativistic fluid Poisson model supported by fully relativistic particle in cell (PIC) simulations. The study considers exponential, linear, quadratic, and unchirped phase-modulated laser drivers propagating in an underdense plasma. Numerical solutions of the

Rachit Mehra, M Parimi, Amol Yerudkar, S. R. Wagh

We present a unifying Nearly Asymptotically Invariant Manifold (NAIM) framework for understanding Nesterovs Accelerated Gradient (NAG) method. By lifting the first-order gradient flow into a second-order phase space we construct a NAIM a slow, attracting graph and show that acceleration emerges from a curvature aware perturbation of this graph. The evolving

Vishnuprasadh Kumaravelu, Sunil Gupta, P. K. Srijith

Exponential growth in the scale of modern foundation models has led to the widespread adoption of Low-Rank Adaptation (LoRA) as a parameter-efficient fine-tuning technique. However, standard LoRA implementations disregard the varying intrinsic dimensionality of model layers and enforce a uniform rank, leading to parameter redundancy. We propose Post-Optimiza

CMS Collaboration

A search is presented for a light charged Higgs boson H$^\pm$ in top quark pair production ($\mathrm{t\bar{t}}$), where one of the top quarks decays to an H$^\pm$ and a bottom quark, while the other decays to a W$^\mp$ boson and a bottom quark. The H$^\pm$ is assumed to decay into a charm and a strange quark, whereas the W$^\mp$ boson decays into a charged l

Feiyu Peng, Hongfei Shu

We develop the ODE/IM correspondence for the higher-order Mathieu equation arising from the quantum Seiberg-Witten curve of the pure $SU(r+1)$ ${\cal N}=2$ supersymmetric Yang-Mills theory. From the subdominant solutions, we construct the Q-/Y-systems and derive the corresponding TBA equations. The dependence of the moduli parameters is found to be encoded i

Zakhar Kabluchko, Philipp Schange

Let $X_1,\ldots,X_n$ be independent random points in the closed unit ball of $\mathbb{R}^d$. Assume that each $X_i$ has a beta distribution with parameter $\beta_i \ge -1$: if $\beta_i>-1$, then $X_i$ has Lebesgue density proportional to $(1-\|x\|^2)^{\beta_i}$ on $\{\|x\|<1\}$, whereas the case $\beta_i=-1$ corresponds to the uniform distribution on the uni

Don van den Bergh, Merlise A. Clyde, Adrian E. Raftery, Maarten Marsman

Bayesian variable selection requires sampling from a posterior distribution that combines discrete model indicators with continuously varying parameters, a challenge often addressed through reversible jump Markov chain Monte Carlo (RJMCMC). Despite its generality, RJMCMC is widely regarded as difficult to design and implement correctly. We present mixtures o

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li

Decentralized, agentic AI marketplaces are rapidly emerging to support software engineering tasks such as debugging, patch generation, and security auditing, often operating without centralized oversight. However, existing reputation mechanisms fail in this setting for three fundamental reasons: agents can strategically optimize against evaluation procedures

Riley Grossman, Songjiang Liu, Michael K. Chen, Mike Smith

Generative AI is being increasingly integrated into web search for the convenience it provides users. In this work, we aim to understand how generative AI disrupts web search by retrieving and presenting the information and sources differently from traditional search engines. We introduce a public benchmark dataset of 11,500 user queries to support our study

Mohd Sameen Chishti, Damilare Peter Oyinloye, Jingyue Li

Large Language Models (LLMs) are increasingly used as core dependencies in software systems. However, the hosted LLM services evolve continuously through provider-side updates without explicit version changes. These silent updates can introduce behavioral drift, causing regressions in functionality, formatting, safety constraints, or other application-specif

Xiaozhou Zan, Hangzhe Li, Jiawei Guo, Gengdong Zhou

Rhombohedral graphene with topological flat bands offers an ideal platform for realizing correlated and topological quantum phases. Here we investigate hBN aligned eight-layer rhombohedral graphene moire superlattices, which host a robust quantum anomalous Hall (QAH) state alongside three unconventional superconducting phases. For electron-doped carriers awa

Chendi Qian, Christopher Morris

Semidefinite programs (SDPs) are a powerful framework for convex optimization and for constructing strong relaxations of hard combinatorial problems. However, solving large SDPs can be computationally expensive, motivating the use of machine learning models as fast computational surrogates. Graph neural networks (GNNs) are a natural candidate in this setting

Hai-Jun Li

We propose a novel and generalized mechanism, dubbed stochastic axion mixing. In a multi-axion framework, this mixing occurs naturally provided that the masses of all ultra-light axion-like particles (ALPs) are distinct and lighter than the zero-temperature mass of the QCD axion. Crucially, this mechanism is independent of the relative magnitudes of the axio

Yu. A. Biriukov, R. D. Morozov, I. V. Dyakonov, S. S. Straupe

This paper addresses the problem of finding the densest $k$-vertex subgraph in an arbitrary graph. This problem is NP-hard and has important applications in social network analysis, fraud detection, recommendation systems, and bioinformatics. We propose two quantum approaches to solve this problem: reduction to Quadratic Unconstrained Binary Optimization (QU

Carmine Cesarano, Martin Monperrus

AI systems rest on software with low integrity mechanisms, leaving AI systems exposed across every stage from data acquisition to final inference. This paper makes the AI supply chain a first-class object of analysis, decomposing it across four architectural layers: data acquisition, model training, model inference, and a cross-cutting substrate. Within thes

Arnau Ayguadé Domingo, Miquel Alberti-Binimelis, Cristian Gutierrez-Gomez, Emanuele Parisi

Large Language Models (LLMs) have rapidly improved in performance across code-related tasks, making their integration into Register Transfer Level (RTL) development increasingly attractive. Mimicking the behavior of inline code assistants, many benchmarks evaluate LLMs' capabilities in code completion, either assessing the generation of entire hardware modul

F. Tolea, M. Tolea

We model a direct solid-state phase transition through a nucleation-and-growth process in which plates have simple, regular shapes - squares, cubes, or square-faced lamellae - and grow homothetically (self-similarly) until they either reach a randomly assigned maximum size or are stopped by impingement with previously formed plates. The reverse transformatio

Qiang Tan, Zuyi Zhang

The main theorem of the paper provides an existence criterion of holomorphic discs for higher $A_\infty$ operations. The key step is to show that if a minimal disc in a K\"ahler manifold with boundary in a sequence of Lagrangian submanifolds intersecting transversely such that its partial Maslov indices are either all no less than $1$ or all no larger than $

Julianna Winnik, Adam Walocha, Wojciech Ogonowski, Wiktor Forjasz

We present YOSO (You Only Shot Once), a single-frame phase retrieval framework for digital in-line holographic microscopy (DIHM) in which supervised deep learning is used to numerically generate an additional hologram corresponding to different defocus distance, creating a so-called multi-height dataset, which is then conventionally processed with a well-est

Jinchao Li, Yunxin Li, Chenrui Zhao, Zhenran Xu

While GUI agents have shown impressive capabilities in common computer-use tasks such as OSWorld, current benchmarks mainly focus on isolated and single-application tasks. This overlooks a critical real-world requirement of coordinating across multiple applications to accomplish complex profession-specific workflows. To bridge this gap, we present a computer

Yevgeny Slobodkin, Ori Katz

Photoacoustic imaging is the leading technique for deep tissue optical imaging, allowing single-shot imaging at depths. However, its resolution may be limited by acoustic aberrations, caused by natural unknown heterogeneities in the tissue speed of sound. In recent years, reflection-matrix based scattering-compensation techniques have been successfully emplo

Amare Abebe

Cosmology has entered a precision era in which discrepancies between independent datasets, most notably the $H_0$ and $S_8$ tensions, have become robust and statistically significant. These tensions are no longer isolated anomalies but increasingly appear as global consistency constraints on the underlying cosmological model, defining what we will refer to h

Davide Ferrari

A test of uniformity on [0,1] is developed for the setting of a single observation recorded with sufficient precision. Although consistency against general alternatives is not attainable with only one draw in the classical large-sample sense, a multiscale harmonic digit expansion provides a framework for structured inference. By aggregating trigonometric com

Jonas G. Matt, Saverio Bolognani, Florian Dörfler

We study the design of functional incentive mechanisms for dynamical systems, in which a leader designs a fixed incentive function to motivate a self-interested follower to actuate the system beneficially over an extended horizon, without real-time revision of the incentive. This stands in contrast to the adaptive paradigm, in which the incentive is itself a

Tudor-Gabriel Dumitru, Anna Sitek, Gunnar Thorgilsson, Sigurdur I. Erlingsson

We study theoretically the spin-orbit interaction of electrons confined in a tubular semiconductor nanowire, between an inner semiconductor core and an outer metallic extra shell. A band off-offset potential is present at the inner semiconductor-semiconductor interface and a more complex potential barrier at the outer metal-semiconductor contact. The cross s

Christian Oswald, Josef Kulmer, Franz Pernkopf

In this paper, we extend our method [1] for FMCW radar mutual interference mitigation (IM) based on the discrete fractional Fourier transform (DFrFT). Firstly, we propose a radar signal processing chain including our DFrFT-based IM for real-valued receivers, which we compare to reference algorithms on a synthetic data set. We then reduce computational comple

Abdelrahman Sadallah, Kareem Elozeiri, Mervat Abassy, Rania Elbadry

Poetry has long been a central art form for Arabic speakers, serving as a powerful medium of expression and cultural identity. While modern Arabic speakers continue to value poetry, existing research on Arabic poetry within Large Language Models (LLMs) has primarily focused on analysis tasks such as interpretation or metadata prediction, e.g., rhyme schemes

Ekram Alam, Jaydip Sanyal, Akhil Kumar Das, Arijit Bhattacharya

Mango cultivation is crucial in the agricultural sector, significantly contributing to economic development and food security. However, diseases affecting mango leaves can significantly reduce both the production and overall fruit grade. Detecting leaf diseases at an early stage with precision is key to effective disease prevention and sustaining crop produc

Zhuoran Pan, Yue Li, Zhi Guan, Jianbin Hu

The emergence of Large Language Models (LLMs) offers a transformative interface for Web3, yet existing benchmarks fail to capture the complexity of translating high-level user intents into functionally correct, state-dependent on-chain transactions. We present \textsc{Intent2Tx}, a high-fidelity benchmark featuring 29,921 single-step and 1,575 multi-step ins

Sudeshna Lahiri, Sarita Ojha, Riddhick Birbonshi

In this paper, we compute the iterated Aluthge transforms $\widetilde{C_\phi}^{(n)}$ of the composition operator $C_\phi$ on the weighted Bergman spaces $\mathcal{A}_\alpha^2(\mathbb{D})$, where $\phi(z)=az+(1-a)$ for $0<a<1$. Also, we obtain the norm and numerical radius of $\widetilde{C_\phi}^{(n)}$ on $\mathcal{A}_\alpha^2(\mathbb{D})$. We establish that

Timon Schapeler, Fabian Schlue, Isabell Mischke, Michael Stefszky

Photon counting is a cornerstone of quantum optics. Here, we demonstrate precisely counting from 0 to over 9000 photons, beating the Poisson noise limit by at least $4.1~\mathrm{dB}$ across this range. We achieve sub-single-photon precision up to 276 photons per pulse. To do so, we multiplex eight intrinsically photon-number-resolving superconducting nanowir

Yuri Z. Sinzato, Annemieke M. Drost, Dedmer B. Van de Waal, Robert Uittenbogaard

Toxic cyanobacterial blooms are a growing environmental concern that affects freshwater ecosystems, drinking water supplies, and public health. The cyanobacterium Microcystis is among the most important bloom forming species. It often grows in large colonies, which enhances its flotation, reduces grazing, and improves nutrient regulation. Microcystis cells a

Jiutian Zeng, Junjie Li, Chengwei Dai, Jie Liang

We present XekRung, a frontier large language model for cybersecurity, designed to provide comprehensive security capabilities. To achieve this, we develop diverse data synthesis pipelines tailored to the cybersecurity domain, enabling the scalable construction of high-quality training data and providing a strong foundation for cybersecurity knowledge and un

Gurucharan Srinivas, Joshua Niemeijer, Frank Köster

Integrating domain knowledge into deep neural networks is a promising way to improve generalization. Existing methods either encode prior knowledge in the loss function or apply post-processing modules, but both depend on identifying useful symbolic knowledge to integrate. Since such rules are often unavailable in real-world vision tasks, we propose a method

Nuutti Hyvönen, Yuya Suzuki

This work studies numerical integration by the M\"obius-transformed trapezoidal rule, which combines the classical trapezoidal rule with a change of variables induced by a M\"obius transformation that maps the unit circle onto the real line. It is shown that this method achieves the optimal convergence rate for a polynomially weighted integral over the real

Sarah E. Dean, Neuton Li, Josephine Munro, Benjamin Laudert

Multispectral polarisation imaging has a broad range of applications, from biological cell imaging to agricultural remote surveying. For such applications, especially involving lightweight unmanned aerial vehicles like drones, it is necessary to have compact, single-shot, efficient optical systems. We present a metasurface design that diffractively separates

Amit Kumar, Mahen Gandhi, Meher Bhardwaj, Hrishikesh Ethari

Open-source projects often rely on a small group of highly active contributors known as hero developers. Prior work shows that hero developers are common in many OSS and enterprise projects, yet who qualifies as a hero depends heavily on the chosen contribution metric. Code-based metrics identify implementation-focused developers, whereas discussion-based me

Sohail Sarkar

The Big-Line-Big-Clique Conjecture of Kara, Por and Wood asserts that, for every fixed $k$ and $\ell$, every sufficiently large finite planar point set contains either $k$ collinear points or $\ell$ pairwise visible points. We prove a quantitative form in two structured regimes and isolate the precise ambient obstruction to the full conjecture. The main resu

Salman Jan, Toqeer Ali Syed, Shahid Kamal, Qamar Wali

This article outlines a new framework of traffic light optimization through a digital twin of the transport infrastructure, managed by agentic AI to ensure real-time autonomous decisions. The framework relies on physical sensors and edge computing to measure real-time traffic information and simulate traffic flow in a constantly updated digital twin. The tra

Javira Altmann, Lorenzo Bernardinis, Peter Skands, Valentina Zaccolo

Measurements at LHC show an increased production of strange hadrons with charged multiplicity in pp collisions, which is not described by the Lund String Model (with the Monash tune) implemented in PYTHIA. This work investigates string closepacking, a mechanism invoked during hadronization where overlapping strings create a background field that increases th

Keidai Akiba, Naoki Yamamoto

Using the path-integral formalism, we show that photons possess a nontrivial quantum metric in momentum space. We derive the semiclassical action and equations of motion by taking into account the quantum metric. In media with a spatially varying refractive index $n(\mathbf{x})$, the quantum metric induces a shift in the trajectory of light at second order i

Carlos Batista, Jean Paul Menotti, Dasol Kim, Bikash Kumar Das

The polarization state of light plays a central role in strong-field light--matter interactions and is widely used to probe electronic structure in solids via high-order harmonic generation (HHG). In particular, helicity-resolved HHG has been interpreted as a fingerprint of crystal symmetry and topology. Here, we demonstrate deterministic and continuous cont

Tabea Herrmann, Felix Fritzsch, Arnd Bäcker

Isolated quantum systems typically approach thermal equilibrium as described by the Eigenstate Thermalization Hypothesis (ETH). Going beyond this involves either higher order correlators (full thermalization) or the formation of state designs, i.e., the approach of moments of state ensembles after a projective measurement towards thermal equilibrium (deep th

Ryoko Kino, Patrick Achenbach, Pascal Klag, Sho Nagao

We respond to the recent suggestion by A. Gal [arXiv:2604.18259] that the sharp pion-momentum peak at $p_{\pi^-} \approx 113.8$~MeV/$c$ observed in our $^7\mathrm{Li}(e,e^\prime K^+)$ electroproduction experiment at MAMI [Phys. Rev. Lett. 136, 152301 (2026)] originates from $^7_\Lambda\mathrm{He}$ weak decay rather than from $^3_\Lambda\mathrm{H} \to \pi^- +

Jiaju Chen, Chongming Gao, Chenxiao Fan, Haoyan Liu

Large language model (LLM)-based generative list-wise recommendation has advanced rapidly, but decoding remains sequential and thus latency-prone. To accelerate inference without changing the target distribution, speculative decoding (SD) uses a small draft model to propose several next tokens at once and a target LLM to verify and accept the longest prefix,

Kohei Tokura, Takato Masuta, Kazushi Aoyama, Hiroki Akutsu

We have developed a novel BEDT-TTF-based organic conductor, $\kappa$-(BEDT-TTF)$_2 m$-HOOCC$_6$H$_4$SO$_3$ ($\kappa$-$m$-SBA), and propose it as a candidate for altermagnet. Tight-binding band calculations of $\kappa$-$m$-SBA provide a $t'/t$ of 1.01 at 100 K, indicating that the spin structure is closely aligned to an equilateral triangle ($t'/t= 1$). While

Leo van Iersel, Mark Jones, Jannik Schestag, Celine Scornavacca

We investigate parameterized algorithms for computing the average-tree phylogenetic diversity (APD) in rooted phylogenetic networks, studying the problem under different structural parameters that capture the deviation of a network from a tree. Our primary parameter is the scanwidth, a measure of the tree-likeness of a given directed acyclic graph. We show t

Wei Zhou, Rashina Hoda, Joycelyn Ling

AI applications are increasingly being introduced into digital health. While technical performance has advanced rapidly, successful deployment mainly depends on consumer attitudes, especially to patient-facing applications. However, most existing research examines consumer attitudes towards healthcare AI at an abstract level rather than in response to concre

Yuval Domb

Self-supervised learning has achieved remarkable empirical success in learning robust representations without explicit labels, most recently demonstrated within the framework of Joint-Embedding Predictive Architectures (JEPA). However, a fundamental question remains: what analytical principles drive these encoders toward specific distributional states? In th

Mehryar Mohri, Yutao Zhong

A fundamental dichotomy in the theory of classification sets smoothness against statistical efficiency: smooth surrogate losses such as the logistic loss enable fast $O(1/T)$ optimization but yield slow square-root $H$-consistency bounds, while piecewise-linear losses like the Hinge loss achieve optimal linear $H$-consistency rates but are non-differentiable

Sascha Xu, Jilles Vreeken

We study the problem of understanding where two populations differ within a feature space, which we formalize in the concept of a differential subgroup: a subset of individuals from both populations who, despite sharing similar characteristics, exhibit exceptional differences in a target outcome. Differential subgroups reveal the regions of the feature space

Zhipeng Wu, Linbin Yang

In this paper, we study the three-dimensional inviscid incompressible resistive Hall-MHD system in the axisymmetric setting with nontrivial swirl velocity and purely azimuthal magnetic. Assuming only that the swirl component of the initial velocity is sufficiently small, we prove that the lifespan of the strong solution can be sufficiently large. An explicit

Suman Karan, Swati Chaudhary, Harshwardhan Wanare, Anand Kumar Jha

We propose an OAM sorter based on a novel optical element that we refer to as a wavefront twister. It is a generalization of the conventional wavefront rotators such as the Dove prism. However, unlike a Dove prism, which simply rotates a wavefront, the rotation generated by a wavefront twister varies linearly with radial position, resulting in the twisting o

Piotr Białas, Piotr Korcyl, Tomasz Stebel, Adam Stefański

Autoregressive Neural Networks based on dense or convolutional layers have recently been shown to be a viable strategy for generating classical spin systems. Unlike these methods, sampling with transformers is commonly considered to be computationally inefficient. In this work, we propose a novel approach to transformer-based neural samplers in which we gene

Mohcine Chraibi, Krisztina Konya, Ezel Üsten

Crowds have long held a paradoxical place in the human imagination, feared for their destructive potential yet essential for collective expression. This tension was tragically manifested in the 1919 Jallianwala Bagh massacre, when British colonial troops opened fire on a peaceful gathering in Amritsar, India. Although officially 379 deaths were recorded, eye

Grzegorz Biskowski, Franco Ferrari, Marcin R. Piatek, Artur R. Pietrykowski

We study the celestial three-gluon amplitude in a dilaton background through the Mellin-Liouville formulation proposed by Stieberger, Taylor and Zhu (STZ). The original map contains an ambiguity in the identification of Liouville and Mellin variables; we resolve it by requiring global conformal covariance and compatibility with the semiclassical expansion of

Anna Schwarz, Jens Keim, Christian Rohde, Andrea Beck

High-order methods offer superior dispersion and dissipation properties compared to low-order schemes but require robust stabilization for discontinuities. To ensure stability, local artificial viscosity is common, but often degrades sub-element resolution. Conversely, subcell resolution preserving limiting strategies such as the finite volume subcell method

Mehryar Mohri, Yutao Zhong

Aligning Large Language Models (LLMs) with human intent, whether through explicit reward modeling or direct methods such as DPO, fundamentally relies on minimizing a surrogate loss as a proxy for the true pairwise ranking objective. We prove that this reliance is flawed for the standard surrogate losses used: for the equicontinuous hypothesis sets characteri

Ronald Richman, Mario V. Wüthrich

Claims reserving is one of the most important actuarial tasks in non-life insurance modeling. There are several popular methods to perform claims reserving such as the chain-ladder (CL), the Bornhuetter--Ferguson (BF) or the generalized Cape Cod (GCC) methods. These methods have originally been introduced as deterministic algorithms, and only in a later step

Alexandre Caboussat, Martin T. Leclercq, Anna Peruso

As an alternative to PINNs, a Deep Ritz framework is proposed to solve fully nonlinear PDEs. A least-squares algorithm is advocated to decouple the nonlinearities from the variational features of several fully nonlinear PDEs. A splitting method allows to iteratively solve local nonlinear problems and linear variational problems at each iteration. While exist

Iqra Aslam, Nour Habib, Abhishek Buragohain, Meng Zhang

The advancement of automated vehicles introduces complex safety challenges, particularly in dynamic and unpredictable environments where AI-enabled perception systems must operate reliably. Ensuring compliance with safety standards such as ISO 26262 and ISO/PAS 21448 (SOTIF) is essential for addressing system malfunctions and mitigating unsafe behavior in un

Md Faizul Ibne Amin, Yutaka Watanobe, Daniel M. Muepu, Haruto Suzuki

LLMs are increasingly employed both as judges for evaluating open-ended outputs and as co-creation partners in AI-assisted programming; yet rigorous evaluation in human-AI co-creation settings remains underdeveloped as judgments must be reliable, comparable across models, and interpretable over multi-turn interaction. To address this gap, a rubric-driven LLM

Ilya Olevsko, Maria Shehadeh, Dmytro Ohorodniichuk, Leonid Weisman

Fabricating brightly fluorescent layers with nanometric thickness and digitally controlled lateral structuration remains a challenge for next-generation photonic devices, optical calibration standards, and biocompatible interfaces. Here, we introduce Nano-Bead Emitters (NBEs), hydrogel nanoparticles covalently functionalized with fluorophores, as a universal

Jiaju Chen, Jinghua Piao, Xia Xu, Songwei Li

A long-standing challenge in economics lies not in the lack of intuition, but in the difficulty of translating intuitive insights into verifiable research. To address this challenge, we introduce AgentEconomist, an end-to-end interactive system designed to translate abstract intuitions into executable computational experiments. Grounded in a domain-specific

Xupeng Chen, Binbin Shi, Chenqian Le, Jiaqi Zhang

Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual content (tables, figures, structured layouts) of original document pages. We propose MED-VRAG, an iterative multimodal RAG framework that retrieves and reasons over PMC document page images instead of OCR'd te

Corinna Cortes, Anqi Mao, Mehryar Mohri, Yutao Zhong

Learning algorithms can be significantly improved by routing complex or uncertain inputs to specialized experts, balancing accuracy with computational cost. This approach, known as learning to defer, is essential in domains like natural language generation, medical diagnosis, and computer vision, where an effective deferral can reduce errors at low extra res

Kenneth See, Xue Wen Tan

Agentic payment systems extend delegated action to financial transfers, but scaling them on stablecoin rails in regulated settings requires safeguards that remain effective when humans are not continuously in the loop. We present a compliance-aware architecture that combines x402-style, signature-based payment authorisation and relayed execution with program

Samuel Croquette, Pierre Chantelot, Daniel A. Kiefer, Claire Prada

Elastic wave propagation is intrinsically sensitive to the mechanical properties of the medium through which it travels. In soft elastomers, this makes guided elastic waves natural probes of viscoelastic and acoustoelastic behavior over a broad frequency range. In this work, we introduce a wave-based mechanical characterization method in which a thin elastom

Oleg I. Berngardt, Sergey N. Ponomarchuk

This paper presents a physically-informed fuzzy clustering of vertical sounding ionograms for automatically separating the ionogram into tracks suitable for further interpretation and determining their optimal number. The model is designed for use not only in conditions where the number of tracks is known, but also in disturbed ionospheric conditions where t

Edgar Chaillou, Sebastian Rodriguez, Yves Tourbier, Francisco Chinesta

We present CRADIPOR, a numerical dispersion prediction tool for automotive crash simulations. Finite Element (FE) crash models are widely used throughout vehicle development, but their predictions are not strictly repeatable because of parallel computation and model complexity. As a result, performance criteria evaluated during post-processing may exhibit si

Pratim K. Saha

Room-temperature single-photon emission (SPE) resulting from a biexciton-exciton cascaded decay is demonstrated for the first time from chemically and photoelectrochemically etched site-controlled In0.14Ga0.86N quantum dots (QDs) embedded in vertical GaN nanowires. Diameter-dependent biexciton-exciton dynamics are analysed to determine the eligibility of QD