November 2025 arXiv papers — page 139

Triet M. Le, Arjun Chandra, C. Anton Rytting, Valerie P. Karuzis

Predicting an individual's personalities from their generated texts is a challenging task, especially when the text volume is large. In this paper, we introduce a straightforward yet effective novel strategy called targeted preselection of texts (TPoT). This method semantically filters the texts as input to a deep learning model, specifically designed to pre

Yicheng Li, Qian Lin

Theoretically exploring the advantages of neural networks might be one of the most challenging problems in the AI era. An adaptive feature program has recently been proposed to analyze feature learning, the characteristic property of neural networks, in a more abstract way. Motivated by the celebrated Le Cam equivalence, we advocate the over-parameterized se

Henrique de Oliveira, Jeffrey Mensch

We consider an agent with a rationally inattentive preference over menus of acts, as in de Oliveira et al (2017). We show that two axioms, Independence of Irrelevant Alternatives and Ignorance Equivalence, are necessary and sufficient for this agent to have a posterior-separable cost satisfying a mild smoothness condition, called joint-directional differenti

Nicolas Escobar-Velasquez

Mat\'ern covariance functions are ubiquitous in spatial statistics, valued for their interpretable parameters and well-understood sample path properties in Euclidean settings. This paper examines whether these desirable properties transfer to manifold domains through rigorous analysis of Mat\'ern processes on tori using pseudo-differential operator theory. W

Jiangxu Huang, Zhenhua Chai, Xi Liu, Changsheng Huang

This paper proposes a diffuse-interface model for simulating gas-liquid-solid multiphase flows involving solid-liquid phase change, solute transport, and the Marangoni effect. In this model, a phase-field method is employed to capture the evolution of fluid-fluid interfaces, while an enthalpy-based approach is used to describe the temperature field and impli

Arindam Panda, Sunil P Singh, Roland G. Winkler

The conformational and rheological properties of active polar linear polymers (APLPs) under linear shear flow are studied analytically. We describe a discrete APLP as an inextensible flexible Gaussian bead-spring chain supplemented by active forces along the bonds. The linear, non-Hermitian equations of motion are solved by an eigenfunction expansion in term

Johannes Hulsman, Philipp Azzarello, Joerg Bayer, Franck Cadoux

Gamma-Ray Bursts (GRBs) are among the most energetic events in the Universe. Despite over 50 years of research and measurements their prompt emission remains poorly understood, with key questions surrounding the structure of relativistic jets, magnetic field configurations, and dominant radiation mechanisms. Polarization measurements are critical in resolvin

Nishant Mehrotra, Sandesh Rao Mattu, Robert Calderbank

There is significant recent interest in designing new modulation schemes for doubly-selective channels with large delay and Doppler spreads, where legacy modulation schemes based on time-frequency signal representations underperform. Multiple modulation schemes, e.g., in the delay-Doppler, chirp, time-sequency, and other domains, have been proposed in the li

Julia Peters, Karin Mora, Miguel D. Mahecha, Chaonan Ji

Earth observation (EO) foundation models have emerged as an effective approach to derive latent representations of the Earth system from various remote sensing sensors. These models produce embeddings that can be used as analysis-ready datasets, enabling the modelling of ecosystem dynamics without extensive sensor-specific preprocessing. However, existing mo

Jinghang Zhang, Yu Luo

Quantum memory plays a critical role in quantum communication, sensing, and computation. However, studies on quantum memory under a unified benchmarking framework remain scarce. In this paper, we propose a weight-based quantifier as a benchmarking method to evaluate the performance advantage of quantum memory in nonlocal exclusion tasks. We establish a gener

Philipp Anthes, Dominik Sobania, Franz Rothlauf

Transformer Semantic Genetic Programming (TSGP) is a semantic search approach that uses a pre-trained transformer model as a variation operator to generate offspring programs with high semantic similarity to a given parent. Unlike other semantic GP approaches that rely on fixed syntactic transformations, TSGP aims to learn diverse structural variations that

Yu Luo, Zhihua Guo, Fanxu Meng, Chen-Ming Bai

Multipartite entanglement is regarded as a crucial physical resource in quantum network communication. However, due to the intrinsic complexity of quantum many-body systems, identifying a multipartite entanglement measure that is both efficiently computable and capable of accurately characterizing entanglement remains a challenging problem. To address these

Arya Narang

This paper determines the extent to which short textual inputs (in this case, names of dishes) can improve calorie estimation compared to an image-only baseline model and whether any improvements are statistically significant. Utilizes the TensorFlow library and the Nutrition5k dataset (curated by Google) to train both an image-only CNN and multimodal CNN th

Jiao Chen, Weihua Li, Jianhua Tang

In dynamic Industrial Internet of Things (IIoT) environments, models need the ability to selectively forget outdated or erroneous knowledge. However, existing methods typically rely on retain data to constrain model behavior, which increases computational and energy burdens and conflicts with industrial data silos and privacy compliance requirements. To addr

Gerliz M. Gutiérrez-Finol, Kirill Zinovjev, Alejandro Gaita-Ariño, Salvador Cardona-Serra

Polymer-assisted ion transport underpins both energy storage technologies and emerging neuromorphic computing devices. Efficient modeling of ion migration is essential for understanding the performance of batteries and memristors, but it remains challenging because of the interplay of drift, diffusion, and electrostatic interactions, as well as the limitatio

Jonathan E. W. Huffmann, Holger Boche

Rate distortion theory treats the problem of encoding a source with minimum codebook size while at the same time allowing for a certain amount of errors in the reconstruction measured by a fidelity criterion and distortion level. Similar to the channel coding problem the optimal rate of the codebook with respect to the blocklength is given by a convex optimi

Gustavo Bodanza

In this research note, we show the relationship between two non-admissible argumentation framework semantics: cogent and weakly admissible semantics. We prove that, while cogent extensions are weakly admissible, the converse is not true.

Wolfgang Otto, Lu Gan, Sharmila Upadhyaya, Saurav Karmakar

Research in Machine Learning (ML) and AI evolves rapidly. Information Extraction (IE) from scientific publications enables to identify information about research concepts and resources on a large scale and therefore is a pathway to improve understanding and reproducibility of ML-related research. To extract and connect fine-grained information in ML-related

Yusuf Motiwala

The queue is conceptually one of the simplest data structures-a basic FIFO container. However, ensuring correctness in the presence of concurrency makes existing lock-free implementations significantly more complex than their original form. Coordination mechanisms introduced to prevent hazards such as ABA, use-after-free, and unsafe reclamation often dominat

A. C. S. Readhead, M. F. Aller, A. G. Sullivan, R. D. Blandford

We recently discovered a supermassive black hole binary (SMBHB) candidate, PKS J1309+1154, in the combined 46-yr University of Michigan Radio Astronomy Observatory (UMRAO) plus Owens Valley Radio Observatory (OVRO) blazar monitoring programs at 14.5/15 GHz. The light curve of PKS 1309+1154 exhibits a 17.9 year periodicity. We also reported a hint of a first

Mohamed Mahdi

Large Language Models (LLMs) are the engines driving today's AI agents. The better these models understand human languages, the more natural and user-friendly the interaction with AI becomes, from everyday devices like computers and smartwatches to any tool that can act intelligently. Yet, the ability of industrial-scale LLMs to comprehend low-resource langu

Ming Yang, Dongrun Li, Xin Wang, Feng Li

In privacy-preserving mobile network transmission scenarios with heterogeneous client data, personalized federated learning methods that decouple feature extractors and classifiers have demonstrated notable advantages in enhancing learning capability. However, many existing approaches primarily focus on feature space consistency and classification personaliz

Temesgen Muruts Weldengus, Binnan Liu, Fei Kou, Youwei Lyu

Personalized image retouching aims to adapt retouching styles of individual users from reference examples, but existing methods often require user-specific fine-tuning or fail to generalize effectively. To address these challenges, we introduce \textbf{RefRetouch}, a general framework for personalized image retouching that instantly adapts to user retouching

Bichen Wang, Yixin Sun, Junzhe Wang, Hao Yang

The mismatch between the growing demand for psychological counseling and the limited availability of services has motivated research into the application of Large Language Models (LLMs) in this domain. Consequently, there is a need for a robust and unified benchmark to assess the counseling competence of various LLMs. Existing works, however, are limited by

Alexander Korochkin, Dmitri Semikoz, Peter Tinyakov

The ultra-high-energy cosmic ray (UHECR) spectra measured by the Pierre Auger Observatory (Auger) and the Telescope Array (TA) agree very well below $10^{19.5}$ eV but differ significantly at higher energies. We show that these differences can be explained by a single nearby source superimposed on a nearly isotropic background. Taking into account deflection

Maxime Devogèle, Olivier R. Hainaut, Marco Micheli, Petr Pravec

On 27 December 2024, near-Earth object (NEO) 2024 YR$_4$ was discovered by the ATLAS survey and identified as a virtual impactor. A few weeks later, it eventually reached level 3 on the Torino Scale and was the first and only asteroid to be ever classified at that level. Here we report an intensive observational campaign combining time-series photometry in t

Qiming Guo, Wenbo Sun, Wenlu Wang

Spatio-temporal graphs are widely used in modeling complex dynamic processes such as traffic forecasting, molecular dynamics, and healthcare monitoring. Recently, stringent privacy regulations such as GDPR and CCPA have introduced significant new challenges for existing spatio-temporal graph models, requiring complete unlearning of unauthorized data. Since e

Ian Low, Ming-Lei Xiao, Yu-Hui Zheng

We present a new on-shell recursion relation for scattering amplitudes involving Nambu-Goldstone bosons with a gauged unbroken symmetry. A central challenge is that gauge interactions break Adler's zero condition for charged scalars, invalidating the standard soft recursion. To overcome this, we introduce a ``gauged soft recursion'' that leverages the soft t

Zihao Huang, Zhan Wang, Hengxing Tan, Zhen Zhao

The kagome metals and superconductors hosting rich correlated and topological electronic states have captivated quantum materials research. These states are triggered by an unconventional chiral charge density wave (CDW) wherein a chiral superconductivity emerges at low temperatures, yet the origin of this chiral CDW order, the parent state, is unresolved. H

Chenyue Guo, Hongzheng Zhao, Zi Cai

In this study, we show that dynamical frustration can spontaneously emerge in frustration-free magnetic systems under periodic driving. Specifically, we consider a classical spin system and demonstrate the emergence of spin-ice physics when drive-induced heating is well suppressed. In particular, we focus on the dynamics of magnetic monopole excitations, whi

Philip Sosnin, Matthew Wicker, Josh Collyer, Calvin Tsay

The impact of inference-time data perturbation (e.g., adversarial attacks) has been extensively studied in machine learning, leading to well-established certification techniques for adversarial robustness. In contrast, certifying models against training data perturbations remains a relatively under-explored area. These perturbations can arise in three critic

Tingyang Wei, Jiao Liu, Abhishek Gupta, Chin Chun Ooi

Many real-world applications require solving families of expensive multi-objective optimization problems~(EMOPs) under varying operational conditions. This can be formulated as parametric expensive multi-objective optimization problems (P-EMOPs) where each task parameter defines a distinct optimization instance. Current multi-objective Bayesian optimization

Slimane Zaim, Fatma Zohra Bara, Mohamed Aimen Larbei

We investigate the thermodynamic properties of a Schwarzschild-AdS black hole within the framework of noncommutative geometry. We derive and analyze the black hole's thermodynamic functions, showing that they depend critically on the noncommutativity parameter denoted as {\Theta}, while still satisfying the first law of thermodynamics. Stability analysis rev

Haiyi Li, Qi Chen, Denis Kalkofen, Hsiang-Ting Chen

Recent advances in 3D Gaussian Splatting (3DGS) have achieved state-of-the-art results for novel view synthesis. However, efficiently capturing high-fidelity reconstructions of specific objects within complex scenes remains a significant challenge. A key limitation of existing active reconstruction methods is their reliance on scene-level uncertainty metrics

Lukas Arana, Julen Etxaniz, Ander Salaberria, Gorka Azkune

Current Multimodal Large Language Models exhibit very strong performance for several demanding tasks. While commercial MLLMs deliver acceptable performance in low-resource languages, comparable results remain unattained within the open science community. In this paper, we aim to develop a strong MLLM for a low-resource language, namely Basque. For that purpo

Matvey Skripkin, Elizaveta Goncharova, Andrey Kuznetsov

We present a lightweight yet effective pipeline for training vision-language models to solve math problems by rendering LaTeX encoded equations into images and pairing them with structured chain-of-thought prompts. This simple text-to-vision augmentation enables compact multimodal architectures to achieve state-of-the-art reasoning accuracy. Through systemat

Olcay Coskun, Alp Eden

We study a seven-dimensional non-associative algebra, the \emph{exceptional Vidinli algebra}, defined by lifting the bilinear product introduced by H\"{u}seyin Tevfik Pasha (Vidinli) in 1882 from three to seven dimensions via the octonionic cross product. This algebra is unital, simple, and non-associative, with automorphism group $U(3)$. Its multiplication

Danli Shi, Xiaolan Chen, Bingjie Yan, Weiyi Zhang

Artificial intelligence has shown promise in medical imaging, yet most existing systems lack flexibility, interpretability, and adaptability - challenges especially pronounced in ophthalmology, where diverse imaging modalities are essential. We present EyeAgent, the first agentic AI framework for comprehensive and interpretable clinical decision support in o

Lin Wang, Miaomiao Zhu

For a complete noncompact Riemannian manifold with nonnegative Ricci curvature, we show that bounded biharmonic functions are constant and the space consists of biharmonic functions with polynomial growth of a fixed rate is finite dimensional. Also, we derive a Weyl type bound for this space. Finally, we present a finite dimensional result for a class of fou

Rangel Daroya, Subhransu Maji

Satellite missions provide valuable optical data for monitoring rivers at diverse spatial and temporal scales. However, accessibility remains a challenge: high-resolution imagery is ideal for fine-grained monitoring but is typically scarce and expensive compared to low-resolution imagery. To address this gap, we introduce SuperRivolution, a framework that im

Jiajie Su, Zihan Nan, Yunshan Ma, Xiaobo Xia

Sequential Recommenders, which exploit dynamic user intents through interaction sequences, is vulnerable to adversarial attacks. While existing attacks primarily rely on data poisoning, they require large-scale user access or fake profiles thus lacking practicality. In this paper, we focus on the Profile Pollution Attack that subtly contaminates partial user

Gabriel Elvin, Hajrudin Fejzić, Youngsu Kim

We provide a simplified proof of the following special case of Wegner's conjecture: every planar graph of maximum degree at most three admits a distance-2 coloring with at most eight colors. Our main contribution is significant simplification of the most technically challenging part of Wegner's proof: the case involving the removal of a 5-cycle.

D. Amato, P. Facchi, G. Marmo

In this work, we present several aspects of the interplay between classical and quantum theories. After reviewing the equivalence between positivity and complete positivity in the commutative setting, we introduce and analyze intermediate notions that interpolate between these two properties for linear maps on the space of operators on a Hilbert space, highl

Lorenzo Branca, Rune Rost, Tobias Buck

Radiative transfer is a key bottleneck in computational astrophysics: it is nonlocal, stiff, and tightly coupled to hydrodynamics. We introduce Ray-trax, a GPU-oriented, fully differentiable 3D ray tracer written in JAX that solves the time-dependent emission--absorption problem and runs directly on turbulent gas fields produced by hydrodynamic simulations.

Yang Chen, Miaoge Li, Zhijie Rao, Deze Zeng

Recognizing unseen skeleton action categories remains highly challenging due to the absence of corresponding skeletal priors. Existing approaches generally follow an ``align-then-classify'' paradigm but face two fundamental issues, \textit{i.e.}, (i) fragile point-to-point alignment arising from imperfect semantics, and (ii) rigid classifiers restricted by s

Chihiro Kubota, Taizo Sadahiro, Yoshika Ueda

In this note, we explicitly compute the probability that a given cell in a random standard Young tableau of the shifted staircase shape $(2n-1, 2n-3, \ldots, 3,1)$ contains the maximal label. We also show that the asymptotic distribution of the cell containing the maximal label is governed by the quarter-circle law. The bijection between the tableaux and the

Ruibo Deng, Duanyu Feng, Wenqiang Lei

Offline preference optimization offers a simpler and more stable alternative to RLHF for aligning language models. However, their effectiveness is critically dependent on ranking accuracy, a metric where further gains are highly impactful. This limitation arises from a fundamental problem that we identify and formalize as the Overfitting-Underfitting Dilemma

Matteo Nerini, Bruno Clerckx

Smart radio environments (SREs) enhance wireless communications by allowing control over the channel. They have been enabled through surfaces with reconfigurable electromagnetic (EM) properties, known as reconfigurable intelligent surfaces (RISs), and through flexible antennas, which can be viewed as realizations of SREs in the EM domain and space domain, re

Rüveyda Yilmaz, Julian Thull, Johannes Stegmaier, Volkmar Schulz

Accurate PET imaging increasingly requires methods that support unconstrained detector layouts from walk-through designs to long-axial rings where gaps and open sides lead to severely undersampled sinograms. Instead of constraining the hardware to form complete cylinders, we propose treating the missing lines-of-responses as a learnable prior. Data-driven ap

Mingkuan Zhao, Wentao Hu, Jiayin Wang, Xin Lai

The design of Large Language Models (LLMs) has long been hampered by a fundamental conflict within their core attention mechanism: its remarkable expressivity is built upon a computational complexity of O(H N^2) that grows quadratically with the context size (N) and linearly with the number of heads (H). This standard implementation harbors significant compu

Yu. A. Biriukov, R. D. Morozov, K. I. Okhlopkov, I. V. Dyakonov

We present an experimental demonstration of boson sampling enhanced by optical feedback lines, a novel approach that introduces temporal correlations among photons to amplify computational complexity. We utilize a 25-mode femtosecond laser-written interferometer with five output channels connected to five input channels to create correlations between consecu

Hossein A. Rahmani, Satyapriya Krishna, Xi Wang, Mohammadmehdi Naghiaei

Large language models have recently demonstrated remarkable abilities to self-correct their responses through iterative refinement, often referred to as self-consistency or self-reflection. However, the dynamics of this self-correction mechanism may differ substantially depending on whether the model is tasked with open-ended text generation or with selectin

Junho Jeong, Jang Soo Kim, Eunjeong Lee

A Bott manifold is a smooth projective toric variety having an iterated $\mathbb{C} P^1$-bundle structure. A certain family of Bott manifolds is used to understand the structure of Bott--Samelson varieties (or Bott--Samelson--Demazure--Hansen varieties), which provide desingularizations of Schubert varieties. Indeed, each Bott--Samelson variety is diffeomorp

Xinyu Wang, Huan Ye, Xiao-Xiong Zeng

We investigate the imaging and polarization properties of Kerr-MOG black holes surrounded by geometrically thick accretion flows. The MOG parameter $\alpha$ introduces deviations from the Kerr metric, providing a means to test modified gravity in the strong field regime. Two representative accretion models are considered: the phenomenological radiatively ine

Alejandro Argudín-Monroy, Octavio Mendoza, Carlos E. Parra

We introduce a notion similar to the AB4 (resp. AB4{*}) condition for abelian categories but in the context of extriangulated categories. We will refer to this notion as AET4 (resp. AET4{*}). One of our main results shows equivalent statements for AET4 (resp. AET4{*}), which generalize statements commonly used in homological constructions in abelian categori

Minju Lee, Hee Oh

We study totally geodesic submanifolds in the convex core of geometrically finite rank-one locally symmetric manifolds. Although the infinite-volume setting can exhibit highly complicated behavior, including geodesic planes with fractal closures, we show that a strong rigidity persists inside the convex core. This rigidity has striking consequences in the in

Alexander Nadel, Ron Wettenstein

SHapley Additive exPlanations (SHAP) is a key tool for interpreting decision tree ensembles by assigning contribution values to features. It is widely used in finance, advertising, medicine, and other domains. Two main approaches to SHAP calculation exist: Path-Dependent SHAP, which leverages the tree structure for efficiency, and Background SHAP, which uses

Mykhailo Hontarenko, Javier de Lucas, Adam Maskalaniec

We propose a starting point to the geometric description for the pseudo-gauge ambiguity in relativistic hydrodynamics, showing that it corresponds to the freedom to redefine the thermodynamic equilibrium state of the system. To do this, we develop for the first time a description of a relativistic hydrodynamic-like theory using $k$-contact geometry. In this

Rhitabrat Pokharel, Ameeta Agrawal

The use of large language models (LLMs) for evaluating outputs is becoming an increasingly effective and scalable approach. However, it remains uncertain whether this capability extends beyond task-specific evaluations to more general assessments of text quality, particularly in multilingual contexts. In this study, we introduce, MTQ-Eval, a novel framework

Adam Štorek, Vikas Upadhyay, Marianne Menglin Liu, Daniel W. Peterson

LLMs now tackle a wide range of software-related tasks, yet we show that their performance varies markedly both across and within these tasks. Routing user queries to the appropriate LLMs can therefore help improve response quality while reducing cost. Prior work, however, has focused mainly on general-purpose LLM routing via black-box models. We introduce R

Navid Amani, Filiberto Bilotti, Davide Dardari, Raffaele D Errico

The massive scale of Internet of Things (IoT) connectivity expected in 6G networks raises unprecedented challenges in energy use, battery waste, and lifecycle sustainability. Current cellular IoT solutions remain bound to the lifetime of underlying network generations and rely on billions of disposable batteries, creating unsustainable economic and environme

Roy Magen

In this article, we study criteria for producing six-functor formalisms and morphisms between them. One notable application is that the motivic homotopy theory of algebraic stacks is the universal six-functor functor formalism in a strong sense: it is initial in some category whose objects are six-functor formalisms, and whose morphisms commute with all six

Corentin Presvôts, Michel Kieffer, Thibault Prevost

This paper adapts a Multiple-Model Coding (MMC) approach for sampled electrical signal waveforms to satisfy reconstructed signal quality constraints. The baseline MMC approach consists of two stages processing vectors of Voltage and Current Signal (VCS) of constant size and producing bitstreams of constant rate but varying quality. In the proposed approach,

Dimitris Moustos, Obinna Abah

We investigate a two-qubit SWAP thermal machine -- a streamlined analogue of the four-stroke Otto cycle -- whose working medium comprises inertially moving Unruh-DeWitt qubit detectors, each coupled to a thermal quantum field bath prepared at a different temperature. In the presence of relative motion between the working medium and the thermal baths, we deri

Huabin Ge, Longsong Jia, Hao Yu, Puchun Zhou

Since Thurston pioneered the connection between circle packing (abbr. CP) and three-dimensional geometric topology, the characterization of CPs and hyperbolic polyhedra has become increasingly profound. Some milestones have been achieved, for example, Rodin-Sullivan \cite{Rodin-Sullivan} and Schramm \cite{schramm91} proved the rigidity of infinite CPs with t

Bahram Houchmandzadeh

Given an evolutionary model, such as Wright--Fisher (WF) or Moran, the n-coalescent problem consists of going backward in time to find for example the time to the most recent common ancestor (MRCA) and the topology of the tree. In the literature, this problem is tackled mostly by computing directly the random variable t, time to reach the MRCA. I show here t

Meijie Kong, Hongfei Fu

We propose a fast collocation method based on Krylov subspace iterative solver on general nonuniform grids for the fractional Laplacian problem, in which the fractional operator is presented in a singular integral formulation. The method is proved to be uniquely solvable on general nonuniform grids for $\alpha\in(0,1)$, provided that the sum-of-exponentials

Felix F Zimmermann

Ultra-low-field (ULF) MRI promises broader accessibility but suffers from low signal-to-noise ratio (SNR), reduced spatial resolution, and contrasts that deviate from high-field standards. Image-to-image translation can map ULF images to a high-field appearance, yet efficacy is limited by scarce paired training data. Working within the ULF-EnC challenge cons

Ben Green, Mehtaab Sawhney

Let $r$ be a sufficiently large positive integer, and let $N \ge \exp\exp(r^{50})$. Then any $r$-colouring of $[N]$ contains a monochromatic copy of $\{x+y,xy\}$ with $x > y > 2$.

Ruiyang Ma, Yunhao Zhou, Yipeng Wang, Yi Liu

There is a growing body of work on using Graph Neural Networks (GNNs) to learn representations of circuits, focusing primarily on their static characteristics. However, these models fail to capture circuit runtime behavior, which is crucial for tasks like circuit verification and optimization. To address this limitation, we introduce DR-GNN (DynamicRTL-GNN),

Ali Taheri, Alireza Taban, Sadegh Soudjani, Ashutosh Trivedi

Safety verification of dynamical systems via barrier certificates is essential for ensuring correctness in autonomous applications. Synthesizing these certificates involves discovering mathematical functions with current methods suffering from poor scalability, dependence on carefully designed templates, and exhaustive or incremental function-space searches.

Sizhuo Zhou, Yuou Sun, Bailin Deng, Juyong Zhang

Designing freeform surfaces to control light based on real-world illumination patterns is challenging, as existing caustic lens designs often assume oversimplified point or parallel light sources. We propose representing surface light sources using an optimized set of point sources, whose parameters are fitted to the real light source's illumination using a

Karl-Hermann Neeb

In these notes, we describe an interesting connection between unitary representations of Lie groups and nets of local algebras, as they appear in Algebraic Quantum Field Theory (AQFT). It is based on first translating the axioms for nets of operator algebras parameterized by regions in a space-time manifold into those for nets of real subspaces, and then stu

Dany Davesne, Alessandro Pastore, Jesus Navarro

Hartree Fock equations for finite range interactions in a slab of nuclear matter are presented and solved using an algorithm based on the Lagrange mesh method. This approach is faster and more efficient than the Numerov algorithm commonly used in the literature. Thanks to the improved numerical accuracy, we were able to perform calculations with sufficiently

Toshiya Hikihara

We propose a protocol to generate an antiferromagnetic S=1/2 Heisenberg model with the exact ground state based on a tree graph. The generated model has a correspondence with a tree graph and possesses the product state of singlet dimers as its unique ground state. A procedure for constructing a model with exact, massively degenerate ground states is also in

Liang Luo, Lei Zhang

Image restoration requires a careful balance between noise suppression and structure preservation. While first-order total variation (TV) regularization effectively preserves edges, it often introduces staircase artifacts, whereas higher-order TV removes such artifacts but oversmooths fine details. To reconcile these competing effects, we propose a semi-conv

Ye Ling, Yuting Wang, Wenan Guo, Yuhai Liu

The sign-problematic generalized Baxter-Wu (GBW) model with asymmetric complex couplings is mapped onto a one-dimensional quantum model. Utilizing the model's exactly known critical properties, we study the relation between the conventional and the modified average signs and the phase transitions in the GBW model. We find that the average sign develops a neg

Qing-Hua Zhu

Motivated by recent images of black holes in M87 and our galaxy, efficient relativistic ray tracing was developed to simulate the snapshots of variable emissions around the black holes. Half a century ago, the appearance of a moving emission source was addressed by Terrell and Penrose, who independently found that the aberration effect induces a conformal tr

Martin Vejvar, Yasutaka Fujimoto

We present Spider4SSC dataset and S2CLite parsing tool. S2CLite is a lightweight, ontology-agnostic parser that translates SPARQL queries into Cypher queries, enabling both in-situ and large-scale SPARQL to Cypher translation. Unlike existing solutions, S2CLite is purely rule-based (inspired by traditional programming language compilers) and operates without

Yujing Gao, Xiang Zhang, Shu Yang

External controls (ECs) from historical trials or real-world data have gained increasing attention as a way to augment hybrid and single-arm trials, especially when balanced randomization is infeasible. While most existing work has focused on post-trial inference using ECs, their role in prospective trial design remains less explored. We address this gap by

Min Liang, Ruihao Gao, Jiali Wu

Key-length extension (KLE) techniques provide a general approach to enhancing the security of block ciphers by using longer keys. There are mainly two classes of KLE techniques, cascade encryption and XOR-cascade encryption. This paper presents several quantum meet-in-the-middle (MITM) attacks against two specific KLE constructions. For the two-key triple en

Hou Jinghua, Su Nan, Liu Yao, Liu Zhihui

The conversion of the modulation signal from the coupling light to the probe light and the conversion of the additional phase noise from the coupling light to the amplitude noise of the probe light in the electromagnetically induced transparency (EIT) spectrum of the cesium atomic ladder type three level system were investigated by detecting the probe light

Dhananjaya Mahapatra, Harekrishna Bhunia, Manu S Pattelath, Partha Mitra

We investigate orbital current induced effects arising from the orbital Hall effect in light-metal/ferromagnet bilayers. Thin films of Ti in ohmic contact with Ni were studied using second-harmonic longitudinal and transverse voltage measurements under an applied a.c. current. From these signals, we extract the orbital Hall torque (OHT) efficiency and the un

Yanpeng Gong, Sishuai Li, Yue Mei, Bingbing Xu

This study presents a finite element and virtual element (FE-VE) coupled method for thermomechanical analysis in electronic packaging structures. The approach partitions computational domains strategically, employing FEM for regular geometries to maximize computational efficiency and VEM for complex shapes to enhance geometric flexibility. Interface compatib

Jiangyong Yu, Changyong Shu, Sifan Zhou, Zichen Yu

Camera-based multi-view 3D detection is crucial for autonomous driving. PETR and its variants (PETRs) excel in benchmarks but face deployment challenges due to high computational cost and memory footprint. Quantization is an effective technique for compressing deep neural networks by reducing the bit width of weights and activations. However, directly applyi

Guillaume Jeanmairet, Luc Belloni, Daniel Borgis

We propose a generalisation of molecular density functional theory to describe inhomogeneous solvent mixture, with the objective of modelling electrolytic solutions. Two electrolytic models are presented, both within the HNC approximation. The first one is a two-components mixture representing a primitive-like model of sodium chloride, where the solvent is d

E. Novais

I analyze the decoherence of a $\pi$-junction qubit encoded by two co-located Majorana modes. Although not topologically protected, the qubit leverages distinct spatial profiles to couple to two independent environmental baths, realizing the phenomenon of quantum frustration. This mechanism is tested against the threat of quasiparticle poisoning (QP). I show

Shiyu Ji, Yixuan Wang, Yijun Liu, Qingfu Zhu

Test-time scaling improves the inference performance of Large Language Models (LLMs) but also incurs substantial computational costs. Although recent studies have reduced token consumption through dynamic self-consistency, they remain constrained by the high latency of sequential requests. In this paper, we propose SeerSC, a dynamic self-consistency framewor

Twan J. S. Wilting, Adriana W. B. P. Reijnier, Michiel H. M. Brebels, Alexandre Villie

Bacteria living on surfaces are often confined to droplets. When these droplets evaporate, the motion of the liquid-air interface and the associated internal capillary flow confine the bacteria. Here we study how \emph{E. coli} bacteria interact with this capillary confinement and agglomerate at the droplet's contact line. We identify three different types o

Sanja Atanasova, Smiljana Jakšić, Snježana Maksimović, Stevan Pilipović

In this paper, we first present an Abelian-type theorem for the fractional Hankel transform (FrHT) within Zemanian generalized function spaces. To prove this, we show that these spaces have the Montel property. Next, we construct a new Zemanian-type space as a projective limit of suitable Banach spaces. Its dual is the largest known distribution space admitt

Junyi Duan, Jiageng Chen, Zuyuan He

Fiber-optic distributed acoustic sensing (DAS) has emerged as a critical Internet-of-Things (IoT) sensing technology with broad industrial applications. However, the two-dimensional spatial-temporal morphology of DAS signals presents analytical challenges where conventional methods prove suboptimal, while being well-suited for deep learning approaches. Altho

Weiran Yang, Yiqi Cai, Handi Deng, Cheng Ma

The sensitivity of the acoustic detection subsystem in photoacoustic imaging (PAI) critically affects image quality. However, previous studies often focused only on front-end acoustic components or back-end electronic components, overlooking end-to-end coupling among the transducer, cable, and receiver. This work develops a complete analytical model for syst

Arka Mukherjee, Shreya Ghosh

Contemporary vision-language models (VLMs) perform well on existing multimodal reasoning benchmarks (78-85\% accuracy on MMMU, MathVista). Yet, these results fail to sufficiently distinguish true scientific reasoning articulation capabilities from pattern-matching. To address this gap, we introduce \textbf{mmJEE-Eval}, a multimodal bilingual (English and Hin

Jake R. Patock, Rinki Ratnapriya, Arko Barman

The identification of disease-gene associations is instrumental in understanding the mechanisms of diseases and developing novel treatments. Besides identifying genes from RNA-Seq datasets, it is often necessary to identify gene clusters that have relationships with a disease. In this work, we propose a graph-based method for using an RNA-Seq dataset with kn

A. I. Krivchikov, A. Jeżowski, M. S. Barabashko, G. Dovbeshko

The specific heat of expanded graphite (EG) and EG--multiwalled carbon nanotube (MWCNT) composites (1.0 and 3.0 wt.\% MWCNTs) was measured between 2 and 300~K. The low-temperature heat capacity is dominated by out-of-plane flexural phonons with quadratic dispersion, characteristic of two-dimensional layered systems. Compared with crystalline graphite, EG exh

Ziyong Ma, Richard D. Boyce, Adam Perer, Venkatesh Sivaraman

Electronic health record (EHR) data is an essential data source for machine learning for health, but researchers and clinicians face steep barriers in extracting and validating EHR data for modeling. Existing tools incur trade-offs between expressivity and usability and are typically specialized to a single data standard, making it difficult to write tempora

Amedeo Altavilla, Swanhild Bernstein, Martha Lina Zimmermann

We introduce a $q$-deformation of the Fock space of holomorphic functions on $\mathbb{C}$, based on a geometric definition of $q$-analyticity. This definition is inspired by a standard construction in complex differential geometry. Within this framework, we define $q$-analytic monomials $z_q^n$ and construct the associated $q$-Fock space as a Hilbert space w

E. Abasov, L. Dudko, E. Iudin, A. Markina

We present a methodology for training foundational transformer models capable of processing collider data with diverse kinematic signatures. Our universal foundation model is designed for simultaneous analysis of all processes involving from one to four top-quarks production with their corresponding background processes. The approach employs multi-task pre-t

V. Sau, R. Giustozzi, P. Piergentili, D. Vitali

We describe the generation of correlated photon pairs by means of spontaneous parametric down-conversion of an optical pump in the form of a finite energy Airy beam. The optical system function, which contributes to the propagation of the down-converted beam before being registered by the detectors, is computed. The spectral function is utilized to calculate

Roland Becker, Franz Chouly, Michel Duprez, Thomas Richter

This chapter describes how a posteriori error estimates targeting a user-defined quantity of interest, using the Dual Weighted Residual (DWR) technique, can be easily applied for biomechanical simulations in current engineering practice. The proposed method considers a very general setting that encompasses complex geometries, model non-linearities (hyperelas