December 2025 arXiv papers — page 57

T. Shin, E. J. Baxter, E. Lee, N. Battaglia

We use weak gravitational lensing measurements from Year 3 Dark Energy Survey data to calibrate the masses of 443 galaxy clusters selected via the Sunyaev-Zel'dovich effect from Atacama Cosmology Telescope Data Release 5 maps of the cosmic microwave background. We incorporate redshift and SZ measurements for individual clusters into a hierarchical model for

Hang Yu, Juntu Zhao, Yufeng Liu, Kaiyu Li

Vision-Language-Action (VLA) models align vision and language with embodied control, but their object referring ability remains limited when relying solely on text prompt, especially in cluttered or out-of-distribution (OOD) scenes. In this study, we introduce the Point-VLA, a plug-and-play policy that augments language instructions with explicit visual cues

Sarwan Ali

Differential privacy (DP) has emerged as the gold standard for protecting user data in recommender systems, but existing privacy-preserving mechanisms face a fundamental challenge: the privacy-utility tradeoff inevitably degrades recommendation quality as privacy budgets tighten. We introduce DPSR (Differentially Private Sparse Reconstruction), a novel three

Bingxin Li, Shanglong Ning, Chunyang Miao, Chenyang Guo

Thiol-based self-assembled monolayers (SAMs) on gold surfaces are one of the fundamental building blocks of molecular electronics. The strong chemical affinity of the gold and sulfur (Au-S) enables the formation of close-packed SAMs, but it also has recently been found to create a dynamic interface where surface reconstruction can occur under illumination, e

Raina Panda, Daniel Fein, Arpita Singhal, Mark Fiore

Artistic style transfer in generative models remains a significant challenge, as existing methods often introduce style only via model fine-tuning, additional adapters, or prompt engineering, all of which can be computationally expensive and may still entangle style with subject matter. In this paper, we introduce a training- and inference-light, interpretab

Bin Wang, Jiazheng Quan, Xingrui Yu, Hansen Hu

Contemporary large language model (LLM) agents are remarkably capable, but they still lack reliable safety controls and can produce unconstrained, unpredictable, and even actively harmful outputs. To address this, we introduce Reflection-Driven Control, a standardized and pluggable control module that can be seamlessly integrated into general agent architect

Cagatay Tekin, Charbel Barakat, Luis Joseph Luna Limgenco

Iterative summarization based reasoning frameworks such as InftyThink enable long-horizon reasoning in large language models (LLMs) by controlling context growth, but they repeatedly regenerate similar reasoning strategies across tasks. We introduce InftyThink with Cross-Chain Memory, an extension that augments iterative reasoning with an embedding-based sem

Chengkang Liang, Quanying Li, Jiale Xu, Pingqi Gao

Efficient nonlinear frequency conversion in nanophotonics requires not only strong fundamental field but also precise phase matching among distributed nonlinear sources. Here, we develop the two-dimensional Green's function integral method (GFIM), which enables direct visualization and optimization of phase matching in nonlinear guided-mode resonators. Using

Mohammadhossien Rashidi

Exit timing after an IPO is one of the most consequential decisions for venture capital (VC) investors, yet existing research focuses mainly on describing when VCs exit rather than evaluating whether those choices are economically optimal. Meanwhile, large language models (LLMs) have shown promise in synthesizing complex financial data and textual informatio

J. P. Mendonça, S. Biswas, M. Dziurawiec, U. Bhattacharya

Band flattening has been identified as key ingredient to correlation phenomena in Moiré materials and beyond. Here, we examine strongly repulsive fermions on a ladder -- a minimal platform for unconventional $d$-wave pairing -- and show that flattening of the lower band through an additional diagonal hopping term produces non-Fermi liquid behavior, evidenced

Charlotte Brandebusemeyer, Tobias Schimmer, Bert Arnrich

With the rise of AI-powered coding assistants, firms and programmers are exploring how to optimize their interaction with them. Research has so far mainly focused on evaluating output quality and productivity gains, leaving aside the developers' experience during the interaction. In this study, we take a multimodal, developer-centered approach to gain in

Rolf Zeißler, Sandra Krüger, Robin Horstmann, Till Böhmer

We investigate how anisotropic molecular rotation and internal molecular flexibility influence liquid dynamics in 1-phenylalkanes. To this end, we combine depolarized dynamic light scattering, nuclear magnetic resonance spectroscopy and molecular dynamics simulations. Our results show that anisotropic rotations and internal molecular flexibility substantiall

Nadhia Monim, Wolfgang Langbein, Francesco Masia

Photonic crystal cavities (PCCs) are defects in host photonic crystals (PCs) which create bound states in the PC band gap. These bound states are resonant states of the electromagnetic field with a complex resonance frequency and can have very small mode volumes. PCCs are attractive for a variety of applications, from cavity quantum electrodynamics to biosen

Abhikbrata Sarkar, Daniel Loss

We study a vertical double quantum dot (DQD) in a Si/Si$_{1-x}$Ge$_x$/Si double-well heterostructure for full electrical control of electron Loss-DiVincenzo (LD) spin qubits, using realistic device modeling and numerical simulations. Due to the emerging spin-orbit interaction in the DQD, as well as strain from the gate electrodes, small (percentage range) bu

Jyotiranjan Beuria, Venkatesh H. Chembrolu

Non-reciprocal interactions, where the influence of agent $i$ on $j$ differs from that of $j$ on $i$, are fundamental in active and living matter. Yet, most models implement such asymmetry phenomenologically. Here we show that non-reciprocity can emerge from internal topology alone. Agents evolve on an internal ``context manifold'' coupled to a Chern

Chi Zhang, Braedon Gunn, Andrew M. Read-Fuller

Poor adaptation of orbital implants remains a major contributor to postoperative complications and revision surgery. Although preformed orbital plates are widely used to reduce cost and operative time compared with customized implants, surgeons currently lack publicly available tools and standardized metrics to quantitatively compare plate fit across vendors

Yang Zhang, Ling-Fang Lin, Adriana Moreo, Satoshi Okamoto

Motivated by recent reports of ambient-pressure superconductivity in La$_3$Ni$_2$O$_7$ films grown on LaSrAlO$_4$, we investigate the superconducting instability in a one-unit cell thin film using {\it ab initio} and random-phase approximation techniques. Compared to the high-pressure bulk system, the ratio of inter-layer $d_{3z^2-r^2}$ hopping to intra-laye

Keivan Faghih Niresi, Jun Qing, Mengjie Zhao, Olga Fink

Structural Health Monitoring (SHM) plays a crucial role in maintaining the safety and resilience of infrastructure. As sensor networks grow in scale and complexity, identifying the most informative sensors becomes essential to reduce deployment costs without compromising monitoring quality. While Graph Signal Processing (GSP) has shown promise by leveraging

Shakir Ali, Atif Ahmad Khan, Abhishek Kesarwani

Let $s,m$ be the positive integers and $p$ be any prime number. Next, let $GR(p^s,p^{sm})$ be a Galois ring of characteristic $p^s$ and cardinality $p^{sm}$. In the present paper, we explore the construction of Cauchy MDS matrices over Galois rings. Moreover, we introduce a new approach that considers nilpotent elements and Teichmüller set of Galois ring $GR

René Pollmann, Franz Roeder, Christine Silberhorn, Benjamin Brecht

We introduce a method for determining the sensitivity of any given Entangled Two-Photon Absorption (ETPA) measurement. By modeling all signal and noise contributions to the measurement, we derive a single numerical value that describes the sensitivity of the ETPA measurement in Göppert-Mayer units. This allows us to directly compare vastly different experime

Yusei Shimizu, Shunichiro Kittaka, Yohei Kono, Shota Nakamura

We report the results of high-resolution dc magnetization and specific-heat measurements at very low temperatures for a single crystal \color{black} of UBe$_{13}$ in magnetic fields applied along the [001] and [111] directions, in both the normal and superconducting states. In the normal state, magnetic susceptibility $χ(T) = M/H$ exhibits a logarithmic temp

Christof Lorenz, Nils Brinckmann, Jan Bumberger, Marc Hanisch

Deriving reliable conclusions and insights from environmental observational data urgently requires the enrichment with consistent and comprehensive metadata, including time-resolved context such as changing deployments, configurations, and maintenance actions. We have therefore developed the Sensor Management System (SMS), which provides a user-friendly and

Nicolas Boulle, Guilherme Franzmann

Recent proposals suggest that detecting entanglement between two spatially superposed masses would establish the quantum nature of gravity. However, these gravitationally induced entanglement (GIE) experiments rely on assumptions about subsystem independence. We sharpen the theoretical underpinnings of such proposals by examining them through the lens of alg

Ludwig Nützel, Michael J. Hartmann, Henrik Dreyer, Etienne Granet

Estimating molecular ground-state energies is a central application of quantum computing, requiring both the preparation of accurate quantum states and efficient energy readout. Understanding the effect of hardware noise on these experiments is crucial to distinguish errors that have low impact, errors that can be mitigated, and errors that must be reduced a

Beatrice Magni, Xhek Turkeshi

We investigate the emergence of quantum complexity and chaos in doped Clifford circuits acting on qudits of odd prime dimension $d$. Using doped Clifford Weingarten calculus and a replica tensor network formalism, we derive exact results and perform large-scale simulations in regimes challenging for tensor network and Pauli-based methods. We begin by analyzi

Len Kimms, Diddo Diddens, Andreas Heuer

Block-copolymer electrolytes with lamellar microstructure show promising results regarding the ion transport in experiments. Motivated by these observations we study block-copolymers consisting of a polystyrene (PS) block and a poly(ethylene oxide) (PEO) block which were assembled in a lamellar structure. The lamella was doped with various amounts of lithium

Seiichiro Kusuoka, Hirotatsu Nagoji

We consider the stochastic quantization equation associated with the weighted exponential quantum field model (or the H{\o}egh-Krohn model) on the two dimensional torus. Unlike in the case of the usual (unweighted) exponential model, the drift term of the stochastic quantization equation can be both positive and negative, and that makes the equation more dif

Jean-Paul Blaizot, Giuliano Giacalone, Alessandro Lovato

High-energy nuclear collisions have opened a new experimental method to reveal collective behavior in nuclear ground states through the lens of many-body correlations of nucleons. Using ab initio lattice and variational calculations of $^{20}$Ne and $^{16}$O, we study how emergent phenomena such as deformation or clustering can be identified in these systems

Shaokang Jiang, Daye Nam

While Large Language Models (LLMs) have demonstrated remarkable capabilities, research shows that their effectiveness depends not only on explicit prompts but also on the broader context provided. This requirement is especially pronounced in software engineering, where the goals, architecture, and collaborative conventions of an existing project play critica

Jonquil Z. Liao, Joshua Cape

This paper considers the problem of testing for latent structure in large symmetric data matrices. The goal here is to develop statistically principled methodology that is flexible in its applicability, computationally efficient, and insensitive to extreme data variation, thereby overcoming limitations facing existing approaches. To do so, we introduce and s

Matt DeVos, Kathryn Nurse, Robert Šámal

In 1983, A. Bouchet extended W.T. Tutte's notion of nowhere-zero flows to signed graphs, and conjectured that every flow-admissible signed graph has a nowhere-zero 6-flow. In this paper we prove that every flow-admissible signed graph that is 3-edge-connected has a nowhere-zero 8-flow. This is a continuation of a previous paper where we proved the same concl

Tianyuan Liu, Richard Dazeley, Benjamin Champion, Akan Cosgun

In this paper, we study whether inexpensive, physics-free supervision can reliably prioritize grasp-place candidates for budget-aware pick-and-place. From an object's initial pose, target pose, and a candidate grasp, we generate two path-aware geometric labels: path-wise inverse kinematics (IK) feasibility across a fixed approach-grasp-lift waypoint template

Oliver Huang, Muhammad Fatir, Steven Luo, Sangho Suh

When exploring data, analysts construct narratives about what the data means by asking questions, generating visualizations, reflecting on patterns, and revising their interpretations as new insights emerge. Yet existing analysis tools treat narrative as an afterthought, breaking the link between reasoning, reflection, and the evolving story from exploration

Gian Jaeger, Wang Ngai Yeung, Renaud Lambiotte

Although the automation and digitisation of anti-financial crime investigation has made significant progress in recent years, detecting insider trading remains a unique challenge, partly due to the limited availability of labelled data. To address this challenge, we propose using a data-driven networks approach that flags groups of corporate insiders who rep

Ivan Kostov

We investigate the universal behaviour of a one-parameter generalisation of the six-vertex model on planar graphs, which we refer to as the seven-vertex model, or 7vM for quick reference. The 7vM is characterised by a temperature coupling and its continuum limit exhibits massive, dilute and dense phases similarly to the $O(n)$ loop model. However, there is a

Ivan Čilić, Ivana Podnar Žarko, Pantelis Frangoudis, Schahram Dustdar

As computation shifts from the cloud to the edge to reduce processing latency and network traffic, the resulting Computing Continuum (CC) creates a dynamic environment where meeting strict Quality of Service (QoS) requirements and avoiding service instance overload becomes challenging. Existing methods often prioritize global metrics and overlook per-client

P. Altshuler, R. Pupo-Santos, A. Rivera, E. Altshuler

We study the role of repulsive granular interactions between identical intruders as they impact a granular bed. We demonstrate experimentally that repulsion does have a measurable effect in the aspect ratio of binary craters. Furthermore, we show that the protocol followed for the preparation of the granular bed plays a crucial role in the output of table-to

Matt DeVos, Kathryn Nurse

Let $G$ be a graph and let $\{X_0,X_1\}$ be a partition of $V(G)$. This partition is called external or unfriendly if every $x \in X_i$ has at least as many neighbours in $X_{1-i}$ as in $X_i$. Every maximum edge-cut gives rise to an external partition, so these partitions are always guaranteed to exist. However, it remains a challenge to find such partition

Hao Geng, Daniel Jafferis, Pushkal Shrivastava, Neeraj Tata

The AdS/CFT correspondence states an equivalence between a quantum gravitational theory in a (d+1)-dimensional anti-de Sitter spacetime (AdS$_{d+1}$) and a d-dimensional conformal field theory (CFT$_{d}$). The CFT$_{d}$ lives on the asymptotic boundary of the bulk AdS$_{d+1}$. Hence a local operator in the bulk of the AdS$_{d+1}$ should be reconstructable us

Yongteng Gu, Xiangdi Huang

In this paper, we investigate the finite time blow-up of strong solutions to the compressible magnetohydrodynamic (MHD) system (without magnetic diffusion) coupled with entropy transport, and derive an upper bound for the lifespan of such solutions. We first establish the local well-posedness of strong solutions for bounded domains and study the mechanism of

Mohamad Zamini, Diksha Shukla

Multimodal Large Language Models (MLLMs) combine visual and textual representations to enable rich reasoning capabilities. However, the high computational cost of processing dense visual tokens remains a major bottleneck. A critical component in this pipeline is the visual projector, which bridges the vision encoder and the language model. Standard designs o

Anshika Bansal, Jack Jenkins, Daniel Winney

We study dispersive representations of nonlocal form factors in $K^+ \to \pi^+ \ell^+ \ell^-$ and $K^+ \to \pi^+ \nu \bar{\nu}$ decays, with an aim of improving the theoretical description of the spectrum and decay rate of the neutrino mode. Based on unitarity, these representations invoke the $K^+ \pi^- \to \pi^+ \pi^-$ amplitude in $P$-wave and the pion ve

Szymon Rusiecki, Cecilia G. Morales, Kimberly Elenberg, Leonard Weiss

Mass Casualty Incidents can overwhelm emergency medical systems and resulting delays or errors in the assessment of casualties can lead to preventable deaths. We present a decision support framework that fuses outputs from multiple computer vision models, estimating signs of severe hemorrhage, respiratory distress, physical alertness, or visible trauma, into

Gregory Reznik, Jan Dziewior, Shrobona Bagchi, Lev Vaidman

An approach for analysis of effective interaction between pre- and postselected quantum particles is developed. It is argued that the cases of complete pre- and postselection of particles are more profound than the cases of partial pre- and postselection, since the former goes beyond modification of the average of interactions on an ensemble of experiments.

Shaomu Tan, Ryosuke Mitani, Ritvik Choudhary, Qiyu Wu

Over the years, automatic MT metrics have hillclimbed benchmarks and presented strong and sometimes human-level agreement with human ratings. Yet they remain black-box, offering little insight into their decision-making and often failing under real-world out-of-distribution (OOD) inputs. We introduce Remedy-R, a reasoning-driven generative MT metric trained

Chunmei Wang, Shangyou Zhang

This paper proposes a weak Galerkin (WG) finite element method for elliptic interface problems defined on nonconvex polygonal partitions. The method features a built-in stabilizer and retains a simple, symmetric, and positive definite formulation. An optimal-order error estimate is rigorously derived in the discrete $H^1$ norm. Furthermore, a series of numer

Thiago T. Tsutsui, Alison A. Silva, Antonio S. M. de Castro, Fabiano M. Andrade

The Dirac oscillator is a relativistic quantum system, characterized by its linearity in both position and momentum. Moreover, considering $(1{+}1)$ and $(2{+}1)$ dimensions, the system can be mapped onto the Jaynes-Cummings and anti-Jaynes-Cummings models, as illustrated in an exact manner by Bermudez \emph{et al.} [\href{ https://doi.org/10.1103/PhysRevA.7

Valenitn D. Ivanov

The searches for other life and for intelligence are fundamental problems that science faces today. Most searches so far have been focused on radio, but optical laser communication is an alternative, well suited for a ground-based observatory. A project to search for artificial laser communications with the current and future extreme multiplexity spectroscop

Saurabh Bhardwaj, Smriti Srivastava, Abhishek Bhandari, Krit Gupta

This paper proposes a novel Wavelet Packet based feature extraction approach for the task of text independent speaker recognition. The features are extracted by using the combination of Mel Frequency Cepstral Coefficient (MFCC) and Wavelet Packet Transform (WPT).Hybrid Features technique uses the advantage of human ear simulation offered by MFCC combining it

Gökdeniz Gülmez

We present Gabliteration, a novel neural weight modification technique that advances beyond traditional abliteration methods by implementing adaptive multi-directional projections with regularized layer selection. Our approach addresses the fundamental limitation of existing methods that compromise model quality while attempting to modify specific behavioral

Adam Rutkowski

Kadison--Schwarz (KS) maps form a natural class of positive linear maps lying strictly between positivity and complete positivity. Despite their relevance in operator algebras and quantum dynamics, explicit analytic sufficient conditions for the KS property remain scarce beyond low-dimensional or highly symmetric settings. In this work we analyze unital posi

Sanbo Qin, Huan-Xiang Zhou

Gibbs-ensemble Monte Carlo (GEMC) is a powerful method for calculating the gas-liquid binodals of simple models and small molecules, but is too demanding computationally for realistic models of proteins. Here we discover that the main reason for long simulations is that volume exchange is very slow to achieve, and develop a variant GEMC without volume exchan

Dmitry Demidov, Zaigham Zaheer, Zongyan Han, Omkar Thawakar

Vocabulary-free fine-grained image recognition aims to distinguish visually similar categories within a meta-class without a fixed, human-defined label set. Existing solutions for this problem are limited by either the usage of a large and rigid list of vocabularies or by the dependency on complex pipelines with fragile heuristics where errors propagate acro

Hans Schoutens

The category of models of any theory $T$ in any first-order language $L$ has the surprising property that any small category that is elementarily equivalent with it, already embeds in it. The proof uses an abstract argument via ultrapowers, leaving one wonder which concrete categorical axioms, depending on $T$ and $L$, are responsible for this embedding resu

Ilija Rakic

We compute the quantum rate for massless charged scalar emission by a near-extremal Reissner-Nordstr\"om black hole using Schwarzian theory as the effective description of the black hole. This is compared to the semi-classical Hawking rate which we also compute near extremality. We classify black holes into small and large, each with a unique spectrum. For s

Yihe Zhang, Yash Kurkure, Yiheng Tao, Michael E. Papka

High-performance computing (HPC) workloads are becoming increasingly diverse, exhibiting wide variability in job characteristics, yet cluster scheduling has long relied on static, heuristic-based policies. In this work we present SchedTwin, a real-time digital twin designed to adaptively guide scheduling decisions using predictive simulation. SchedTwin perio

Alejandra Martinez, Dennis Novy, Carlo Perroni

A large literature has documented transitivity as a key feature of social networks: individuals are more likely connected with each other if they share common connections with other individuals. We take this idea to trading relationships between firms: firms are more likely to trade with each other if they share common trading partners. Transitivity leads to

Yucheng Yang, Chiyuan Wang, Andreas Schaab, Benjamin Moll

We present a new approach to formulating and solving heterogeneous agent models with aggregate risk. We replace the cross-sectional distribution with low-dimensional prices as state variables and let agents learn equilibrium price dynamics directly from simulated paths. To do so, we introduce a structural reinforcement learning (SRL) method which treats pric

Yuchen Zhang, Eva Lagunas, Xue Xian Zheng, Symeon Chatzinotas

Inter-satellite-link-enabled low-Earth-orbit (LEO) satellite constellations are evolving toward networked architectures that support constellation-level cooperation, enabling multiple satellites to jointly serve user terminals through cooperative beamforming. While such cooperation can substantially enhance link budgets and achievable rates, its practical re

Ashley Colley, Emma Kirjavainen, Sari Tapio, Jonna Häkkilä

This article examines household plastic recycling in Finland through two qualitative studies and four design concepts. Study 1 reports short interviews with residents about how they store, sort, and dispose of plastic packaging in their homes. The findings highlight recurring frictions: limited space, improvised storage, uncertainty about correct sorting, an

Johannes Hofscheier, Alexander Kasprzyk

We introduce Tadao Oda's famous question on lattice polytopes which was originally posed at Oberwolfach in 1997 and, although simple to state, has remained unanswered. The question is motivated by a discussion of the two-dimensional case - including a proof of Pick's Theorem, which elegantly relates the area of a lattice polygon to the number of lattice poin

Akshit Achara, Peter Triantafillou, Esther Puyol-Antón, Alexander Hammers

Deep neural networks often exploit shortcuts. These are spurious cues which are associated with output labels in the training data but are unrelated to task semantics. When the shortcut features are associated with sensitive attributes, shortcut learning can lead to biased model performance. Existing methods for localising and understanding shortcut learning

Aylar G. M. Ghashghaei, Mahboubeh Khorrami, Mohammad Ebrahim Bahrololoom

The molecular mechanisms by which organic additives such as saccharin control microstructure in nickel electrodeposition remain inadequately understood, particularly the role of the intense interfacial electric field. This study employs density functional theory (DFT) calculations to elucidate the field dependent adsorption behavior of neutral saccharin and

Rhea Fernandez, Sarah Hagstrom, Liesel Malanos, Lachlan McGinness

We conducted a literature review and expert interviews to determine the most common methods being used to teach quantum physics and quantum computing concepts to primary and secondary students. Based on the findings of this review, we provide a framework of seven categories of teaching approaches for teaching mathematically accessible quantum concepts; they

Mingxuan Li, Wei Wei, Yin Xu, Ying Wang

Dispatching mobile resources such as repair crews and mobile emergency generators is essential for the rapid restoration of distribution systems after extreme events. However, the restoration process is affected by various uncertain factors including repair time, road condition, and newly observed failures, necessitating online decision-making in response to

Moreno Bevilacqua, Xavier Emery, Francisco Cuevas-Pacheco

The efficient simulation of Gaussian random fields with flexible correlation structures is fundamental in spatial statistics, machine learning, and uncertainty quantification. In this work, we revisit the \emph{spectral turning-bands} (STB) method as a versatile and scalable framework for simulating isotropic Gaussian random fields with a broad range of cova

Kijung Lee

The 2024 U.S. Presidential Election unfolded within an information environment of unprecedented volatility, challenging citizens to navigate a torrent of rapidly evolving, often contradictory information while determining what to believe. This study investigates the cognitive mechanisms underlying epistemic self-efficacy - the perceived ability to distinguis

Nitin Shukla, Alessandro Romeo, Caterina Caravita, Lubomir Riha

High Performance Computing (HPC) based simulations are crucial in Astrophysics and Cosmology (A&C), helping scientists investigate and understand complex astrophysical phenomena. Taking advantage of exascale computing capabilities is essential for these efforts. However, the unprecedented architectural complexity of exascale systems impacts legacy codes. The

Tylor Adkins, Shahed Shayan Arani, Kam Arnold, Carlo Baccigalupi

We present a search for polarization oscillation of the Crab Nebula, also known as Tau A, at millimeter wavelengths using observations with the Simons Array, the successor experiment to POLARBEAR. We follow up on previous work by POLARBEAR using 90 GHz band data of the 2023 observing season of the Simons Array to evaluate the variability of Tau A's polarizat

İzzet Sakallı, Erdem Sucu, Ahmad Al-Badawi, Faizuddin Ahmed

We present an investigation of a static, spherically symmetric Letelier black hole (BH) immersed in an electromagnetic universe (EMU), characterized by the cloud of strings (CoS) parameter $\alpha$ and the EMU parameter $a$. The photon sphere and shadow radius are derived analytically, revealing how both parameters modify the apparent BH silhouette compared

Ming Li, Han Chen, Yunze Xiao, Jian Chen

Accurate estimation of item (question or task) difficulty is critical for educational assessment but suffers from the cold start problem. While Large Language Models demonstrate superhuman problem-solving capabilities, it remains an open question whether they can perceive the cognitive struggles of human learners. In this work, we present a large-scale empir

Leonardo Colombo

We develop a discrete Pontryagin Maximum Principle (PMP) for controlled open quantum systems governed by Lindblad dynamics, and introduce a second--order \emph{contact Lie--group variational integrator} (contact LGVI) that preserves both the CPTP (completely positive and trace--preserving) structure of the Lindblad flow and the contact geometry underlying th

Kaidi Liang, Ke Li, Xianbiao Hu, Ruwen Qin

Automating crash video analysis is essential to leverage the growing availability of driving video data for traffic safety research and accountability attribution in autonomous driving. Crash video analysis is a challenging multitask problem due to the complex spatiotemporal dynamics of crash events in video data and the diverse analytical requirements invol

Susumu Ariki, Sinéad Lyle, Liron Speyer, Qi Wang

Schurian-finiteness, also known as $\tau$-tilting finiteness, is equivalent to the finiteness of various representation theoretic objects such as wide subcategories. The first three authors classified Schurian-finite blocks of type A Hecke algebras in [ALS23]. Here we study the Schurian-finiteness of blocks of type B Hecke algebras, and determine the Schuria

Lauren McClure, Suzana Silva, Gary Verth, Istvan Ballai

Small-scale vortices in the solar photosphere play a central role in transporting mass, energy, and momentum into the upper solar atmosphere, yet reliably detecting these structures remains rather challenging. We address this problem by introducing a simple preprocessing step that normalises the velocity field by its magnitude. Our method preserves flow topo

Danil Gubarevich

Even dimensional complete intersections $X$ of two quadrics in projective space are exceptional from the point of view of the Gromov-Witten theory: they are (together with qubic surfaces) the only complete intersections whose Gromov-Witten theory is not invariant under the full orthogonal or symplectic group acting on the primitive cohomology. The genus~0 Gr

Dirk Erhard, Tertuliano Franco, Wanessa Muricy

In the 1950s, W. Feller characterized the most general Brownian motion on the closed half-line. He showed that any such process is a mixture of reflected, sticky, and killed Brownian motions. By most general Brownian motion, we mean a strong Markov process whose excursions away from zero coincide with those of standard Brownian motion, and which may be sent

Airton Deppman

We present the first exact, multi-mode solutions to the Plastino-Plastino nonlinear diffusion equation with arbitrary power-law drift. By allowing each $q$-exponential mode to have its own independent, time-dependent centre, all inter-mode couplings in the drift term vanish, yielding fully separable evolution equations for centre motion, probability content,

Paolo Luppi, Claudia Benedetti, Andrea Smirne

We investigate the genuinely quantum features of continuous-time quantum walks by combining a single-time and a multi-time quantifier of nonclassicality. On the one hand, we consider the quantum-classical dynamical distance $D_{\mathrm{QC}}(t)$, which measures the departure of the time-evolved quantum state of a continuous-time quantum walk from the classica

Gábor Gévay, György Kiss, Tomaž Pisanski

In 1990, Branko Gr\"unbaum and John Rigby presented a 4-configuration, known today as the \emph{Gr\"unbaum--Rigby configuration}; it is denoted by $\mathrm{GR}(21_4)$. Independently and earlier, in 1986, Ferenc K\'arteszi published a paper in which he proved a theorem in real geometry that gives rise to a series of 4-configurations $\mathrm{K}(n;\ell,m)$. In

Bruno Campello de Souza

The rapid diffusion of generative artificial intelligence (GenAI) systems has introduced new forms of human-technology interaction, raising the question of whether sustained engagement gives rise to stable, internalized modes of cognition rather than merely transient efficiency gains. Grounded in the Cognitive Mediation Networks Theory, this study investigat

Tian-ye Xia, Juntai Shen, John Magorrian, Yu-jing Qin

We present a novel method for classifying two-dimensional orbits in rotating bar potentials, based on an empirical proxy for the second integral of motion, Calibrated Angular Momentum (CAM), which is defined as the ratio of the time-averaged angular momentum ($\overline{L_z}$) to its temporal dispersion ($\sigma_{L_z}$) in the corotating frame. We show that

Georg Nawratil

In the 19th International Symposium on Advances in Robot Kinematics the author introduced a novel class of continuous flexible discrete surfaces and mentioned that these so-called P-hedra (or P-nets) allow direct access to their spatial shapes by three control polylines. In this follow-up paper we study this intuitive method, which makes these flexible plana

Generoso Immediato

In direct response to requests for a logico-mathematical test of the conjecture, we formally disprove a recently conjectured artificial intelligence trade-off between epistemic certainty and scope in its published universal hyperbolic product form, as introduced in Philosophy and Technology. Certainty is defined as the worst-case correctness probability over

Anastasia Stavrova

Let $A$ be a regular ring of dimension $\le 2$. Let $G$ be a reductive group over $A$ such that its derived group is a split, i.e. a Chevalley--Demazure, semisimple group. We prove that every Zariski-locally trivial principal $G$-bundle over $A[x_1,\ldots,x_n]$ is extended from $A$, for any $n\ge 1$. This result generalizes to split reductive groups the dime

Valeriy A. Buryachenko

This work presents an enhanced Computational Analytical Micromechanics (CAM) framework for the analysis of linear thermoelastic composite materials (CMs) with random microstructure. The proposed approach is grounded in an exact Additive General Integral Equation (AGIE), specifically formulated for compactly supported loading, including both body forces and l

Garrett Mulcahy, Soumik Pal

We present a collection of explicit diffusion approximations to small temperature Schr\"{o}dinger bridges on manifolds. Our most precise results are when both marginals are the same and the Schr\"{o}dinger bridge is on a manifold with a reference process given by a reversible diffusion. In the special case that the reference process is the manifold Brownian

Yong-Kang Huang, Dong-Hao Li, Cai-Dian Lü, Bo-Xuan Shi

By incorporating the available leading-power results at $\mathcal{O}(\alpha_s)$ and next-to-leading-power corrections at tree level, we improve the precision of the theoretical predictions for $B\to\pi$ form factors to the $\mathcal{O}(\alpha_s^2\beta_0)$ level in the large-recoil region using the light-cone sum rule approach with $B$-meson light-cone distri

Maksym Voloshchuk, Bohdana Zarembovska, Mykola Kozlenko

Handwritten text recognition and optical character recognition solutions show excellent results with processing data of modern era, but efficiency drops with Latin documents of medieval times. This paper presents a deep learning method to extract text information from handwritten Latin-language documents of the 9th to 11th centuries. The approach takes into

Alina Elena Baia, Andrea Cavallaro

Concept-driven counterfactuals explain decisions of classifiers by altering the model predictions through semantic changes. In this paper, we present a novel approach that leverages cross-modal decompositionality and image-specific concepts to create counterfactual scenarios expressed in natural language. We apply the proposed interpretability framework, ter

Attila Simkó, Matthias Kronsteiner, Simon Glatzer, Minh Vu

Radiotherapy treatment planning remains a time-intensive iterative process requiring expert intervention in commercial treatment planning system (TPS). While machine learning approaches have demonstrated promise, most remain depedent on TPS-based dose calculation or surrogate dose models, preventing direct optimization of deliverable treatment plan parameter

Octavio A. Agustín-Aquino, Brandon J. Curiel-López

We address certain structural innovations in the music of Claudio Monteverdi, which defined the pivotal transition from the Renaissance prima pratica to the Baroque seconda pratica. To formalize this analysis, we employ Mazzola's symmetry-based framework for counterpoint and quantum/duality models for tonal modulation. Our findings demonstrate that these mat

Matilde Marcolli, David Skigin

We study the dynamical properties of a Hopf algebra Markov chain with state space the binary rooted forests with labelled leaves. This Markovian dynamical system describes the core computational process of structure formation and transformation in syntax via the Merge operation, according to Chomsky's Minimalism model of generative linguistics. The dynamics

Merle Munko, Simon Mack, Marc Ditzhaus, Stefan Fröhling

The progression-free survival ratio (PFSr) is a widely used measure in personalized oncology trials. It evaluates the effectiveness of treatment by comparing two consecutive event times - one under standard therapy and one under an experimental treatment. However, most proposed tests based on the PFSr cannot control the nominal type I error rate, even under

Thammarat Yawisit, Pittaya Pannil

Time misalignment and intermittent readout can bias multichannel dependence estimates by mixing timing error with missing data. Time-Aligned Multichannel Coherence Estimation (TAMCE) reports a causal network coherence statistic G together with an explicit observation-support state Q using normalized recursive channel states, independent timing calibration, a

Avirup Chakraborty, Shirsa Maitra, Tathagata Banerjee, Diganta Mukherjee

Rating systems play a crucial role in evaluating player skill across competitive environments. The Elo rating system, originally designed for deterministic and information-complete games such as chess, has been widely adopted and modified in various domains. However, the traditional Elo rating system only considers game outcomes for rating calculation and as

Zijun Gao, Zhikun Xu, Xiao Ye, Ben Zhou

Large language models (LLMs) often solve challenging math exercises yet fail to apply the concept right when the problem requires genuine understanding. Popular Reinforcement Learning with Verifiable Rewards (RLVR) pipelines reinforce final answers but provide little fine-grained conceptual signal, so models improve at pattern reuse rather than conceptual ap

Kyu-Won Park, Soojoon Lee, Kabgyun Jeong

Non-Hermitian physics has become a fundamental framework for understanding open systems where gain and loss play essential roles, with impact across photonics, quantum science, and condensed matter. While the role of complex eigenvalues is well established, the nature of the corresponding eigenfunctions has remained a long-standing problem. Here we show that

Badis Ydri

Noncommutative field theory (NCFT) is an extension of quantum field theory (QFT) that redefines spacetime, replacing commuting coordinates with a noncommutative structure. This shift fundamentally alters the way fields, interactions, and symmetries are understood. NCFT uniquely integrates with supersymmetry, making it a natural framework for unifying quantum

Xiarui Su, Xihui Teng, Yiyang Yu, Yiming Yang

On-chip reconfigurable intelligent surfaces (RIS) are expected to play a vital role in future 6G communication systems. This work proposed a CMOS-compatible on-chip RIS capable of achieving beam steering for the first time. The proposed unit cell design is a combination of a slot, a phase-delay line with VO2, and a ground. Under the two states of the VO2, th