December 2025 arXiv papers — page 77

Ingrid Amaranta Membrillo Solis, Maria van Rossem, Tristan Madeleine, Tetiana Orlova

A complex system comprises multiple interacting entities whose interdependencies form a unified whole, exhibiting emergent behaviours not present in individual components. Examples include the human brain, living cells, soft matter, Earth's climate, ecosystems, and the economy. These systems exhibit high-dimensional, non-linear dynamics, making their modelli

Nima Dehmamy, Benjamin Hoover, Bishwajit Saha, Leo Kozachkov

Generative Pre-trained Transformer (GPT) architectures are the most popular design for language modeling. Energy-based modeling is a different paradigm that views inference as a dynamical process operating on an energy landscape. We propose a minimal modification of the GPT setting to unify it with the EBM framework. The inference step of our model, which we

Wafa Labidi, Vida Gholamian, Yaning Zhao, Christian Deppe

Molecular Communication (MC) is an emerging field of research focused on understanding how cells in the human body communicate and exploring potential medical applications. In theoretical analysis, the goal is to investigate cellular communication mechanisms and develop nanomachine-assisted therapies to combat diseases. Since cells transmit information by re

Tianshuai Hu, Xiaolu Liu, Song Wang, Yiyao Zhu

Autonomous driving has long relied on modular "Perception-Decision-Action" pipelines, where hand-crafted interfaces and rule-based components often break down in complex or long-tailed scenarios. Their cascaded design further propagates perception errors, degrading downstream planning and control. Vision-Action (VA) models address some limitations by learnin

Dante de Roos, Ben Chugg, Peter Grünwald, Aaditya Ramdas

We show that for any concave utility, the expected utility of an e-variable can only increase after conditioning on a sufficient statistic. The simplest form of the result has an extremely straightforward proof, which follows from a single application of Jensen's inequality. Similar statements hold for compound e-variables, asymptotic e-variables, and e-proc

Maximilian Zimmermann, Elke Pilat-Lohinger

The discovery of exoplanets in binary star systems-now numbering about 850 of the nearly 4,600 known exoplanet systems-raises questions about whether observational bias or stellar companions inhibit planet formation. While most studies on terrestrial planet formation assume planar configurations, wide binaries likely feature random inclinations, potentially

Kamal Aghazade, Toktam Zand, Ali Gholami

Full-waveform inversion (FWI) is a powerful seismic imaging technique used to estimate high-resolution physical properties of subsurface structures by minimizing the misfit between observed and modeled seismic data. FWI is inherently a highly non-linear and ill-posed inverse problem. Extended-source approaches, such as the augmented Lagrangian (AL) method, a

Siqi Wang, Chao Liang, Yunfan Gao, Erxin Yu

Vision-Language Models (VLMs) have made significant progress in explicit instruction-based navigation; however, their ability to interpret implicit human needs (e.g., "I am thirsty") in dynamic urban environments remains underexplored. This paper introduces CitySeeker, a novel benchmark designed to assess VLMs' spatial reasoning and decision-making capabilit

Claire Rigouzzo, Sebastian Zell

For axions present during inflation, it has been shown that a non-minimal coupling $\xi_\sigma$ of the inflaton to gravity worsens isocurvature bounds, while a non-minimal coupling $\xi_\rho$ of the radial Peccei-Quinn field can alleviate them. We analyze the simultaneous presence of both couplings and determine when one effect dominates the other, in both t

Danielle Frostig, Nathan Lourie, Viraj Karambelkar, Mansi M. Kasliwal

The Wide-field Infrared Transient Explorer (WINTER) is a near-infrared time-domain survey instrument operating on a dedicated 1-meter robotic telescope at Palomar Observatory. The project takes advantage of recent technology advances in time-domain astronomy, robotic telescopes, large-format sensors, and rapid data reduction and alert software for timely fol

Hana KimLee, Leonardo Bacciottini, Abhishek Bhatt, Andrew Kille

Progress in quantum computing and networking depends on codesign across abstraction layers: device-level noise and heterogeneous hardware, algorithmic structure, and distributed classical control. We present QuantumSavory, an open-source toolkit built to make such end-to-end studies practical by cleanly separating a symbolic computer-algebra frontend from in

A. Iosevich, Z. Li, E. Palsson, A. Yavicoli

We introduce a continuous analog of the Fourier ratio for compactly supported Borel measures. For a measure \(\mu\) on \(\mathbb{R}^d\) and \(f\in L^2(\mu)\), the Fourier ratio compares \(L^1\) and \(L^2\) norms of a regularized Fourier transform at scale \(R\). We develop a fractal uncertainty principle giving sharp two-sided bounds in terms of covering num

Claudia Vale Oliveira, Nelson Zagalo, Filipe Silva, Anabela Brandao

Large language models (LLMs) are increasingly used as epistemic partners in everyday reasoning, yet their errors remain predominantly analyzed through predictive metrics rather than through their interpretive effects on human judgment. This study examines how different forms of epistemic failure emerge, are masked, and are tolerated in human AI interaction,

Ulrich Bunke

This paper investigates a variety of coarse homology theories and natural transformations between them. We in particular study the commutativity of a square relating analytical and topological transgressions with algebraic and homotopy theoretic Chern characters. Here a transgression is a natural transformation from a coarse homology theory to a functor whic

Derek Long

We study portfolio selection with a Conditional Value-at-Risk (CVaR) constraint under distribution shift and serial dependence. While Wasserstein distributionally robust optimization (DRO) offers tractable protection via an ambiguity ball around empirical data, choosing the ball radius is delicate: large radii are conservative, small radii risk violation und

Yilin Ye, Denis S. Grebenkov

We investigate the statistical correlation between the first-reaction time of a diffusing particle and its boundary local time accumulated until the reaction event. Since the reaction event occurs after multiple encounters of the particle with a partially reactive boundary, the boundary local time as a proxy for the number of such encounters is not independe

Polra Victor Falade, Oluwafemi Osho

This paper examines Nigeria's pursuit of digital sovereignty through two core instruments: the Cybercrimes (Prohibition, Prevention, etc.) Act and the National Cybersecurity Policy and Strategy (NCPS). Despite recent reforms, it remains unclear whether these frameworks effectively secure Nigeria's digital domain and advance its digital sovereignty amid escal

Boaz Moerman

We establish an asymptotic formula for the number of $\mathcal{M}$-points of bounded height on split toric varieties, for the height induced by any big and nef divisor class. This formula establishes new cases of the extension of Manin's conjecture to $\mathcal{M}$-points, as introduced by the author. As a special case of our result, we strengthen the result

Simon Donker van Heel, Neil Shephard

We propose using a discounted version of a convex combination of the log-likelihood with the corresponding expected log-likelihood such that when they are maximized they yield a filter, predictor and smoother for time series. This paper then focuses on working out the implications of this in the case of the canonical exponential family. The results are simpl

Miguel Escobar Azor, David D. O'Regan, Ali Safavi, Jacek Dziedzic

We present a spin-dependent extension of the non-orthogonal generalized Wannier function (NGWF) formalism within the framework of linear-scaling density functional theory (LS-DFT) as implemented in the ONETEP code. In traditional LS-DFT representations, both spin channels are constrained to share a common variational basis, which limits the accuracy for syst

Mahadev Prasad Panda, Purnachandra Rao Makkena, Srivatsa Prativadibhayankaram, Siegfried Fößel

Reducing computational complexity remains a critical challenge for the widespread adoption of learning-based image compression techniques. In this work, we propose TreeNet, a novel low-complexity image compression model that leverages a binary tree-structured encoder-decoder architecture to achieve efficient representation and reconstruction. We employ atten

Wisnu Uriawan, Muhamad Veva Ramadhan, Firman Adi Nugraha, Hasbi Nur Wahid

The rapid digitalization of Hajj and Umrah services in Indonesia has significantly facilitated pilgrims but has concurrently opened avenues for digital fraud through counterfeit mobile applications. These fraudulent applications not only inflict financial losses but also pose severe privacy risks by harvesting sensitive personal data. This research aims to a

Zaheed Ahmed, Philip Makedonski, Jens Grabowski

Mutation analysis is a well-established technique for assessing test quality in the traditional software development paradigm by injecting artificial faults into programs. Its application to deep learning (DL) has expanded beyond classical testing to support tasks such as fault localization, repair, data generation, and model robustness evaluation. The core

Yunkai Yang, Yudong Zhang, Kunquan Zhang, Jinxiao Zhang

With the rapid progress of controllable generation, training data synthesis has become a promising way to expand labeled datasets and alleviate manual annotation in remote sensing (RS). However, the complexity of semantic mask control and the uncertainty of sampling quality often limit the utility of synthetic data in downstream semantic segmentation tasks.

Dionysios Anninos, Damián A. Galante, Silvia Georgescu, Chawakorn Maneerat

We consider four-dimensional general relativity with a positive cosmological constant, $\Lambda$, in the presence of a boundary, $\Gamma$, of finite spatial size. The boundary is located near a cosmological event horizon, and is subject to boundary conditions that fix the conformal class of the induced metric, and, $K$, the trace of the extrinsic curvature a

Sayan Dutta, Maria C. Lesniewski, Muhammad Nawaz Qaisrani, W. G. Noid

Conjugated organic molecules play a central role in a wide range of optoelectronic devices, including organic light-emitting diodes, organic field-effect transistors, and organic solar cells. A major bottleneck in the computational design of these materials is the discrepancy between simulation and experimental time and length scales. Coarse-graining (CG) of

Xiaofeng Zong, Ming-Yu Wang, Jimin Wang, Ji-Feng Zhang

This paper investigates the differentially private consensus problem for general linear multi-agent systems (MASs) based on output feedback protocols. To protect the output information, which is considered private data and may be at high risk of exposure, Laplace noise is added to the information exchange. The conditions for achieving mean square and almost

Sotiris Skaperas, Arsenia Chorti

A framework is presented for analyzing the impact of active attacks to location-based physical layer authentication (PLA) using the machinery of misspecified Cram\'er--Rao bound (MCRB). In this work, we focus on the MCRB in the angle-of-arrival (AoA) based authentication of a single antenna user when the verifier posseses an $M$ antenna element uniform linea

Jonathan Kriewald, Emanuelle Pinsard, Ana M. Teixeira

Within the context of heavy neutral lepton extensions of the Standard Model, we consider the rare di-Higgs production mode $\ell^+\ell^-\to hh$ at future high-energy lepton colliders. As a concrete example, we study the impact of a low-scale Inverse Seesaw realisation on the prospects for di-Higgs production. Our results show that the presence of TeV-scale h

Zhenyang Gao, Pengyuan Ren, Yifeng Dong, Gengchen Zheng

Metamaterials benefit from unique architected patterns to achieve lightweight with exceptional mechanical properties inaccessible to conventional materials. Typical mechanical metamaterials are inspired by crystal-like lattice structures, whose closely packed frameworks often exhibit a rigid mechanical nature. Here, we present polymer-inspired metamaterials

Md. Wali Hossain

Allowing for greater low-redshift flexibility through parametrizations such as CPL can lead to apparent deviations from $\Lambda$CDM, with the latter lying at roughly the $2\sigma$ level from the best-fit model. This motivates an investigation into whether such deviations reflect genuine dynamical dark energy or arise from parametrization choices. We investi

Sandeep R. Murthy

Three non-empty subsets $S,T,U$ of a group $G$ are said to satisfy the triple product property (TPP) if, for elements $s,s' \in S$, and $t,t' \in T$, and $u,u' \in U$, the equation $s's^{-1}t't^{-1}u'u^{-1}=1$ holds if and only if $s = s'$, $t = t'$, $u = u'$. If this is the case then $(S,T,U)$ is called a TPP triple of $G$ and $|S||T||U|$ the size of the tr

Rebeca Miyar, Bar Favelukis, Eva B. Mayer, Manoj Prabhakar

MXenes are promising candidates for electrochemical applications due to their high conductivity, tunable surface chemistry, and catalytic potential. However, their use in bulk electrode form remains unexplored despite advantages such as higher current density and improved mechanical integrity. Herein, we present a methodology for the fabrication of self-supp

M. Messa, E. Vanzella, T. Morishita, M. Stiavelli

We report the unprecedented Ly$\alpha$ properties of AMORE6, an extremely metal-poor ($12+\log({\rm O/H}) < 6$), low-mass ($M_\star = 4.4\times10^{5}\,M_\odot$), and ultracompact (effective radius $\sim30$ pc) dwarf galaxy at $z=5.7253$, which is gravitationally lensed by the cluster A2744. A prominent, narrow, and nearly symmetric Ly$\alpha$ emission line i

Haochen Chang, Pengfei Ren, Buyuan Zhang, Da Li

Online micro gesture recognition from hand skeletons is critical for VR/AR interaction but faces challenges due to limited public datasets and task-specific algorithms. Micro gestures involve subtle motion patterns, which make constructing datasets with precise skeletons and frame-level annotations difficult. To this end, we develop a multi-view self-supervi

Alexandru Ciobanu, David Dahmen, John Paul Strachan, Moritz Helias

Combinatorial optimization problems have a broad range of applications and map to physical systems with complex dynamics. Among them, the 3-SAT problem is prominent due to its NP-complete nature. In physics terms, its solution corresponds to finding the ground state of a disordered Ising spin Hamiltonian with third-order, or tensor, interactions. The large g

Yixiang Chen, Yan Huang, Keji He, Peiyan Li

When performing 3D manipulation tasks, robots have to execute action planning based on perceptions from multiple fixed cameras. The multi-camera setup introduces substantial redundancy and irrelevant information, which increases computational costs and forces the model to spend extra training time extracting crucial task-relevant details. To filter out redun

Kai Hu, Abhinav Aggarwal, Mehran Khodabandeh, David Zhang

This paper introduces Jailbreak-Zero, a novel red teaming methodology that shifts the paradigm of Large Language Model (LLM) safety evaluation from a constrained example-based approach to a more expansive and effective policy-based framework. By leveraging an attack LLM to generate a high volume of diverse adversarial prompts and then fine-tuning this attack

Lei Wang, Xin Tan, Mingwei Wang, Ying Zhang

Recent selective state space models (SSMs), such as Mamba and Mamba-2, have demonstrated strong performance in sequence modeling owing to input-dependent selection mechanisms. However, these mechanisms lack theoretical grounding and cannot support context-aware selection from latent state dynamics. To address these limitations, we propose KOSS, a Kalman-opti

Hosein Gholami, Marco Hofmann, Débora Mroczek, Jacquelyn Noronha-Hostler

Current observations of neutron stars and measurements of gravitational waves only provide constraints on the zero temperature ($T=0$) equation of state (EoS) of dense matter. The detection of the post-merger gravitational-wave signal from a binary neutron star merger would additionally provide access to finite-temperature properties of the EoS which contain

Atsu Kokuvi Angelo Passah, Rodrigo C. de Lamare, Arsenia Chorti

This paper introduces an adaptive preprocessing technique to enhance the accuracy of channel state information-based physical layer authentication (CSI-PLA) alleviating CSI variations and inconsistencies in the time domain. To this end, we develop an adaptive robust principal component analysis (A-RPCA) preprocessing method based on robust principal componen

Yuriy N. Bakhvalov

In a previous paper it was shown that a machine learning regression problem can be solved within the framework of random function theory, with the optimal kernel analytically derived from symmetry and indifference principles and coinciding with a polyharmonic spline. However, a direct application of that solution is limited by O(N^3) computational cost and b

Rudra Dubey, Arpit Mani Tripathi, Archit Srivastava, Sarvpal Singh

In actuality, phishing attacks remain one of the most prevalent cybersecurity risks in existence today, with malevolent actors constantly changing their strategies to successfully trick users. This paper presents an AI model for a phishing detection system that uses an ensemble approach to combine character-level Convolutional Neural Networks (CNN) and Light

Sanjeeb Poudel, Sanghyun Lee, Lin Mu

We propose a pressure-robust enriched Galerkin (EG) finite element method for the incompressible Navier-Stokes and heat equations in the Boussinesq regime. For the Navier-Stokes equations, the EG formulation combines continuous Lagrange elements with a discontinuous enrichment vector per element in the velocity space and a piecewise constant pressure space,

Oliver Stritzel, Nick Hühnerbein, Simon Rauch, Itzel Zarate

In recent years, Predictive Process Mining (PPM) techniques based on artificial neural networks have evolved as a method for monitoring the future behavior of unfolding business processes and predicting Key Performance Indicators (KPIs). However, many PPM approaches often lack reproducibility, transparency in decision making, usability for incorporating nove

Ian Wong, William M. Grundy, Joshua P. Emery, Richard P. Binzel

We present new visible-wavelength spectroscopic observations of the Patroclus-Menoetius binary system in the Jupiter Trojan population. Motivated by previously published spectra from different instruments that showed evidence of significant longitudinal variability, we obtained two spectra spanning 440-680 nm at near-opposite rotational phases with the Gemin

J. Berteaud, F. Calore, M. Clavel, J. Marvil

The existence of a population of millisecond pulsars in the Galactic bulge is supported, along with other evidence, by the Fermi GeV excess, an anomalous {\gamma}-ray emission detected almost 15 years ago in the direction of the Galactic center. However, radio surveys searching for pulsations have not yet revealed bulge millisecond pulsars. Identifying promi

Didier Barret, Simon Dupourqué

Simulation-based inference (SBI) with neural posterior estimation (NPE) provides rapid X-ray spectral fitting in both Gaussian and Poisson regimes by learning approximate parameter posteriors from simulations. We investigate auto-encoders for compressing high-resolution X-ray spectra, motivated by newAthena X-ray Integral Field Unit (X-IFU), and use likeliho

Michael A. Kuhn, Robert A. Benjamin, Simran S. Singh

The Serpens OB2 association (l ~ 18.5 deg, b ~ 1.9 deg, d = 1950 +/- 30 pc) is a large star-forming complex ~65 pc above the Galactic midplane, with a clumpy, elongated structure extending ~50 pc parallel to the plane. We analyse probable association members, including OB stars and low-to-intermediate-mass young stellar objects (YSOs) from the SPICY catalogu

Abhisek Ganguly

We formalize two independent computational limitations that constrain algorithmic intelligence: formal incompleteness and dynamical unpredictability. The former limits the deductive power of consistent reasoning systems while the latter bounds long-term prediction under finite precision. We show that these two extrema together impose structural bounds on an

Antonella Rech, Nicola Conci, Nicola Garau

Neural radiance fields (NeRF) have driven impressive progress in view synthesis by using ray-traced volumetric rendering. Splatting-based methods such as 3D Gaussian Splatting (3DGS) provide faster rendering by rasterizing 3D primitives. RadiantFoam (RF) brought ray tracing back, achieving throughput comparable to Gaussian Splatting by organizing radiance wi

David Müller, Espen Knoop, Dario Mylonopoulos, Agon Serifi

Animated characters often move in non-physical ways and have proportions that are far from a typical walking robot. This provides an ideal platform for innovation in both mechanical design and stylized motion control. In this paper, we bring Olaf to life in the physical world, relying on reinforcement learning guided by animation references for control. To c

Juan C. Rocha, Maike Hamann, Jiangxiao Qiu, Tong Wu

The relationship between inequality and the biosphere has been hypothesized to mutual dependecies and feedbacks. If that is true, such feedbacks may give rise to inequality regimes and potential tipping points between them. Here we explore synergies and trade-offs between inequality and biosphere-related sustainable development goals. We used the openly avai

Giovanni Adorni

Generative Artificial Intelligence (GenAI) is rapidly reshaping how knowledge is produced and validated in education. Rather than adding another digital tool, large language models reconfigure reading, writing, and coding into hybrid human-AI workflows, raising concerns about epistemic automation, cognitive offloading, and the de-professiona\-lisation of tea

John M. Statheros, Hairong Wang, Richard Klein

The interpretation of chest X-rays (CXRs) poses significant challenges, particularly in achieving accurate multi-label pathology classification and spatial localization. These tasks demand different levels of annotation granularity but are frequently constrained by the scarcity of region-level (dense) annotations. We introduce CLARiTy (Class Localizing and A

Keith Zengel, Anna Klales

We present a simple experiment that can be run in class or remotely with minimal materials. Students use the principles of geometric optics to create their own versions of the bat signal.

J. Berteaud, F. Calore, M. Clavel, S. Dai

The mysterious Galactic Center Excess of gamma rays could be explained by a large population of millisecond pulsars hiding in the Galactic bulge, too faint to be detected as individual high-energy point sources by the Fermi Large Area Telescope, as well as too fast and too dispersed to be detected in shallow radio pulsation surveys. Motivated by an innovativ

Mahbub E Sobhani, Md. Faiyaz Abdullah Sayeedi, Mohammad Nehad Alam, Proma Hossain Progga

Diagram-grounded geometry problem solving is a critical benchmark for multimodal large language models (MLLMs), yet the benefits of multi-agent design over single-agent remain unclear. We systematically compare single-agent and multi-agent pipelines on four visual math benchmarks: Geometry3K, MathVerse, OlympiadBench, and We-Math. For open-source models, mul

Chris Kapulkin, Yufeng Li

We provide a formulation of the univalence axiom in a universe category model of dependent type theory that is convenient to verify in homotopy-theoretic settings. We further develop a strengthening of the univalence axiom, called pointed univalence, that is both computationally desirable and semantically natural, and verify its closure under Artin-Wraith gl

Marco Sangalli, Erik Quaeghebeur, Thomas Krak

We study the computation of lower and upper probabilities of hitting a target set of states for imprecise Markov chains, where transition uncertainty is modelled by a convex set of transition matrices. In the precise case, hitting probabilities are the minimal nonnegative solution of a linear system and admit a closed-form expression. We investigate the noti

Andrey M. Pupasov-Maksimov, Marcelo Silva Oliveira

Darboux transformations of the singular harmonic oscillator are considered. Analytical expressions for the propagators are obtained, using the image method applied to formal singular propagators. Two-well and three-well families of potentials and the corresponding propagators are presented. Axially symmetric magnetic field configurations corresponding to the

Wisnu Uriawan, Achmad Ajie Priyajie, Angga Gustian, Fikri Nur Hidayat

This research stems from the urgency to automate the thematic grouping of hadith in line with the growing digitalization of Islamic texts. Based on a literature review, the unsupervised learning approach with the Apriori algorithm has proven effective in identifying association patterns and semantic relations in unlabeled text data. The dataset used is the I

Antoine Martinez, Hiroki Karyu, Amanda Brecht, Gabriella Gilli

In the context of future Venusian missions, it is crucial to improve our understanding of Venus upper atmosphere through 3D modeling, notably for spacecraft orbit computation. This study compares three General Circulation Models (GCMs) of the Venusian atmosphere up to the exosphere: the Venus Planetary Climate Model (Venus PCM), the Venus Thermospheric Globa

V. Paul-Boncour, O. Isnard

TbFe$_{2}$D$_{4.2}$ deuteride crystallizes in a monoclinic structure ($Pc$ space group) with deuterium inserted into 13 [Tb$_{2}$Fe$_{2}$] and 5 [TbFe$_{3}$] tetrahedral interstitial sites. Its structural evolution versus temperature has been investigated by combining in-situ X-ray and neutron diffraction (XRD and NPD) with differential scanning calorimetry

Luca Forte, Leo van Iersel, Steven Kelk, Ruben Meuwese

In this note we demonstrate that a number of case-heavy combinatorial proofs in the mathematical phylogenetics literature can be proven more compactly using computational support. We use these techniques to also prove several new combinatorial lemmas that would have taken considerable effort to prove by hand. We are optimistic that similar approaches can be

Justus Teller, Abdur Rehman Jalil, Florian Lentz, Detlev Grützmacher

Stencil mask lithography is an advanced technique for fully in-situ fabricating Josephson junctions, which is increasingly being used for multi-terminal Josephson junctions. This study provides information on the optimal mask design and mask reliability. For this, 270 mask designs were systematically fabricated and investigated under scanning electron micros

Federico Fiorenza, Sara Dubbioso, Gianmaria De Tommasi, Alfredo Pironti

In this work, we propose a novel physics informed neural network based algorithm for real time plasma boundary reconstruction in tokamak devices. The approach is based on a single Extreme Learning Machine network used to solve the homogeneous Grad Shafranov equation, which is required to identify the plasma boundary. This architecture enables the real time t

Serafino Pandolfini, Lorenzo Pellegrini, Matteo Ferrara, Davide Maltoni

The rapid progress of generative AI has enabled highly realistic image manipulations, including inpainting and region-level editing. These approaches preserve most of the original visual context and are increasingly exploited in cybersecurity-relevant threat scenarios. While numerous detectors have been proposed for identifying fully synthetic images, their

Natnael Tilahun Sinshaw, Mengmei He, Tadesse K. Bahiru, Sudhir Kumar Mohapatra

Text classification problems, such as gender classification from a blog, have been a well-matured research area that has been well studied using machine learning algorithms. It has several application domains in market analysis, customer recommendation, and recommendation systems. This study presents a comparative analysis of the widely used machine learning

Xinqun Mei, Guofang Wang, Liangjun Weng

We study the prescribed Lp curvature problem for convex capillary hypersurfaces in the Euclidean half-space. By reducing the problem to finding a convex solution of a Hessian quotient type equation with a Robin boundary condition on a spherical cap, we establish the existence and uniqueness of smooth admissible (in fact, strictly convex) solutions. As applic

Gonçalo Gaspar Alves, Shekoufeh Gorgi Zadeh, Andreas Husch, Ben Bausch

Combining open-source datasets can introduce data leakage if the same subject appears in multiple sets, leading to inflated model performance. To address this, we explore subject fingerprinting, mapping all images of a subject to a distinct region in latent space, to enable subject re-identification via similarity matching. Using a ResNet-50 trained with tri

Bentley DeVilling

Multimodal AI systems integrate text generation, image generation, and other capabilities within a single conversational interface. These systems employ safety mechanisms to prevent disallowed actions, including the removal of watermarks from copyrighted images. While single-turn refusals are expected, the interaction between safety filters and conversation-

Yann Disser, Georg Loho, Matthew Maat, Nils Mosis

The existence of a polynomial pivot rule for the simplex method for linear programming, policy iteration for Markov decision processes, and strategy improvement for parity games each are prominent open problems in their respective fields. While numerous natural candidates for efficient rules have been eliminated, all existing lower bound constructions are ta

Nikodem Tomczak

We describe the Lockchain Protocol, a lightweight Bitcoin meta-protocol that enables highly efficient transaction discovery at zero marginal block space cost, and data verification without introducing any new on-chain storage mechanism. The protocol repurposes the mandatory 4-byte nLockTime field of every Bitcoin transaction as a compact metadata header. By

Nick von Selzam, Florian Marquardt

Bell nonlocality is an intriguing property of quantum mechanics with far reaching consequences for information processing, philosophy and our fundamental understanding of nature. However, nonlocality is a statement about static correlations only. It does not take into account dynamics, i.e. time evolution of those correlations. Consider a dynamic situation w

Jay Jorgenson, Lejla Smajlovic, Polyxeni Spilioti

Let $X$ be an orbisurface, meaning a compact hyperbolic Riemann surface possibly with a finite number of elliptic points, and let $X_1$ denote its unit tangent bundle. We consider the twisted Selberg zeta function $Z(s;\rho)$ associated to a representation $\rho: \pi_1(X_1) \to \text{GL}(V_\rho)$. We prove a relation between the twisted Selberg zeta function

Gilles Felber

We prove a non-trivial bound for $\operatorname{Sp}(2n)$ Kloosterman sums of moduli not equal to a prime multiple of the identity. These sums are attached to Siegel modular forms on the group $\operatorname{Sp}(2n)$ and appear in the corresponding Petersson formula. We give an application to equidistribution of coprime symmetric pairs.

Guoying Zhao, WeiKang Zheng, Rong-Feng Shen, Qingcang Shui

Stellar flares are an intense stellar activity that can significantly impact the atmospheric composition of the surrounding planets and even the possible existence of life. During such events, the radiative energy of the star is primarily concentrated in the optical and X-ray bands, with the X-ray flux potentially increasing by tens or even hundreds of times

Mark Helman, Ronaldo A. Garcia, Dan Reznik

We show that the focus of the Kiepert in-parabola remains stationary over a family of circle-inscribed Poncelet triangles which contain an equilateral triangle.

Emiel Slootman, Vijay Gopal Chilkuri, Aurelien Delval, Max Hoffer

Quantum Monte Carlo (QMC) methods deliver highly accurate electronic structure calculations but are computationally intensive. The quantum Monte Carlo kernel library (QMCkl) provides a modular, portable collection of high-performance kernels implementing the core building blocks of QMC calculations. It offers a C-compatible API, supports the TREXIO standard

Hao Liang, Xiaochen Ma, Zhou Liu, Zhen Hao Wong

The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines. However, current practices remain dominated by ad-hoc scripts and loosely specified workflows, which lack principled abstractions, hinder reproducibility, and offer limited support

Mauve Science Collaboration, Marcel Agueros, Don Dixon, Chuanfei Dong

Mauve is a low-cost small satellite developed and operated by Blue Skies Space Ltd. The payload features a 13 cm telescope connected with a fibre that feeds into a UV-Vis spectrometer. The detector covers the 200-700 nm range in a single shot, obtaining low resolution spectra at R~20-65. Mauve has launched on 28th November 2025, reaching a 510 km Low-Earth S

Ritu Nehra, Poetri Sonya Tarabunga, Martina Frau, Mario Collura

Topological matter provides natural platforms for robust, non-local information storage, central to quantum error correction. Yet, while the relation between entanglement and topology is well established, little is known about the role of nonstabilizerness (or magic), a pivotal concept in fault-tolerant quantum computation, in topological phases. We introduc

Ilsun Chang

Cardinality estimation is a cornerstone of cost-based optimizers (CBOs), yet real-world workloads often violate the assumptions behind static statistics, degrading decision stability and increasing plan flip rates. We empirically characterize failures caused by stale statistics, skew, join correlations, hidden distributions in bind variables, and sampling bi

Charles Parton-Barr, Stuart R. Berrow, Calum J. Gibb, Jordan Hobbs

Fluid ferroelectrics, a recently discovered class of liquid crystals that exhibit switchable, long-range polar order, offer opportunities in ultrafast electro-optic technologies, responsive soft matter, and next-generation energy materials. Yet their discovery has relied almost entirely on intuition and chance, limiting progress in the field. Here we develop

Ole Beisswenger, Jan-Niklas Dihlmann, Hendrik P. A. Lensch

Neural rendering for interactive applications requires translating geometric and material properties (G-buffer) to photorealistic images with realistic lighting on a frame-by-frame basis. While recent diffusion-based approaches show promise for G-buffer-conditioned image synthesis, they face critical limitations: single-image models like RGBX generate frames

Benjamin J. Dringoli, Stefano Mocatti, Giovanni Marini, Zhongzhen Luo

Time-resolved multi-terahertz (THz) spectroscopy is used to observe pump fluence-dependent dynamics in the optical conductivity of photoexcited tin selenide (SnSe) over an ultrabroadband spectral range of 0.5 - 11 THz at fluences from 0.1 - 7.5 mJ/cm$^2$. A free carrier Drude spectrum is observed at pump fluences below 3 mJ/cm$^2$, with optical phonons well

Fabius Krämer, Tim Laux

We introduce a simple and efficient numerical method to compute mean curvature flow with obstacles. The method augments the Merrimam-Bence-Osher scheme with a pointwise update that enforces the constraint and therefore retains the computational complexity of the original scheme. Remarkably, this naive scheme inherits both crucial structural properties of obs

Viacheslav A. Emelyanov

Non-relativistic quantum particles in the Earth's gravitational field are successfully described by the Schr\"{o}dinger equation with Newton's gravitational potential. Particularly, quantum mechanics is in agreement with such experiments as free fall and quantum interference induced by gravity. However, quantum mechanics is a low-energy approximation to quan

William T. Emond, Christian Käding, Peter Millington

It is known that quantum field theories in curved spacetime suffer from a number of pathologies, including the inability to relate states on different spatial slices by proper unitary time-evolution operators. In this article, we illustrate this issue by describing the canonical quantisation of a free scalar field in de Sitter space and explicitly demonstrat

Bin Han, Yao Zhu, Rafael F. Schaefer, Giuseppe Caire

This paper investigates two distinct types of block errors - undetected errors (confusions) and erasures - in additive white Gaussian noise (AWGN) channels with error-bounded block decoders operating in the finite blocklength (FBL) regime. While block error rate (BLER) is a common metric, it does not distinguish between confusions and erasures, which can hav

Raja Sridharan, Sumit Kumar Upadhyay

In this article, we prove the algebraic counterpart of the topological results $H^1(S^1, \mathbb{Z}) \cong \mathbb{Z}$ and $H^1(S^2, \mathbb{Z}) \cong \{0\}$. We also see that a non-trivial element of the algebraic cohomotopy groups of certain rings associated with some known topological spaces provides examples of non-free stably free module of rank two ove

Philip Hendrik Matthias, Abdullah Makkeh, Michael Wibral, Aaron J. Gutknecht

Partial Information Decomposition (PID) seeks to disentangle how information about a target variable is distributed across multiple sources, separating redundant, unique, and synergistic contributions. Despite extensive theoretical development and applications across diverse fields, the search for a unique, universally accepted solution remains elusive, with

Shikshya Shiwakoti, Samuel Goldsmith, Ujjwal Pandit

In today's information-driven world, access to scientific publications has become increasingly easy. At the same time, filtering through the massive volume of available research has become more challenging than ever. Graph Neural Networks (GNNs) and graph attention mechanisms have shown strong effectiveness in searching large-scale information databases, par

Matthew Thompson

Large Language Models deployed as code generation agents exhibit stochastic behavior incompatible with the deterministic guarantees required by software engineering. We formalize the Dual-State Action Pair (DSAP), an execution primitive that couples stochastic generation with deterministic post-condition verification. Guard functions act as sensing actions t

Moritz Pascal Reiter, Kriti Mahajan, Meetika Narang, Carsten Zuelch

Molecules have proven to be sensitive tools for studying physics beyond the standard model, with heavy and deformed nuclei offering decisive sensitivity to parity- and time-reversal-violating effects. However, almost all elements beyond lead, occupying the 6p~to~5f atomic orbitals, lack stable isotopes, hence molecules containing them are referred to as radi

Sangeeth B, Serena Nicolazzo, Deepa K., Vinod P

The rapid proliferation of deep neural networks (DNNs) across several domains has led to increasing concerns regarding intellectual property (IP) protection and model misuse. Trained DNNs represent valuable assets, often developed through significant investments. However, the ease with which models can be copied, redistributed, or repurposed highlights the u

J. R. Silva, C. Antunis B. S. Santos

In this work, we investigate how different reservoir memory profiles influence the dynamical evolution of a single waveguide coupled to an external environment. We compare three representative memory kernels: Lorentzian, Gaussian and Uniform, highlighting their distinct spatial correlations and their impact on system behavior. We compute the transmission amp

Sri Yash Tadimalla, Justin Cary, Gordon Hull, Jordan Register

The rapid assimilation of Artificial Intelligence technologies into various facets of society has created a significant educational imperative that current frameworks are failing to effectively address. We are witnessing the rise of a dangerous literacy gap, where a focus on the functional, operational skills of using AI tools is eclipsing the development of

Wanbing Zhao, H. W. Shawn Liew, Wen Wei Ho, Chunxiao Liu

Soon after the dawn of quantum error correction, DiVincenzo and Peres observed that stabilizer codewords could give rise to simple proofs of quantumness via contextuality. This discovery can be recast in the language of nonlocal games: every $n$-qubit stabilizer state defines a specific "stabilizer-testing" $n$-player nonlocal game, which quantum players can