December 2025 arXiv papers — page 43

Mariana Badano

Herbrand's Theorem is a fundamental result in mathematical logic which provides a reduction of first-order formulas satisfied by a universal class to formulas free of existential quantifiers. In this work, a simpler and self-contained formulation of Herbrand's Theorem is presented, along with a model-theoretic proof of its general version.

He Zhu, Zheng Liu, Xingyang Li, Anbang Wu

3D Gaussian splatting (3DGS) has drawn significant attention in the architectural community recently. However, current architectural designs often overlook the 3DGS scalability, making them fragile for extremely large-scale 3DGS. Meanwhile, the VR bandwidth requirement makes it impossible to deliver high-fidelity and smooth VR content from the cloud. We pres

Alexander Bastien, Omid Khormali

We extend the study of link-irregular graphs to directed graphs (digraphs), where a digraph is link-irregular if no two vertices have isomorphic directed links. We establish that link-irregular digraphs exist on $n$ vertices if and only if $n \geq 5$, and prove that their underlying graphs must contain 3-cycles. We conjecture that link-irregular tournaments

Theodoros Ilias, Fangjun Hu, Marti Vives, Hakan E. Türeci

We introduce an end-to-end optimization strategy for quantum machine learning that directly targets performance under finite measurement resources, where learning objectives are defined directly at the level of task performance. The method is applied on a Bayesian quantum metrology task since it provides a natural testbed with known fundamental limits and sc

Chen Hu, Haikuo Du, Heng Wang, Lin Lin

As LLMs shift toward autonomous agents, Deep Research has emerged as a pivotal metric. However, existing academic benchmarks like BrowseComp often fail to meet real-world demands for open-ended research, which requires robust skills in intent recognition, long-horizon decision-making, and cross-source verification. To address this, we introduce Step-DeepRese

Callum Deakin, Zichuan Zhou, Ronit Sohanpal, Zhixin Liu

We demonstrate a dual optical frequency comb concept that down-converts arbitrary narrowband D-band (110-170 GHz) signals to baseband without any filter or optical/RF frequency tuning, using low frequency RF components.

Aktaş, Arzu, Yılmaz, İhsan

Rapid advancements in quantum computing and machine learning threaten the long-term security of classical blockchain systems, whose protection mechanisms largely rely on computational difficulties. In this study, we propose a quantum blockchain protocol whose protection mechanism is directly derived from quantum mechanical principles. The protocol combines h

Sébastien Breteaux, Jérémy Faupin, Viviana Grasselli

We establish a maximal velocity bound for a pseudo-relativistic quantum particle in an external time-dependent potential. Our estimate shows that the probability for the particle, starting in a convex set $X\subset\mathbb{R}^d$ at $t=0$, to reach a convex set $Y\subset\mathbb{R}^d$ at a time $t>0$, is bounded by $e^{-2\delta}$ where $\delta$ is the distance

James E. Gallagher, Edward J. Oughton, Jana Kosecka

Landmines remain a persistent humanitarian threat, with 110 million actively deployed mines across 60 countries, claiming 26,000 casualties annually. This research evaluates adaptive Red-Green-Blue (RGB) and Long-Wave Infrared (LWIR) fusion for Unmanned Aerial Systems (UAS)-based detection of surface-laid landmines, leveraging the thermal contrast between th

Ştefan Ciobâcă, K. Rustan M. Leino, Ştefan-Alexandru Mercaş, Roxana-Mihaela Timon

We propose to extend the Dafny system with an interactive proof mode. We present a motivating example, how the IPM works, including the main design choices we make, and a prototype implementation.

Tanisha Fonseca, Gengrui Zhang

Modern distributed systems face a critical challenge: existing consensus protocols optimize for either node heterogeneity or workload independence, but not both. For example, Cabinet leverages weighted quorums to handle node heterogeneity but serializes all operations through a global leader, limiting parallelism. EPaxos enables parallel execution for indepe

Anamika Pandey, T. Raja Sekhar

We investigate supersonic transonic phenomena in the two-dimensional compressible Euler equations governed by a polytropic van der Waals equation of state. In contrast to the ideal gas setting, the non-ideal pressure law introduces stronger nonlinear effects and modifies the degeneracy structure near sonic states, which significantly complicates the analytic

Steven Creech, Henry Twiss, Zhining Wei, Peter Zenz

We let $f$ be a half-integral weight modular form of weight $\kappa>4$ on $\Gamma_0(4)$ that is an eigenfunction of all Hecke operators $T_n$, so that $T_nf = \Lambda_f(n)n^{\frac{\kappa-1}{2}}f$. Let $\|f\|$ denote the Petersson norm of $f$. We study a weighted second moment of the central value of the $L$-function associated to $f$ over an orthogonal basis

Revanth Gangi Reddy, Ye Liu, Wenting Zhao, JaeHyeok Doo

Maintaining large-scale, multilingual codebases hinges on accurately localizing issues, which requires mapping natural-language error descriptions to the relevant functions that need to be modified. However, existing ranking approaches are often Python-centric and perform a single-pass search over the codebase. This work introduces SweRank+, a framework that

Kaifeng Wu, Junyan Wu, Qiang Liu, Jiarui Zhang

Long-document topic segmentation plays an important role in information retrieval and document understanding, yet existing methods still show clear shortcomings in ultra-long text settings. Traditional discriminative models are constrained by fixed windows and cannot model document-level semantics; generative large language models can output paragraph bounda

Davide Staub, Finn Rabe, Akhil Misra, Yves Pauli

To maintain coherence in language, the brain must satisfy key competing temporal demands: the gradual accumulation of meaning across extended context (drift) and the rapid reconfiguration of representations at event boundaries (shift). How these processes are implemented in the human brain during naturalistic listening remains unclear. Here, we tested whethe

Donggang Cao, Sankha Shuvra Das, Gilad Yossifon

Controlled assembly of active-passive colloidal mixtures offers a route to reconfigurable microscale machines, but their self-assembly pathways remain poorly understood. We study the directed assembly of metallo-dielectric Janus particles (JPs) and passive polystyrene (PS) beads using optoelectrically reconfigurable AC-field patterning, which allows precise

Yiming Zhao, Yuanpeng Gao, Yuxuan Luo, Jiwei Duan

AI-assisted graphic design has emerged as a powerful tool for automating the creation and editing of design elements such as posters, banners, and advertisements. While diffusion-based text-to-image models have demonstrated strong capabilities in visual content generation, their text rendering performance, particularly for small-scale typography and non-Lati

Zepeng Wang, Juan Peypouquet

We propose an adaptive accelerated gradient method for solving smooth convex optimization problems. The method incorporates a scheme to determine the step size adaptively, by means of a local estimation of the smoothness constant, which is assumed unknown, without resorting to line search procedures. The sequence generated by this method converges weakly to

Ilias Aarab

In Aarab (2020), I examine U.S. stock return predictability across economic regimes and document evidence of time-varying expected returns across market states in the long run. The analysis introduces a state-switching specification in which the market state is proxied by the slope of the yield curve, and proposes an Aligned Economic Index built from the pop

Andrea Ponticelli, Francesco Giuseppe Capone, Vittorio Cataudella, Giulio De Filippis

We investigate the impact of quantum and thermal phase fluctuations on the suppression of superconducting order in two-dimensional systems. Within the two-dimensional quantum XY model in the phase representation, where on-site interaction terms govern quantum phase fluctuations, we perform extensive path-integral quantum Monte Carlo simulations. The resultin

Maulana Bisyir Azhari, Donghun Han, Je In You, Sungjun Park

The Abu Dhabi Autonomous Racing League(A2RL) x Drone Champions League competition(DCL) requires teams to perform high-speed autonomous drone racing using only a single camera and a low-quality inertial measurement unit -- a minimal sensor set that mirrors expert human drone racing pilots. This sensor limitation makes the system susceptible to drift from Visu

Giacomo Ferrante

The Standard Model of particle physics and the $\Lambda$CDM model of cosmology provide an incomplete description of our Universe. Both models face challenges, including explaining the nature of dark matter, the origin of the Universe's initial conditions, and the fine-tuning of the Higgs boson mass. This thesis investigates the cosmological implications of s

Daniel Baldassare, Abby Lute, Hikari Murayama, Cora Kingdon

Global warming is often framed in broad planetary numbers such as the 1.5C and 2C warming thresholds, creating the false impression that individual corporations efforts to reduce emissions are meaningless in the absence of collective action. This perspective causes companies to reduce ambition towards voluntarily cutting emissions, as they believe their poll

Wille Liu, Kari Vilonen, Ting Xue

In this paper we give a complete classification of cyclically graded semisimple Lie algebras that afford cuspidal character sheaves and determine the support of the cuspidal character sheaves. This constitutes a major step towards the explicit classification of cuspidal character sheaves for graded Lie algebras.

Yong-Kang Huang, Yao Ji, Bo-Xuan Shi, Yu-Ming Wang

We determine for the first time the two-loop renormalization-group (RG) equation for the nucleon light-cone distribution amplitude, which constitutes the last missing ingredient for the complete next-to-leading-logarithmic corrections to the nucleon form factors in the hard-collinear factorization framework. Applying the conformal expansion for this fundamen

Laura Fields, Sudeshna Ganguly

Over the past six decades, accelerator-based neutrino beams have revolutionized particle physics. Neutrinos created with accelerators have been used to discover the muon neutrino and tau neutrinos was discovered and to confirm the existence of neutrino oscillations. More recently, long-baseline experiments have offered the first experimental hint of CP viola

Linfeng Zhang, Siheng Chen, Yuzhu Cai, Jingyi Chai

AI agents are emerging as a practical way to run multi-step scientific workflows that interleave reasoning with tool use and verification, pointing to a shift from isolated AI-assisted steps toward \emph{agentic science at scale}. This shift is increasingly feasible, as scientific tools and models can be invoked through stable interfaces and verified with re

Haoyue Zhang, Dong Ye, Peng Xu, Yunhai Geng

Accurately calibrating the center-of-mass (CoM) offset between the spacecraft (SC) and the inertial sensor test mass (TM) is crucial for space-based gravitational-wave (GW) antennas, such as LISA and Taiji. Current calibration methods require additional spacecraft maneuvers that disrupt science data continuity and inter-satellite links, compromising the cohe

Samuel Nyckees, Pratyay Ghosh, Frédéric Mila

We study the quantum phase diagram of the spin-$1/2$ nearest-neighbor Heisenberg model on the maple-leaf lattice using infinite projected entangled pair states (iPEPS) combined with a corner transfer matrix renormalization group scheme adapted to $C_3$-symmetric lattices. Focusing on the fully antiferromagnetic $J$-$J_d$ model with $J_h = J_t := J$, we map o

Giovanni Landi, Chiara Pagani

We study the push-forward of Hopf--Galois extensions as the algebraic counterpart of the pullback of principal bundles. We apply the theory of twisted tensor product algebras to endow covariant extensions of modules along a map $\mathsf{F}$ with an algebra structure, under compatibility conditions between $\mathsf{F}$ and the twisting map. The push-forward o

Kristine M. L. Krighaar, Silas B. Schack, Nicolai L. Amin, Gregory S. Tucker

Using the Monte Carlo ray tracing package McStas, we illustrate the possibilities of creating virtual experiments of the neutron spectrometer BIFROST at the European Spallation Source, ESS. With this model, we are able to benchmark BIFROST with respect to expected intensity, $Q$- and energy-resolution. The simulations reproduce the expected resolution behavi

Günter Leugering, Charlotte Rodriguez, Yue Wang

We consider networks of elastic strings with end masses, where the coupling is modeled via elastic springs. The model is representative of a network of nonlinear strings, where the strings are coupled to elastic bodies. The coupled system converges to the classical string network model with Kirchhoff and continuity transmission conditions as the spring stiff

Peter Vang Uttenthal

This paper gives a classification of even representations onto $\operatorname{SL}(2,\mathbb{Z}_3)$ of prime conductor. In addition, an explicit algorithm based on global class field theory is exhibited, computing an exhaustive series of such even representations.

Ilias Aarab

A growing empirical literature suggests that equity-premium predictability is state dependent, with much of the forecasting power concentrated around recessionary periods (Henkel et al., 2011; Dangl and Halling, 2012; Devpura et al., 2018). I study U.S. stock return predictability across economic regimes and document strong evidence of time-varying expected

E. Stazzu, G. A. P. Sacchetto, I. Carusotto

We build a minimal theoretical model to describe the opening of a gap in the dispersion of the collective excitations of a driven-dissipative condensate when the condensate phase is fixed by an additional coherent phase-locking drive. We map out the phase diagram as a function of the amplitude and frequency of the coherent drive, identifying distinct regions

Shuting Wang, Qiaolin Xia, Vich Wang, Herberttli

Recent advances in Large Language Models (LLMs) and Large Reasoning Models (LRMs) have enabled agentic search systems that interleave multi-step reasoning with external tool use. However, existing frameworks largely rely on unstructured natural-language reasoning and accumulate raw intermediate traces in the context, which often leads to unstable reasoning t

Marco Aruta, Francesco Improta, Vadim Malvone, Aniello Murano

In formal strategic reasoning for Multi-Agent Systems (MAS), agents are typically assumed to (i) employ arbitrarily complex strategies, (ii) execute each move at zero cost, and (iii) operate over fully crisp game structures. These idealized assumptions stand in stark contrast with human decision making in real world environments. The natural strategies frame

Vance Blankers, Maria Gillespie, Jake Levinson

We use sign-reversing involutions to solve two computational problems that arise naturally in the geometry of moduli spaces of curves. In particular, we give an explicit combinatorial formula for arbitrary $\psi$ class intersection products on the genus zero multicolored spaces $\overline{M}_{0,[r_1,\ldots,r_m]}$ using a novel sign reversing involution on de

K. Nobleson, Churchil Dwivedi, Shantanu Desai, Bhal Chandra Joshi

We present the results of customised single-pulsar noise analysis of 27 millisecond pulsars from the second data release of the Indian Pulsar Timing Array (InPTA-DR2). We model various stochastic noise sources present in the dataset using stationary Gaussian processes and estimate the noise budget of the InPTA-DR2 using Bayesian inference, involving model se

Dengge Jin, Samuele Ferracin, Vincent Tournat, Jordan R. Raney

Surfaces and structures capable of multiple stable configurations have attracted growing interest for on-demand shape morphing. In this work, we consider an elastic compliant plate coupled to a two-dimensional foundation comprising an array of bistable elements, a system that can form and retain complex continuous morphologies without sustained actuation via

Chung-Chin Shih, Ti-Rong Wu, Ting Han Wei, Yu-Shan Hsu

This paper analyzes the behavior of solving Life-and-Death (L&D) problems in the game of Go using current state-of-the-art computer Go solvers with two techniques: the Relevance-Zone Based Search (RZS) and the relevance-zone pattern table. We examined the solutions derived by relevance-zone based solvers on seven L&D problems from the renowned book "Life and

Filip Bočinec, Stanislav Nagy, Hyemin Yeon

We introduce a novel projection depth for data lying in a general Hilbert space, called the regularized projection depth, with a focus on functional data. By regularizing projection directions, the proposed depth does not suffer from the degeneracy issue that may arise when the classical projection depth is naively defined on an infinite-dimensional space. C

Anh Dao, Manh Tran, Yufei Zhang, Xiaoming Liu

Human motion understanding has advanced rapidly through vision-based progress in recognition, tracking, and captioning. However, most existing methods overlook physical cues such as joint actuation forces that are fundamental in biomechanics. This gap motivates our study: if and when do physically inferred forces enhance motion understanding? By incorporatin

Viviana Gubitosi, Pablo Rosero

This paper addresses the combinatorial structure of $m$-colored mutation classes. We provide an explicit and purely combinatorial description of the $m$-colored quivers that arise within the $m$-colored mutation class of a quiver of type $\mathbb{\widetilde{A}}$. Our results generalize and extend existing work, specifically recovering a description by Bastia

A. Deur, M. M. Dalton, S. Širca

The Gerasimov-Drell-Hearn sum rule is a generic relation that has been used to make significant contributions to research in hadronic physics. It connects the spin-dependent cross-section for photoproduction off a particle to the squared ratio of the particle's anomalous magnetic moment and its mass, $(\kappa/M)^2$. Thus, for a nucleon embedded in a nucleus,

Francesco Mauro, Francesca De Falco, Lorenzo Papa, Andrea Ceschini

The rapid adoption of diffusion models (DMs) in the Earth Observation (EO) domain has unlocked new generative capabilities aimed at producing new samples, whose statistical properties closely match real imagery, for tasks such as synthesizing missing data, augmenting scarce labeled datasets, and improving image reconstruction. This is particularly relevant i

Marco Roschkowski, Karim Cherifi, Hannes Gernandt

The use of machine learning models in system identification has increased due to their ability to approximate complex nonlinear dynamics with high accuracy. However, often it is not clear how the performance of trained models scales with given resources such as data, compute, and model size. To allow for a better understanding of the scalability of the perfo

Günter Leugering, Yue Wang, Qiong Zhang

This paper investigates the boundary controllability and stabilizability of a Timoshenko beam subject to degeneracy at one end, while control is applied at the opposite boundary. Degeneracy in this context is measured by the real parameters for $\mu_a\in [0,2)$ for $a\in\{K,EI\}$, where $K(x)$ denotes shear stiffness and $EI(x)$ bending stiffness. We differe

Paul Blesse, Janis Dücker, Albrecht Klemm, Julian F. Piribauer

We use Dwork's deformation method to calculate the Hasse-Weil Zeta function of multi-parameter families of Calabi-Yau three and fourfolds. This information is used to identify subslices of codimension one in the complex-structure moduli space, where the Hodge structure splits in particular ways and different type IIB flux vacua emerge. We calculate the corre

Phi-Hung Hoang, Nam-Thuan Trinh, Van-Manh Tran, Thi-Thu-Hong Phan

Deploying deep learning models on resource-constrained edge devices remains a major challenge in smart agriculture due to the trade-off between computational efficiency and recognition accuracy. To address this challenge, this study proposes a hybrid knowledge distillation framework for developing a lightweight yet high-performance convolutional neural netwo

Alexandros Kanargias, Elias Kiritsis, Sameer Murthy, Olga Papadoulaki

The strongly-coupled 3-dimensional theory, holographically dual to black branes at fixed chemical potential $\muext$ and temperature $T \ll \mu$ is considered in AdS$_4$ Einstein-Maxwell theory. The retarded Green's functions at frequency $\omega$ is calculated using holography in the regime $\omega, T \ll \muext$ but otherwise arbitrary. When the transverse

Yakob Kahane

In 2005, Watanabe and Yoshida formulated a conjecture for a lower bound of the Hilbert-Kunz multiplicity of local rings that was recently settled by Meng using analytic methods. More recently, Pak-Shapiro-Smirnov-Yoshida used Ehrhart theory to compute explicitly the multiplicity and reduced the conjecture to showing an inequality of the values of the Ehrhart

Christophe Charlier, Edwin Langmann, Jonatan Lenells

We propose an analytical method for the construction of Hartree-Fock phase diagrams for the (fermion) Hubbard model and various generalizations thereof. Such phase diagrams are traditionally constructed numerically, but we argue that, by using asymptotic techniques, it is possible to obtain analytic formulas approximating the curves separating the different

Faqiang Yuan, Shengzhi Li, Zhen Li, Yongge Ma

The effective dynamics of the Janis-Newman-Winicour spacetime inspired by loop quantum gravity is studied. Two different schemes are considered to regularize the Hamiltonian constraint for the quantum dynamics. In the $\mu_0$ scheme in which the quantum parameters are treated as constants, the equations of motion generated by the effective Hamiltonian are so

Fábio J. Bertoloto, Elisa R. Santos

In this paper, we introduce the polynomial numerical index of a pair of Banach spaces with respect to a norm-one polynomial. This index generalizes the concept of polynomial numerical index defined by Y. S. Choi et al. in 2006 and extends to polynomials the notion of numerical index with respect to an operator, introduced by M. A. Ardalani in 2014. We invest

Jibin Joseph

Many businesses depend on their mobile apps and websites, so user frustration while trying to complete a task on these channels can cause lost sales and complaints. In this research, I use clickstream data from a real e-commerce site to predict whether a session is frustrated or not. Frustration is defined using certain rules based on rage bursts, back and f

Paul J. Christiansen, Daniel Ohl de Mello, Cedric Brügmann, Steffen Hien

In this work, we propose a hybrid quantum-inspired heuristic for automatically tuning the Lorenz-96 model -- a simple proxy to describe atmospheric dynamics, yet exhibiting chaotic behavior. Building on the history matching framework by Lguensat et al. (2023), we fully automate the tuning process with a new convergence criterion and propose replacing classic

Muhammad Usman, Azka Rehman, Muhammad Mutti Ur Rehman, Abd Ur Rehman

Accurate segmentation of ischemic stroke lesions from diffusion magnetic resonance imaging (MRI) is essential for clinical decision-making and outcome assessment. Diffusion-Weighted Imaging (DWI) and Apparent Diffusion Coefficient (ADC) scans provide complementary information on acute and sub-acute ischemic changes; however, automated lesion delineation rema

César Benito, Alfredo Ricci Vasquez, Jonathan Home, Karan K. Mehta

We present a footprint study for the scaling of modular quantum error correction (QEC) protocols designed for triangular color codes, including a lattice-surgery-based logical teleportation gadget, and compare the performance of various possible architectures based on trapped ions. The differences in these architectures arise from the technology that enables

José Cantarero, Higinio Serrano Garcia

In this article we give an elementary introduction to the representation theory of finite magnetic groups from a purely mathematical point of view. -- En este art\'iculo damos una introducci\'on elemental a la teor\'ia de representaciones de grupos magn\'eticos finitos desde un punto de vista puramente matem\'atico.

Felipe Atenas

We propose the shadow Davis-Yin three-operator splitting method to solve nonconvex optimisation problems. Its convergence analysis is based on a merit function resembling the Moreau envelope. We explore variational analysis properties behind the merit function and the iteration operators associated with the shadow method. By capitalising on these results, we

Ji Song, Xing Wang, Jianguo Wu, Xiaowei Yue

In the realm of diverse high-dimensional data, images play a significant role across various processes of manufacturing systems where efficient image anomaly detection has emerged as a core technology of utmost importance. However, when applied to textured defect images, conventional anomaly detection methods have limitations including non-negligible misiden

Abdullah Al Shafi, Abdul Muntakim, Pintu Chandra Shill, Rowzatul Zannat

Skin cancer can be identified by dermoscopic examination and ocular inspection, but early detection significantly increases survival chances. Artificial intelligence (AI), using annotated skin images and Convolutional Neural Networks (CNNs), improves diagnostic accuracy. This paper presents an early skin cancer classification method using a soft voting ensem

Marcel Guardia, José Lamas, Tere M-Seara

Consider the Restricted Planar Circular Three Body Problem (RPC3BP), which models the motion of a massless particle (Asteroid) under the gravitational influence of two massive bodies (the primaries) moving on circular orbits. By considering the ratio between the masses of the primaries to be arbitrarily small, we construct orbits with close encounters with t

Bruna Sahdo, Natália Salomé Móller

The aim of this article is to provide an introduction to the use of quantum information methods for investigating the interface between quantum theory and gravity. To this end, we discuss the basic principles of two current research streams that use this approach. The first one explores a phenomenon known as gravitationally induced entanglement, which aims t

A. E. Cárcamo Hernández, Andrés Enríquez, Sergey Kovalenko, Eduardo Peinado

We propose the first scotogenic neutrino mass model with gauged lepton number $U(1)_L$, which is spontaneously broken by three units $\Delta L=3$ down to a residual discrete gauge symmetry $\mathbb{Z}_6$. The latter guarantees that neutrinos acquire tiny Dirac masses via a one-loop scotogenic mechanism, simultaneously stabilizing the lightest electrically ne

Igor B. Furtat

A fast convergence in a fixed-time of solutions of nonlinear dynamical systems, for which special requirements are satisfied on the derivative of a quadratic function calculated along the solutions of the system, is proposed. The conditions for the system solutions to converge to zero and to a given region within a fixed-time are obtained. To achieve fast co

Thierry Chanelière

I present a general laser modulation control algorithm. I implement the LIDAR Frequency Modulated Continuous Wave (FMCW) scheme as a special case of study. My proposal applies to any arbitrary modulation pattern and is based on an iterative algorithm that infers the laser transfer function in order to perform on-the-fly deconvolution. I present an experiment

Hao Gao, Yue-Wen Fang, Ion Errea

First-principles based crystal structure prediction (CSP) methods have revealed an essential tool for the discovery of new materials. However, in solids close to displacive phase transitions, which are common in ferroelectrics, thermoelectrics, charge-density wave systems, or superconducting hydrides, the ionic contribution to the free energy and lattice anh

Adam Elaoumari

The purpose of this project is to assess how well defenders can detect DNS-over-HTTPS (DoH) file exfiltration, and which evasion strategies can be used by attackers. While providing a reproducible toolkit to generate, intercept and analyze DoH exfiltration, and comparing Machine Learning vs threshold-based detection under adversarial scenarios. The originali

Francesco Paolo Maiale, Anastasiia Trofimova, Arturo De Marinis

This paper studies the approximation capacity of neural networks with an arbitrary activation function and with norm constraint on the weights. Upper and lower bounds on the approximation error of these networks are computed for smooth function classes. The upper bound is proven by first approximating high-degree monomials and then generalizing it to functio

Mihai Suteu, Ovidiu Serban

Multi-task learning (MTL) aims to leverage shared knowledge across tasks to improve generalization and parameter efficiency, yet balancing resources and mitigating interference remain open challenges. Architectural solutions often introduce elaborate task-specific modules or routing schemes, increasing complexity and overhead. In this work, we show that norm

Edoardo Boretti, Kostiantyn Torokhtii, Enrico Silva, Andrea Alimenti

In both research and industrial settings, it is often necessary to expand the input/output channels of measurement instruments using relay-based multiplexer boards. In research activities in particular, the need for a highly flexible and easily configurable solution frequently leads to the development of customized systems. To address this challenge, we deve

I. B. Furtat, N. V. Kuznetsov

The classical Andronov-Vyshnegradsky problem, which deals with locating regions of stability and oscillations in control systems with a Watt regulator, is solved using a divergence method for studying the stability of dynamic systems. This system is studied both with and without the self-regulation effect. The exact value of the hidden boundary of the global

Pedro Domingos, João Pereira, Vasco Lopes, João Neves

Automated video surveillance with Large Vision-Language Models is limited by their inherent bias towards normality, often failing to detect crimes. While Chain-of-Thought reasoning strategies show significant potential for improving performance in language tasks, the lack of inductive anomaly biases in their reasoning further steers the models towards normal

Emmanuel N. Saridakis

For most of its history, cosmology was a qualitatively constrained discourse on the universe, shaped by limited observational access and the absence of global dynamical laws. This situation has changed decisively in recent decades. Modern cosmology is now driven by an unprecedented flow of high-precision data from a wide range of independent probes, includin

Prasoon Saurabh

The rigorous description of Conical Intersections (CIs) remains the central challenge of non-adiabatic quantum chemistry. While the ``Yarkony Seam'' -- the $(3N-8)$-dimensional manifold of degeneracy -- is well-understood geometrically, its accurate characterization by high-level electronic structure methods is plagued by numerical instabilities. Specificall

Peter Vang Uttenthal

In a letter from Tate to Serre dated March 26, 1974, Tate suggested a classification of weight one modular forms of prime level in terms of their associated odd Artin representations. This paper carries out an analogous classification of Maass wave forms of prime power level in terms of complex even representations. The parameters are identified with techniq

Mario Ayala, D. R. Michiel Renger

We extend the usual hydrodynamic description of the symmetric exclusion process by keeping track of collision events corresponding to jumps into already occupied sites, thereby quantifying the dissipated part of the microscopic activity that is otherwise discarded by the empirical density in the macroscopic limit. In addition to the empirical density and net

José N. Gama, Diogo Cunha, Carla Estévez-Varela, Marina García-Pardo

Hyperbolic metamaterials enable extreme light confinement and control of photonic states, but their realization has been restricted to inorganic architectures. Here, a fully organic route to fabricate artificial hyperbolic metamaterials based on multilayered thin films of J-aggregate carbocyanine dyes alternated with polyelectrolytes is introduced. These str

Sayantan Nag Chowdhury, Hildegard Meyer-Ortmanns

Non-reciprocal couplings are frequently found in systems out-of-equilibrium such as neuronal networks. We consider generalized Kuramoto models with non-reciprocal adaptive couplings. The non-reciprocity refers to the type of couplings according to Hebbian or anti-Hebbian rules and to different time scales on which the couplings evolve. The main effect of thi

Junho Yoon, Jaemo Jung, Hyunju Kim, Dongman Lee

Aligning egocentric video with wearable sensors have shown promise for human action recognition, but face practical limitations in user discomfort, privacy concerns, and scalability. We explore exocentric video with ambient sensors as a non-intrusive, scalable alternative. While prior egocentric-wearable works predominantly adopt Global Alignment by encoding

Lorenzo Schiavon, Mattia Stival, Angela Andreella, Stefano Campostrini

Behavioral risk factors, i.e., smoking, poor nutrition, alcohol misuse, and physical inactivity (SNAP), are leading contributors to chronic diseases and healthcare costs worldwide. Their prevalence is shaped %not only by demographic characteristics %but and also by contextual ones such as socioeconomic and occupational environments. In this study, we leverag

Rajdeep Chatterjee, Sudip Chakrabarty, Trishaani Acharjee, Deepanjali Mishra

Unmanned aerial vehicles (UAVs), commonly known as drones, are increasingly used across diverse domains, including logistics, agriculture, surveillance, and defense. While these systems provide numerous benefits, their misuse raises safety and security concerns, making effective detection mechanisms essential. Acoustic sensing offers a low-cost and non-intru

M. Cristina Câmara, C. Carteiro, C. Diogo

Toeplitz kernels can be defined by Riemann-Hilbert problems, by maximal functions, or by multipliers acting on model spaces. In this paper we study those different characterisations and their relations, highlighting, on the one hand, the crucial role played by symbol factorisation in obtaining multipliers from a model space onto a Toeplitz kernel, in particu

Kanchon Gharami, Sanjiv Kumar Sarkar, Safayat Bin Hakim, Yongxin Liu

Large Language Models (LLMs) like ChatGPT are now widely used in writing and reviewing scientific papers. While this trend accelerates publication growth and reduces human workload, it also introduces serious risks. Papers written or reviewed by LLMs may lack real novelty, contain fabricated or biased results, or mislead downstream research that others depen

Junyi Liu, Stanley Kok

With the rapid growth of unstructured data from social media, reviews, and forums, text mining has become essential in Information Systems (IS) for extracting actionable insights. Summarization can condense fragmented, emotion-rich posts, but existing methods-optimized for structured news-struggle with noisy, informal content. Emotional cues are critical for

Xuan-An Le, Minh-Nam Tran, Son Nguyen

Distilling knowledge from large proprietary models (e.g., GPT-4) to tiny deployable models (less than 1B parameters) faces a critical capacity-budget trap: the 1000x capacity gap between teachers and students prevents effective direct transfer, while API costs prohibit extensive data collection. We introduce BRIDGE (Budget-Aware Reasoning via Intermediate Di

Niccolò Scatena, Pericle Perazzo, Giovanni Nardini

This paper proposes iblock, a comprehensive C++ library for Bitcoin simulation, designed for OMNeT++. iblock offers superior efficiency and scalability with respect to state-of-the-art simulators, which are typically written in high-level languages. Moreover, the possible integration with other OMNeT++ libraries allows highly detailed simulations. We measure

Leonid Fel

We consider the problem of isotropic effective conductivity $\sigma_e(\sigma_1,\ldots,\sigma_n)$ in two-dimensional three- and four-phase symmetric composites with a partial isotropic conductivity $\sigma_j$ of the $j$-th phase. The upper $\Omega(\sigma_1,\ldots,\sigma_n)$ and lower $\omega(\sigma_1,\ldots,\sigma_n)$, $n=3,4$, bounds for effective conductivi

Byung-Kwan Lee, Yu-Chiang Frank Wang, Ryo Hachiuma

Large-scale vision-language models (VLMs) have recently achieved remarkable multimodal understanding, but their massive size makes them impractical for deployment on mobile or edge devices. This raises the need for compact yet capable VLMs that can efficiently learn from powerful large teachers. However, distilling knowledge from a large teacher to a small s

Spencer Hagen§, Dulcce A Valenzuela§, Parag V Chitnis, Shirin Movaghgharnezhad

Ultrasound transducers made from rigid piezoceramics are difficult to adapt for wearable or conformal applications. Piezopolymer-based transducers offer a practical alternative; however, most existing studies focus on piezoelectric materials, while the influence of electrode material and electrode-polymer interface remains underexplored. This study leverages

Boris Y. Rubinstein

Sylvester showed that the partition function can be written as a sum of the polynomial term and quasiperiodic components called the Sylvester waves. Recently an explicit expression of the Sylvester wave as a finite sum over the Bernoulli polynomials of higher order with periodic coefficients was found. This expression can be also written as the weighted sum

Xin-Xiang Ju, Bo-Hao Liu, Ya-Wen Sun, Bo-Yu Xu

We investigate how IR modifications of the bulk geometry reshape long-range multipartite entanglement on the boundary in holography. We modify the IR geometries in two opposite directions: spherical modifications that enhance long-range entanglement and hyperbolic modifications that suppress them. We utilize various multipartite entanglement measures/signals

Zifeng Wang, Zheng Chen, Ziwei Yang, Xuan Wang

Biomedical knowledge graphs (KGs) encode vast, heterogeneous information spanning literature, genes, pathways, drugs, diseases, and clinical trials, but leveraging them collectively for scientific discovery remains difficult. Their structural differences, continual evolution, and limited cross-resource alignment require substantial manual integration, limiti

Narges Khakpour, Nicolas Berthier

We introduce a scalable, modular, and sound approach for automatically constructing formal security specifications for Java bytecode programs in the form of method summaries. A summary provides an abstract representation of a method's security behavior, consisting of the conditions under which the method can be securely invoked, together with specifications

Mohammad Walid Charrwi, Zaid Hussain

As Network-on-Chip (NoC) and Wireless Sensor Network architectures continue to scale, the topology of the underlying network becomes a critical factor in performance. Gaussian Interconnected Networks based on the arithmetic of Gaussian integers, offer attractive properties regarding diameter and symmetry. Despite their attractive theoretical properties, adap

Thomas Iadecola, Rahul Nandkishore

We show how combining a discrete symmetry with topological Hilbert space fragmentation can give rise to exponentially many topologically stable qubits protected by a single discrete symmetry. We illustrate this explicitly with the example of the $\mathsf{CZ}_p$ model, where the encoded qubits are stable to arbitrary symmetry-respecting perturbations for para

Marcus Kühn, Lisa Sauermann, Raphael Steiner, Yuval Wigderson

We prove that there exist graphs which do not contain $K_t$ as an odd minor and whose chromatic number is at least $(\frac 32-o(1))t$. This disproves, in a strong form, the odd Hadwiger conjecture of Gerards and Seymour from 1993.