November 2025 arXiv papers — page 102

Solmaz Golmohammadi, Mina Zarei, Jacopo Grilli

We investigate stochastic predator-prey dynamics and their spatial phase synchronization using the Rosenzweig-MacArthur model coupled across multiple patches. Combining stochastic simulations based on the Gillespie algorithm with analytical methods inspired by the XY model, we uncover fundamental mechanisms through which demographic noise and dispersal shape

Ting Chen, Hanwen Lu, Wenchang Sun

Gabor phase retrieval stands for recovering a square integrable function up to a global phase from absolute values of its Gabor transform. In this paper, we study Gabor phase retrieval from discrete samples. We consider three types of sampling sequences, which include square root lattices, square root sequences on two intersecting lines and on three parallel

Anil Alan, Bart De Schutter

We study feasibility guarantees for safety filters developed using Control Barrier Functions (CBFs) when a safe set is defined using the pointwise minimum of continuously differentiable functions, a construction that is common for the backup CBF (BCBF) method and typically nonsmooth. We replace the minimum by its log-sum-exp (soft-min) smoothing and show tha

Kieran Calvert, Aram Dermenjian, Alex Fink, Ben Smith

Tropicalisation (with trivial coefficients) is a process that turns a polynomial equation into a combinatorial predicate on subsets of the set of variables. We show that for each minuscule representation of a simple reductive group, there is a set of quadratic equations cutting out the orbit of the highest weight vector whose tropicalisation characterises th

Liudmila A. Zhukas, Vivian Ni Zhang, Qiang Miao, Qingfeng Wang

Quantum machine learning (QML) has attracted growing interest with the rapid parallel advances in large-scale classical machine learning and quantum technologies. Similar to classical machine learning, QML models also face challenges arising from the scarcity of labeled data, particularly as their scale and complexity increase. Here, we introduce self-superv

Han-Yao Liu, Shi-Yong Chen, Wei Dai, Ben-Wei Zhang

We present a systematic study of medium-induced modifications in charge-dependent jet substructure using the charge-weighted Energy-Energy Correlators (EEC) in p+p and 0-10\% central Pb+Pb collisions at a center-of-mass energy of 5.02 TeV. Charged hadron jets as well as flavor separated quark and gluon-initiated jets with momentum 40-60 GeV and R=0.4 are ana

Jae Joong Lee

Recent vision-language models (VLMs) such as CLIP, OpenCLIP, EVA02-CLIP and SigLIP achieve strong zero-shot performance, but it is unclear how reliably they respond to controlled linguistic perturbations. We introduce Language-Guided Invariance Probing (LGIP), a benchmark that measures (i) invariance to meaning-preserving paraphrases and (ii) sensitivity to

V. Apinyan, M. Sahakyan

The subject of the present study is the double-layer square-lattice system with the intralayer phonon modulations. We investigate the superconducting and excitonic pairings, as well as their coexistence, as functions of various physical parameters in the system. These parameters include temperature, intralayer and interlayer Coulomb interactions, the electro

Kento Takemura, Mikio Eto, Tomohiro Yokoyama

Multi-terminal Josephson junction with three or more superconductors is an attractive quantum system to emerge and tune exotic electronic states. In four terminal Josephson junctions, the Weyl physics, namely topologically protected zero energy state, emerges without assuming any exotic materials. In this study, we consider the four-terminal Josephson juncti

Jesus Fernandez-Bes, Rocío Arroyo-Valles, Jesús Cid-Sueiro

The problem of cooperative data censoring in battery-powered multihop sensor networks is analyzed in this paper. We are interested in scenarios where nodes generate messages (which are related to the sensor measurements) that can be graded with some importance value. Less important messages can be censored in order to save energy for later communications. Th

Calum Spicer, Roberto Svaldi, Sebastian Velazquez

We present a definition of stable family of foliations and show that the corresponding moduli functor for foliated surfaces is representable by a Deligne-Mumford stack.

Gautam Nagarajan, Omir Kumar, Sudarsun Santhiappan

All citizens of a country are affected by the laws and policies introduced by their government. These laws and policies serve essential functions for citizens. Such as granting them certain rights or imposing specific obligations. However, these documents are often lengthy, complex, and difficult to navigate, making it challenging for citizens to locate and

Lipeng Wang, Hongxing Fan, Haohua Chen, Zehuan Huang

Generating high-quality human interactions holds significant value for applications like virtual reality and robotics. However, existing methods often fail to preserve unique individual characteristics or fully adhere to textual descriptions. To address these challenges, we introduce InterMoE, a novel framework built on a Dynamic Temporal-Selective Mixture o

Wei-Wei Yang, Shao-Hang Shi, Zongsheng Zhou, Zi-Xiang Li

Two-dimensional superconductors undergo a Berezinskii-Kosterlitz-Thouless transition driven by vortex-antivortex unbinding, yet experimental signatures beyond transport remain limited. Here, we show that the spin-lattice relaxation rate provides a direct probe of this transition. In a 2-dimensional $s$-wave superconductor, $1/T_1T$ develops a Hebel-Slichter-

Alastair N. Fletcher, Alexandra Hill

We show that every cubic Blaschke product has a unique hyperbolic inflection point in the unit disk and, moreover, this point lies at the hyperbolic midpoint of the two critical points. Using this structure result for cubic Blaschke products, we give an explicit expression in terms of the parameters which determines when cubic Blaschke products are elliptic,

Lorena Acuña-Aguirre, Laura Kreidberg, Paul Mollière, Nora Bachmann

WASP-80 b is an unusually low-density exoplanet in tension with the metal-rich composition expected for a planet of its mass. We aim to derive precise constraints on WASP-80 b's bulk metal mass fraction, atmospheric composition, and thermal structure. We conducted a suite of retrievals using three approaches: traditional interior-only, atmosphere-only, and j

Shenrui Lin, Shuowen Zhang

Pixel antenna is a promising technology to enhance the wireless communication data rate by adaptively reconfiguring each antenna's radiation pattern via a so-called antenna coding technique which controls the states of switches connected to multiple pixel ports. This paper studies a multiple-input multiple-output (MIMO) system where both the transmitter and

Attapol T. Rutherford, Sirisak Chueykamhang, Thachaparn Bunditlurdruk, Nanthicha Angsuwichitkul

Understanding sentiment in financial documents is crucial for gaining insights into market behavior. These reports often contain obfuscated language designed to present a positive or neutral outlook, even when underlying conditions may be less favorable. This paper presents a novel approach using Aspect-Based Sentiment Analysis (ABSA) to decode obfuscated se

Yanwei Xiong, Haoran Zhao, Sri Bhavya Muvva, Cuong Le

Gas phase ultrafast electron diffraction (GUED) has become a powerful technique to directly observe the structural dynamics of photoexcited molecules. GUED reveals information about the nuclear motions that is complementary to the information on the electronic states provided by spectroscopic measurements. GUED experiments so far have utilized a single laser

Adam Hazimeh, Ke Wang, Mark Collier, Gilles Baechler

Multimedia documents such as slide presentations and posters are designed to be interactive and easy to modify. Yet, they are often distributed in a static raster format, which limits editing and customization. Restoring their editability requires converting these raster images back into structured vector formats. However, existing geometric raster-vectoriza

Francesco Navarra, Ayesha Asloob Qureshi, Dharm Veer

We introduce a new class of simplicial complexes, called \emph{$t$-Young complexes}, arising from a Young diagram and a positive integer~$t$. We show that every $t$-Young complex is either contractible or homotopy equivalent to a wedge of spheres. A complete characterization of their vertex-decomposability is provided, and in several cases, we establish expl

Zhipeng Ma, Ali Rida Bahja, Andreas Burgdorf, André Pomp

Enhancing fuel efficiency in public transportation requires the integration of complex multimodal data into interpretable, decision-relevant insights. However, traditional analytics and visualization methods often yield fragmented outputs that demand extensive human interpretation, limiting scalability and consistency. This study presents a multi-agent frame

Zahra Abedi, Richard M. K. van Dijk, Gijs Wijnholds, Tessa Verhoef

This research digitizes and analyzes the Leidse hoogleraren en lectoren 1575-1815 books written between 1983 and 1985, which contain biographic data about professors and curators of Leiden University. It addresses the central question: how can we design an automated pipeline that integrates OCR, LLM-based interpretation, and database linking to harmonize dat

Felipe Cano, Beatriz Molina-Samper

Radial germs of holomorphic foliations in dimension two have a characteristic property: they are the only singular foliations whose reduction of singularities has no singular points. We also know that they are desingularized by a single dicritical blowing-up. Let us say that a foliated space ((C3, 0),E,F) is almost radial when it has a reduction of singulari

Alix Deruelle, Vincent Guedj, Henri Guenancia, Ahmed Zeriahi

Given a compact K\"ahler manifold $X$ and a closed, positive $(1,1)$-current $T$ on $X$, we find sufficient conditions for $T$ to induce a metric structure $(X,d_T)$ which is the Gromov-Hausdorff limit of compact K\"ahler manifolds either in a "static" way or at time zero of smooth K\"ahler-Ricci flows. In dimension $1$ we extend works of T. Richard and M. S

Xiongfeng Zhan, Zhe You

In this paper, we study the higher Steklov eigenvalues of graphs on surfaces. We obtain the upper bound of higher Steklov eigenvalues of a finite graph $G$ with boundary $B$ and genus $g$ by using metrical deformation via probability flows. Our result can be regarded as a discrete analogue of Karpukhin's bound in spectral geometry. Moreover, this result impl

K. K. Ernazarov

In this article we investigate the properties of the asymptotically Schwarzschild-like metric as an alternative to the Schwarzschild solution in General Relativity. While asymptotically flat and similar to Schwarzschild at large distances $r$, this metric exhibits a fundamentally different strong-field behavior: it lacks an event horizon and is best interpre

Shiyuan Luo, Chonghao Qiu, Runlong Yu, Yiqun Xie

Environmental modeling faces critical challenges in predicting ecosystem dynamics across unmonitored regions due to limited and geographically imbalanced observation data. This challenge is compounded by spatial heterogeneity, causing models to learn spurious patterns that fit only local data. Unlike conventional domain generalization, environmental modeling

Jean Rodriguez, Holger Grisk, Alberto Anadón, Harjinder Singh

Magnetic imaging techniques are widespread critical tools used in fields such as magnetism, spintronics or even superconductivity. Among them, one of the most versatile methods is the magneto-optical Kerr effect. However, as soon as light is blocked from interacting with the magnetic layer, such as in deeply buried layers, optical techniques become ineffecti

Serge Gladkoff, Lifeng Han, Katerina Gasova

Analytic Translation Quality Evaluation (TQE), based on Multidimensional Quality Metrics (MQM), traditionally uses a linear error-to-penalty scale calibrated to a reference sample of 1000-2000 words. However, linear extrapolation biases judgment on samples of different sizes, over-penalizing short samples and under-penalizing long ones, producing misalignmen

Jaclyn Ocumpaugh, Luc Paquette, Ryan S. Baker, Amanda Barany

Data Driven Classroom Interviews (DDCIs) are an interviewing technique that is facilitated by recent technological developments in the learning analytics community. DDCIs are short, targeted interviews that allow researchers to contextualize students' interactions with a digital learning environment (e.g., intelligent tutoring systems or educational games) w

Hussein Rajabu, Lijun Qian, Xishuang Dong

In the area of explainable artificial intelligence, Symbolic Regression (SR) has emerged as a promising approach by discovering interpretable mathematical expressions that fit data. However, SR faces two main challenges: most methods are evaluated on scientific datasets with well-understood relationships, limiting generalization, and SR primarily targets sin

DUNE Collaboration, S. Abbaslu, A. Abed Abud, R. Acciarri

We present the measurement of $\pi^{+}$--argon inelastic cross sections using the ProtoDUNE Single-Phase liquid argon time projection chamber in the incident $\pi^+$ kinetic energy range of 500 -- 800 MeV in multiple exclusive channels (absorption, charge exchange, and the remaining inelastic interactions). The results of this analysis are important inputs t

Elias Hess-Childs, Matthew Rosenzweig, Sylvia Serfaty

We prove a functional inequality in any dimension controlling the derivative along a transport of the Riesz modulated energy in terms of the modulated energy itself. This modulated energy was introduced by the third author and collaborators in the study of mean-field limits and statistical mechanics of Coulomb/Riesz gases, where this control is an essential

Bingkun Huang, Yuhe Gong, Zewen Yang, Tianyu Ren

Reinforcement learning (RL) approaches based on Markov Decision Processes (MDPs) are predominantly applied in the robot joint space, often relying on limited task-specific information and partial awareness of the 3D environment. In contrast, episodic RL has demonstrated advantages over traditional MDP-based methods in terms of trajectory consistency, task aw

Hugo Gimbert, Corto Mascle, Patrick Totzke

We provide a new algebraic technique to solve the sequential flow problem in polynomial space. The task is to maximise the flow through a graph where edge capacities can be changed over time by choosing a sequence of capacity labelings from a given finite set. Our method is based on a novel factorization theorem for finite semigroups that, applied to a suita

Agnese Chiatti, Lara Piccolo, Sara Bernardini, Matteo Matteucci

With the growing deployment of Vision-Language Models (VLMs), pre-trained on large image-text and video-text datasets, it is critical to equip users with the tools to discern when to trust these systems. However, examining how user trust in VLMs builds and evolves remains an open problem. This problem is exacerbated by the increasing reliance on AI models as

Bin Liu, Qinghao Zhao, Yuxi Zhou, Zhejun Sun

Right heart failure (RHF) is a disease characterized by abnormalities in the structure or function of the right ventricle (RV), which is associated with high morbidity and mortality. Lung disease often causes increased right ventricular load, leading to RHF. Therefore, it is very important to screen out patients with cor pulmonale who develop RHF from people

Zhi-Jie Sun, Yong-Jin Sun, Zhi-Qing Zhang, You-Ya Yang

Recently, many new excited states of heavy mesons have been discovered in recent experiments, including radially excited states. The production processes of these states from the $B_{(s)}$ meson have drawn significant interest. In this paper, we use the covariant light-front approach to study the nonleptonic $B_{(s)}$ meson decays to the first radially excit

Giacomo Albi, Dante Kalise, Chiara Segala, Franco Zivcovich

We study the sparse stabilization of nonlinear multi-agent systems within a mean-field optimal control framework. The goal is to drive large populations of interacting agents toward consensus with minimal control effort. In the mean-field limit, the dynamics are described by a Vlasov-type kinetic equation, and sparsity is enforced through an l1-l2 penalizati

Bogi Kim, Jehan Oh

We establish gradient higher integrability results for weak solutions to degenerate parabolic equations of double phase type $$ u_t-\operatorname{div} \left(|Du|^{p-2}Du + a(x,t)|Du|^{q-2}Du\right)=0 $$ in $\Omega_T := \Omega\times (0,T)$, where $a(\cdot)\in C^{\alpha,\frac{\alpha}{2}}(\Omega_T)$. For bounded solutions, we prove that the result holds under t

Iulius Gherasim, Carlos García Sánchez

The pervasive integration of Artificial Intelligence models into contemporary mobile computing is notable across numerous use cases, from virtual assistants to advanced image processing. Optimizing the mobile user experience involves minimal latency and high responsiveness from deployed AI models with challenges from execution strategies that fully leverage

Álvaro Corrochano López, Carlos García Sánchez

The rise of AI and its growing computational demands have driven the integration of domain-specific accelerators (such as GPUs, TPUs, and NPUs) across the entire computing infrastructure. Following the precedent set by the GPGPU which popularized GPUs for general-purpose tasks, this research asks whether this phenomenon can be replicated with specialized acc

Li Gao, Bang Xu

In this paper, we establish dimension-free $L_p$-estimates for operator-valued maximal spherical means over cyclic groups $\Z_{m+1}^d$ for all $p>1$ and $m\geq1$. The key ingredient is a noncommutative extension of the spectral technique developed by Nevo and Stein. As an application, we obtain a noncommutative spherical maximal inequality for automorphism a

Rodrigo Fernández-Quevedo García, Gonçalo Cruz Antunes, Jens Harting, Holger Stark

Flow networks are fundamental for understanding systems such as animal and plant vasculature or power distribution grids. These networks can encode, transmit, and transform information embodied in the spatial and temporal distribution of their flows. In this work, we focus on a minimal yet physically grounded system that allows us to isolate the fundamental

Pietro Freni

I analyze $\mathcal{O}$-weakly immediate and $\mathcal{O}$-residual types in an o-minimal expansion of an ordered field $\mathbb{E}$, where $\mathcal{O}$ is a convex valuation ring. The main result is a characterization of those exponential theories $T$ such that for all $(\mathbb{E}, \mathcal{O})\models T_{\mathrm{convex}}$ the image of any $\mathcal{O}$-we

Jean-Luc Baril, José Luis Ramí rez

We investigate paths in the hexagonal circle packing and enumerate them with respect to width, height, number of steps, area, and kissing number. Functional equations and the kernel method yield closed bivariate generating functions together with coefficient formulas and asymptotics. We establish bijections with skew Dyck paths, constrained Motzkin paths, an

Clemens Anzinger, Jiehua Chen, Christian Hatschka, Manuel Sorge

We study the computational complexity of explaining preference data through Boolean attribute models (BAMs), motivated by extensive research involving attribute models and their promise in understanding preference structure and enabling more efficient decision-making processes. In a BAM, each alternative has a subset of Boolean attributes, each voter cares a

Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Grace Ma

Industrial process monitoring increasingly relies on sensor-generated time-series data, yet the lack of labels, high variability, and operational noise make it difficult to extract meaningful patterns using conventional methods. Existing clustering techniques either rely on fixed distance metrics or deep models designed for static data, limiting their abilit

Zhuchao Ji, Junyi Xie, Geng-Rui Zhang

Let $f:\mathbb{A}^N\to\mathbb{A}^N$ be a regular endomorphism of algebraic degree $d\geq2$ (i.e., $f$ extends to an endomorphism on $\mathbb{P}^N$ of algebraic degree $d$) defined over a number field. We prove that if the set of cyclotomic $f$-preperiodic points is Zariski-dense in $\mathbb{A}^N$, then some iterate $f^{\circ l}$ ($l\geq1$) is a quotient of a

Rui Zuo, Qinyue Tong, Zhe-Ming Lu, Ziqian Lu

With the rapid advancement of artificial intelligence-generated content (AIGC) technologies, including multimodal large language models (MLLMs) and diffusion models, image generation and manipulation have become remarkably effortless. Existing image forgery detection and localization (IFDL) methods often struggle to generalize across diverse datasets and off

Daisuke Kurisu, Yuta Okamoto, Taisuke Otsu

Since the seminal work by Beresteanu and Molinari(2008), the random set theory and related inference methods have been widely applied in partially identified econometric models. Meanwhile, there is an emerging field in statistics for studying random objects in metric spaces, called metric statistics. This paper clarifies a relationship between two fundamenta

Sarah Klanderman, Chloe Lewis, Harlea Monson, Koki Shibata

For a finite group $G$, the notion of a $G$-transfer system provides homotopy theorists with a combinatorial way to study equivariant objects. In this paper, we focus on the properties of transfer systems for non-abelian groups. We explicitly describe the width of all dihedral groups, quaternion groups, and dicyclic groups. For a given $G$, the set of all $G

Dongfen Bian, Shouyi Dai, Emmanuel Grenier

It is well-known that shear flows in a strip or in the half plane are unstable for the Navier-Stokes equations if the viscosity $\nu$ is small enough, provided the horizontal wave number $\alpha$ lies in a small interval, between the so called lower and upper marginal stability curves. The corresponding instabilities are called Tollmien-Schlichting waves. In

Geng-Rui Zhang

We prove several results on the multiplier spectrum of polynomials. We provide a detailed proof of the theorem stating that the multiplier spectrum morphism is generically injective on the moduli space of polynomials. We obtain a description of the non-injective locus of the multiplier spectrum morphism for polynomials of degree $d\geq2$. Roughly speaking, w

You Zhou

The Moon-forming giant impact significantly influenced the initial thermal state of Earth's mantle by generating a global magma ocean, marking the onset of mantle evolution. Recent Smoothed Particle Hydrodynamics (SPH) simulations indicate that such a collision would produce a superheated core, whose cooling would strongly influence subsequent mantle dynamic

Victoria Gould, Marianne Johnson

We initiate the study of the expansion $\mathcal{S}(M)$ of a monoid $M$ obtained via the semidirect product of $M$ acting naturally on the left of its power set (regarded as a semilattice under union). We term this the `subset expansion' of $M$. The monoid $\mathcal{S}(M)$ contains the images of several expansions of $M$ of wide interest and use in semigroup

Federico Chiossi, Alexey Tiranov, Luois Nicolas, Diana Serrano

We present a comprehensive study of spin relaxation dynamics at cryogenic temperatures in a rare-earth-doped crystal used for quantum memory applications: $^{171}$Yb:Y$_2$SiO$_5$. Spin relaxation is indeed a major limiting factor for both the efficiency and storage time of quantum memory protocols based on atomic frequency combs in rare-earth materials. The

Emmanuel Flachaire, Bertille Picard

The Kitagawa-Oaxaca-Blinder decomposition splits the difference in means between two groups into an explained part, due to observable factors, and an unexplained part. In this paper, we reformulate this framework using potential outcomes, highlighting the critical role of the reference outcome. To address limitations like common support and model misspecific

Valentin Khrulkov, Andrey Galichin, Denis Bashkirov, Dmitry Vinichenko

Recent advances in LLM-guided evolutionary computation, particularly AlphaEvolve (Novikov et al., 2025; Georgiev et al., 2025), have demonstrated remarkable success in discovering novel mathematical constructions and solving challenging optimization problems. However, the high-level descriptions in published work leave many implementation details unspecified

Subramanyam Sahoo, Aditi Chhawacharia

As artificial intelligence systems become increasingly powerful and pervasive, democratic societies face unprecedented challenges in governing these technologies while preserving core democratic values and institutions. This paper presents a comprehensive framework to address the full spectrum of risks that AI poses to democratic societies. Our approach inte

Hugo A. Hof, Matthias Walter

The reformulation-linearization-technique (RLT) is a well-known strengthening technique for binary mixed-integer optimization. It is well known to dominate lift-and-project strengthening, which is based on disjunctive programming (DP) for single-variable disjunctions. In contrast to the latter, the geometry of RLT is not understood completely. We provide som

Mohammad Javaheri

We prove that every odd-order group is symmetric harmonious: there exists a permutation $g_0,g_1,\ldots, g_{\ell-1}$ of elements of $G$ such that the consecutive products $g_0g_1,g_1g_2,\ldots, g_{\ell-1}g_0$ also form a permutation of elements of $G$ and $g_{\ell-i}=g_i^{-1}$ for all $1\leq i \leq \ell-1$. We apply this result to obtain new examples of R*-s

Yuqi Ping, Tingting Zhang, Tianhao Liang

In this paper, we study a cellular-connected unmanned aerial vehicle (UAV) which aims to fly between two predetermined locations while maintaining ultra-reliable low-latency communications (URLLC) for command-and-control (C2) links with terrestrial base stations (BSs). Long-range flights often trigger frequent inter-cell handovers, which may introduce delays

Levin Maier, Francesco Ruscelli

In this article, we introduce Tonelli Lagrangians on half-Lie groups equipped with a strong right-invariant Riemannian metric. These are right-invariant Lagrangians defined on the tangent bundle of a half-Lie group with quadratic growth on each fiber. The main examples of half-Lie groups are groups of $H^s$ or $C^k$ diffeomorphisms of compact manifolds. We s

Shivani Gupta, Archana Soam, Janik Karoly, Chang Won Lee

Linearly polarized dust emission traces the plane-of-sky magnetic field structure, thus allowing us to investigate the role of magnetic fields in the formation and evolution of cloud cores. In this work, we present observations of dust polarization at 850 $\mu{\rm m}$ wavelength toward the LDN\,328 (hereafter, L328) core and its neighborhood regions, classif

Dilip Kumar Ghosh, Debadrita Mukherjee, Koustav Mukherjee, Rohan Pramanick

The Standard Model (SM) cannot explain the observed baryon asymmetry of the Universe (BAU), thus driving the need for physics beyond the SM, which can generate electroweak baryogenesis through a strong first-order electroweak phase transition (SFOPT). We extend the SM with a complex singlet scalar (cxSM) and examine the phase transition behavior using a full

Haidong Liu

Let $X$ be a $\mathbb Q$-factorial canonical weak Fano variety of dimension $n\geq 2$. We show that if the $\mathbb Q$-Fano index $q_{\mathbb Q}(X)\geq 3$, then $X$ satisfies a Kawamata--Miyaoka type inequality: \[c_1(X)^n\leq 4\,\hat c_2(X)\cdot c_1(X)^{n-2}.\] As an application, we show that the $\mathbb Q$-Fano index of a Gorenstein canonical Fano $3$-fol

Bowen Tian, Roel C. G. M. Loonen, Roland M. E. Valckenborg, Jan L. M. Hensen

Accurate performance modeling of PV systems in urban environments is a significant challenge due to complex partial shading. This study introduces a high-resolution, hierarchical modeling framework that provides detailed insights from the solar cell to the system level. Rigorously validated against field-test data from calibrated equipment, the model demonst

Jorge Lamas

We investigate the Coherence--Curvature Model (CCM), a dynamical ensemble of connected graphs governed by a Hamiltonian that couples algebraic connectivity, Ollivier-Ricci curvature, and an edge-density penalty. Using connected simulated annealing we generate low-energy graph configurations and characterize their emergent geometry through the spectral dimens

Tingkai Yan, Haodong Wen, Binghui Li, Kairong Luo

While data scaling laws of large language models (LLMs) have been widely examined in the one-pass regime with massive corpora, their form under limited data and repeated epochs remains largely unexplored. This paper presents a theoretical analysis of how a common workaround, training for multiple epochs on the same dataset, reshapes the data scaling laws in

Shaheen Mohammed Saleh Ahmed, Hakan Hakan Guneyli

Accurate short-range prediction of extreme air temperature events remains a fundamental challenge in operational climate-risk management. We present Multi-Modal Weather State Transition Model with Anomaly-Driven Recurrent Attention Network Plus (MMWSTM-ADRAN+), a dual-stream deep learning architecture that couples a regime-aware dynamics model with an anomal

Allaa Boutaleb, Bernd Amann, Rafael Angarita, Hubert Naacke

Open-domain question answering over datalakes requires retrieving and composing information from multiple tables, a challenging subtask that demands semantic relevance and structural coherence (e.g., joinability). While exact optimization methods like Mixed-Integer Programming (MIP) can ensure coherence, their computational complexity is often prohibitive. C

Mykola Lavreniuk, Nataliia Kussul, Andrii Shelestov, Yevhenii Salii

Accurate delineation of agricultural field boundaries from satellite imagery is essential for land management and crop monitoring, yet existing methods often produce incomplete boundaries, merge adjacent fields, and struggle to scale. We present the Delineate Anything Flow (DelAnyFlow) methodology, a resolution-agnostic approach for large-scale field boundar

Leandro Chiarini, Ellen Powell

In this article, we derive precise estimates for the probability that a Bessel bridge of dimension $d \ge 0$ and end points $x$ and $a+bT-j$ stays below the linear barrier $a + bt$ for all $t \in [0,T]$. We identify the leading order term as well as the asymptotic error for this probability as $T\to \infty$, depending on $a,b,j,x$. We also derive the behavio

Wanqing Cui, Wei Huang, Yazhi Guo, Yibo Hu

Visual document retrieval requires understanding heterogeneous and multi-modal content to satisfy implicit information needs. Recent advances use screenshot-based document encoding with fine-grained late interaction to encode holistic information and capture nuanced alignments, significantly improving retrieval performance. However, retrievers are still trai

Hanwen Hu, Zimo Wen, Shiyou Qian, Jian Co

Traffic time series imputation is crucial for the safety and reliability of intelligent transportation systems, while diverse types of missing data, including random, fiber, and block missing make the imputation task challenging. Existing models often focus on disentangling and separately modeling spatial and temporal patterns based on relationships between

Sara P. Gandelman, Georgi Gary Rozenman

Quantum cryptography remains a topic of enduring scientific and educational interest. Here, we present a clear and accessible framework for exploring the six-state quantum key distribution protocol, an enhanced three-basis extension of the BB84 scheme that combines optical experiments with computational analysis. Designed for testing quantum communication pr

Liyang Jin, Zichen Xi, Joseph G. Thomas, Jun Ji

Electrical isolation is critical to ensure safety and minimize electromagnetic interference (EMI), yet existing methods struggle to simultaneously transmit power and signals through a unified channel. Here we demonstrate a mechanically-isolated gate driver based on microwave-frequency surface acoustic wave (SAW) device on lithium niobate that achieves galvan

Przemyslaw Chojecki

We propose a Kardashev-inspired yet operational Autonomous AI (AAI) Scale that measures the progression from fixed robotic process automation (AAI-0) to full artificial general intelligence (AAI-4) and beyond. Unlike narrative ladders, our scale is multi-axis and testable. We define ten capability axes (Autonomy, Generality, Planning, Memory/Persistence, Too

Zhaopei Huang, Qifeng Dai, Guozheng Wu, Xiaopeng Wu

With the rise of smart personal devices, service-oriented human-agent interactions have become increasingly prevalent. This trend highlights the need for personalized dialogue assistants that can understand user-specific traits to accurately interpret requirements and tailor responses to individual preferences. However, existing approaches often overlook the

Benjamin Hinrichs, Pascal Mittenbühler

We study the convergence rate of translation-invariant discrete-time quantum dynamics on a one-dimensional lattice. We prove that the cumulative distributions function of the ballistically scaled position $X(n)/{n}$ after $n$ steps converges at a rate of $n^{-1/3}$ in the L\'evy metric as $n\to\infty$. In the special case of step-coin quantum walks with two-

Zhenyu Chen, Yuguo Shao, Zhengwei Liu, Zhaohui Wei

Quantum algorithms based on parameterized quantum circuits (PQCs) have enabled a wide range of applications on near-term quantum devices. However, existing PQC architectures face several challenges, among which the ``barren plateaus" phenomenon is particularly prominent. In such cases, the loss function concentrates exponentially with increasing system size,

S. V. Trofymenko, I. V. Kyryllin

K-shell ionization and characteristic x-ray radiation (CXR) by high-energy electrons and positrons in oriented silicon crystals are studied using computer simulation. A method for this simulation has been developed and is described in detail. The evolution of the angular distribution of CXR from the upstream surface of the crystal with changes in the angle b

Rubén Caballero, Alexandre N. Carvalho, Pedro Marín-Rubio, José Valero

In this paper we study the robustness of dynamically gradient multivalued semiflows. As an application, we describe the dynamical properties of a family of Chafee-Infante problems approximating a differential inclusion studied in [3], proving that the weak solutions of these problems generate a dynamically gradient multivalued semiflow with respect to suitab

Mingxin Zhang, Cuiying Pei, Bangshuai Zhu, Qi Wang

Materials with graphene-like layers attract tremendous attention due to their electronic structures and superconducting properties. In this study, we synthesized LaP2 polycrystalline and observed a superconducting transition around 30 GPa. The critical temperature Tc increases monotonically with pressure, which is nearing saturation and reaches 7.8 K at 78 G

Ziyu Liu, Jiehao Wan

This article establishes several necessary and sufficient criteria on asymptotic stability and mean ergodicity in various types of topologies for Feller processes taking values in Polish spaces. In particular, asymptotic stability and mean ergodicity in Wasserstein distance and weighted total variation distance are considered. The characterizations are formu

Yuzhou Fang, Juha Kinnunen, Chao Zhang

We investigate a class of degenerate fully nonlinear nonlocal elliptic equations with Hamiltonian terms. By precisely characterizing the interaction between the degeneracy law of equations and the growth behavior of the Hamiltonian terms, we establish the Lipschitz regularity of viscosity solutions by the Ishii-Lions method, and further show the gradient H\"

Xavier Gràcia, Ángel Martínez-Muñoz, Xavier Rivas, Narciso Román-Roy

Some mechanical systems with dissipation can be described within the framework of the so-called contact mechanics: a modified form of the Euler-Lagrange equations stemming from Herglotz's variational principle, which admits a geometric formulation in terms of contact geometry. On the other hand, the study of singular Lagrangian systems and Dirac's theory of

Jinkun Zhao, Lei Huang, Haixin Ge, Wenjun Wu

We introduce Embedded Stroop, a controlled diagnostic paradigm for measuring image-embedded prompt interference in Multimodal Large Language Models (MLLMs), where the query is rendered directly inside the visual input. Using the What-Color-Is-the-Text (WCIT) benchmark, which covers 59 fine-grained colors under Standard, Flipped, and Masked variants, we evalu

Yuchen Bao, Yiting Wang, Wenjian Huang, Haowei Wang

Scene Text Editing (STE) aims to naturally modify text in images while preserving visual consistency, the decisive factors of which can be divided into three parts, i.e., text style, text content, and background. Previous methods have struggled with incomplete disentanglement of editable attributes, typically addressing only one aspect - such as editing text

Gleb Berloff, Anne-Marie Broomhall, George T. Hookway, Mikkel N. Lund

We present the results of an investigation into the possible presence of magnetic activity cycles in stars observed in two observational campaigns by the K2 mission. This study was based on the KEYSTONE asteroseismic sample of solar-like oscillators, which contained 20 stars for which we were able to determine whether the asteroseismic p-mode frequencies var

Jayanta Mukherjee, Xuejiao Kang, David F. Gleich, Ahmed Sameh

Eigenvalue problems serve as fundamental substrates for applications in large-scale scientific simulations and machine learning, often requiring computation on massively parallel platforms. As these platforms scale to hundreds of thousands of cores, hardware failures become a significant challenge to reliability and efficiency. In this paper, we propose and

Temitayo Adefemi

MPI's derived datatypes (DDTs) promise easier, copy-free communication of non-contiguous data, yet their practical performance remains debated and is often reported only for a single MPI stack. We present a cross-implementation assessment using three 2D applications: a Jacobi CFD solver, Conway's Game of Life, and a lattice-based image reconstruction. Each a

N. Thatte, D. Rigopoulou, F. R. Donnan, I. Garcia-Bernete

We have carried out a detailed analysis of the 3.4 micron spectral feature arising from Polycyclic Aromatic Hydrocarbons (PAH), using JWST archival data. For the first time in an external galaxy (NGC 6240), we have identified two distinct spectral components of the PAH 3.4 micron feature: a shorter wavelength component at 3.395 micron, which we attribute to

Vasilis Gkolemis, Christos Diou, Michael U. Gutmann

Bayesian parameter inference for complex stochastic simulators is challenging due to intractable likelihood functions. Existing simulation-based inference methods often require large number of simulations and become costly to use in high-dimensional parameter spaces or in problems with partially uninformative outputs. We propose a new method for differentiab

P. W. R. Lima, J. A. S. Lima

A dark-energy-free cosmological model ($\Omega_{DE} \equiv 0$) based on gravitationally induced adiabatic particle creation is proposed. The thermodynamics of particle production yields an effective negative pressure that drives both primordial inflation and late-time cosmic acceleration. The model, characterized by four components and two free parameters ($

Riccardo Torchio, Sebastian Schöps, Francesco Lucchini

A Block Structure Preserving Model Order Reduction approach is proposed for Integral Equations methods based on the Augmented Electric Field Integral Equation. This approach allows for representing the unknown fields with dedicated subspaces. Numerical results show that this leads to smaller reduced-order models and higher accuracy.

Zhipeng Ma, Bo Nørregaard Jørgensen, Zheng Grace Ma

Improving energy efficiency in industrial foundry processes is a critical challenge, as these operations are highly energy-intensive and marked by complex interdependencies among process variables. Correlation-based analyses often fail to distinguish true causal drivers from spurious associations, limiting their usefulness for decision-making. This paper app

Bastian Schäfer, Dominik Dörr, Naim Naouar, Jan Paul Wank

Macroscopic modeling of a non-crimp fabric's (NCF's) forming behavior is challenging as it strongly depends on the textile architecture, fiber type, and stitching type. While shear is the main deformation mode of woven fabrics, membrane modeling approaches for NCFs should also consider stitching deformation and roving slippage. However, for 0{\textdegree}/90