December 2025 arXiv papers — page 22

Yuhan Li, Hongyu Liu, Catharine W. K. Lo

This paper addresses an open inverse problem at the interface of mathematical analysis and spatial ecology: the unique identification of unknown spatial anomalies -- interpreted as zones of habitat degradation -- and their associated ecological parameters in multi-species predator-prey systems with multiple chemical signals, using only boundary measurements.

Benjamin J. Owen

Continuous gravitational waves from rapidly rotating neutron stars are on the new frontiers of gravitational wave astrophysics and have strong connections to electromagnetic astronomy, nuclear astrophysics, and condensed matter physics. In this Colloquium I survey prospects for detection of continuous gravitational waves from various neutron star populations

Vincent Herrmann, Eric Alcaide, Michael Wand, Jürgen Schmidhuber

Measuring the in-context computational effort of language models is a key challenge, as metrics like next-token loss fail to capture reasoning complexity. Prior methods based on latent state compressibility can be invasive and unstable. We propose Multiple Token Divergence (MTD), a simple measure of computational effort defined as the KL divergence between a

Alexey Remizov

We present the Legendre transformation in a geometric way based on the procedure of the Legendrian lift. This approach allows us to understand some interesting properties of it, in particular, the reason for the appearance of singularities of dual curves. Also we consider application of the Legendre transformation to the Clairaut differential equation. Final

Anwesha Chakraborty, Lucas Hackl, Mario Kieburg

We study the average bipartite entanglement entropy of Haar-random pure states in quantum many-body systems with global $\mathrm{SU}(2)$ symmetry, constrained to fixed total spin $J$ and magnetization $J_z = 0$. Focusing on spin-$\tfrac12$ lattices and subsystem fractions $f < \frac{1}{2}$, we derive a asymptotic expression for the average entanglement entro

Tianyi Hu, Zhiqiang Pu, Yuan Wang, Tenghai Qiu

Heterogeneity is a fundamental property in multi-agent reinforcement learning (MARL), which is closely related not only to the functional differences of agents, but also to policy diversity and environmental interactions. However, the MARL field currently lacks a rigorous definition and deeper understanding of heterogeneity. This paper systematically discuss

Bijender, Ajay Kumar

In 2017, Cooper et al. proposed a conjecture providing a lower bound for the Waldschmidt constant of monomial ideals. We confirm this conjecture for some classes of monomial ideals. Recently, M\'endez, Pinto, and Villarreal formulated a conjecture stating that if $I$ is a monomial ideal without embedded associated primes, whose irreducible decomposition is m

Qihang Peng, Xuesong Chen, Chenye Yang, Shaoshuai Shi

Autonomous driving requires generating safe and reliable trajectories from complex multimodal inputs. Traditional modular pipelines separate perception, prediction, and planning, while recent end-to-end (E2E) systems learn them jointly. Vision-language models (VLMs) further enrich this paradigm by introducing cross-modal priors and commonsense reasoning, yet

Benjamin J. Owen, Binod Rajbhandari

Continuous gravitational waves have the potential to transform gravitational wave astronomy and yield fresh insights into astrophysics, nuclear and particle physics, and condensed matter physics. We evaluate their detectability by combining various theoretical and observational arguments from the literature and systematically applying those arguments to know

Amar Abane, Junxiao Shi, Van Sy Mai, Abderrahim Amlou

We present MQNS, a discrete-event simulator for rapid evaluation of entanglement routing under dynamic, heterogeneous configurations. MQNS supports runtime-configurable purification, swapping, memory management, and routing, within a unified qubit lifecycle and integrated link-architecture models. A modular, minimal design keeps MQNS architecture-agnostic, e

Arthur D. Yaghjian

By means of a brief review of the derivation of the causal modified Lorentz-Abraham-Dirac classical equation of motion from the renormalization of the mass in the modified equation of motion of an extended charged sphere as its radius approaches zero, it is shown that Zin and Pylak's objection that the jumps in velocity allowed across transition intervals ne

René L. Schilling, Jian Wang, Bingyao Wu, Jie-Xiang Zhu

Let $X:=(X_t)_{t\geq 0}$ be an ergodic Markov process on $\real^d$, and $p>0$. We derive upper bounds of the $p$-Wasserstein distance between the invariant measure and the empirical measures of the Markov process $X$. For this we assume, e.g.\ that the transition semigroup of $X$ is exponentially contractive in terms of the $1$-Wasserstein distance, or that

Danni Xu, Shaojing Fan, Harry Cheng, Mohan Kankanhalli

Multimodal misinformation increasingly leverages visual persuasion, where repurposed or manipulated images strengthen misleading text. We introduce RW-Post, a post-aligned text--image benchmark for real-world multimodal fact-checking with auditable annotations: each instance links the original social-media post with reasoning traces and explicitly linked evi

Masanori Hanada, Shunji Matsuura, Andreas Schafer, Jinzhao Sun

Quantum simulation of non-Abelian gauge theories requires careful handling of gauge redundancy. We address this challenge by presenting universal principles for treating gauge symmetry that apply to any quantum simulation approach, clarifying that physical states need not be represented solely by gauge singlets. Both singlet and non-singlet representations a

Ling Xin, Mojtaba Nayyeri, Zahra Makki Nayeri, Steffen Staab

Structural knowledge graph foundation models aim to generalize reasoning to completely new graphs with unseen entities and relations. A key limitation of existing approaches like Ultra is their reliance on a single relational transformation (e.g., element-wise multiplication) in message passing, which can constrain expressiveness and fail to capture diverse

Tim Engel, Marco Rocco, Adrian Signer, Yannick Ulrich

We present a fully differential computation of $e^+\,e^-\to\gamma\,\gamma$ at next-to-next-to-leading order in QED. The process has been implemented into McMule, completing its set of next-to-next-to-leading-order calculations for the most important $2 \to 2$ processes. The results allow for generic applications to electron-positron colliders with centre-of-

Fuat Berkin Altunkaynak, Aslı Tuncer

We develop a semiclassical geometric framework to constrain information transfer through traversable wormholes. This study is motivated by the growing intersection between spacetime geometry and quantum information theory, specifically the ER=EPR conjecture and the bit-thread formulation of holographic entropy. First, we prove a geometric monotonicity result

Daqian Cao, Quan Yuan, Weibang Bai

Traditional geometric inverse kinematics methods for parallel mechanisms rely on specific spatial geometry constraints. However, their application to redundant parallel mechanisms is challenged due to the increased constraint complexity. Moreover, it will output no solutions and cause unpredictable control problems when the target pose lies outside its works

Dongli Cai, Xihe Chen, Yaosheng Chen, Hong Xian

Heartbeat interval can be detected from ballistocardiogram (BCG) signals in a non-contact manner. Conventional methods achieved heartbeat detection from different perspectives, where template matching (TM) and deep learning (DL) were based on the similarity of neighboring heartbeat episodes and robust spatio-temporal characteristics, respectively, and thus,

Panlong Wu, Yifei Zhong, Danyang Chen, Ting Wang

Large Language Models (LLMs) are rapidly being integrated into real-world applications, yet their autoregressive architectures introduce significant inference time variability, especially when deployed across heterogeneous edge-cloud systems. Existing solutions largely neglect the dynamic, stochastic, and heterogeneous nature of such environments, often igno

Brahim Asfour, Farida Bargach, Yahya Ladghami, Ahmed Errahmani

In this paper, we investigate the production of primordial black holes (PBHs) during the radiation-dominated era. The collapse of significant density perturbations originating from large primordial scalar fluctuations generated during inflation can lead to the formation of primordial black holes. In our study, we adopt the Higgs hybrid metric-Palatini model

Anton A. Stoorvogel, Ali Saberi, Zhenwei Liu, Tayaba Yeasmin

In this paper, we study scale-free weak synchronization for multi-agent systems (MAS). In other words, we design a protocol for the agents without using any knowledge about the network. We do not even require knowledge about the connectivity of the network. Each protocol contains an adaptive parameter to tune the protocol automatically to the demands of the

Shenghan Li, Yong Wang

Motivated by the work of D. Hoff and K. Zumbrun (Indiana Univ. Math. J. 44: 603-676, 1995), we investigate the diffusion wave phenomena in three-dimensional incompressible viscoelastic flows. By employing the representation formula of the wave equation and the stationary phase methods on the sphere $\mathbb{S}^{d-1}$, we establish $L^p$ decay estimates for t

Takayuki Tsuchida

Integrable discretizations of the sine-Gordon equation in characteristic (or light-cone) coordinates have been extensively studied after the seminal works of Hirota and Orfanidis in the late 1970s. In contrast, integrable discretizations of the sine-Gordon equation in non-characteristic coordinates have been scarcely studied except the lattice sine-Gordon mo

Yujin Guo, Yuan Lou, Hongfei Zhang

In this paper, we are concerned with the following eigenvalue problem with an advection term: \begin{equation}\label{0.1} \left\{ \begin{split} -\epsilon\Delta \phi-2\alpha\nabla m(x)\cdot\nabla \phi+V(x)\phi&=\lambda \phi\ \ \text{in}\ \ \Omega,\\ \phi&=0\ \ \hbox{on}\ \ \partial\Omega, ~~~\text{(0.1)} \end{split} \right. \end{equation} where $\Omega\subset

Z. Kepuladze, J. Jejelava

Lorentz invariance (LI) is a foundational principle of modern physics, yet its possible violation (LIV) remains an intriguing window to physics beyond the Standard Model. While stringent constraints exist in the electromagnetic and hadronic sectors, the weak sector-particularly unstable bosons-remains largely unexplored. In this work, based on our recent stu

Ken Kurata, Gen Sato, Izumi Tsunokuni, Yusuke Ikeda

The room impulse response (RIR) characterizes sound propagation in a room from a loudspeaker to a microphone under the linear time-invariant assumption. Estimating RIRs from a limited number of measurement points is crucial for sound propagation analysis and visualization. Physics-informed neural networks (PINNs) have recently been introduced for accurate RI

Meicong Zhang, Tiancheng su, Guoxiu He

In recent years, using predefined agentic workflows to guide large language models (LLMs) for literature classification and review has become a research focus. However, writing research introductions is more challenging. It requires rigorous logic, coherent structure, and abstract summarization. Existing workflows often suffer from long reasoning chains, err

Su Yang

In the present work, we review two well-established quasi-continuum models of a Fermi-Pasta-Ulam lattice with Hertzian type potentials, and utilize these two models to approximate the discrete dispersive shock waves (DDSWs) which are numerically observed in the simulation of the lattice. To perform analysis on the various characteristics of the DDSW, we anal

Xuanchao Zhang, Yang-Cheng Ye, Panpan Zhang, Xiangmei Duan

In this paper, we investigate coherent control of nonadiabatic dynamics at a conical intersection (CI) using engineered ultrafast laser pulses. Within a model vibronic system, we tailor pulse chirp and temporal profile and compute the resulting wave-packet population and coherence dynamics using projections along the reaction coordinate. This approach allows

Samin Riasat, Hessam Mahdavifar

We study covering problems in Hamming and Grassmann spaces through a unified coding-theoretic and information-theoretic framework. Viewing covering as a form of quantization in general metric spaces, we introduce the notion of the average covering radius as a natural measure of average distortion, complementing the classical worst-case covering radius. By le

Ünver Çiftçi

Deep Q-learning algorithms remain notoriously unstable, especially during early training when the maximization operator amplifies estimation errors. Inspired by bounded rationality theory and developmental learning, we introduce Sat-EnQ, a two-phase framework that first learns to be ``good enough'' before optimizing aggressively. In Phase 1, we train an ense

Zhaosong Lu, Sanyou Mei

In this paper we study a nonconvex-strongly-concave constrained minimax problem. Specifically, we propose a first-order augmented Lagrangian method for solving it, whose subproblems are nonconvex-strongly-concave unconstrained minimax problems and suitably solved by a first-order method developed in this paper that leverages the strong concavity structure. U

Debkanta Ghosh, Tanoy Kanti Konar, Gianluca Francica, Amit Kumar Pal

Regular graphs find broad applications ranging from quantum communication to quantum computation. Motivated by this, we investigate the design of a quantum battery based on a K-regular graph, where K denotes the number of edges incident on each vertex. We show that a 0-regular graph battery exhibits extractable work that scales linearly with the system-size

Sauhard Dubey

Cross-domain scientific synthesis requires connecting mechanistic explanations across fragmented literature, a capability that remains challenging for both retrieval-based systems and unconstrained language models. While recent work has applied large language models to scientific summarization and question answering, these approaches provide limited control

Wei-Wei Qi

In this paper, we investigate some q-congruences for truncated ${}_{4}\phi_3$ series by using Singh's quadratic transformation and the creative microscoping method (introduced by Victor J. W. Guo and Zudilin in 2019).

Kai Liu, Jungang Li, Yuchong Sun, Shengqiong Wu

This paper presents JavisGPT, the first unified multimodal large language model (MLLM) for joint audio-video (JAV) comprehension and generation. JavisGPT has a concise encoder-LLM-decoder architecture, which has a SyncFusion module for spatio-temporal audio-video fusion and synchrony-aware learnable queries to bridge a pretrained JAV-DiT generator. This desi

Jin Wu, Chanjin Zheng

Cognitive diagnosis is an essential research topic in intelligent education, aimed at assessing the level of mastery of different skills by students. So far, many research works have used deep learning models to explore the complex interactions between students, questions, and skills. However, the performance of existing method is frequently limited by the l

Chumeng Liang, Zhanyang Jin, Zahaib Akhtar, Mona Pereira

Tabular log abstracts objects and events in the real-world system and reports their updates to reflect the change of the system, where one can detect real-world inconsistencies efficiently by debugging corresponding log entries. However, recent advances in processing text-enriched tabular log data overly depend on large language models (LLMs) and other heavy

Goran Dražić, Matija Kazalicki, Rudi Mrazović

For a fixed integer n, a pair of nonzero integers {a, c} is called a D(n)-pair if the product ac plus n is a perfect square. In this short note we prove that D(n)-pairs are asymptotically equidistributed (via their associated quadratic forms) among proper SL_2(Z)-equivalence classes of binary quadratic forms of discriminant 4n with fixed content. As a conseq

Si-Yu Xiao, Xin-Di Zhao, Xiang-Zhan Wang, Tian-Hao Mao

Casing collar locator (CCL) measurements are widely used as reliable depth markers for positioning downhole instruments in cased-hole operations, enabling accurate depth control for operations such as perforation. However, autonomous collar recognition in downhole environments remains challenging because CCL signals are often corrupted by toolstring- or casi

Mikhail Kabenyuk

In a finite group, a subset is called a Lagrange subset if its size divides the group order, and a factor if it admits a complementary subset. We provide a new and comparatively direct proof of the classification of groups in which every Lagrange subset is a factor. We show that any nontrivial such group must be a cyclic group of prime order, the cyclic grou

Yaping Zhang, Qixuan Zhang, Xingquan Zhang, Zhiyuan Chen

The rapid advancement of large language models (LLMs) and multimodal foundation models has sparked growing interest in their potential for scientific research. However, scientific intelligence encompasses a broad spectrum of abilities ranging from understanding fundamental knowledge to conducting creative discovery, and existing benchmarks remain fragmented.

Serge N. Gavrilov, Anton M. Krivtsov, Ekaterina V. Shishkina

In this paper, we introduce "the Schr\"odinger plate." This is an infinite two-dimensional linear micro-polar elastic medium, with out-of-plane degrees of freedom, lying on a linear elastic foundation of a special kind. Any free motion of the plate can be corresponded to a solution of the two-dimensional Schr\"odinger equation for a single particle in the ex

Suyan Dai, Gan Sun, Fazeng Li, Xu Tang

Spectral clustering has emerged as one of the most effective clustering algorithms due to its superior performance. However, most existing models are designed for centralized settings, rendering them inapplicable in modern decentralized environments. Moreover, current federated learning approaches often suffer from poor generalization performance due to reli

A. N. Hopersky, A. M. Nadolinsky, S. A. Novikov, R. V. Koneev

Within the framework of the second-order non-relativistic quantum perturbation theory, the methods of the theory of irreducible tensor operators, and nonorthogonal orbitals, the absolute values and shape of the generalized cross-sections of the two-photon double ionization (sweeping) of the K-shell of a heavy neon-like ion of an iron atom were predicted. The

Xiaotian Ren, Nuerxiati Abudurexiti, Zhengyong Jiang, Angelos Stefanidis

Portfolio optimization in non-stationary markets is challenging due to regime shifts, dynamic correlations, and the limited interpretability of deep reinforcement learning (DRL) policies. We propose a Segmented Allocation with Momentum-Adjusted Utility for Multi-agent Portfolio Management via Hierarchical Deep Reinforcement Learning (SAMP-HDRL). The framewor

Phil Cuvin, Hao Zhu, Diyi Yang

Deceptive UI designs, widely instantiated across the web and commonly known as dark patterns, manipulate users into performing actions misaligned with their goals. In this paper, we show that dark patterns are highly effective in steering agent trajectories, posing a significant risk to agent robustness. To quantify this risk, we introduce DECEPTICON, an env

Simu Liu, Kailin Jiao, Junping Du, Yawen Li

This work addresses a route planning problem constrained by a bus road network that includes the schedules of all buses. Given a query with a starting bus stop and a set of Points of Interest (POIs) to visit, our goal is to find an optimal route on the bus network that allows the user to visit all specified POIs from the starting stop with minimal travel tim

Amit N. Sawant, Mats J. Stensrud

As AI systems are increasingly used to guide decisions, it is essential that they follow ethical principles. A core principle in medicine is non-maleficence, often equated with ``do no harm''. A formal definition of harm based on counterfactual reasoning has been proposed and popularized. This notion of harm has been promoted in simple settings with binary t

Shaona Das, Ravi Kiran Dokala, Subhash Thota

We report the influence of Ce$^{3+}$ substitution on the magnetic structures and phonon dynamics in SmCrO$_3$ perovskites. Magnetic landscapes are spanned by long-range canted anti-ferromagnetism, AFM with Neel temperatures $\sim$196 K accompanied by spin-reorientation transitions, T$_{SRPT}$ at 42 K. In Sm$_{0.9}$Ce$_{0.1}$CrO$_3$ (SCCO), Ce$^{3+}$ substitu

Sosuke Ito, Yoh Maekawa, Ryuna Nagayama, Andreas Dechant

Information flow between subsystems is a central concept in information thermodynamics, which provides the second-law-like inequalities for subsystems. This paper discusses the geometric decomposition of information flow, which was introduced for Markov jump systems [Physical Review Research, 8, 023292 (2026)], and applies it to overdamped Langevin systems.

Maria Spichkova

The spatial and temporal aspects of system properties are crucial for many types of systems. In this short paper, we present a TopFunST framework to analyse topological dependencies among features of the system, covering also spatial and temporal aspects. TopFunM is based on an extended version of the language of Topological Functioning Models (TFM). The TFM

Giovanni Canossa, Lode Pollet, Miguel A. Martin-Delgado, Hao Song

Fracton codes have been intensively studied as novel topological states of matter, yet their fault-tolerant properties remain largely unexplored. Here, we investigate the optimal thresholds of self-dual fracton codes, in particular the checkerboard code, against stochastic Pauli noise. By utilizing a statistical-mechanical mapping combined with large-scale p

Shunrui Li, Yang Liu

The Atiyah-Singer index theorem, a cornerstone of modern mathematics, has traditionally been derived from supersymmetric (SUSY) physics. This paper demonstrates a direct derivation from non-supersymmetric quantum statistics by establishing a fundamental correspondence: the grand partition functions of non-interacting bosonic and fermionic systems are precise

Anqi Mao

Large language models (LLMs) have achieved remarkable performance but face critical challenges: hallucinations and high inference costs. Leveraging multiple experts offers a solution: deferring uncertain inputs to more capable experts improves reliability, while routing simpler queries to smaller, distilled models enhances efficiency. This motivates the prob

Zongyi Lv, Changwei Xiong, Yuxun Zou

In the first part, we derive monotonicity of the normalized spectra for the second-order Steklov problem and two fourth-order Steklov problems on the $2$-dimensional geodesic disks with respect to the geodesic radius in the sphere and the hyperbolic space. The normalizations are made using four natural geometric factors. As corollaries, we get Escobar-type b

Ravi Kiran Dokala, Shaona Das, Subhash Thota

We investigate the effect of Ce$^{3+}$ substitution on the magnetic ordering and phonon dynamics of the GdCrO$_3$ orthorhombic perovskite. The Ce doped compound exhibits long-range canted antiferromagnetism with Neel transitions, T$_N$ at $\sim$ 173 K, accompanied by spin-flip, T$_{SF}$ at $\sim$ 10 K. Ce$^{3+}$ incorporation drives a modification of the spi

Tao Li, Quanyan Zhu

Cybersecurity is being fundamentally reshaped by foundation-model-based artificial intelligence. Large language models now enable autonomous planning, tool orchestration, and strategic adaptation at scale, challenging security architectures built on static rules, perimeter defenses, and human-centered workflows. This chapter argues for a shift from preventio

Yangzhi Ma, Bojun Liu, Jie Li, Li Li

Hash grids are widely used to learn an implicit neural field for Gaussian splatting, serving either as part of the entropy model or for inter-frame prediction. However, due to the irregular and non-uniform distribution of Gaussian splats in 3D space, numerous sparse regions exist, rendering many features in the hash grid invalid. This leads to redundant stor

Haosen Li, Wenshuo Chen, Shaofeng Liang, Lei Wang

Iterative refinement methods based on a denoising-inversion cycle are powerful tools for enhancing the quality and control of diffusion models. However, their effectiveness is critically limited when combined with standard Classifier-Free Guidance (CFG). We identify a fundamental limitation: CFG's extrapolative nature systematically pushes the sampling path

Yutao Zhong

In machine learning, the loss functions optimized during training often differ from the target loss that defines task performance due to computational intractability or lack of differentiability. We present an in-depth study of the target loss estimation error relative to the surrogate loss estimation error. Our analysis leads to $H$-consistency bounds, whic

Hasan Faraz Khan, Noor Fatima, Muzammil Behzad

The recent integration of artificial intelligence into medical imaging has driven remarkable advances in automated organ segmentation. However, most existing 3D segmentation frameworks rely exclusively on visual learning from large annotated datasets restricting their adaptability to new domains and clinical tasks. The lack of semantic understanding in these

Ju-Hsuan Weng, Jia-Wei Liao, Cheng-Fu Chou, Jun-Cheng Chen

Text-to-image diffusion models may generate harmful or copyrighted content, motivating research on concept erasure. However, existing approaches primarily focus on erasing concepts from text prompts, overlooking other input modalities that are increasingly critical in real-world applications such as image editing and personalized generation. These modalities

Maksim Kryzhanovskiy, Svetlana Glazyrina, Roman Ischenko, Konstantin Vorontsov

Modern AI systems often comprise multiple learnable components that can be naturally organized as graphs. A central challenge is the end-to-end training of such systems without restrictive architectural or training assumptions. Such tasks fit the theory and approaches of the collaborative Multi-Agent Reinforcement Learning (MARL) field. We introduce Reinforc

Shen-Shi Du, Yi Gong, Jun-Jie Wei, Zi-Ke Liu

Gamma-ray bursts (GRBs) are among the most potent probes of Lorentz invariance violation (LIV), offering direct constraints on the quantum gravity energy scale ($E_{\rm QG}$) based on observations of energy-dependent time lags. Individual GRBs with well-defined positive-to-negative lag transitions have been used to set lower limits on $E_{\rm QG}$, but they

Weiwei Li, Junzhuo Liu, Yuanyuan Ren, Yuchen Zheng

Deep learning models are known to often learn features that spuriously correlate with the class label during training but are irrelevant to the prediction task. Existing methods typically address this issue by annotating potential spurious attributes, or filtering spurious features based on some empirical assumptions (e.g., simplicity of bias). However, thes

Huanjun Wang, Qizhi Fang, Wenjing Liu

In this paper, we study mechanism design for single-facility location games where each agent has multiple private locations in [0, 1]. The individual objective is a satisfaction function that measures the discrepancy between the optimal facility location for an agent and the location provided by the mechanism. Based on different distance functions from agent

Ziyu Zhou, Haozhe Luo, Mohammad Reza Hosseinzadeh Taher, Jiaxuan Pang

Foundation models have been successful in natural language processing and computer vision because they are capable of capturing the underlying structures (foundation) of natural languages. However, in medical imaging, the key foundation lies in human anatomy, as these images directly represent the internal structures of the body, reflecting the consistency,

Chuan-Tsung Chan, Chan-Yi Chang, Zhong-Tang Wu

Based on a cocycle structure, we identify a new derivation of the Boltzmann distribution for finite energy-level systems from the maximal entropy principle (MEP). Our approach does not rely on the method of the Lagrange multiplier, and it provides a more transparent way to understand the dependence on the energy levels of the temperature $T = 1/\beta$ for th

Marco Cicalese, Giuliana Fusco, Giovanni Savaré

We continue the variational study of the discrete-to-continuum evolution of lattice systems of Blume-Emery-Griffith type which model two immiscible phases in the presence of a surfactant. In our previous work \cite{CFS}, we analyzed the case of a completely wetted crystal and described how the interplay between surfactant evaporation and mass conservation le

Matej Hoffmann

Applying the lens of computation and information has been instrumental in driving the technological progress of our civilization as well as in empowering our understanding of the world around us. The digital computer was and for many still is the leading metaphor for how our mind operates. Information theory (IT) has also been important in our understanding

Alexandros Christoforos

Large Language Models (LLMs) are often evaluated against ideals of perfect Bayesian inference, yet growing evidence suggests that their in-context reasoning exhibits systematic forgetting of past information. Rather than viewing this behavior as a limitation, we reinterpret forgetting as a functional cognitive mechanism. Drawing inspiration from human memory

Afshin Yaghoubi, Esmaile Khorram, Omid Naghshineh Arjmand

The Lindley distribution was first introduced by Lindley in 1958 for Bayesian computations. Over the past years, various generalizations of this distribution have been proposed by different authors. The generalized Lindley distributions sometimes have many parameters, and although they show good flexibility, their statistical form becomes complicated. In thi

Luise Puhlmann, Niklas Schlomberg

In an undirected graph, the odd cycle packing number is the maximum number of pairwise vertex-disjoint odd cycles. The odd cycle transversal number is the minimum number of vertices that hit every odd cycle. The maximum ratio between transversal and packing number is called Erd\H{o}s-P\'osa ratio. We show that in planar graphs, this ratio does not exceed 4.

Jan H. R. Dressler, Peter Kurz, Winfried J. Steiner

Despite a substantial body of theoretical and empirical research in the fields of conjoint and discrete choice analysis as well as product line optimization, relatively few papers focused on the simulation of subsequent competitive dynamics employing non-cooperative game theory. Only a fraction of the existing frameworks explored competition on both product

Jianting Yang

This paper presents a counterexample to the optimality conjecture in convex quantum channel optimization proposed by Coutts et al. The conjecture posits that for nuclear norm minimization problems in quantum channel optimization, the dual certificate of an optimal solution can be uniquely determined via the spectral calculus of the Choi matrix. By constructi

Sitender Pratap Kashyap

We present a prescription for computing the tree-level two-point amplitude of closed strings in the pure spinor superstring formalism, thereby completing the analysis of such superstring amplitudes. The construction relies on fixing the residual conformal Killing group using a mostly BRST-exact operator that has been successfully applied in the open-string c

Aleksei Kobzev

In this paper, based on a construction by J. Fickenscher, we construct a family of non-uniquely ergodic interval exchange transformations on $n$ intervals with the maximal possible number of measures, $\left\lfloor \frac{n}{2} \right\rfloor$. Subsequently, we generalize J. Chaika's result on estimating the Hausdorff dimension of the two measures from M. Kean

Soham Padia, Dhananjay Vaidya, Ramchandra Mangrulkar

Securing blockchain-enabled IoT networks against sophisticated adversarial attacks remains a critical challenge. This paper presents a trust-based delegated consensus framework integrating Fully Homomorphic Encryption (FHE) with Attribute-Based Access Control (ABAC) for privacy-preserving policy evaluation, combined with learning-based defense mechanisms. We

Tegenu Argaw Woldegiyorgis, Hong Xian Li, Fekadu Chekol Admassu, Merkebu Gezahegne

This study aims to evaluate the techno-economic feasibility of hybrid energy systems (HES) including Grid for providing reliable and sustainable power to Boru Meda Hospital, Ethiopia. HOMER pro 3.11.2 was used to design and evaluate a novel, integrated optimization and comparative assessment of diverse HRES, specif ically adjusted to the energy consumptions

Abdulrahman Qadi, Akash Sharma, Francesca Medda

Islamic equity screening relies on multiple binary rulebooks that often classify the same firm differently. This paper develops a Continuous Shariah Compliance Index (CSCI) on $[0,1]$ that embeds the published business-activity and financial-ratio thresholds of six leading standards in a single transparent measure. Using CRSP/Compustat U.S. equities from 199

Shihao Cai, Runnan Fang, Jialong Wu, Baixuan Li

Conducting reinforcement learning (RL) in simulated environments offers a cost-effective and highly scalable way to enhance language-based agents. However, previous work has been limited to semi-automated environment synthesis or tasks lacking sufficient difficulty, offering little breadth or depth. In addition, the instability of simulated users integrated

Matthaus Zering, Jolyon Joyce, Tal Gurfinkel, Jingbo Wang

The Quantum Approximate Optimization Algorithm (QAOA) is a leading candidate for achieving quantum advantage in combinatorial optimization on Near-Term Intermediate-Scale Quantum (NISQ) devices. However, random initialization of the variational parameters typically leads to vanishing gradients, rendering standard variational optimization ineffective. This pa

Alexandru Hegyi

Consistent glacier boundary delineation is essential for monitoring glacier change, yet many existing approaches are difficult to scale across long time series and heterogeneous environments. In this report, we present a GeoSAM-based, semi-automatic workflow for rapid glacier delineation from Sentinel-2 surface reflectance imagery. The method combines late-s

Bangya Liu, Xinyu Gong, Zelin Zhao, Ziyang Song

Human-object interaction (HOI) video generation has garnered increasing attention due to its promising applications in digital humans, e-commerce, advertising, and robotics imitation learning. However, existing methods face two critical limitations: (1) a lack of effective mechanisms to inject multi-view information of the object into the model, leading to p

Wen-Xiang Chen

We investigate the microstructure of Kerr Newman black holes in modified gravity of the f(R) type using a topological complex analytic framework inspired by holography. In this approach, black hole microstates are identified with singularities of an analytically continued partition function, and the entropy is obtained from residues weighted by winding numbe

Tatsuya Goto

This paper is a continuation of the paper [Got25] and studies Goldstern's principle, a principle about unions of continuum many null sets, further. The main result is that the Hausdorff measure version of Goldstern's principle for $\boldsymbol{\Pi}^1_1$ sets fails in $L$, despite the fact that the Lebesgue measure version is true. Moreover, we show that this

Helle Hvid Hansen, Wolfgang Poiger

We present a coalgebraic framework for studying generalisations of dynamic modal logics such as PDL and game logic in which both the propositions and the semantic structures can take values in an algebra $\mathbf{A}$ of truth-degrees. More precisely, we work with coalgebraic modal logic via $\mathbf{A}$-valued predicate liftings and interpret actions (abstra

Shi-cheng Yu, Hua Guan, Lei She, Cheng-Bin Li

We present relativistic many-body perturbation theory plus configuration interaction (MBPT+CI) calculations of the lowest four excited states of Ni$^{12+}$, a promising candidate for highly charged ion (HCI) optical clocks. By combining the convergence behavior from multiple calculation models, we perform a detailed analysis of the electron-correlation effec

Peter Koymans, Yuan Liu

Let $p$ be an odd prime. We give a formula for the bad part of $p$-class groups that is valid for $100\%$ of the abelian $p$-extensions when ordered by product of ramified primes.

Ricard Grebol, Margarita Machelett, Jan Stuhler, Ernesto Villanueva

We study the evolution of intergenerational educational mobility and related distributional statistics in Spain. Over recent decades, mobility has risen by one-third, coinciding with pronounced declines in inequality and assortative mating among the same cohorts. To explore these patterns, we examine regional correlates of mobility, using split-sample techni

Tomoki Yuji

In this paper, we introduce a Grothendieck topology on the category of totally bounded metric spaces and develop a theory of stacks with respect to this topology. We further define the fine moduli stack of compact metric spaces and prove that its coarse moduli space is isometric to the Gromov--Hausdorff space.

Pengcheng Xie

This paper focuses on solving unconstrained privacy-preserving black-box optimization (PBBO), its corresponding least Frobenius norm updating of quadratic models, and the differentially privacy mechanisms for PBBO. Optimization problems with transformed/encrypted objective functions aim to minimize F(x), which is encrypted/transformed/encrypted to F_k(x) as

Masahiro Kato

This study proposes an end-to-end algorithm for policy learning in causal inference. We observe data consisting of covariates, treatment assignments, and outcomes, where only the outcome corresponding to the assigned treatment is observed. The goal of policy learning is to train a policy from the observed data, where a policy is a function that recommends an

Zan Xu, Sari Nurfauziyyah, Anastasia Romanova, Kaamesh G S

Many recent research studies have focused on the well-being of software development team members, as this aspect may be critical not only for productivity and performance at work but also for the physical health and personal life of employees. Many studies agree that an important factor of team member well-being is whether team members feel appreciated and a

Panqiu Xia, Jiayu Zheng

In this paper, we introduce a natively positive approximation method based on the Feynman-Kac representation using random walks, to approximate the solution to the one-dimensional parabolic Anderson model of Skorokhod type, with either a flat or a Dirac delta initial condition. Assuming the driving noise is a fractional Brownian sheet with Hurst parameters $

Amit Cohen, Jonathan Ludwick, Ward Yahya, Maria Baskin

$SrVO_3$ (SVO), a model correlated metal and a promising transparent conducting oxide, develops a several-nanometer-thick near-surface region (NSR), rich in $V^{5+}$ species under ambient conditions. This oxidized layer obscures the intrinsic correlated-metallic $V^{4+}$ character and limits both fundamental studies of the physics and the material's integrat

Jan-Willem van Holten

In this note I sketch the work of Christiaan Huygens to develop a theory of motion and its application to elastic collisions. In this theory he uses the relativity of uniform linear motion to derive the conservation of momentum and kinetic energy (at the time referred to as living force or vis viva). The conservation of living force was used subsequently by

Konstantinos Tsouvalas

We exhibit examples of finitely presented subgroups $P$ of direct products of hyperbolic groups for which there is no algorithm that detects whether a finitely presented group has a quotient isomorphic to $P$. For any torsion-free, linear, hyperbolic group $Q$ that maps onto the free group of rank $2$ and $m\geq 2$, we construct a recursive sequence $(\Gamma