December 2025 arXiv papers — page 29

Yu Takahashi, Shun Takeuchi, Kexuan Xin, Guillaume Pelat

Question answering (QA) systems are increasingly deployed across domains. However, their reliability is undermined when retrieved evidence is incomplete, noisy, or uncertain. Existing knowledge graph (KG) based QA frameworks typically represent facts as static and deterministic, failing to capture the evolving nature of information and the uncertainty inhere

Bhabana Kumar, Debajyoti Dutta, Mrinal Kumar Das

We have realized different two-zero textures within the framework of the left right symmetric model using the $\Gamma_{3}\cong A_{4}$ modular group. The matter multiplets of the model are assigned as three singlet representations of the $A_{4}$ group, and their charge assignments together with the modular weights of the Yukawa couplings are chosen in such a

Ali Reza Mavaddat, Saeid Alikhani

A pair of numbers is amicable if each number equals the sum of the proper divisors of the other. This paper after exploring the history and evolution of amicable numbers, introduces a novel characterization of amicable pairs whose greatest common divisor is a power of two, using their distinct prime factorizations. Specifically, we examine pairs of the forms

Xuan-Heng Zhang, Cong-Feng Qiao

Recently, the BESIII Collaboration indicate that no $\Lambda_c\bar{\Sigma}_c$ bound-state with a mass near threshold in the range $4715$--$4735~\mathrm{MeV}$ was observed. In order to determine the plausible mass region of the states in this structure, we calculate the mass spectrum of the $\Lambda_c\bar{\Sigma}_c$ configuration with the method of QCD sum ru

Julian Evan Chrisnanto, Salsabila Rahma Alia, Nurfauzi Fadillah, Yulison Herry Chrisnanto

Simulating nonlinear reaction-diffusion dynamics on complex, non-Euclidean manifolds remains a fundamental challenge in computational morphogenesis, constrained by high-fidelity mesh generation costs and symplectic drift in discrete time-stepping schemes. This study introduces the Intrinsic-Metric Physics-Informed Neural Network (IM-PINN), a mesh-free geomet

Silvia Novo, César Sánchez-Sellero

This paper introduces new methods for constructing prediction intervals using quantile-based techniques. The procedures are developed for both classical (homoscedastic) autoregressive models and modern quantile autoregressive models. They combine quantile estimation with multiplier bootstrap schemes to approximate the sampling variability of coefficient esti

Chorok Lee

Probabilistic knowledge graph embeddings represent entities as distributions, using learned variances to quantify epistemic uncertainty. We identify a fundamental limitation: these variances are relation-agnostic, meaning an entity receives identical uncertainty regardless of relational context. This conflates two distinct out-of-distribution phenomena that

Xiangwen Zhang, Xiaowei Dai, Runnan Chen, Xiaoming Chen

Creating physically realistic content in VR often requires complex modeling tools or predefined 3D models, textures, and animations, which present significant barriers for non-expert users. In this paper, we propose SketchPlay, a novel VR interaction framework that transforms humans' air-drawn sketches and gestures into dynamic, physically realistic scenes,

Biman Bagchi

Diffusion in rugged free-energy landscapes is central to diverse problems in chemical physics, biomolecular dynamics, polymer transport and numerous disordered systems. Zwanzig's well-known classic mean-field theory predicts that roughness reduces the diffusion coefficient by an exponential factor determined solely by the variance of the disorder. However, t

Chengyu Tian, Wenbin Pei

Robustness in complex systems is of significant engineering and economic importance. However, conventional attack-based a posteriori robustness assessments incur prohibitive computational overhead. Recently, deep learning methods, such as Convolutional Neural Networks (CNNs) and Graph Neural Networks (GNNs), have been widely employed as surrogates for rapid

Jun-Jie Huang

For an integer $s\geq1$ and a graph $\Gamma$, a path $(u_0, u_1, \ldots, u_{s})$ composed of vertices of $\Gamma$ is called an {\em $s$-geodesic} if it is a shortest path between $u_0$ and $u_s$. We say that $\Gamma$ is {\em $s$-geodesic transitive} if for each $i\leq s$, $\Gamma$ contains at least one $i$-geodesic, and its automorphism group acts transitive

Aldo Conca, Emanuela De Negri, Volkmar Welker

Binomial edge ideals associated to a simple graph G were introduced by Herzog and collaborators and, independently, by Ohtani. They became an ``instant classic" in combinatorial commutative algebra with more than 100 papers devoted to their investigation over the past 15 years. They exhibit many striking properties, including being radical and, moreover, Car

Sounak Bandyopadhyay, Arnab Ghosh

This article traces the development of fluctuation theory and its deep connection to irreversibility, from equilibrium to near-equilibrium, and finally to far-from-equilibrium systems. Classical fluctuation theorems, which capture the statistical behaviour of thermodynamic systems far from equilibrium, are now well established. Their quantum counterparts, ho

Wen Jiang, Li Wang, Kangyao Huang, Wei Fan

Unmanned aerial vehicles (UAVs) are crucial tools for post-disaster search and rescue, facing challenges such as high information density, rapid changes in viewpoint, and dynamic structures, especially in long-horizon navigation. However, current UAV vision-and-language navigation(VLN) methods struggle to model long-horizon spatiotemporal context in complex

Sarthak Mehrotra, Sairam V C Rebbapragada, Mani Hemanth Reddy Bonthu, Vineeth N Balasubramanian

Multimodal Large Language Models (MLLMs) show strong potential for interpreting and interacting with complex, pixel-rich Graphical User Interface (GUI) environments. However, building agents that are both efficient for high-level tasks and precise for fine-grained interactions remains challenging. GUI agents must perform routine actions efficiently while als

Mirza Karamehmedović, Kristoffer Linder-Steinlein, Jesper Glückstad

We propose a rigorous, physically interpretable, and quantifiable definition of the photonic nanojet (PNJ). This framework resolves longstanding ambiguities in measuring PNJ dimensions and leverages an optimal mass transport-based metric to quantify PNJ quality. Building on this metric, we develop a PNJ steering methodology that requires no opto-mechanical i

Aicha Boutorh, Soumia Bouyahiaoui, Sara Belhadj, Nour El Yakine Guendouz

Predicting the binding affinity between antigens and antibodies is fundamental to drug discovery and vaccine development. Traditional computational approaches often rely on experimentally determined 3D structures, which are scarce and computationally expensive to obtain. This paper introduces DuaDeep-SeqAffinity, a novel sequence-only deep learning framework

Jinsil Lee, Youngjoon Hong, Seungchan Ko, Jae Yong Lee

Recent advances in machine learning (ML) have opened new possibilities for solving partial differential equations (PDEs), yet robust performance in challenging regimes remains limited. In particular, singularly perturbed differential equations exhibit sharp boundary or interior layers with rapid transitions, where standard ML surrogates often fail without ex

Rei Inoue, Atsuo Kuniba

We construct a new solution $(R,K)$ to the three-dimensional reflection equation, a boundary analogue of the tetrahedron equation. The $R$-operator is the one obtained by Sun, Terashima, Yagi, and the authors in 2024, involving four quantum dilogarithms with arguments in the $q$-Weyl algebra. The new $K$-operator similarly involves ten such quantum dilogarit

Zongyuan Ge, Chenwaner Zhang, Wei Zhou, Hongyu Zeng

Geomagnetic storms (GSTs) driven by solar wind-magnetosphere coupling can severely disrupt technological systems, motivating the need for improved prediction accuracy and longer warning times. In this study, we develop a physics-informed Long Short-Term Memory (LSTM) model that incorporates cosmic-ray flux modulation as an additional precursor signal. As cor

Irene De León, Danel Arias, Manuel Martín-Cordero, María Esperanza Molina

We present a scalable, hardware-aware methodology for extending the Variational Quantum Eigensolver (VQE) to large, realistic Dynamic Portfolio Optimization (DPO) problems. Building on the scaling strategy from our previous work, where we tailored a VQE workflow to both the DPO formulation and the target QPU, we now put forward two significant advances. The

Gete Umbrey, Riken Kaye, Drema Lhamu, Monkhum Khilak

In our study, Darbo's fixed point theorem(DFPT) has been extended and generalized using $\mathbb{H}$-class mappings and the measure of noncompactness. Utilizing this Darbo-type theorem, we provided a solvability result for a system of a $(k,\rho)$-fractional Hilfer integral equations, accompanied by an appropriate example to illustrate the findings.

Jiayu Hu, Beibei Li, Jiangwei Xia, Yanjun Qin

While Vision-Language Models (VLMs) have garnered increasing attention in the AI community due to their promising practical applications, they exhibit persistent hallucination issues, generating outputs misaligned with visual inputs. Recent studies attribute these hallucinations to VLMs' over-reliance on linguistic priors and insufficient visual feature inte

Yafei Wang, Yiming Zhu, Vu Nguyen Ha, Wenjin Wang

This paper studies multi-satellite multi-stream (MSMS) beamspace transmission, where multiple satellites cooperate to form a distributed multiple-input multiple-output (MIMO) system and jointly deliver multiple data streams to multi-antenna user terminals (UTs), and beamspace transmission combines earth-moving beamforming with beam-domain precoding. For the

Daan Beijersbergen, Jérôme Charmet

Affinity-based biosensors have become indispensable in modern diagnostics and health monitoring. While considerable research has focused on optimizing analyte transport and binding kinetics, a fundamental parameter - sample volume - remains largely underexplored in biosensor design. This is critical because biosensor performance depends on the absolute numbe

Ashwin Mohan, Radha S

In order to further investigate the magnetic state of the RAgAl series, the magnetization measurements on the TbAgAl compound from this series have been extended to higher fields of 12 Tesla in the temperature range 2K-300K. The electrical resistivity in the temperature range 2-300K has been measured up to fields of 9 Tesla. The field dependence of magnetiza

Yang Ding, Yizhen Zhang, Xin Lai, Ruihang Chu

Multimodal Large Language Models (MLLMs) have achieved remarkable progress in vision-language tasks yet remain limited in long video understanding due to the limited context window. Consequently, prevailing approaches tend to rely on uniform frame sampling or static pre-selection, which might overlook critical evidence and unable to correct its initial selec

Carmen A. Tachino, Federio J. Gonzalez, Alberto S. Muzas, J. Iñaki Juaristi

In this work, we investigate the relative importance of electronic and phononic energy dissipation during the molecular adsorption of CO on Cu(110). Initial sticking probabilities as a function of impact energy for CO impinging at normal incidence at a surface temperature of 90 K were computed using classical trajectory simulations. To this aim, we use a ful

Sobhan Kazempour, Sichun Sun, Chengye Yu

We study thermodynamic properties and the entanglement island of a black hole in asymptotically safe quantum gravity, analyzing key thermodynamic quantities such as the Hawking temperature, heat capacity, and entropy, as well as the mass-horizon radius relation. Unlike Schwarzschild black holes, the temperature decreases with mass near the evaporation endpoi

Federico J. Gonzalez, Carmen A. Tachino, H. Fabio Busnengo

In this work we investigate the dissociation of CO$_2$ on Cu(110) by performing density functional theory calculations using the vdW-DF2 exchange-correlation functional, with a potential energy surface parameterized using artificial neural networks. We computed quasi-classical trajectory calculations of molecular and dissociative adsorption probabilities as

Tayyab Naseer, M. Sharif

In this article, we are devoted to discuss different compact stars admitting anisotropic interiors in a particular modified theory of gravity. For this purpose, a spherically symmetric metric is adopted to formulate the field equations corresponding to two different $f(\mathcal{R},\mathcal{T},\mathcal{Q})$ models, where $\mathcal{Q}=\mathcal{R}_{\alpha\gamma

Yu Guo, Zhixiang Jin

Characterizing entanglement, including quantifying and distribution of entanglement, which lies at heart of the quantum resource theory, have been investigated extensively ever since Bennett \etal proposed three seminal measures of entanglement in 1996. Up to now, there are numerous measures of entanglement that have been proposed from different point of vie

Cory T. Aitchison, Benjamin Béri

A powerful method for analyzing quantum error-correcting codes is to map them onto classical statistical mechanics models. Such mappings have thus far mostly focused on static codes, possibly subject to repeated syndrome measurements. Recent progress in quantum error correction, however, has prompted new paradigms where codes emerge from stabilizer circuits

Irina Nesterova, Rustem Sirazov, Aleksey Khlyupin

The simulation of fluid flow in real, multiscale porous media remains challenging due to the complexity of nanoscale phenomena and the difficulty of developing upscaling methodologies. In this study, we introduce a multiscale filtration framework based on quasi-static Pore Network Modelling, incorporating the effects of pore blockage resulting from capillary

Thomas Bartz-Beielstein, Eva Bartz, Alexander Hinterleitner, Christoph Leitenmeier

Industrial experimental designs frequently lack optimal space-filling properties, rendering them unrepresentative. This study presents a comprehensive methodology to refine existing designs by enhancing coverage quality while optimizing experimental outcomes. We discuss and analyse variants of the Morris-Mitchell criterion to quantify and improve spatial dis

Amin Hajihasani, Mahmoud Modaresi

Data centers are among the fastest growing electricity consumers and can impose severe voltage drops and feeder losses when connected to weak distribution networks. This paper formulates a techno economic siting problem in which each candidate data center site is mapped to a bus of the distribution network and is assumed to deploy on site renewable generatio

Tariq Ahmad Mir, Marcel Ausloos

The first digit (FD) phenomenon i.e., the significant digits of numbers in large data are often distributed according to a logarithmically decreasing function was first reported by S. Newcomb and then many decades later independently by F. Benford. After its century long neglect the last three decades have seen huge growth in the number of relevant publicati

Thai P. D. Nguyen, Hong T. M. Chu, Kim-Chuan Toh

Comparing time series in a principled manner requires capturing both temporal alignment and distributional similarity of features. Optimal transport (OT) has recently emerged as a powerful tool for this task, but existing OT-based approaches often depend on manually selected balancing parameters and can be computationally intensive. In this work, we introduc

Alexander Koebler, Lukas Kuhn, Ingo Thon, Florian Buettner

In high-stakes domains, small task-specific vision models are crucial due to their low computational requirements and the availability of numerous methods to explain their results. However, these explanations often reveal that the models do not align well with human domain knowledge, relying instead on spurious correlations. This might result in brittle beha

Qi Lai, JunYan Li, Qiang Cai, Lei Wang

Real-time instance segmentation for spinal endoscopy is important for identifying and protecting critical anatomy during surgery, but it is difficult because of the narrow field of view, specular highlights, smoke/bleeding, unclear boundaries, and large scale changes. Deployment is also constrained by limited surgical hardware, so the model must balance accu

Saksham Gupta, Sarthak Mishra, Arshad Ayub, Kamran Farooque

Endotracheal intubation is a critical yet technically demanding procedure, with failure or improper tube placement leading to severe complications. Existing robotic and teleoperated intubation systems primarily focus on airway navigation and do not provide integrated control of endotracheal tube advancement or objective verification of tube depth relative to

Nicola Baglioni, Daniele Bielli, Michele Galli, Gabriele Tartaglino-Mazzucchelli

Auxiliary field techniques have recently gained interest in four-dimensional non-linear electrodynamics and two-dimensional integrable sigma models. In these settings, coupling a suitable ``seed'' theory to auxiliary fields provides a powerful mechanism to generate infinite families of models while preserving key dynamical properties, such as electromagnetic

Rami V. Tabri

Entropically regularized optimal transport between probability measures supported on compact subsets of Euclidean space admits a representation as an information projection under moment inequality constraints. Exploiting this structure, I develop a sieve-based approximation of the Fenchel dual, yielding a sequence of finite-dimensional convex programs whose

Ju. T. Lisica

The basic one in this work is the axiomatic set theory $NBG$ (von Neumann-Bernays-G{\"o}del), which is a first-order theory with its own axioms, including in particular the axiom of choice ${\bf AC}$ and the axiom of regularity ${\bf RA}$. The universal class ${\bf V}$ of all sets in this theory exactly coincides with the class of all founded sets, i.e., suc

A. I. Perminov

This paper presents a new state-of-the-art algorithm for exact $3\times3$ matrix multiplication over general non-commutative rings, achieving a rank-23 scheme with only 58 scalar additions. This improves the previous best additive complexity of 60 additions without a change of basis. The result was discovered through an automated search combining ternary-res

Praveen Kumar Donta, Alaa Saleh, Ying Li, Shubham Vaishnav

Agentic Artificial Intelligence (AI) represents a fundamental shift in the design of intelligent systems, characterized by interconnected components that collectively enable autonomous perception, reasoning, planning, action, and learning. Recent research on agentic AI has largely focused on technical foundations, including system architectures, reasoning an

Suvikranth Gera, Poulami Dutta Roy

A tertiary body near a coalescing binary can imprint its influence on the gravitational waves (GWs) emitted by that binary in the form of center-of-mass (CoM) acceleration. An example of such a scenario is a binary black hole (BBH) merging near a supermassive black hole, which is touted to occur frequently. The limited low-frequency sensitivity of current GW

Deep Sagar, Abhishek Sharma, Arti Kashyap

We present a comprehensive density functional theory (DFT) study of the electronic, magnetic, and topological properties of the layered pnictides EuMnXBi2 (X = Mn, Fe, Co, Zn), focusing in particular on the relatively unexplored Bi-based member of the EuMn2X2 family. Unlike the well-studied As-, Sb-, and P--based analogues, we show that EuMn2Bi2 stabilizes i

Umberto De Ambroggio, Luca Makowiec

We study a model of random weighted uniform spanning trees on the complete graph with $n$ vertices, where each edge is assigned a weight of $n^{1+\gamma}$ with probability $1/n$ and $1$ otherwise. Whenever $\gamma$ is large enough, we prove that the diameter of the resulting tree is typically of order $n^{1/3} \log n$, up to a $\log \log n$ correction. Our a

Vladimir Dragović, Milena Radnović

We solve two long standing open problems, one from probability theory formulated by Malyshev in 1970 and another one from a crossroad of geometry and dynamics, of Darboux from 1879. The Malyshev problem is of finding effective, explicit necessary and sufficient conditions in the closed form to characterize all random walks in the quarter plane with the finit

Wenzhang Du

Closed-loop decision-making systems (e.g., lending, screening, or recidivism risk assessment) often operate under fairness and service constraints while inducing feedback effects: decisions change who appears in the future, yielding non-stationary data and potentially amplifying disparities. We study online learning of a one-dimensional threshold policy from

Zhuoyu Wu, Wenhui Ou, Qiawei Zheng, Jiayan Yang

Motion blur caused by camera or object movement severely degrades image quality and poses challenges for real-time applications such as autonomous driving, UAV perception, and medical imaging. In this paper, a lightweight U-shaped network tailored for real-time deblurring is presented and named RT-Focuser. To balance speed and accuracy, we design three key c

Jing-Jing Ma, Lei Chang, Ming-Yang Wu, Hua Zhou

Helicon plasma sources play a central role in applications ranging from material treatment to space propulsion and fusion, yet the physical processes governing their ignition, transient ionization, and mode evolution remain incompletely understood. Here we develop a self-consistent, fully coupled multiphysics framework that integrates Maxwell equations, elec

Xin Xu

The regularized Barzilai-Borwein (RBB) method represents a promising gradient-based optimization algorithm. In this paper, by splitting the gradient into two parts and analyzing the dynamical system of difference equations governing the ratio of their magnitudes, we establish that the RBB method achieves R-linear convergence for strongly convex quadratic fun

Dongyue Jiang, Lei Qian, Minglei Guo, Qiaoli Hao

We observed comet C/2025 A6 with the Five-hundred-meter Aperture Spherical radio Telescope (FAST) equipped with the ultra-wideband receiver from 2025 October 23 to November 8, and it was the first detection for this comet with FAST.Through trapezoidal fitting of the OH line profiles, we derived the expansion velocities of the water which showed an increase f

Kureha Hamagashira, Miyuki Azuma, Sotaro Shimada

The full-body illusion (FBI) refers to the experience of perceiving a virtual avatar as one's own body. In virtual reality (VR) environments, inducing the FBI has been shown to modulate users' bodily experiences and behavior. Previous studies have demonstrated that embodying avatars with specific characteristics can influence users' actions, largely through

Qi Gao, Wei Chen

The impact of projective lattice symmetry on electronic band structures has attracted significant attention in recent years, particularly in light of growing experimental studies of two-dimensional hexagonal materials in magnetic fields. Yet, most theoretical work to date has focused on the square lattice due to its relative simplicity. In this work, we inve

Kostia Chardonnet, Marc de Visme, Benoît Valiron, Renaud Vilmart

We propose a graphical language that accommodates two monoidal structures: a multiplicative one for pairing and an additional one for branching. In this colored PROP, whether wires in parallel are linked through the multiplicative structure or the additive structure is implicit and determined contextually rather than explicitly through tapes, world annotatio

Dunyuan XU, Xikai Yang, Yaoqian Li, Juzheng Miao

Medical Multi-modal Large Language Models (MLLMs) have shown promising clinical performance. However, their sensitivity to real-world input perturbations, such as imaging artifacts and textual errors, critically undermines their clinical applicability. Systematic analysis of such noise impact on medical MLLMs remains largely unexplored. Furthermore, while se

Shohei Satake, Yoshinori Yamasaki

The generalized Markoff mod $p$ graph is defined via the equation $x^2+y^2+z^2=xyz+\kappa$ over the finite field $\mathbb{F}_p$ of prime order $p$. In this paper, we investigate the topological properties of the graph such as non-planarity, surface embeddability, and the existence of short cycles. Our approach is based on a systematic construction of $K_{3,3

Qin Deng, Alessandro Pigati

We show that non-collapsed $\text{RCD}(K,3)$ spaces without boundary are orbifolds whose topological singularities are locally finite and locally homeomorphic to cones over $\mathbb{RP}^2$, and that the topology of such spaces is stable under non-collapsed Gromov-Hausdorff convergence. We study the notion of non-orientability on these spaces as a key part of

Frédéric Cazals, Antoine Commaret, Louis Goldenberg

A parametric cluster model is a statistical model providing geometric insights onto the points defining a cluster. The {\em spherical cluster model} (SC) approximates a finite point set $P\subset \mathbb{R}^d$ by a sphere $S(c,r)$ as follows. Taking $r$ as a fraction $\eta\in(0,1)$ (hyper-parameter) of the std deviation of distances between the center $c$ an

Junhui Cao, Jinling Wang, Kirill Bazarov, Chenqi Jin

We demonstrate the spontaneous formation of acoustic black holes in exciton-polariton condensates triggered by discontinuous Riemann-type initial conditions. Starting from a quasi-conservative Gross-Pitaevskii model, we show that nonlinear dispersive shock waves naturally generate spatial regions where the local flow velocity exceeds the speed of sound, crea

Rakesh Arora, Hichem Hajaiej, Kanishka Perera

In this work, we show the existence of an unbounded sequence of minimax eigenvalues for the logarithmic $p$-Laplacian via the $\mathbb{Z}_2$-cohomological index of Fadell and Rabinowitz. As an application of these minimax eigenvalues and $p$-logarithmic Sobolev inequality proved in [4], we prove new existence results for nonlocal Dirichlet problems involving

Wei Liang, Ming Zhong

The Wiener path integral framework is proposed to model military combat dynamics by incorporating the neglected stochastic effects to the Lanchester's square law. This framework is applied to evaluate the empirical 3:1 combat rule, which posits that an attacker requires a threefold force superiority to achieve victory. Specifically, the attacker's winning pr

Tal Halevi, Yarden Tzach, Ronit D. Gross, Shalom Rosner

The self-attention mechanism has significantly advanced the field of natural language processing, facilitating the development of advanced language-learning machines. Although its utility is widely acknowledged, the precise mechanisms of self-attention underlying its advanced learning and the quantitative characterization of this learning process remains an

Indra Kumar Banerjee, Sandeep Chatterjee, Biswarup Das, Ujjal Kumar Dey

Neutron stars such as pulsars and magnetars lose angular momentum primarily through electromagnetic dipole radiation, gravitational waves, $r$-mode oscillation, and also affected by fallback accretion processes. However, anomalous spin variations, particularly sudden enhanced spin-down rates, indicate additional spin-down mechanisms. We propose superradiant

Mohsen Amidzadeh

We consider a cellular network equipped with cache-enabled base-stations (BSs) leveraging an orthogonal multipoint multicast (OMPMC) streaming scheme. The network operates in a time-slotted fashion to serve content-requesting users by streaming cached files. The users being unsatisfied by the multicat streaming face a delivery outage, implying that they will

Venkatesh Tentu, Henk Wymeersch, Musa Furkan Keskin, Sauradeep Dey

We investigate distributed multiple-input multiple-output (D-MIMO) integrated sensing and communication (ISAC) systems, in which multiple phase-synchronized access points (APs) jointly serve user equipments (UEs) while cooperatively detecting and estimating multiple static targets. To achieve high-accuracy multi-target estimation, we propose a two-stage sens

Md Fantacher Islam, Emeral Norzagaray, Corneliu Antonescu, Vignesh Subbian

Fungal infections, such as Coccidioidomycosis, Aspergillosis, and Histoplasmosis, represent a growing public health concern in the United States. The rising incidence of these mycoses is linked to climate shifts, demographic changes, and social determinants of health. However, the actual burden of these infections is often underestimated by traditional surve

Elena F. Silkina, Evgeny S. Asmolov, Olga I. Vinogradova

When two reservoirs of a distinct salinity are connected by channels or pores, a fluid flow termed diffusio-osmotic is generated. This article investigates the flow emerging in an uniformly charged long slit whose thickness exceeds the local Debye screening length. Attention is focussed on the role of hydrostatic pressure drop $Δp$ in establishing diffusioos

Debraj Das, Soumendra Lahiri

High dimensional central limit theorems (the CLTs) have been extensively studied in recent years under a variety of sufficient moment conditions connecting the dimension growth rate with the tail decay rate. In this article, we investigate whether the existing moment conditions are also necessary under the independence of the components. We consider four exh

Raphael Yuster

For a digraph $G$, let $f(G)$ be the maximum chromatic number of an acyclic subgraph of $G$. For an $n$-vertex digraph $G$ it is proved that $f(G) \ge n^{5/9-o(1)}s^{-14/9}$ where $s$ is the bipartite independence number of $G$, i.e., the largest $s$ for which there are two disjoint $s$-sets of vertices with no edge between them. This generalizes a result of

Valenitn D. Ivanov

The enormous multiplexity of the WST opens up the possibility to trigger alerts for variable objects - an option that has been reserved so far only for imaging surveys. WST can go further by detecting spectroscopic line profile and line strength variations. I review previous alert-issuing surveys that are limited to imaging, and describe some of the new rese

Ali Lotfi, Adam Carter, Thuan Ha, Mohammad Meysami

Spectral indices such as NDVI have driven vegetation monitoring for decades, yet their design remains largely manual and ad hoc. Their usefulness stems not only from their empirical performance, but also from algebraic forms that remain compact and biologically interpretable. However, the space of possible algebraic expressions relating spectral bands is eff

Chia-Kai Kuo, Qinglin Yang

We study five-point off-shell conformal integrals and the associated half-BPS correlation functions at two loops in the 't Hooft coupling expansion of maximally supersymmetric Yang-Mills theory. We construct a basis of uniform-transcendental (UT) pure integrals spanning six distinct topologies by diagonalizing leading singularities subject to conformal invar

G. D. Alexeev, M. G. Alexeev, C. Alice, A. Amoroso

In 2022, the COMPASS collaboration performed semi-inclusive measurements of deep-inelastic muon-scattering on a transversely polarised deuteron (6LiD) target. From these data, transverse-spin-dependent dihadron asymmetries are extracted using pairs of oppositely charged hadrons. These asymmetries are directly sensitive to the quark transversity distributions

Marc Distel

Quasi-isometry is a measure of how similar two graphs are at `large-scale'. Nguyen, Scott, and Seymour [arXiv:2501.09839] and Hickingbotham [arXiv:2501.10840] independently gave a characterisation of graphs quasi-isometric to graphs of treewidth $k$. In this paper, we give a new characterisation of such graphs. Specifically, we show that such graphs $G$ are

Ying Zhao, Michiel J. van Setten, Anastasiia Kruv, Pietro Rinaudo

Thin-film transistors based on amorphous oxide semiconductors (AOS) are promising candidates for enabling further DRAM scaling and 3D integration, which are critical for advanced computing. Despite extensive research, the charge transport mechanism in these disordered semiconductors remains poorly understood. In this work, we investigate charge transport in

Yiquan Gao, John See

By contrast with the prevailing works of low-light enhancement in natural images and videos, this study copes with the low-illumination quality degradation in anime scenery images to bridge the domain gap. For such an underexplored enhancement task, we first curate images from various sources and construct an unpaired anime scenery dataset with diverse envir

Teng Wang, Xu Feng, Bing-Nan Lu

Nuclear lattice effective field theory (NLEFT) is an efficient \textit{ab initio} tool for solving nuclear many-body systems using the imaginary-time projection technique, where the preparation of trial states is essential for substantially reducing the computational cost required to achieve the desired numerical precision. It has been challenging in forming

Indiwara Nanayakkara, Dehan Jayawickrama, Dasuni Jayawardena, Vijitha R. Herath

Automatic Modulation Classification (AMC) is a vital component in the development of intelligent and adaptive transceivers for future wireless communication systems. Existing statistically-based blind modulation classification methods for Orthogonal Frequency Division Multiplexing (OFDM) often fail to achieve the required accuracy and performance. Consequent

Riccardo Castagna

Finite coherent quantum systems exhibit a nontrivial response to local sources of phase curvature, which cannot be reduced to conventional forces, disorder-induced localization, or simple gap opening. Here we show that, in finite fermionic rings, a localized symmetry-breaking perturbation acts as a source of phase curvature in the many-body Hilbert space, in

M. Al Busaidi, F. Al Ma'Mari, R. Sbiaa

Magnetic skyrmions exhibit particle-like stability and rich dynamical behaviour arising from their topological nature, making them promising building blocks for future spintronic devices. In this work, we investigate the interaction dynamics of two Neel-type skyrmions in an ultrathin ferromagnetic film through a combined analytical and numerical approach. Fu

Run Ling, Ke Cao, Jian Lu, Ao Ma

Multi-subject video generation aims to synthesize videos from textual prompts and multiple reference images, ensuring that each subject preserves natural scale and visual fidelity. However, current methods face two challenges: scale inconsistency, where variations in subject size lead to unnatural generation, and permutation sensitivity, where the order of r

Zheng-Nan Hu, Jin Woo Jang, Zheng-An Yao, Yu-Long Zhou

The inverse power potential $U(r)=r^{-1/s}, 0<s<1$, generates the Boltzmann kernel $B^{s}=|v-v_*|^{1-4s} b_s(\theta)$ with an angular singularity as $\theta\to 0$. Jang-Kepka-Nota-Vel\'azquez (2023) proved the limit $B^{s}\to \frac14|v-v_*|$ as $s\to 0$, as well as weak convergence of solutions based on this kernel convergence. In this work we establish the

Zhen Du, Fan Liu, Jie Yang, Yuanhao Cui

Synthetic aperture radar (SAR) on unmanned aerial vehicles (UAVs) enables high-resolution sensing in low-altitude wireless networks, while requiring reliable uplink data backhaul to ground base stations under dynamic channel conditions. Conventional orthogonal frequency division multiplexing (OFDM)-based SAR systems rely on pilot or deterministic signaling,

Sahana Balasubramanya, Talia Fernos

We present a new notion of non-positively curved groups: the collection of discrete countable groups acting (AU-)acylindrically on finite products of $\delta$-hyperbolic spaces with general type factors and associated subdirect products. This work is inspired by the classical theory of $S$-arithmetic lattices and the flourishing theory of acylindrically hype

Hongjin Wu, Ulrik Brandes

We study the homogeneous Kuramoto model on a graph and the geometry of its underlying optimization landscape $\min_{\boldsymbol \theta \in \mathbb R^n}-\sum_{1\leq i,j\leq n} A_{ij}\cos(\theta_i-\theta_j).$ This problem admits a dual interpretation. On the one hand, it can be viewed as an unconstrained optimization problem, seeking configurations of points o

Jia Su, Zenghao Kong, Fei Kong, Xing Liu

Fluorescent nanodiamonds (FNDs) hosting nitrogen-vacancy (NV) centers have attracted considerable attention for quantum sensing applications, particularly owing to notable advancements achieved in the field of weak magnetic signal detection in recent years. Here, we report a practical quantum-sensing platform for the controlled production and real-time monit

Sachin Pawar, Manoj Apte, Kshitij Jadhav, Girish Keshav Palshikar

Tokenization is the first step in training any Large Language Model (LLM), where the text is split into a sequence of tokens as per the model's fixed vocabulary. This tokenization in LLMs is different from the traditional tokenization in NLP where the text is split into a sequence of "natural" words. In LLMs, a natural word may also be broken into multiple t

Zhixiu Fan

We prove that for log canonical foliations which are birationally bounded by algebraically integrable families, the set of their volumes satisfies the DCC. This answers a special case of a question posed by Cascini, Hacon, and Langer. As a key ingredient, we establish the deformation invariance of relative log canonical volumes for a family of weak semistabl

Koki Numa, Eri Matsuda, Akimitsu Kirikoshi, Junya Otsuki

The heavy-fermion superconductor CeRh2As2 exhibits a non-superconducting phase transition that precedes the emergence of superconductivity. The nature of the corresponding order parameter remains under debate, with competing proposals involving magnetic dipoles or electric quadrupoles. We derive the momentum-dependent multipolar susceptibilities and effectiv

S Akbar Jafari, Hendrik J Bluhm, David P Divincenzo

Increasing the valley splitting in Si-based heterostructures is critical for improving the performance of semiconductor qubits. This paper demonstrates that the two low-energy conduction band valleys are not independent parabolic bands. Instead, they originate from the X-point of the Brillouin zone, where they are interconnected by a degeneracy protected by

Oladiran Johnson Abimbola

The Great Red Spot (GRS) of Jupiter has been observed for over a century, with researchers studying its characteristics and dynamics, including its size, depth, movement, and interactions with its environment. Recently, the f-plane thin-shell asymptotic analysis was used to explain some of the GRS features, but the method failed to capture the observed westw

Bingqiu Chen, Guangxing Li, Haibo Yuan, Maosheng Xiang

Stellar feedback is a crucial mechanism in galactic evolution, as demonstrated by the widespread bubbles observed with JWST. In this study, we combine data from Gaia and LAMOST to obtain a sample of young O-B2 stars with full three-dimensional velocity information. Focusing on the largest known superbubble in the Milky Way, we identify groups of O-B2 stars a

Kongchang Zhou, Tingyu Zhang, Wei Chen, Fang Kong

The problem of combinatorial multi-armed bandits with probabilistically triggered arms (CMAB-T) has been extensively studied. Prior work primarily focuses on either the online setting where an agent learns about the unknown environment through iterative interactions, or the offline setting where a policy is learned solely from logged data. However, each of t

Tao Yang, Xiuying Wang, Hao Liu, Guanzhong Gong

Detection of various lesions in brain MRI is clinically critical, but challenging due to the diversity of lesions and variability in imaging conditions. Current unsupervised learning methods detect anomalies mainly through reconstructing abnormal images into pseudo-healthy images (PHIs) by normal samples learning and then analyzing differences between images

Qianlan Bai, Yuedong Xu, Zhijian Zhou, Xin Wang

Transaction fee plays an important role in determining the priority of transaction processing in public blockchain systems. Owing to the observability of unconfirmed transactions, a strategic user can postpone his transaction broadcasting time and set a fee as low as possible by prying into his mempool that stores them. However, the stochastic mining interva

Yiming Li, Zimu Li, Zi-Wen Liu, Quynh T. Nguyen

Quantum LDPC codes have attracted intense interest due to their advantageous properties for realizing efficient fault-tolerant quantum computing. In particular, sheaf codes represent a novel framework that encompasses all well-known good qLDPC codes with profound underlying mathematics. In this work, we generalize Poincar\'e duality from manifolds to both cl