December 2025 arXiv papers — page 4

Duván Cardona, William Obeng-Denteh, Frederick Opoku

In this paper, we develop boundedness estimates for Fourier integral operators on Fourier Lebesgue spaces when the associated canonical relation is parametrised by a complex phase function. Our result constitutes the complex analogue of those obtained for real canonical relations by Rodino, Nicola, and Cordero. We prove that, under the spatial factorization

Koki Suenaga, Tomohiro Furuta, Satoshi Ono

Technologies for automatically generating work schedules have been extensively studied; however, in long-term care facilities, the conditions vary between facilities, making it essential to interview the managers who create shift schedules to design facility-specific constraint conditions. The proposed method utilizes constraint templates to extract combinat

Shusaku Sasaki, Takunori Ishihara, Hirofumi Kurokawa

Why are interventions with weak evidence still adopted? We study charitable incentives for physical activity in Japan using three linked methods, including a randomized field experiment (N=808), a stakeholder belief survey (local government officials and private-sector employees, N=2,400), and a conjoint experiment on policy choice. Financial incentives incr

Xunyi Zhao, Gengze Zhou, Qi Wu

Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities across a wide range of vision-language tasks. However, their performance as embodied agents, which requires multi-round dialogue spatial reasoning and sequential action prediction, needs further exploration. Our work investigates this potential in the context of Vision-and-Lan

Ruiliang Li

Erd\H{o}s and Lov'asz asked whether there exists a "3-critical" 3-uniform hypergraph in which every vertex has degree at least 7. The original formulation does not specify what 3-critical means, and two non-equivalent notions have appeared in the literature and in later discussions of the problem. In this paper we resolve the question under both interpretati

Daniil Poletaev, Artem Oganov

Accurate crystal structure prediction (CSP) at finite temperatures with quantum anharmonic effects remains challenging but very prominent in systems with lightweight atoms such as superconducting hydrides. In this work, we integrate machine-learned interatomic potentials (MLIPs) with the stochastic self-consistent harmonic approximation (SSCHA) to enable evo

Srija Mukhopadhyay, Sathwik Reddy, Shruthi Muthukumar, Jisun An

Personalized AI agents rely on access to a user's digital footprint, which often includes sensitive data from private emails, chats and purchase histories. Yet this access creates a fundamental societal and privacy risk: systems lacking social-context awareness can unintentionally expose user secrets, threatening digital well-being. We introduce PrivacyBench

Linhao Fan, Hongqiang Fang, Jingyang Dai, Yong Jiang

High-quality reconstruction of Aerosol Optical Depth (AOD) fields is critical for Atmosphere monitoring, yet current models remain constrained by the scarcity of complete training data and a lack of uncertainty quantification.To address these limitations, we propose AODDiff, a probabilistic reconstruction framework based on diffusion-based Bayesian inference

Qiuyi Gu, Yuze Sheng, Jincheng Yu, Jiahao Tang

3D scene graphs have empowered robots with semantic understanding for navigation and planning. However, current functional scene graphs primarily focus on static element detection, lacking the actionable kinematic information required for physical manipulation, particularly regarding articulated objects. Existing approaches for inferring articulation mechani

Mariusz Pietruszka

Understanding how soft matter systems, including biological ones, can develop collective electromagnetic phenomena under external fields at ambient conditions remains a central challenge, as thermal fluctuations are generally expected to suppress long-range organization. Here, we report that hydrated DNA exhibits a reproducible magnetic-field-induced transit

Ratnesh Pathak, Nitesh Kumar Sahu, Pradeep Kumar Sonkar

This study examines the effect of centre-body geometry on the dynamics of an isothermal, non-reacting swirl combustor through computational fluid dynamics (CFD) simulations. Two different central body shapes were considered in a lab-scale combustor configuration, modelled as transient, incompressible flow using the SST k-omega turbulence model. The numerical

Alexandra Suvorikova, Alexey Kroshnin, Dmirijs Lvovs, Vera Mukhina

The analysis of the interaction matrix between two distinct sets is essential across diverse fields, from pharmacovigilance to transcriptomics. Not all interactions are equally informative: a marker gene associated with a few specific biological processes is more informative than a highly expressed non-specific gene associated with most observed processes. I

Yanan Long

Multilingual language models achieve strong aggregate performance yet often behave unpredictably across languages, scripts, and cultures. We argue that mechanistic explanations for such models should satisfy a \emph{causal} standard: claims must survive causal interventions and must \emph{cross-reference} across environments that perturb surface form while p

Zongyue Teng, Jun Yan, Dandan Liu, Panpan Zhang

Selecting the number of communities is a fundamental challenge in network clustering. The silhouette score offers an intuitive, model-free criterion that balances within-cluster cohesion and between-cluster separation. Albeit its widespread use in clustering analysis, its performance in network-based community detection remains insufficiently characterized.

Jun-Chao Liang, Yin-Bi Li, A-Li Luo, Fang Zuo

To enhance the efficiency, scalability, and cross-survey applicability of stellar parameter inference in large spectroscopic datasets, we present a modular, parallelized Python framework with automated error estimation, built on the LAMOST Atmospheric Parameter Pipeline (LASP) originally implemented in IDL. Rather than a direct code translation, this framewo

Arunabha Das, Paranjoy Chaki, Priya Ghosh, Ujjwal Sen

We investigate the quantum Mpemba effect in a dissipative Dicke model, which consists of a spin-1/2 ensemble coupled to a bosonic mode, which in turn is coupled to a bosonic bath. We derive a sufficient criterion for occurrence of the quantum Mpemba effect, characterized by quantum coherence, in this model. We introduce the phenomenon of role reversal in the

Ruiyang Zhang, Zhiyong Zhang, Zengxuan Huang, Yong Zhou

In this paper, we present a Time Projection Chamber (TPC) system for low-background beta radiation measurements. The system consists of a TPC with two-dimensional-strip readout Micromegas and an anti-coincidence detector with readout pads for cosmic ray veto. The detector system utilize an AGET-based waveform sampling system for data acquisition. The beta de

Sandip Maiti, Debasish Banerjee, Shailesh Chandrasekharan, Marina K. Marinkovic

We explore the phase diagram of a lattice fermion model that exhibits three distinct phases: a massless fermion (MF) phase; a massive fermion phase with spontaneous symmetry breaking (SSB) induced by a fermion bilinear condensate; and a massive fermion phase with symmetric mass generation (SMG). Using the fermion-bag Monte Carlo method on large cubical latti

Helene Cyris, Joanna Janczewska, Nils Waterstraat

We obtain novel criteria for the existence of local bifurcation for periodic solutions of Hamiltonian systems by a comparison principle of the spectral flow. Our method allows to find the appearance of new solutions by a simple inspection of the coefficients of the system.

Marko Jojic, Nebojsa Jojic

We present GenZ, a hybrid model that bridges foundational models and statistical modeling through interpretable semantic features. While large language models possess broad domain knowledge, they often fail to capture dataset-specific patterns critical for prediction tasks. Our approach addresses this by discovering semantic feature descriptions through an i

Marcela Cárdenas

These lecture notes are a contribution to the proceedings of the school "Geometric, Algebraic and Topological Methods for Quantum Field Theory", held in Villa de Leyva, Colombia, from 31st of July to 9th of August 2023. Its intention is to put together several basic tools of classical integrability and contrast them with those available in the formulation of

Ádám Sagmeister, Konrad J. Swanepoel

We consider the problem of finding the maximum number $e_d(n)$ of pairs of touching circles in a packing of $n$ congruent circles of diameter $d$ in the hyperbolic plane of curvature $-1$. In the Euclidean plane, the maximum comes from a spiral construction of the tiling of the plane with equilateral triangles (Harborth 1974), with a similar result in the hy

Xinloong Han, Jun Zhan, Jiangping Hu, Fu-chun Zhang

We comprehensively study the unconventional pairing and collective modes in the multiband kagome superconductors AV$_3$Sb$_5$ (A=$\mathrm{K},\mathrm{Cs},\mathrm{Rb}$). By solving gap equations at zero temperature, we identify a transition from normal $s++/s\pm$-wave pairing to time-reversal symmetry (TRS) breaking pairing with a variation of inter-pocket int

Michiko Shimokawa, Lucas Goehring, Akie Kinoshita, Ludovic Pauchard

Local variations in surface tension can induce complex fracture dynamics in thin interfacial films. Here, we investigate the fracture patterns that emerge when a localized surface-tension perturbation is applied to a sumi film supported on a water-glycerol subphase. Sumi is a traditional Japanese carbon black ink, and this process, referred to as sumi-wari,

Yujin Kim

The rapid proliferation of low Earth orbit (LEO) satellite constellations has introduced a new class of radio frequency interference (RFI) that poses a fundamental challenge to modern radio astronomy. In particular, unintended electromagnetic radiation emitted by satellite electronics exhibits strong temporal variability and weak spectral regularity, limitin

Emmanuel Fashae, Michael Burke, Leimin Tian, Lingheng Meng

Robotic systems for household object rearrangement often rely on latent preference models inferred from human demonstrations. While effective at prediction, these models offer limited insight into the interpretable factors that guide human decisions. We introduce an explicit formulation of object arrangement preferences along four interpretable constructs: s

Mrityunjoy Ghosh, Ali Hyder

In this article, we study higher-order Bol's inequality for radial normal solutions to a singular Liouville equation. By applying these inequalities along with compactness arguments, we derive necessary and sufficient conditions for the existence of radial normal solutions to a singular $Q$-curvature problem. Moreover, under suitable assumptions on the $Q$-c

Raul D. Steleac, Mohan Sridharan, David Abel

Temporally extended actions improve the ability to explore and plan in single-agent settings. In multi-agent settings, the exponential growth of the joint state space with the number of agents makes coordinated behaviours even more valuable. Yet, this same exponential growth renders the design of multi-agent options particularly challenging. Existing multi-a

Jason Armitage, Rico Sennnrich

Cross-modal systems trained on 2D visual inputs are presented with a dimensional shift when processing 3D scenes. An in-scene camera bridges the dimensionality gap but requires learning a control module. We introduce a new method that improves multivariate mutual information estimates by regret minimisation with derivative-free optimisation. Our algorithm en

Malvina Nissim, Viviana Patti, Beatrice Savoldi

As Natural Language Processing (NLP) systems become more pervasive, integrating ethical considerations into NLP education has become essential. However, this presents inherent challenges in curriculum development: the field's rapid evolution from both academia and industry, and the need to foster critical thinking beyond traditional technical training. We in

Yuzhen Chen, Bin Yao

Index structures are fundamental for efficient query processing on large-scale datasets. Learned indexes model the indexing process as a prediction problem to overcome the inherent trade-offs of traditional indexes. However, most existing learned indexes optimize only for limited objectives like query latency or space usage, neglecting other practical evalua

Snigdhadev Chakraborty, Mukul Sagar, Atanu Ghosh, Krishna Kumari Swain

Accessing the properties of a plant cell interior non-invasively is difficult due to the presence of a cell wall. Nanoparticles larger than 5 nm cannot be readily phagocytosed inside the cell like animal cells. It is here that we realise that Tradescantia zebrina plant cells have prismatic forms of calcium oxalate crystals present inside them naturally. Thes

Chen-Yang Wang, Jing-Ping Xu, Ce Wang, Ya-Ping Yang

Floquet engineering offers an unparalleled platform for realizing novel non-equilibrium topological phases. However, the unique structure of Floquet systems, which includes multiple quasienergy gaps, poses a significant challenge to classification using conventional analytical methods. We propose a novel unsupervised machine learning framework that employs a

Yinhe Peng

We introduce a variant of the Kurepa family. We then use one such family to construct a ccc indestructible property associated with a complete coherent Suslin tree $S$. Moreover, in every ccc forcing extension that preserves Suslin of $S$, forcing with $S$ induces a strong negative partition relation.

Shulun Chen, Runlong Zhou, Zihan Zhang, Maryam Fazel

Aligning large language models (LLMs) with human preferences has proven effective for enhancing model capabilities, yet standard preference modeling using the Bradley-Terry model assumes transitivity, overlooking the inherent complexity of human population preferences. Nash learning from human feedback (NLHF) addresses this by framing non-transitive preferen

Ivan Novak

In this article, we study how to compute the number of $K$-rational points with a given $j$-invariant on an arbitrary modular curve. As an application, for each positive integer $n$, we determine the list of possible numbers of cyclic $n$-isogenies an elliptic curve over some number field can admit. Similarly, for an odd prime power $p^k$, we calculate the p

Boyao Li, Qinwei He, Boao Zhang, Xiaopeng Yuan

Wireless powered integrated sensing and communication (ISAC) faces a fundamental tradeoff between energy supply, communication throughput, and sensing accuracy. This paper investigates a wireless powered ISAC system with target localization requirements, where users harvest energy from wireless power transfer (WPT) and then conduct ISAC transmissions in a ti

Wanyun Chen, Chih-Ting Lu, Hanxin Shen

The dark sector may possess a rich structure yet to be uncovered, and a QCD-like dark sector with GeV-scale dark hadrons can yield novel signatures at the Large Hadron Collider (LHC). In this work, we focus on a light singlet pseudoscalar mediator that connects the QCD-like dark sector to the Standard Model (SM) sector via the Higgs portal. Notably, when the

Mohammed Sardar, Małgorzata J. Zimoń, Samuel Draycott, Alistair Revell

We investigate the statistical accuracy of temporally interpolated spatiotemporal flow sequences between sparse, decorrelated snapshots of turbulent flow fields using conditional Denoising Diffusion Probabilistic Models (DDPMs). The developed method is presented as a proof-of-concept generative surrogate for reconstructing coherent turbulent dynamics between

Roberto Castorrini, Théophile Dolmaire

We consider a system of four one-dimensional inelastic hard spheres evolving on the real line $\mathbb{R}$, and colliding according to a scattering law characterized by a fixed restitution coefficient $r$. We study the possible orders of collisions when the inelastic collapse occurs, relying on the so-called $\mathfrak{b}$-to-$\mathfrak{b}$ mapping, a two-di

A. Mironov, A. Morozov, A. Popolitov

We consider eigenfunctions of many-body system Hamiltonians associated with generalized (a-twisted) Cherednik operators used in construction of other Hamiltonians: those arising from commutative subalgebras of the Ding-Iohara-Miki (DIM) algebra. The simplest example of these eigenfunctions is provided by non-symmetric Macdonald polynomials, while generally t

Bence Bolgár, András Millinghoffer, Péter Antal

Precise probabilistic information about drug-target interaction (DTI) predictions is vital for understanding limitations and boosting predictive performance. Gaussian processes (GP) offer a scalable framework to integrate state-of-the-art DTI representations and Bayesian inference, enabling novel operations, such as Bayesian classification with rejection, to

Federico Cornalba, Julian Fischer, Erika Maringová Kokavcová

The thin-film equation $\partial_t u = -\nabla \cdot (u^n \nabla \Delta u)$ describes the evolution of the height $u=u(x,t)\geq 0$ of a viscous thin liquid film spreading on a flat solid surface. We prove H\"older continuity of energy-dissipating weak solutions to the thin-film equation in the physically most relevant case of two spatial dimensions $d=2$. Wh

Yahya Ladghami, Taoufik Ouali

In this paper, based on the Anti-de Sitter/Conformal Field Theory (AdS/CFT) correspondence, we highlight the fundamental role of the holographic central charge in connecting the boundary theory to quantum information, black hole thermodynamics, and the nature of gravity in the bulk. We establish that the large central charge of the boundary conformal field t

Nalin Dhiman

\FANOS{} is a PyTorch optimizer that augments RMS-preconditioned momentum with a scalar feedback controller over update energy. The public reference implementation stores momentum in parameter-update units, applies a non-negative thermostat damping coefficient, supports diagonal, factored, and raw-gradient preconditioning, and exposes diagnostics intended fo

Kingshuk Panja, Rajesh Singh

Dry active matter systems are well-known to exhibit Motility-Induced Phase Separation (MIPS). However, in wet active systems, attractive hydrodynamic interactions mediated by active particles stalled at a boundary can introduce complementary mechanisms for aggregation. In the work of Caciagli et al. (PRL 125, 068001, 2020), it was shown that the attractive h

Yuan Gao, Guangjin Pan, Zhiyong Zhong, Zhengyu Jin

With the integration of cellular networks in vertical industries that demand precise location information, such as vehicle-to-everything (V2X), public safety, and Industrial Internet of Things (IIoT), positioning has become an imperative component for future wireless networks. By exploiting a wider spectrum, multiple antennas and flexible architectures, cell

Sayantan Choudhury

In this work, we compute quantum discord between two causally independent areas in $3+1$ dimensions global de Sitter Axiverse to investigate the signs of quantum entanglement. For this goal, we study a bipartite quantum field theoretic setting driven by an Axiverse that arises from the compactification of Type IIB strings on a Calabi-Yau three fold. We consi

Sabrina Herbst, Ivona Brandić, Adrián Pérez-Salinas

Sampling tasks have been successful in establishing quantum advantages both in theory and experiments. This has fueled the use of quantum computers for generative modeling to create samples following the probability distribution underlying a given dataset. In particular, the potential to build generative models on classically hard distributions would immedia

Amaresh Mahato, Sampad Das, Manasi Mandal

In this article, we define the concept of an $S$-$k$-irreducible ideal and $S$-$k$-maximal ideal in a commutative semiring. We also establish several results concerning $S$-$k$-primary ideals and prove the existence theorem and the $S$-version of the uniqueness theorem using localization, for $S$-$k$-primary decompositions. Also we show that the $S$-radical

Yongteng Gu, Xiangdi Huang

In 1871, Saint-Venant introduced the shallow water equations. Since then, the global classical solutions for arbitrary large initial data of the multi-dimensional viscous Saint-Venant system have remained a well-known open problem. It was only recently that [Huang-Meng-Zhang, http:arXiv:2512.15029, 2025], under the assumption of radial symmetry, first proved

Madhuri Mukhopadhyay

Through periodic Training we can gradually buildup a reproducible responses in a disordered system where plasticity dominates over elasticity as is known in classical amorphous materials and soft matter 1, 6. Here we show that a similar concept can be extended to disordered quantum systems. Periodic electrical or mechanical driving of a disordered quantum-do

Rongge Xu, Hui Dai, Yiming Fu, Jiedong Jiang

While large language models (LLMs) have demonstrated impressive capabilities in formal theorem proving, current benchmarks fail to adequately measure library-grounded abstraction -- the ability to reason with high-level interfaces and reusable structures central to modern mathematics and software engineering. We introduce LeanCat, a challenging benchmark com

Daniel Wysocki

This PhD Thesis consists of two parts. The first part focuses on novel algebraic and geometric approaches to the classification problem of coboundary Lie bialgebras up to Lie algebra automorphisms. More specifically, Grassmann, graded algebra and algebraic invariant techniques are discussed. Using these algebraic methods, equivalence classes of r-matrices fo

Andrew Tinits, Stephen Mann

The Noise2Noise method allows for training machine learning-based denoisers with pairs of input and target images where both the input and target can be noisy. This removes the need for training with clean target images, which can be difficult to obtain. However, Noise2Noise training has a major limitation: nonlinear functions applied to the noisy targets wi

Shota Suzuki, Satoshi Ono

Neural architecture search (NAS), which automates the architectural design process of deep neural networks (DNN), has attracted increasing attention. Multimodal DNNs that necessitate feature fusion from multiple modalities benefit from NAS due to their structural complexity; however, constructing an architecture for multimodal DNNs through NAS requires a sub

Takeru Kusakabe, Yudai Hirose, Mashiho Mukaida, Satoshi Ono

Deep neural networks (DNNs) remain vulnerable to adversarial attacks that cause misclassification when specific perturbations are added to input images. This vulnerability also threatens the reliability of DNN-based monocular depth estimation (MDE) models, making robustness enhancement a critical need in practical applications. To validate the vulnerability

Kuankuan Luo, Wei Xiao, Chunping Zhong

Let $ G $ be a connected Lie group with real Lie algebra $ \mathfrak{g}$. Suppose $G$ is also a complex manifold. We obtain explicit holomorphic sectional and bisectional curvature formulas of left-invariant strongly pseudoconvex complex Finsler metrics $F$ on $G$ in terms of the complex Lie algebra $\mathfrak{g}^{1,0}$; we also obtain a necessary and suffic

Arseny Pantsialei

We solve the static isoperimetric problem underlying the Mandelstam-Tamm bound. Among one-dimensional confining potentials with a fixed spectral gap, we prove that the harmonic trap is the unique maximizer of the ground-state position variance. As a consequence, we obtain a sharp geometric quantum speed-limit bound on the position-position component of the q

Sayan Pal

Let $k$ be a field with $\text{char}(k)\neq 2$. We prove that all maximal flags of composition algebras over $k$, appear as the $k$-rational $Sp_{6}$-orbits in a Zariski-dense $Sp_{6}$-invariant subset $V^{ss}\subset V=\wedge^{3}V_{6}$, where $V_{6}$ is the standard $6$-dimensional irreducible representation of $Sp_{6}$. This gives an arithmetic interpretati

Zhixu Wang, Jiacheng Yao, Wei Xu, Wei Shi

To overcome inherent limitations of analog signals in over-the-air computation (AirComp), this letter proposes a two's complement-based coding scheme for the AirComp implementation with compatible digital modulations. Specifically, quantized discrete values are encoded into binary sequences using the two's complement and transmitted over multiple subcarriers

Yunkun Zhao, Xiaoliang Zhang

This study presents the design, simulation, and experimental validation of a dual-tuned concentric multimodal surface coil for 7T 1H/31P magnetic resonance spectroscopic imaging (MRSI), developed to significantly enhance 31P B1 efficiency while improving 1H performance. The coil architecture utilizes two interleaved sets of three concentric loop resonators.

Benedikt Fluhr

Group convolutional layers with respect to some group $G$ are modeled by convolutions or cross-correlations with a filter, and they provide the fundamental building block for group convolutional neural networks. For entirely unconstrained filters and $G$ a non-abelian group, any hidden layer of such a network requires as many nodes as vertices in a fine enou

Roberto Baldacci, Fabio Ciccarelli, Stefano Coniglio, Valerio Dose

We study approximation algorithms for the Bin Packing Problem with Setups (BPPS), a generalization of the classical Bin Packing Problem (BPP) in which items are partitioned into classes and activating a class in a bin consumes a setup weight and incurs a setup cost. We show that direct adaptations of Next Fit (NF), First Fit (FF), Best Fit (BF), and Worst Fi

Toan Trong Dao, Hoang Thanh Nguyen

Extended admissible groups belong to a particular class of graphs of groups that admit a decomposition generalizing those of non-geometric 3-manifold groups and Croke-Kleiner admissible groups. In this paper, we study several coarse-geometric aspects of extended admissible groups. We show that changing the gluing edge isomorphisms does not affect the quasi-i

Happy Gery Pangestu, Andi Prademon Yunus, Siti Khomsah

Neural Style Transfer (NST) provides a computational framework for the digital preservation and generative exploration of Indonesian batik motifs; however, existing approaches remain largely centered on VGG-based architectures whose strong stylistic expressiveness comes at the cost of high computational and memory demands, that limits practical deployment in

Sayan Pal

Let $k$ be a field with characteristic different from $2$. In this paper, we describe the $k$-rational orbit spaces in some irreducible prehomogeneous vector spaces $(G,V)$ over $k$, where $G$ is a connected reductive algebraic group defined over $k$ and $V$ is an irreducible rational representation of $G$ with a Zariski dense open orbit. We parametrize all

Ranfang Zheng, Zheyu Lin, Xu Kong, Dezheng Meng

We propose the Transformer-based Tidal disruption events (TDE) Classifier (\texttt{TTC}), specifically designed to operate effectively with both real-time alert streams and archival data of the Wide Field Survey Telescope (WFST). It aims to minimize the reliance on external catalogs and find TDE candidates from pure light curves, which is more suitable for f

Jan Lukas Igelbrink, Charline Smadi, Anton Wakolbinger

Muller's ratchet, in its prototype version, models a haploid, asexual population whose size~$N$ is constant over the generations. Slightly deleterious mutations are acquired along the lineages at a constant rate, and individuals carrying less mutations have a selective advantage. In the classical variant, an individual's selective advantage is proportional t

Zeray Hagos Gebrezabher

The phase reduction technique is essential for studying rhythmic phenomena across various scientific fields. It allows the complex dynamics of high-dimensional oscillatory systems to be expressed by a single phase variable. This paper provides a detailed review and synthesis of phase reduction with two main goals. First, we develop a solid geometric framewor

A. D. Berezner, V. A. Fedorov, N. S. Perov, G. V. Grigoriev

In this study, novel exact solutions of the Duffing equation with their phase portraits have been proposed and reasoned. It is shown that phase trajectories are initially elliptical and become distorted in the unstable area within the growth of the variable parameter. Instability criteria of identified solutions have been determined together with the Fourier

Anas K. Saeed, Mahmoud M. Salim, Ali Arshad Nasir, Ali H. Muqaibel

Reconfigurable intelligent surfaces (RISs) mounted on unmanned aerial vehicles (UAVs) can reshape wireless propagation on-demand. However, their performance is sensitive to UAV jitter and cascaded channel uncertainty. This paper investigates a downlink multiple-input single-output UAV-mounted RIS system in which a ground multiple-antenna base station (BS) se

Mohammad Zia Ur Rehman, Velpuru Navya, Sanskar, Shuja Uddin Qureshi

Detecting depression from social media text is still a challenging task. This is due to different language styles, informal expression, and the lack of annotated data in many languages. To tackle these issues, we propose, Semi-SMDNet, a strong Semi-Supervised Multilingual Depression detection Network. It combines teacher-student pseudo-labelling, ensemble le

E. T. Akhmedov, D. V. Diakonov, V. I. Lapushkin, D. I. Sadekov

We re-examine the Klein paradox from a many-particle perspective in quantum field theory. Specifically, we compute the expectation value of the particle current induced by a sufficiently strong step-like electric potential in 1+1 dimensions. First, for a constant (eternal) potential, we calculate the current for different Fock space ground states correspondi

A. Barletta

The classical Prats' problem of flow instability in a horizontal porous channel saturated by a fluid subject to a buoyancy force is reconsidered. In the original formulation, the driving buoyancy force results from thermal diffusion. This study, however, substitutes thermal diffusion with mass diffusion. Furthermore, the usual scheme of mass diffusion is ext

Nadjemat El Houda Issaad, Ismail Lotfi, Mohamed Senouci, Zekri Lougmiri

Rural healthcare faces numerous challenges, including limited access to specialized medical services and diagnostic equipment, which delays patient care. Enhancing the ability to transmit medical images and data from rural areas to urban hospitals via wireless networks is critical. However, bandwidth limitations, unreliable networks, and concerns over data s

Nam Phuong Tran, Andi Nika, Goran Radanovic, Long Tran-Thanh

We investigate robustness to strong data corruption in offline sparse reinforcement learning (RL). In our setting, an adversary may arbitrarily perturb a fraction of the collected trajectories from a high-dimensional but sparse Markov decision process, and our goal is to estimate a near optimal policy. The main challenge is that, in the high-dimensional regi

Yutong Cai, Hua Wang

Autonomous taxi services represent a transformative advancement in urban mobility, offering safety, efficiency, and round-the-clock operations. While existing literature has explored user acceptance of autonomous taxis through stated preference experiments and hypothetical scenarios, few studies have investigated actual user behavior based on operational AV

Karthik Dharmarajan, Wenlong Huang, Jiajun Wu, Li Fei-Fei

Generative video modeling has emerged as a compelling tool to zero-shot reason about plausible physical interactions for open-world manipulation. Yet, it remains a challenge to translate such human-led motions into the low-level actions demanded by robotic systems. We observe that given an initial image and task instruction, these models excel at synthesizin

Gug Young Kim, Mi Jin Lee, Seung-Woo Son

Synchronization systems with effective inertia, such as power grid networks and coupled electromechanical oscillators, are commonly modeled by the second-order Kuramoto model. In the forward process, numerical simulations exhibit a staircase-like growth of global synchrony, reflecting temporal oscillations induced by secondary synchronized clusters of whirli

Peng Zhang, Chen-Wei Wang, Zheng-Hang Yu, Ren-Zhou Gui

The increasing data volume of high-energy space monitors necessitates real-time, automated transient classification for multi-messenger follow-up. Conventional methods rely on empirical features like hardness ratios and reliable localization, which are not always precisely available during early detection. We developed the Lightweight Unified Neural Classifi

Ankit Dhiman, Srinath R, Jaswanth Reddy, Lokesh R Boregowda

3D Gaussian Splatting (3DGS) and Neural Radiance Fields (NeRF) have advanced novel-view synthesis. Recent methods extend multi-view 2D segmentation to 3D, enabling instance/semantic segmentation for better scene understanding. A key challenge is the inconsistency of 2D instance labels across views, leading to poor 3D predictions. Existing methods use a two-s

Guorui Zhou, Honghui Bao, Jiaming Huang, Jiaxin Deng

While the OneRec series has successfully unified the fragmented recommendation pipeline into an end-to-end generative framework, a significant gap remains between recommendation systems and general intelligence. Constrained by isolated data, they operate as domain specialists-proficient in pattern matching but lacking world knowledge, reasoning capabilities,

D. Jiménez-Flores, A. Rodríguez-Rivas, J. M. Romero-Enrique

In this paper, we report a Brownian dynamics simulation of the mobility-induced phase separation which occurs in a two-dimensional binary mixture of active soft Brownian particles, whose interactions are modeled by non-additive Weeks-Chandler-Andersen potentials inspired in Lennard-Jones potentials used for glass-forming passive mixtures. The analysis of str

E. Emanuelli, F. Vannini, M. Hoelzl, E. Nardon

The transition of the Divertor Tokamak Test (DTT) facility from its initial commissioning phase (Day-0, plasma current $I_{p}=2$ MA) to the full power scenario ($I_{p}=5.5$ MA) introduces a critical shift in the dynamics of runaway electrons (REs) generation. While previous predictive studies of the low-current scenario indicated a robust safety margin again

Sascha Mücke, Thore Gerlach, Nico Piatkowski

Quantum annealers can solve QUBO problems efficiently but struggle with continuous optimization tasks like regression due to their discrete nature. We introduce Quadratic Continuous Quantum Optimization (QCQO), an anytime algorithm that approximates solutions to unconstrained quadratic programs via a sequence of QUBO instances. Rather than encoding real vari

Mohit Kumar, Sayan Ghosh, Gourab Roy, Ekta Kushwaha

Here we demonstrate the magnetocaloric effect (MCE) of a 4d-4f correlated system, namely Ba3RRu2O9 (R= Ho, Gd, Tb, Nd). The compound Ba3HoRu2O9 antiferromagnetically orders at 50 K where both the Ho and Ru-moments order, followed by another phase transition ~ 10 K. Whereas, the compound Ba3GdRu2O9 and Ba3TbRu2O9 orders at 14.5 and 10.5 K respectively, where

Yutong Wang, Yunxiang Xiao, Yonglin Tian, Junyong Li

Competitive access to modern observatories has intensified as proposal volumes outpace available telescope time, making timely, consistent, and transparent peer review a critical bottleneck for the advancement of astronomy. Automating parts of this process is therefore both scientifically significant and operationally necessary to ensure fair allocation and

Sohan Kumar Jha

With an intent to examine the combined effect of non-linear electrodynamics (NED) and dark matter (DM), we obtain a static and spherically symmetric solution with the black hole (BH) magnetically charged and immersed in the Hernquist DM halo (MHDM). The position of the event horizon $r_h$ and the critical impact parameter $b_m$ are then probed to gauge the e

Arka Ghosh, Sushmita Saha, Alestin Mawrie

We develop a fully quantum-mechanical theory of negative magnetoresistance in multi-Weyl semimetals in the ${\bf E}\parallel{\bf B}$ configuration, where the chiral anomaly is activated. The magnetotransport response is governed by Landau quantization and the emergence of multiple chiral Landau levels associated with higher-order Weyl nodes. These anomaly-ac

Panchugopal Bikram, Hariharan G, Sudipta Kundu, Diptesh Saha

In this article, we establish maximal inequalities and deduce ergodic theorems for state-preserving actions of amenable, locally compact, second-countable groups on tracial non-commutative $L^1$-spaces. As a further consequence, in combination with the Neveu decomposition, we obtain a stochastic ergodic theorem for amenable group actions.

Wenxue Li, Xiangzhou Liu, Yuxuan Li, Yilun Jin

Effective communication is essential in distributed training, with predictability being one of its most significant characteristics. However, existing studies primarily focus on exploiting predictability through online profiling for runtime optimization, without a systematic understanding of it. In this work, we aim to systematically formulate communication

Illya Plotnikov, Alexis P. Rouillard, Athanasios Kouloumvakos, Immanuel Jebaraj

Powerful solar eruptions are known to produce fast and wide shock waves in the solar corona and inner heliosphere. The relationship between the coronal shock waves, solar energetic particles and different types of radio emission is a subject of long-lasting research activity. In this work, we perform a case study of 31 December 2023 eruption that occurred ne

Zhijian Wang, Xingbai Xu, Tuo Liu

This paper develops a quasi-maximum likelihood estimator for genuinely unbalanced dynamic network panel data models with individual fixed effects. We propose a model that accommodates contemporaneous and lagged network spillovers, temporal dependence, and a listing effect that activates upon a unit's first appearance in the panel. We establish the consistenc

Tim J. Boonen, Xinyue Fan, Zixiao Quan

Machine learning improves predictive accuracy in insurance pricing but exacerbates trade-offs between competing fairness criteria across different discrimination measures, challenging regulators and insurers to reconcile profitability with equitable outcomes. While existing fairness-aware models offer partial solutions under GLM and XGBoost estimation method

Vishwa Dewage, Robert Fulsche, Gestur Ólafsson

We investigate the structure of the commutative Banach algebra formed as the direct sum of integrable radial functions on the disc and the radial operators on the Bergman space, endowed with the convolution from quantum harmonic analysis as the product. In particular, we study the Gelfand theory of this algebra and discuss certain properties of the appropria

Roberto Capecelatro, Marco Marciani, Gabriele Campagnano, Roberta Citro

We investigate the electronic transport properties of a superconductor-quantum dot-superconductor Josephson junction coupled to a ferromagnetic metal reservoir in the presence of an external magnetic field. The device is described by an effective non-Hermitian Hamiltonian, whose complex eigenvalues encode the energy (real part) and the broadening (imaginary

Debankan Sannamoth, Kristine Boone, Arnaud Carignan-Dugas, Akel Hashim

Accurate benchmarking of quantum gates is crucial for understanding and enhancing the performance of quantum hardware. A standard method for this is interleaved benchmarking, a technique which estimates the error on an interleaved target gate by comparing cumulative error rates of randomized sequences implemented with the interleaved gate and without it. In

Shan Hu

In $\mathcal{N}=4$ super-Yang-Mills theory with gauge group $G$ spontaneously broken to a subgroup $H$, S-duality requires that the BPS monopole spectrum organizes into the same representation as W-bosons in the dual theory, where $G^{\vee}$ is broken to $H^{\vee}$. The expectation has been extensively verified in the maximally broken phase $G\to U(1)^r$. He

Xiang Liu, Yimin Zhou, Jinxiang Wang, Yujun Huang

The recent advent of 3D Gaussian Splatting (3DGS) has marked a significant breakthrough in real-time novel view synthesis. However, the rapid proliferation of 3DGS-based algorithms has created a pressing need for standardized and comprehensive evaluation tools, especially for compression task. Existing benchmarks often lack the specific metrics necessary to