October 2025 arXiv papers — page 77

Denise Assafrão, Faizuddin Ahmed, Edilberto O. Silva

We develop a unified, single-scale description of thermodynamics and quantum oscillations in electronic systems with a uniform areal density of screw dislocations under a uniform magnetic field. A single tunable gap, $\hbar|\omega_{eff}|$ with $\omega_{eff}=\omega_{c}+\omega_{cl}$, organizes all equilibrium observables obtained from a compact harmonic-oscill

Sahar Maleki, Reza Lashgari, Mahdi Aliyari Shoorehdeli, Mohammad Komareji

Local field potentials (LFPs) have been demonstrated to be an important measurement to study the activity of a local population of neurons. The response tunings of LFPs have been mostly reported as weaker and broader than spike tunings. Therefore, selecting optimized tuning methods is essential for appropriately evaluating the LFP responses and comparing the

M. J. Maureira, J. E. Pineda, H. B. Liu, P. Caselli

We present high-resolution (~7.5 au) ALMA observations at 1.3 and 3 mm of 16 disks around Class 0/I protostars across multiple star-forming regions and a variety of multiplicities, showing a range of disk sizes (~2-100 au) and including circumbinary disks (CBDs) in binaries with separations <100 au. The disk properties show similarities to Class II disks, in

Hrittik Roy, Søren Hauberg, Nicholas Krämer

This paper argues that the method of least squares has significant unfulfilled potential in modern machine learning, far beyond merely being a tool for fitting linear models. To release its potential, we derive custom gradients that transform the solver into a differentiable operator, like a neural network layer, enabling many diverse applications. Empirical

Yohan Mandin--Hublé

We give a new definition of a universal finite type invariant of three-dimensional oriented rational homology spheres which counts configurations of trivalent graphs in such manifolds. Kontsevich introduced this invariant following Witten's study of the perturbative expansion of the Chern-Simons theory, using parallelizations of three-manifolds. In this arti

Yiqian Yang, Tian Lan, Qianghuai Jia, Li Zhu

Effective deep search agents must not only access open-domain and domain-specific knowledge but also apply complex rules-such as legal clauses, medical manuals and tariff rules. These rules often feature vague boundaries and implicit logic relationships, making precise application challenging for agents. However, this critical capability is largely overlooke

Tatsuru Kikuchi

This paper develops a continuous functional framework for analyzing contagion dynamics in financial networks, extending the Navier-Stokes-based approach to network-structured spatial processes. We model financial distress propagation as a diffusion process on weighted networks, deriving a network diffusion equation from first principles that predicts contagi

Xavier Pritchard, Matthew Starbuck, Wingfung Leung

The Standard Model of particle physics successfully describes all known fundamental particles and their interactions; however, it leaves several unanswered questions. Theories beyond the Standard Model typically introduce new particles and symmetries to address these issues. In the early universe, when such particles become non-relativistic, or the symmetrie

Daryna Dementieva, Evgeniya Sukhodolskaya, Alexander Fraser

In the era of social networks and rapid misinformation spread, news analysis remains a critical task. Detecting fake news across multiple languages, particularly beyond English, poses significant challenges. Cross-lingual news comparison offers a promising approach to verify information by leveraging external sources in different languages (Chen and Shu, 202

Han Zhong, Denis Kochan, Igor Zutic, Yingying Wu

As quantum technologies advance, a fundamental challenge is mitigating noise and backscattering in superconducting circuits to achieve scalable, high-fidelity operations. Conventional superconducting components lack directionality, causing energy loss and decoherence. Superconducting diodes, that allow dissipationless current in one direction and resistive f

Yifan Li, Fenghe Tang, Yingtai Li, Shaohua Kevin Zhou

General-purpose large Vision-Language Models (VLMs) demonstrate strong capabilities in generating detailed descriptions for natural images. However, their performance in the medical domain remains suboptimal, even for relatively straightforward tasks, primarily due to the lack of large-scale, high-quality, specialized medical imaging datasets and the neglect

Gianni Manno, Filippo Salis

A classical and long-staying problem addressed, among others, by Calabi and Chern, is that to find a complete list of mutually non-isometric Kaehler-Einstein manifolds immersed in a finite-dimensional Kaehler space form. We address the same problem in the para-Kaehler context and, then, we find a list of mutually non-isometric toric para-Kaehler manifolds an

Lu Wang, Lingyun Deng, Guanqing Wang, Hong Liang

The discrete velocity method (DVM) is a powerful framework for simulating gas flows across continuum to rarefied regimes, yet its efficiency remains limited by existing quadrature rules. Conventional infinite-domain quadratures, such as Gauss-Hermite, distribute velocity nodes globally and perform well near equilibrium but fail under strong nonequilibrium co

Jin Han, Zhe Zheng, Yi Gu, Jia-Rui Lin

Evacuation simulation is essential for building safety design, ensuring properly planned evacuation routes. However, traditional evacuation simulation relies heavily on refined modeling with extensive parameters, making it challenging to adopt such methods in a rapid iteration process in early design stages. Thus, this study proposes DiffEvac, a novel method

Zhengxuan Wei, Jiajin Tang, Sibei Yang

Existing Moment Retrieval methods face three critical bottlenecks: (1) data scarcity forces models into shallow keyword-feature associations; (2) boundary ambiguity in transition regions between adjacent events; (3) insufficient discrimination of fine-grained semantics (e.g., distinguishing ``kicking" vs. ``throwing" a ball). In this paper, we propose a zero

Bas van der Beek, Anurag Bishnoi

The generalized Tur\'an number $\text{ex}(n,H,\mathcal{F})$ denotes the maximum number of copies of $H$ in an $n$-vertex graph which contains no copies of any graph in a family $\mathcal{F}$ of graphs. The generalized rational exponents conjecture states that for every rational $r\geq 1$ there exist graphs $H,F$ such that $\text{ex}(n,H,\{F\})=\Theta(n^r)$.

Patrick Becker, Fabian Frank

Justified representation (JR) and extended justified representation (EJR) are well-established proportionality axioms in approval-based multiwinner voting. Both axioms are always satisfiable, but they rely on a fixed quota (typically Hare or Droop), with the Droop quota being the smallest one that guarantees existence across all instances. With this in mind,

Rajesh ADJ Jeyaprakash, Senthil Arasu Balasubramanian, Vijay Maddikera

Investment style groups investment approaches to predict portfolio return variations. This study examines the relationship between investment style, style consistency, and risk-adjusted returns of Indian equity mutual funds. The methodology involves estimating size and style beta coefficients, identifying breakpoints, analysing investment styles, and assessi

Jack Pessaud, Eric Moran, John Nguyen, Joel Palko

With the increasing adoption of iris recognition systems and the expansion of large-scale enrollment databases, there is a growing need to efficiently assess iris image quality at the time of acquisition, particularly to model user non-compliance in real time. Image quality may degrade due to eyelid occlusion or pupil dilation. Although previous studies have

Junfei Zhou, Penglin Dai, Quanmin Wei, Bingyi Liu

Multi-agent collaboration enhances the perception capabilities of individual agents through information sharing. However, in real-world applications, differences in sensors and models across heterogeneous agents inevitably lead to domain gaps during collaboration. Existing approaches based on adaptation and reconstruction fail to support pragmatic heterogene

Eric Ding

Collaborative Machine Learning is a paradigm in the field of distributed machine learning, designed to address the challenges of data privacy, communication overhead, and model heterogeneity. There have been significant advancements in optimization and communication algorithm design and ML hardware that enables fair, efficient and secure collaborative ML tra

Farhan Farsi, Shayan Bali, Fatemeh Valeh, Parsa Ghofrani

With the increasing adoption of large language models (LLMs), ensuring their alignment with social norms has become a critical concern. While prior research has examined bias detection in various languages, there remains a significant gap in resources addressing social biases within Persian cultural contexts. In this work, we introduce PBBQ, a comprehensive

Zhiping Zhou, Xiaohong Li, Ruitao Feng, Yao Zhang

Decompilation converts machine code into human-readable form, enabling analysis and debugging without source code. However, fidelity issues often degrade the readability and semantic accuracy of decompiled output. Existing methods, such as variable renaming or structural simplification, provide partial improvements but lack robust detection and correction, p

Rufeng Xiao, Zhiping Li, Rujun Jiang

Utility-based shortfall risk (UBSR), a convex risk measure sensitive to tail losses, has gained popularity in recent years. However, research on computational methods for UBSR optimization remains relatively scarce. In this paper, we propose a fast and scalable algorithm for the UBSR-based portfolio optimization problem. Leveraging the Sample Average Approxi

Xiaochen Wang

Let $G$ be a countably infinite discrete amenable group acting continuously on a compact metric space $X$. We study the problem of lowering topological entropy over subsets of $X$ and its connections with asymptotic $h$-expansiveness. Let $\{F_n\}$ be a tempered Følner sequence such that $e_G\in F_1\subseteq F_2\subseteq\cdots$ and $|F_n|/\log n\to\infty$. I

Selma Shikonde, Mike Wa Nkongolo

Over the years, the technological landscape has evolved, reshaping the security posture of organisations and increasing their exposure to cybersecurity threats, many originating from within. Insider threats remain a major challenge, particularly in sectors where cybersecurity infrastructure, expertise, and regulations are still developing. This study propose

Nathanaël Cuvelle--Magar, Stéphane Mallat

A considerable amount of research in harmonic analysis has been devoted to non-linear estimators of signals contaminated by additive Gaussian noise. They are implemented by thresholding coefficients in a frame, which provide a sparse signal representation, or by minimising their $\ell^1$ norm. However, sparse estimators in frames are not sufficiently rich to

Jinpyo Hong, Rachel E. Baker

Precise outbreak forecasting of infectious diseases is essential for effective public health responses and epidemic control. The increased availability of machine learning (ML) methods for time-series forecasting presents an enticing avenue to enhance outbreak forecasting. Though the COVID-19 outbreak demonstrated the value of applying ML models to predict e

Marco Siino, Giuseppe Bonomo, Rosario Sorbello, Ilenia Tinnirello

Brain-computer interfaces (BCIs) based on motor imagery (MI) translate covert movement intentions into actionable commands, yet reliable decoding from non-invasive EEG remains challenging due to nonstationarity, low SNR, and subject variability. We present RatioWaveNet, which augments a strong temporal CNN-Transformer backbone (TCFormer) with a trainable, Ra

P. Peñil, N. Torres-Albà, A. Rico, S. Buson

Time series analysis is fundamental to characterizing the variability inherent in multi-wavelength emissions from blazars. However, a major observational challenge lies in the need for well-sampled, temporally uniform data, which is often hindered by irregular sampling and data gaps. These gaps can significantly affect the reliability and accuracy of methods

Benedetta Tessa, Alejandro Moreo, Stefano Cresci, Tiziano Fagni

Accurately estimating how users respond to moderation interventions is paramount for developing effective and user-centred moderation strategies. However, this requires a clear understanding of which user characteristics are associated with different behavioural responses, which is the goal of this work. We investigate the informativeness of 753 socio-behavi

Yvan Martel, Frank Merle

For the focusing, energy critical wave equation in dimension 5, we construct multi-solitons with any number of solitons, any choice of signs, speeds, scaling parameters and translation parameters. This requires to revisit in depth previous constructions of multi-solitons based on a unidirectional approach, to fully take into account the dimension of the spac

Matthias Ludewig, Konrad Waldorf

Adjustments are additional structures on crossed modules of Lie groups, serving as a tool in higher gauge theory to circumvent the fake flatness of connections on 2-bundles. In this article, we investigate the existence and classification of adjustments, as well as their covariance under weak equivalences. Our approach is based on a differentiation/integrati

Washington R. Carvalho, Lech Wiktor Piotrowski

We show that there is a strong dependence of the radio LDF electric field amplitudes at ground level on the position of $X_{\rm max}$ in the atmosphere, even accounting for differences in the EM energy of the showers. Since an $X_{\rm max}$ dependence leads to a primary composition dependence, this implies that information on the mass composition is encoded

Rachid Benbrik, Mohammed Boukidi, Khouloud Kahime, Stefano Moretti

Recent experimental hints from the Large Hadron Collider (LHC) in di-photon and partially in the $\tau^+\tau^-$ final states suggest the possible existence of an additional Higgs boson with a mass around 95 GeV. Interestingly, these observations are consistent with earlier results from the Large Electron-Positron (LEP) collider, which pointed to an excess in

Francesco Vona, Mohamed Amer, Omar Abdellatif, Michelle Celina Hallmann

Controlling Unmanned Aerial Vehicles (UAVs) is a cognitively demanding task, with accidents often arising from insufficient situational awareness, inadequate training, and poor user experiences. Providing more intuitive and immersive visual feedback, particularly through Digital Twin technologies, offers new opportunities to enhance pilot awareness and overa

James Davies

We prove that for every countable string graph $S$, there is a planar graph $G$ with $V(G)=V(S)$ such that \[ \frac{1}{23660800}d_S(u,v) \le d_G(u,v) \le 162 d_S(u,v) \] for all $u,v\in V(S)$, where $d_S(u,v)$, $d_G(u,v)$ denotes the distance between $u$ and $v$ in $S$ and $G$ respectively. In other words, string graphs are quasi-isometric to planar graphs.

Martín Matamala

In 2008 Chen and Chv\'atal conjectured that any metric space on n points has at least n lines, unless all the points belong to one line. Chv\atal proved in 2014 that this is indeed the case for metric spaces with distances 0, 1 and 2. In this work, we prove that there exists a family of ten graphs such that a metric space defined by a graph of diameter two h

Haozhe Luo, Shelley Zixin Shu, Ziyu Zhou, Sebastian Otalora

Vision-language models (VLMs) have recently shown remarkable zero-shot performance in medical image understanding, yet their grounding ability, the extent to which textual concepts align with visual evidence, remains underexplored. In the medical domain, however, reliable grounding is essential for interpretability and clinical adoption. In this work, we pre

Alexander Ungar, Hao Tang, Andrew Stasiuk, Bo Xing

Spin defects in diamond serve as powerful building blocks for quantum technologies, especially for applications in quantum sensing and quantum networking. Electron-nuclear defects formed in the environment of optically active spins, such as the nitrogen-vacancy (NV) center, provide a resource for multi-qubit quantum registers. However, many of these defects

Zhou Lei, Pan Gang, Wang Jiahao, Sun Di

Image Forgery Localization (IFL) is a crucial task in image forensics, aimed at accurately identifying manipulated or tampered regions within an image at the pixel level. Existing methods typically generate a single deterministic localization map, which often lacks the precision and reliability required for high-stakes applications such as forensic analysis

Madeleine Phillips, C. Stephen Hellberg

Transition metal dichalcogenide (TMD) bilayers with an interlayer twist exhibit a moire super-period, whose effects can manifest in both structural and electronic properties. Atomic displacements can lead to reconstruction into domains of aligned stacking, and flat bands can form that may host correlated electron states. In heterobilayers angular mismatch is

Ratnangshu Das, Subhodeep Choudhury, Pushpak Jagtap

This paper introduces a new framework for synthesizing time-varying control barrier functions (TV-CBFs) for general Signal Temporal Logic (STL) specifications using spatiotemporal tubes (STT). We first formulate the STT synthesis as a robust optimization problem (ROP) and solve it through a scenario optimization problem (SOP), providing formal guarantees tha

Andrea Bocchieri, Luke Booth, Lorenzo V. Mugnai

Launching in 2027 and 2029, respectively, Twinkle and Ariel will conduct the first large-scale homogeneous spectroscopic surveys of the atmospheres of hundreds of diverse exoplanets. This will fundamentally transition the field to an era of population-level characterisation. In this pilot study, we aim to explore possible synergies between Twinkle and Ariel

V. Apinyan, T. K. Kopeć

We study the effects of the electron-electron interactions on the excitonic properties and charge-density modulations in the AB stacked double-layer (DL) graphene, placed in the external gate-potential $V$. The coexistence of the canted antiferromagnetic order and excitonic pairing gap has been studied with the help of the generalized Hubbard model. We calcu

Aoyang Fang, Haowen Yang, Haoze Dong, Qisheng Lu

Root Cause Analysis (RCA) is a crucial aspect of incident management in large-scale cloud services. While the term root cause analysis or RCA has been widely used, different studies formulate the task differently. This is because the term "RCA" implicitly covers tasks with distinct underlying goals. For instance, the goal of localizing a faulty service for r

Su Ho Han, Jeongseok Hyun, Pilhyeon Lee, Minho Shim

Multimodal large language models (MLLMs) demonstrate strong video understanding by attending to visual tokens relevant to textual queries. To directly adapt this for localization in a training-free manner, we cast video reasoning segmentation as a video QA task and extract attention maps via rollout mechanism. However, raw attention maps are noisy and poorly

Marius Potfer, Vianney Perchet

Repeated multi-unit auctions, where a seller allocates multiple identical items over many rounds, are common mechanisms in electricity markets and treasury auctions. We compare the two predominant formats: uniform-price and discriminatory auctions, focusing on the perspective of a single bidder learning to bid against stochastic adversaries. We characterize

Jianhao Yuan, Xiaofeng Zhang, Felix Friedrich, Nicolas Beltran-Velez

This is a short technical report describing the winning entry of the PhysicsIQ Challenge, presented at the Perception Test Workshop at ICCV 2025. State-of-the-art video generative models exhibit severely limited physical understanding, and often produce implausible videos. The Physics IQ benchmark has shown that visual realism does not imply physics understa

David Békollè, Hugues Olivier Défo, Edgar L. Tchoundja

As a class of compact operators on the $\ell^2-$valued Bergman space $A^2_\alpha (\mathbb B_n, \ell^2)$ on the unit ball $\mathbb B_n,$ we study Toeplitz operators with $BMO^1_\alpha (\mathbb B_n, \mathcal L(\ell^2))$ operator-valued symbols. First, we describe a method of restriction to a finite dimension which allows us to apply earlier results of Rahm and

Xingdong Luo, Zhizhen Chen

Periodically driven systems provide unique opportunities to investigate the dynamics of topological excitations far from equilibrium. In this paper, we report a time-crystalline soliton (TCS) state in a driven-dissipative $\phi^4$ model. This state exhibits spontaneous breaking of discrete time-translational symmetry while simultaneously displaying spatial s

Melanie Rey, Andriy Mnih, Maxim Neumann, Matt Overlan

This paper investigates methods for estimating uncertainty in semantic segmentation predictions derived from satellite imagery. Estimating uncertainty for segmentation presents unique challenges compared to standard image classification, requiring scalable methods producing per-pixel estimates. While most research on this topic has focused on scene understan

Yu Wu, Ke Shu, Jonas Fischer, Lidia Pivovarova

This paper presents a novel task of extracting low-resourced and noisy Latin fragments from mixed-language historical documents with varied layouts. We benchmark and evaluate the performance of large foundation models against a multimodal dataset of 724 annotated pages. The results demonstrate that reliable Latin detection with contemporary zero-shot models

Yilong Wang, B. F. Liu, Mingjun Liu

Accretion in black hole X-ray binaries is commonly believed to be supplied by the Roche lobe overflow or the stellar wind. The former is thought to form a geometrically thin disc while the diffuse wind could form a geometrically thick hot accretion flow. In this paper, we instead consider a more generalised case, i.e., accretion with both cold and hot gas su

Subhrajyoty Roy, Abhik Ghosh, Ayanendranath Basu

Estimating the true rank of a noisy data matrix is a fundamental problem underlying techniques such as principal component analysis, matrix completion, etc. Existing rank estimation criteria, including information-based and cross-validation methods, are either highly sensitive to outliers or computationally demanding when combined with robust estimators. Thi

Steffen Berg, Ryan T. Armstrong, Maja Rücker, Alex Hansen

An outstanding characteristic of porous media, desired in many applications, is the large surface area, which facilitates solid-fluid interactions, making porous media an extreme case in colloid and interface science. In two-fluid systems, wetting and the balance of capillary and viscous forces control fluid displacement processes, leading to a wide range of

Meiyu Li, Wei Ai, Naeemul Hassan

Video sharing platforms (VSPs) have become central information hubs but also facilitate the spread of information disorder, from misleading narratives to fabricated content. This survey synthesizes research on VSPs' multimedia ecosystems across three dimensions: (1) types of information disorder, (2) methodological approaches, and (3) platform features. We c

Luca Piano, Peng Huanwen, Radu Ciprian Bilcu

Multi-focus image fusion (MFIF) addresses the depth-of-field (DOF) limitations of optical lenses, where only objects within a specific range appear sharp. Although traditional and deep learning methods have advanced the field, challenges persist, including limited training data, domain gaps from synthetic datasets, and difficulties with regions lacking infor

Pragna Prahallad, Pranathi Prahallad

In this study, we evaluate the ability of OpenAI's gpt-4o model to classify chest X-ray images as either NORMAL or PNEUMONIA in a zero-shot setting, without any prior fine-tuning. A balanced test set of 400 images (200 from each class) was used to assess performance across four distinct prompt designs, ranging from minimal instructions to detailed, reasoning

Austin Christian, Tanushree Shah

We develop a diagrammatic framework for applying the symplectic JSJ decomposition to exact/weak symplectic fillings of 3-dimensional contact manifolds. Namely, we apply the symplectic JSJ decomposition to a contact surgery diagram for some $(Y,\zeta)$, producing a finite collection of contact manifolds, also described diagrammatically, whose exact/weak sympl

Francisco Mena, Dino Ienco, Cassio F. Dantas, Roberto Interdonato

Multi-modal co-learning is emerging as an effective paradigm in machine learning, enabling models to collaboratively learn from different modalities to enhance single-modality predictions. Earth Observation (EO) represents a quintessential domain for multi-modal data analysis, wherein diverse remote sensors collect data to sense our planet. This unprecedente

Junhong Lin, Kangli Wang, Shunzhou Wang, Songlin Fan

Feed-forward surround-view autonomous driving scene reconstruction offers fast, generalizable inference ability, which faces the core challenge of ensuring generalization while elevating novel view quality. Due to the surround-view with minimal overlap regions, existing methods typically fail to ensure geometric consistency and reconstruction quality for nov

Zuoming Fu, Alex Manley, Mohammad Alian

Generative AI is increasing the productivity of software and hardware development across many application domains. In this work, we utilize the power of Large Language Models (LLMs) to develop a co-pilot agent for assisting gem5 users with automating design space exploration. Computer architecture design space exploration is complex and time-consuming, given

Zahra Mirzaiyan, Pierfrancesco Siena, Pasquale Claudio Africa, Michele Girfoglio

This work develops a rigorous numerical framework for solving time-dependent Optimal Control Problems (OCPs) governed by partial differential equations, with a particular focus on biomedical applications. The approach deals with adjoint-based Lagrangian methodology, which enables efficient gradient computation and systematic derivation of optimality conditio

Eojin Kim, Brian F. Farrell

The roll streak structure (RSS) is ubiquitous in shear flow turbulence and is fundamental to the dynamics of the self-sustaining process (SSP) maintaining the turbulent state. The formation and maintenance of the RSS in wall-bounded shear flow suggest the presence of an underlying instability that has recently been identified using statistical state dynamics

Ariana Yi, Ce Zhou, Liyang Xiao, Qiben Yan

As object detection models are increasingly deployed in cyber-physical systems such as autonomous vehicles (AVs) and surveillance platforms, ensuring their security against adversarial threats is essential. While prior work has explored adversarial attacks in the image domain, those attacks in the video domain remain largely unexamined, especially in the no-

Denis Villemonais

We establish a domination principle for positive operators, which provides an upper bound on the essential spectral radius and yields quasi-compactness criteria on weighted supremum spaces with Lyapunov type functions and local domination. In particular, for kernels acting on such spaces, we obtain $r_{ess}(P)\leq r_{ess}(Q)$ whenever $0\leq P\leq Q$ as kern

Petr Pálka, Jiangyu Han, Marc Delcroix, Naohiro Tawara

We present improvements to speaker diarization in the two-stage end-to-end neural diarization with vector clustering (EEND-VC) framework. The first stage employs a Conformer-based EEND model with WavLM features to infer frame-level speaker activity within short windows. The identities and counts of global speakers are then derived in the second stage by clus

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using $(2.712\pm0.014)\times10^{9}$ $\psi(3686)$ events collected with the BESIII detector at the BEPCII collider, we report an evidence of $\Xi^{0}$ transverse polarization with a significance of 4.4$\sigma$, a precise measurement of the branching fraction and the ratios between the $S$-wave and $D$-wave contributions of $\psi(3686)\to\Xi^{0}\bar\Xi^{0}$. T

Qiaochao Xiang, Xiaokang Li, Xiaodong Guo, Zengwei Zhu

It is now known that in addition to electrons, other quasi-particles such as phonons and magnons can also generate a thermal Hall signal. Graphite is a semimetal with extremely mobile charge carriers of both signs and a large lattice thermal conductivity. We present a study of the thermal Hall effect in highly oriented pyrolytic graphite (HOPG) samples with

Miguel Barroso Varela, Álvaro de la Cruz-Dombriz

We provide insight about the full form of the equations for matter density perturbations and the scalar Bardeen metric potentials in general $f(R)$ theories of gravity. When considering viable modifications to the standard $\Lambda$CDM background, the full scale-dependent equations for the metric perturbations are provided and are shown to match the ones obt

Raghavendra Koushik, Hector Zenil

While traditionally not considered part of the scientific method, science communication is increasingly playing a pivotal role in shaping scientific practice. Researchers are now frequently compelled to publicise their findings in response to institutional impact metrics and competitive grant environments. This shift underscores the growing influence of medi

Xiazhi Hao, S. Y. Lou

This paper investigates the algebraic reduction of the infinite-dimensional symmetries of the Ablowitz-Kaup-Newell-Segur system when restricted to multi-soliton solution. By systematically analyzing, we demonstrate that the entire $K$-symmetry hierarchy collapses into a finite-dimensional module over the field of wave parameters, spanned by elementary center

V. Apinyan, T. Kopeć

We have studied the electron-electron interactions in the system composed of two metallic wires, placed in the external magnetic and electric fields. The interactions between the electrons in the wires have been taken into account within the usual Hubbard model. We have considered both half-filling and partial-filling limits for the occupation of the atomic

Takahiro Suzuki, Keisuke Okumura

We consider Connected Unlabeled Multi-Agent Pathfinding (CUMAPF), a variant of MAPF where interchangeable agents must be connected at all times. This problem is fundamental to swarm robotics applications such as self-reconfiguration and marching, where standard MAPF is insufficient as it does not guarantee the connectivity constraint. Despite its simple stru

Riku Rantanen

The order parameter of superfluid $^3$He involves nine complex components, and the multicomponent structure allows quantized vortices in superfluid $^3$He to have complicated cores. One of the vortices found in the B phase is the double-core vortex, which has been often described as a pair of two half-quantum vortices (HQVs) connected by a domain wall. Our n

Simone Göttlich, Jacob Heieck, Andreas Neuenkirch

We study the finite-agent behavior of Consensus-Based Optimization (CBO), a recent metaheuristic for the global minimization of a function, that combines drift toward a consensus estimate with stochastic exploration. While previous analyses focus on asymptotic mean-field limits, we investigate the stability properties of CBO for finite population size \( N \

E. H. Prinsen, A. Borschevsky, S. Hoekstra, A. K. Dutta

We present high-precision ab initio calculations of the static and dynamic polarizability of the barium monohydroxide ($^{138}$BaOH) molecule, using relativistic coupled-cluster theory. By thoroughly investigating the dependence of the calculated polarizabilities on computational parameters (basis set size, treatment of relativity, level of treatment of elec

Runpeng Xie, Quanwei Wang, Hao Hu, Zherui Zhou

Comprehending natural language and following human instructions are critical capabilities for intelligent agents. However, the flexibility of linguistic instructions induces substantial ambiguity across language-conditioned tasks, severely degrading algorithmic performance. To address these limitations, we present a novel method named DAIL (Distributional Al

Yi Hua Lam, Ning Lu, Alexander Heger, Zi Xin Liu

The $^{63}$Ga(p,$\gamma$)$^{64}$Ge and $^{64}$Ge(p,$\gamma$)$^{65}$As thermonuclear reactions connect the ZnGa and GeAs cycles by diverting the flow of the rapid proton capture process from $^{63}$Ga to $^{65}$As. Changes in these two reaction rates regulate the ZnGa and GeAs cycles and may affect the modeled properties matching with the observed counterpart

Yao Deng, Xian Zhong, Wenxuan Liu, Zhaofei Yu

RGB cameras excel at capturing rich texture details with high spatial resolution, whereas event cameras offer exceptional temporal resolution and a high dynamic range (HDR). Leveraging their complementary strengths can substantially enhance object tracking under challenging conditions, such as high-speed motion, HDR environments, and dynamic background inter

Nidham Tekaya, Manuela Waldner, Matthias Zeppelzauer

Large-scale vision-language models (VLMs) such as CLIP have gained popularity for their generalizable and expressive multimodal representations. By leveraging large-scale training data with diverse textual metadata, VLMs acquire open-vocabulary capabilities, solving tasks beyond their training scope. This paper investigates the temporal awareness of VLMs, as

Yassir El Moutaoukal, Rosario R. Riso, Andrea Bianchi, Henrik Koch

Strong coupling with circularly polarized vacuum fluctuations offers a viable route to manipulate molecular chirality. While experiments are advancing toward the realization of chiral cavities, a mean-field theoretical framework for describing electron-photon interaction in this platform has been missing. Here, we present a mean-field theory that can be syst

Zhang Xiaofeng, Aaron Courville, Michal Drozdzal, Adriana Romero-Soriano

Text-to-image (T2I) models offer great potential for creating virtually limitless synthetic data, a valuable resource compared to fixed and finite real datasets. Previous works evaluate the utility of synthetic data from T2I models on three key desiderata: quality, diversity, and consistency. While prompt engineering is the primary means of interacting with

A. Deur

We discuss how the Bjorken sum rule allows access to the QCD running coupling $\alpha_s$ at any scale, including in the deep infrared IR domain. The Bjorken sum data from Jefferson Lab, together with the world data on $\alpha_s$ reported by the Particle Data Group, allow us to determine the running of $\alpha_s(Q)$ over five orders of magnitude in four-momen

Simone Alghisi, Gabriel Roccabruna, Massimo Rizzoli, Seyed Mahed Mousavi

Vision-Language Models (VLMs) have recently gained attention due to their competitive performance on multiple downstream tasks, achieved by following user-input instructions. However, VLMs still exhibit several limitations in visual reasoning, such as difficulties in identifying relations (e.g., spatial, temporal, and among objects), understanding temporal s

Yuyang Peng, Feng Gu, Chuanshan Tian

Understanding specific ion adsorption within the inner Helmholtz layer remains central to electrochemistry yet experimentally elusive. Here we directly quantify counterion adsorption and extract the associated thermodynamic parameters within the inner Helmholtz layer using phase-sensitive sum-frequency vibrational spectroscopy (PS-SFVS). Using sodium dodecyl

Bjorn Poonen

The recent negative answer to Hilbert's tenth problem over rings of integers relies on a theorem that for every extension of number fields $L/K$, if there is an abelian variety $A$ over $K$ such that $0 < \operatorname{rank} A(K) = \operatorname{rank} A(L)$, then $\mathcal{O}_K$ is $\mathcal{O}_L$-diophantine. We present an alternative proof of this theorem

Sreeram PG, J. Bharathi Kannan, M. S. Santhanam

Quantum battery is expected to outperform its classical counterpart due to quantum effects. Usually, in a quantum battery made of $N$ cells, quantum advantage is demonstrated through super-extensive scaling of the upper bound to the charging power with $N$. In this work, we show that potential quantum advantage as measured by the power bounds need not transl

Adrien Arbalestrier, Riccardo Argurio, Giovanni Galati, Elise Paznokas

We revisit Maxwell theory in 4d with a boundary, with particular attention to the global properties of the boundary conditions, both in the free (topological) and interacting (conformal) cases. We analyze the fate of Wilson-'t Hooft lines, identifying the subset that is trivialized on the boundary and the ones that become topological, thus generating a bound

C. Zhang, R. G. Cortiñas, A. H. Karamlou, N. Noll

Quantum-information-inspired experiments in nuclear magnetic resonance spectroscopy may yield a pathway towards determining molecular structure and properties that are otherwise challenging to learn. We measure out-of-time-ordered correlators (OTOCs) [1-4] on two organic molecules suspended in a nematic liquid crystal, and investigate the utility of this dat

Jie Song, Yang Bai, Mikhail Svinin, Naoki Wakamiya

This study presents a control strategy for coordinating multiple unmanned aerial vehicles (UAVs) to monitor unknown flood regions and estimate the extent of inundation. The proposed method adopts a density-driven coverage framework based on Centroidal Voronoi Tessellation (CVT), in which the density function is modeled using a Gaussian Mixture of Density Fun

Rohan Srikanth, Tim Dietrich, Katy Clough

Binary neutron star mergers provide a laboratory for probing fundamental physics through their gravitational-wave emission and electromagnetic counterparts. In particular, they may allow us to explore signatures of physics beyond the Standard Model in strong-gravity regimes, such as those of dark matter. In this work, we investigate the dynamics of light dar

Danni Liu, Jan Niehues

Fine-tuning multilingual foundation models on specific languages often induces catastrophic forgetting, degrading performance on languages unseen in fine-tuning. While this phenomenon is widely-documented, the literature presents fragmented results about when forgetting occurs. To address this ambiguity, we conduct a systematic empirical study using machine

Luca Maria Del Bono, Federico Ricci-Tersenghi, Francesco Zamponi

Combinatorial optimization problems are central to both practical applications and the development of optimization methods. While classical and quantum algorithms have been refined over decades, machine learning--assisted approaches are comparatively recent and have not yet consistently outperformed simple, state-of-the-art classical methods. Here, we focus

Lukas Weissinger, Simon Hubmer, Bernadett Stadler, Ronny Ramlau

Atmospheric tomography, the problem of reconstructing atmospheric turbulence profiles from wavefront sensor measurements, is an integral part of many adaptive optics systems. It is used to enhance the image quality of ground-based telescopes, such as for the Multiconjugate Adaptive Optics Relay For ELT Observations (MORFEO) instrument on the Extremely Large

Francesco Schetter, Shifa Sulaiman, Shoby George, Paolino De Risi

The integration of advanced control strategies into prosthetic hands is essential to improve their adaptability and performance. In this study, we present an implementation of a Model Predictive Control (MPC) strategy to regulate the motions of a soft continuum wrist section attached to a tendon-driven prosthetic hand with less computational effort. MPC play

Samuel Akatchi Ahizi, Francisco Monteiro, Ramon Abarca, Miguel Alfonso Mendez

Vertical forcing of partially filled tanks can induce parametric sloshing. Under non-isothermal conditions, the resulting mixing can disrupt the thermal stratification between liquid and vapor, leading to enhanced heat and mass transfer and large pressure fluctuations. This work presents an experimental investigation of sloshing-induced heat and mass transfe

Keigo Fukumura, Shoji Ogawa, Atsushi Tanimoto, Francesco Tombesi

Powerful ionized accretion disk winds are often observed during episodic outbursts in Galactic black hole transients. Among those X-ray absorbers, \fexxvi\ doublet structure (Ly$\alpha_1$+Ly$\alpha_2$ with $\sim 20$eV apart) has a unique potential to better probe the underlying physical nature of the wind; i.e. density and kinematics. We demonstrate, based o

Jackson C. Turner, Michael I. Weinstein

We study nonlinear bound states -- time-harmonic and spatially decaying ($L^2$) solutions -- of the nonlinear Schr\"odinger / Gross--Pitaevskii equations (NLS/GP) with a compactly supported linear potential. Such solutions are known to bifurcate from the $L^2$ bound states of an underlying Schr\"odinger operator $H_V=-\partial_x^2+V$. In this article we prov