March 2025 arXiv papers — page 40

Haci Ismail Aslan, Philipp Wiesner, Ping Xiong, Odej Kao

Graph Neural Networks (GNNs) are playing an increasingly important role in the efficient operation and security of computing systems, with applications in workload scheduling, anomaly detection, and resource management. However, their vulnerability to network perturbations poses a significant challenge. We propose $\beta$-GNN, a model enhancing GNN robustnes

Iris H. R. Yoon, Gregory Henselman-Petrusek, Yiyi Yu, Robert Ghrist

Neural manifolds summarize the intrinsic structure of the information encoded by a population of neurons. Advances in experimental techniques have made simultaneous recordings from multiple brain regions increasingly commonplace, raising the possibility of studying how these manifolds relate across populations. However, when the manifolds are nonlinear and p

Xu Zhu, Wenwen Zhou, Bin Wu

In this paper, we investigate Carleman estimate and controllability result for the fully-discrete approximations of a one-dimensional Ginzburg-Landau equation with dynamic boundary conditions. We first establish a new discrete Carleman estimate for the corresponding adjoint system. Based on this Carleman estimate, we obtain a relaxed observability inequality

Kayané Robach, Michel H. Hof, Mark A. van de Wiel

Integrating data from multiple sources expands research opportunities at low cost. However, due to different data collection processes and privacy constraints, unique identifiers are unavailable. Record Linkage (RL) algorithms address this by probabilistically linking records based on partially identifying variables. Since these variables lack the strength t

Filipe S. Ribeiro, Pedro D. S. Silva, Manoel M. Ferreira

The arrival time of electromagnetic signals traveling in chiral cosmic media is investigated in the context of Maxwell-Carroll-Field-Jackiw electrodynamics. Considering the interstellar medium (ISM) as a cold, ionized, chiral plasma, we derive the time delay between two traveling signals, expressed in terms of a modified dispersion measure (DM) which receive

Fabian Gasser, Sanjay John, Jorid Smets, Josef Simbrunner

Grazing incidence X-ray diffraction (GIXD) is widely used for the structural characterization of thin films, particularly for analyzing phase composition and the orientation distribution of crystallites. While various tools exist for qualitative evaluation, a widely applicable systematic procedure to achieve quantitative information has not yet been develope

F. Theel, A. G. Volosniev, D. Diplaris, F. Brauneis

We explore the impact and scaling of effective interactions between two and three impurity atoms, induced by a bosonic medium, on their density distributions. To facilitate the detection of mediated interactions, we propose a setup where impurities are trapped in a tilted double-well potential, while the medium is confined to a ring. The tilt of the potentia

Joachim Baumeister, Susana Hahn, Konstantin Herud, Max Ostrowski

We address the challenge of product configuration in the context of increasing customer demand for diverse and complex products. We propose a solution through a curated selection of product model benchmarks formulated in the COOM language, divided into three fragments of increasing complexity. Each fragment is accompanied by a corresponding bike model exampl

Alessandro Maisto

Role-playing games (RPG) are games in which players interact with one another to create narratives. The role of players in the RPG is largely based on the interaction between players and their characters. This emerging form of shared narrative, primarily oral, is receiving increasing attention. In particular, many authors investigated the use of an LLM as an

Cees Haringa, Ryan Rautenbach, Héctor Maldonado de Léon, Pieter Brorens

CFD simulations are widely used to quantify mixing performance of stirred tanks, for various applications in chemical engineering and biotechnology. Due to advances in GPU computing, more and more often these simulations make use of Large Eddy Simulations (LES), which explicitly simulate the dynamics of large-scale turbulence. Although these simulations are

Zheyu Wu, Mengmeng Long, Hanyi Chen, Shubhankar Paul

The metallic oxide RuO$_2$ has emerged as a promising altermagnet candidate, owing to reports of this material hosting antiferromagnetic ordering accompanied by a spin-split electronic band structure characteristic of time-reversal symmetry-breaking. However, recent studies have robustly questioned this scenario. Here we map the Fermi surface of pristine sin

Mark Hagen, Alexandre Martin, Giovanni Sartori

We show that Wise's power alternative is stable under certain group constructions, use this to prove the power alternative for new classes of groups, and recover known results from a unified perspective. For groups acting on trees, we introduce a dynamical condition that allows us to deduce the power alternative for the group from the power alternative for i

Zongyuan Zhang, Tianyang Duan, Zheng Lin, Dong Huang

Deep reinforcement learning (DRL) has emerged as a promising approach for robotic control, but its realworld deployment remains challenging due to its vulnerability to environmental perturbations. Existing white-box adversarial attack methods, adapted from supervised learning, fail to effectively target DRL agents as they overlook temporal dynamics and indis

Alexander Konrad, Robert Gaugl, Christoph Maier, Sonja Wogrin

The rapid growth of photovoltaic (PV) systems in Austria's medium- and low-voltage grids has intensified challenges in grid access, with technical limits increasingly leading to restrictions on full feed-in power. This issue has sparked discussions about limiting PV feed-in power and the implications for both generated and curtailed PV energy. At the same ti

Davide Domini, Gianluca Aguzzi, Mirko Viroli

In recent years, cro:flFederated learning (FL) has gained significant attention within the machine learning community. Although various FL algorithms have been proposed in the literature, their performance often degrades when data across clients is non-independently and identically distributed (non-IID). This skewness in data distribution often emerges from

Henrik Åkesson, Diana P. M. Osorio, Erik G. Larsson

Integrating sensing capabilities into existing massive MIMO communication networks has become crucial, stemming from a need for a more interconnected society. Improved coverage and performance can be obtained by incorporating new network components, such as reconfigurable intelligent surfaces or network-controlled repeaters (NCR). Integrating such components

Xiaoxi Jia, Matteo Lapucci, Pierluigi Mansueto

In this paper, we deal with the problem of optimizing a black-box smooth function over a full-dimensional smooth convex set. We study sets of feasible curves that allow to properly characterize stationarity of a solution and possibly carry out sound backtracking curvilinear searches. We then propose a general pattern search algorithmic framework that exploit

Georgios Poulias, Stefan Vandoren

We continue the study of Carroll limits on partition functions of relativistic conformal theories and their thermodynamics. By introducing imaginary chemical potentials $v$ conjugate to momenta, one can access and study the Carroll regime in which $v\gg c$. We analyze examples of free massless particles, 2d CFTs and some free field theories in $d$ spatial di

Tanmoy Dam, Sanjay Bhargav Dharavath, Sameer Alam, Nimrod Lilith

The fusion of LiDAR and camera sensors has demonstrated significant effectiveness in achieving accurate detection for short-range tasks in autonomous driving. However, this fusion approach could face challenges when dealing with long-range detection scenarios due to disparity between sparsity of LiDAR and high-resolution camera data. Moreover, sensor corrupt

Zongyuan Zhang, Tianyang Duan, Zheng Lin, Dong Huang

Recently, deep reinforcement learning (DRL) has emerged as a promising approach for robotic control. However, the deployment of DRL in real-world robots is hindered by its sensitivity to environmental perturbations. While existing whitebox adversarial attacks rely on local gradient information and apply uniform perturbations across all states to evaluate DRL

Hao Fu, Hanbin Zhao, Jiahua Dong, Henghui Ding

Recent pre-trained vision-language models (PT-VLMs) often face a Multi-Domain Task Incremental Learning (MTIL) scenario in practice, where several classes and domains of multi-modal tasks are incrementally arrived. Without access to previously seen tasks and unseen tasks, memory-constrained MTIL suffers from forward and backward forgetting. To alleviate the

Omid Amini, Shu Kawaguchi, JuAe Song

Given an algebraic variety defined over a discrete valuation field and a skeleton of its Berkovich analytification, the tropicalization process transforms function field of the variety to a semifield of tropical functions on the skeleton. Our main result offers a purely polyhedral characterization of this semifield: we show that a tropical function is in the

Benjamin Campillo Aveleira, Aude Gehrmann-De Ridder, Thomas Gehrmann, Nigel Glover

We present a major update of the publicly available EERAD3 package to calculate perturbative corrections in the strong coupling in hadronic Higgs and $Z$-boson decays. We describe the theoretical framework underlying the numerical implementation and provide a guide to the usage of the program.

Luca Colagrande, Jayanth Jonnalagadda, Luca Benini

Modern general-purpose accelerators integrate a large number of programmable area- and energy-efficient processing elements (PEs), to deliver high performance while meeting stringent power delivery and thermal dissipation constraints. In this context, PEs are often implemented by scalar in-order cores, which are highly sensitive to pipeline stalls. Tradition

Keano De Vos, Gert de Cooman, Alexander Erreygers, Jasper De Bock

We provide a decision-theoretic framework for dealing with uncertainty in quantum mechanics. This uncertainty is two-fold: on the one hand there may be uncertainty about the state the quantum system is in, and on the other hand, as is essential to quantum mechanical uncertainty, even if the quantum state is known, measurements may still produce an uncertain

Vitaliy Grigoryev, Tatiana Demidova

The problem of the formation of exoplanets in inclined orbits relative to the equatorial plane of the parent star or the main plane of the protoplanetary disk can be solved by introducing a smaller inclined disk. However, the question of the nature of such an internal disk remains open. In the paper, we successfully tested the hypothesis about the formation

Elisa Bellantoni, Fabio Guglietta, Francesca Pelusi, Mathieu Desbrun

We develop a mesoscale computational model to describe the interaction of a droplet with a solid. The model is based on the hybrid combination of the immersed boundary and the lattice Boltzmann computational schemes: the former is used to model the non-ideal sharp interface of the droplet coupled with the inner and outer fluids, simulated with the lattice Bo

Alejandro Argudin Monroy, Octavio Mendoza, Carlos E. Parra

Building on the recent work of Adachi, Enomoto and Tsukamoto on a generalization of the Happel-Reiten-Smal{\o} tilting process, we study extended tilting objects in extriangulated categories with negative first extension. These objects coincide with the 1-tilting objects in abelian categories as in the work of Parra, Saor{\'i}n and Virili. We will be particu

John Miller

This paper studies how persistence categories and triangulated persistence categories behave with respect to taking idempotent completions. In particular we study whether the idempotent completion (i.e. Karoubi envelope) of categories admitting persistence refinement also admits such a refinement. In doing so, we introduce notions of persistence semi-categor

Natsumi Nagata, Genta Osaki

We investigate the prospects of probing weak-scale higgsinos through electroweak precision measurements at a future $e^+ e^-$ collider. In the Minimal Supersymmetric Standard Model, higgsinos mix with winos and binos after electroweak symmetry breaking, forming charginos and neutralinos. These states contribute to electroweak precision observables, which can

Soham Pravin Sanyashiv, Sayantan Bhattacharya, Sudip Bhattacharyya

We study the timing and spectral properties of the Be/X-ray binary pulsar SXP 138 using four NuSTAR observations spanning 2016 to 2017. Analysis of the light curves using the Lomb-Scargle periodogram shows an increase in the spin period of SXP 138 from 140.69 to 140.85 seconds, indicating that the source is in the propeller regime. We calculate the associate

Johannes Aastrup, Jesper M. Grimstrup

We show that the structure of an almost-commutative spectral triple emerges in a semi-classical limit from a geometric construction on a configuration space of gauge connections. The geometric construction resembles that of a spectral triple with a Dirac operator on the configuration space that interacts with the so-called $\mathbf{HD}$-algebra, which is an

Andrew Rothwell, Joss Moorkens, Tomas Svoboda

This article reports on the third iteration of a survey of computerized tools and technologies taught as part of postgraduate translation training programmes. While the survey was carried out under the aegis of the EMT Network, more than half of responses are from outside that network. The results show the responsiveness of programmes to innovations in trans

Lars Rothkegel, Jakob Fink-Lamotte

Exposure-based interventions rely on inhibitory learning, often studied through Pavlovian conditioning. While disgust conditioning is increasingly linked to psychiatric disorders, it has been less researched than fear conditioning. In this study, we applied a categorical Pavlovian disgust conditioning paradigm with two CS categories (animals and tools) and d

Zhi Jiang, Danyang Yao, Yu Gao, Xu Ran

High-efficiency second-harmonic generation (SHG) in compact integrated photonic systems is crucial for advancing nonlinear optical technologies. However, achieving exceptional conversion efficiencies while maintaining stable performance remains a significant challenge. Here, we report a high-Q single-resonant photonic crystal nanobeam cavity (PCNBC) on a pol

Jorge A. Vargas

We present an overview of results on branching laws for square integrable representations of a semisimple Lie group, restricted to a closed reductive subgroup. The overview is partial and it is based on joint work with Bent {\O}rsted and the deep work of Toshiyuki Kobayashi.

Franz Dammaß, Karl A. Kalina, Markus Kästner

For the formulation of machine learning-based material models, the usage of invariants of deformation tensors is attractive, since this can a priori guarantee objectivity and material symmetry. In this work, we consider incompressible, isotropic hyperelasticity, where two invariants I1 and I2 are required for depicting a deformation state. First, we aim at e

Haoyang Qi, Renxin Xu

This article discusses strong nuggets (SNs) which means strong interaction condensed matter with a mass of about $10^6\,$g. They may originate from the early universe, supernova, pulsar merger event, and so on. Depending on the equation of state, the SNs could be stable and even be one of the candidates for dark matter. In order to detect SNs which hitting t

Saeedeh Mosaferchi, Alireza Mortezapour, Magnus Liebherr, Francesco Villecco

The introduction of automated vehicles has redefined the level of interaction between the driver and the vehicle, introducing new tasks and so impose different workloads. Existing tools such as NASA-TLX and DALI are still used to assess driving workload in automated vehicles, despite not accounting for new tasks. This study introduces AV-TLX, a specialized t

Trung Duc Ha, Sidney Bender

Counterfactual explanations have been successfully applied to create human interpretable explanations for various black-box models. They are handy for tasks in the image domain, where the quality of the explanations benefits from recent advances in generative models. Although counterfactual explanations have been widely applied to classification models, thei

Tobias Reisch, András Borsos, Stefan Thurner

Supply chain networks (SCN) form the structural backbone of any society. They constitute the societal metabolism that literally produces everything for everybody by coordinating practically every single person on the planet. SCNs are by no means static but undergo permanent change through the entry and exit of firms and the re-arrangement of supply relations

Mathilde Marcy, Jean-Marc Petit, Vasile-Marian Scuturici, Jocelyn Bonjour

Surrogate keys are now extensively utilized by database designers to implement keys in SQL tables. They are straightforward, easy to understand, and enable efficient access, despite lacking any real-world semantic meaning. In this context, complex redundancy issues might emerge and often go unnoticed as long as they do not affect the operational applications

Wantong Huang, Kwan Ho Au-Yeung, Paul Greule, Máté Stark

Precise control of spin states and spin-spin interactions in atomic-scale magnetic structures is crucial for spin-based quantum technologies. A promising architecture is molecular spin systems, which offer chemical tunability and scalability for larger structures. An essential component, in addition to the qubits themselves, is switchable qubit-qubit interac

Benjamin Carver, Jingyuan Zhang, Haoliang Wang, Kanak Mahadik

Interactive notebook programming is universal in modern ML and AI workflows, with interactive deep learning training (IDLT) emerging as a dominant use case. To ensure responsiveness, platforms like Jupyter and Colab reserve GPUs for long-running notebook sessions, despite their intermittent and sporadic GPU usage, leading to extremely low GPU utilization and

Luca Colagrande, Luca Benini

To meet the computational requirements of modern workloads under tight energy constraints, general-purpose accelerator architectures have to integrate an ever-increasing number of extremely area- and energy-efficient processing elements (PEs). In this context, single-issue in-order cores are commonplace, but lean dual-issue cores could boost PE IPC, especial

Wenchao Gu, Juntao Chen, Yanlin Wang, Tianyue Jiang

Repository-level code generation remains challenging due to complex code dependencies and the limitations of large language models (LLMs) in processing long contexts. While retrieval-augmented generation (RAG) frameworks are widely adopted, the effectiveness of different retrieved information sources-contextual code, APIs, and similar snippets-has not been r

Frances Yung, Varsha Suresh, Zaynab Reza, Mansoor Ahmad

Implicit discourse relation recognition (IDRR) -- the task of identifying the implicit coherence relation between two text spans -- requires deep semantic understanding. Recent studies have shown that zero- or few-shot approaches significantly lag behind supervised models, but LLMs may be useful for synthetic data augmentation, where LLMs generate a second a

Sergio F. Flores-Correa, M. L. León Hilario, I. A. Ramos-Pérez, Andres A. Reynoso

Surface-enhanced Raman spectroscopy (SERS) using gold-nanorod-dimer nanoantennas has shown great potential in various applications. This reflects in their large values of the customary figure of merit of SERS: the enhancement factor (EF), which is essentially the fourth power of the electric field integrated at the gap, the location at which target molecules

J. Chilufya, M. J. Hardcastle, J. C. S. Pierce, A. B. Drake

We present the largest visually selected sample of extended ($>$60 arcsec) radio-loud active galactic nuclei (RLAGN) to date, based on the LOw-Frequency Array Two-Metre Sky Survey second data release (LoTSS DR2). From the broader LoTSS DR2 dataset with spectroscopic classifications, we construct a subsample of 2828 RLAGN with radio luminosities greater than

Takayuki Ishitobi

A single-sided magnet generates a magnetic field on only one side while canceling it on the opposite side, a feature that has enabled diverse applications in both fundamental science and engineering. Here, we propose the {\it inverse} single-sided magnet: a non-ferromagnetic system that selectively attracts either the north or south pole of a ferromagnet whi

Nihar Paul, Manikandan Mathur, Jai Sukhatme, J. Thomas Farrar

Freshwater export from the Bay of Bengal (BoB) can drive the regional air-sea interaction in the Arabian Sea (AS). We use AVISO geostrophic and Globcurrent velocities to characterize horizontal stirring on a seasonal and interannual time scale for 1993-2022. With an example of the post-monsoon period of 2015-2016, we estimate the residence time of parcels in

Claudia Quinteros-Cartaya, Javier Quintero-Arenas, Andrea Padilla-Lafarga, Carlos Moraila

Deep learning techniques for processing large and complex datasets have unlocked new opportunities for fast and reliable earthquake analysis using Global Navigation Satellite System (GNSS) data. This work presents a deep learning model, MagEs, to estimate earthquake magnitudes using data from high-rate GNSS stations. Furthermore, MagEs is integrated with the

Ran Wang, Xinlei Zhou, Meng Hu, Rihao Li

Despite the remarkable success of deep neural networks (DNNs), the security threat of adversarial attacks poses a significant challenge to the reliability of DNNs. In this paper, both theoretically and empirically, we discover a universal phenomenon that has been neglected in previous works, i.e., adversarial attacks tend to shift the distributions of featur

Rupert H. Levene, Polona Oblak, Helena Šmigoc

A graph is said to be orthogonalisable if the set of real symmetric matrices whose off-diagonal pattern is prescribed by its edges contains an orthogonal matrix. We determine some necessary and some sufficient conditions on the sizes of the connected components of two graphs for their join to be orthogonalisable. In some cases, those conditions coincide, and

Ling-Nan Zou

We describe Structured Random Binding (SRB), a minimal model of protein-protein interactions rooted in the statistical physics of disordered systems. In this model, nonspecific binding is a generic consequence of the interaction between random proteins, exhibiting a phase transition from a high temperature state where nonspecific complexes are transient and

Zehui Lin, Zahra Hooshmand-Ahoor, Laurence Bodelot, Kostas Danas

This study proposes a family of novel mechanically-soft and magnetically-hard magnetorheological foams that, upon deformation, lead to robust and measurable magnetic flux changes in their surroundings. This allows to infer qualitatively and even quantitatively the imposed deformation and, eventually from that, an estimation of the stiffness and average stres

Berk Çakar, Charles M. Sale, Sophie Chen, Dongyoon Lee

Composing regexes is a common but challenging engineering activity. Software engineers struggle with regex complexity, leading to defects, performance issues, and security vulnerabilities. Researchers have proposed tools to synthesize regexes automatically, and recent advances in LLMs have also shown promise in generating regexes. Meanwhile, developers commo

Alif Al Hasan, Subarna Saha, Mia Mohammad Imran, Tarannum Shaila Zaman

Failure-inducing inputs play a crucial role in diagnosing and analyzing software bugs. Bug reports typically contain these inputs, which developers extract to facilitate debugging. Since bug reports are written in natural language, prior research has leveraged various Natural Language Processing (NLP) techniques for automated input extraction. With the adven

D. A. Bollimpalli, J. Horák, W. Kluźniak, P. C. Fragile

Orbiting matter misaligned with a spinning black hole undergoes Lense-Thirring precession, due to the frame-dragging effect. This phenomenon is particularly relevant for type-C QPOs observed in the hard states of low-mass X-ray binaries. However, the accretion flow in these hard states is complex, consisting of a geometrically thick, hot corona surrounded by

Siyuan Guo, Huiwu Liu, Xiaolong Chen, Yuming Xie

In this work, we explore the potential of large language models (LLMs) for generating functional test scripts, which necessitates understanding the dynamically evolving code structure of the target software. To achieve this, we propose a case-based reasoning (CBR) system utilizing a 4R cycle (i.e., retrieve, reuse, revise, and retain), which maintains and le

Kathryn E. Hare, Franklin Mendivil

In this paper we study the Assouad-like $\Phi$ dimensions of sets and measures that are constructed by a random weighted iterated function system of similarities. These dimensions are distinguished by the depth of the scales considered and thus provide more refined infomation about the local geometry/behaviour of a set or measure. The Assouad dimensions are

Weibing Zhang, Ruiyang Zhao, Xiaoyong Mu, Kazuya Koyama

In this work, we investigate a joint fitting approach based on theoretical models of power spectra associated with density-field reconstruction. Specifically, we consider the matter auto-power spectra before and after baryon acoustic oscillation (BAO) reconstruction, as well as the cross-power spectrum between the pre- and post-reconstructed density fields.

Xicheng Zhang

In this work, we present a theoretical and computational framework for constructing stochastic transport maps between probability distributions using diffusion processes. We begin by proving that the time-marginal distribution of the sum of two independent diffusion processes satisfies a Fokker-Planck equation. Building on this result and applying Ambrosio-F

Silvia Rudà

We present a theory of optimal control for McKean-Vlasov stochastic differential equations with infinite time horizon and discounted gain functional. We first establish the well-posedness of the state equation and of the associated control problem under suitable hypotheses for the coefficients. We then especially focus on the time invariance property of the

Vinzenz Uhr, Ivan Diaz, Christian Rummel, Richard McKinley

Cortical thickness measurements from magnetic resonance imaging, an important biomarker in many neurodegenerative and neurological disorders, are derived by many tools from an initial voxel-wise tissue segmentation. White matter (WM) hypointensities in T1-weighted imaging, such as those arising from multiple sclerosis or small vessel disease, are known to af

Thomas Krämer, Marco Maculan

We prove the Shafarevich conjecture for varieties with globally generated cotangent bundle, subject to mild numerical conditions.

Ivan Diaz, Florin Scherer, Yanik Berli, Roland Wiest

In the setting of clinical imaging, differences in between vendors, hospitals and sequences can yield highly inhomogeneous imaging data. In MRI in particular, voxel dimension, slice spacing and acquisition plane can vary substantially. For clinical applications, therefore, algorithms must be trained to handle data with various voxel resolutions. The usual st

Soumitra Ghosh, Begona Altuna, Saeed Farzi, Pietro Ferrazzi

We present E3C-3.0, a multilingual dataset in the medical domain, comprising clinical cases annotated with diseases and test-result relations. The dataset includes both native texts in five languages (English, French, Italian, Spanish and Basque) and texts translated and projected from the English source into five target languages (Greek, Italian, Polish, Sl

Nicola Mastronardi, Marc Van Barel, Raf Vandebril, Paul Van Dooren

A fast and weakly stable method for computing the zeros of a particular class of hypergeometric polynomials is presented. The studied hypergeometric polynomials satisfy a higher order differential equation and generalize Laguerre polynomials. The theoretical study of the asymptotic distribution of the spectrum of these polynomials is an active research topic

Tuan T. Tran, Per O. Å. Persson, Ngan Pham, Radek Holenak

We investigate the mobility of structural defects, adatoms, and defect-adatom combinations in self-supporting graphene subjected to keV ion irradiation. In the first scenario, homogeneous irradiation using 20 keV Ar$^+$ ions at a dose of $3 \times 10^{14}$ ions/cm$^2$ induces tensile strain of up to 0.8\%. This strain diminishes with increasing defect densit

Yantao Wu, Wen-Yuan Liu

We propose a novel tensor network method to achieve accurate and efficient simulations of Abelian lattice gauge theories (LGTs) in (2+1)D for both ground state and real-time dynamics. The first key is to identify a gauge canonical form (GCF) of gauge-invariant tensor network states, which already simplifies existing algorithms for (1+1)D LGTs. The second key

Muchun Yang, Yibin Huang, D. L. Zhou

The Heisenberg uncertainty principle imposes a fundamental restriction in quantum mechanics, stipulating that measuring one observable completely erases the information on its conjugate one, thereby preventing simultaneous measurements of incompatible observables. Quantum neural networks (QNNs) is one of the most significant applications on near-term devices

Wolfgang Bentz, Ian C. Cloët

We describe the quark substructure of hadrons and the equation of state of high density neutron star matter by using the Nambu$-$Jona-Lasinio (NJL) model, which is an effective quark theory based on QCD. The interaction between quarks fully respects the chiral and flavor symmetries. Guided by the success of various low energy theorems, we assume that the exp

Yuzhu Lei, Guanding Yu

Lithium-ion battery health management has become increasingly important as the application of batteries expands. Precise forecasting of capacity degradation is critical for ensuring the healthy usage of batteries. In this paper, we innovatively propose MSPMLP, a multi-scale capacity prediction model utilizing the mixture of experts (MoE) architecture and pat

Carlos Gomes, Benedikt Blumenstiel, Joao Lucas de Sousa Almeida, Pedro Henrique de Oliveira

TerraTorch is a fine-tuning and benchmarking toolkit for Geospatial Foundation Models built on PyTorch Lightning and tailored for satellite, weather, and climate data. It integrates domain-specific data modules, pre-defined tasks, and a modular model factory that pairs any backbone with diverse decoder heads. These components allow researchers and practition

Vo Hoang Minh Thu, Vu Mai Trang

Let $D$ be a division ring with infinite center $F$; $\sigma$ be an anti-automorphism of $D$ and $m$ be a positive integer such that $\sigma^m\neq \mathrm{Id}$. In this paper, we show that if $D$ satisfies a $\sigma^m$-GRI, then $D$ is centrally finite.

Ryumei Nakada, Wenlong Ji, Tianxi Cai, James Zou

Prompt engineering has emerged as a powerful technique for guiding large language models (LLMs) toward desired responses, significantly enhancing their performance across diverse tasks. Beyond their role as static predictors, LLMs increasingly function as intelligent agents, capable of reasoning, decision-making, and adapting dynamically to complex environme

Lawrence Choo, Senran Lin, Liangfo Zhao

This study investigates the reaction of workers to employer-sponsored general training that provides skills useful not only in the incumbent employer but also in other firms in the industry. While previous research has focused primarily on workers' responses to wage renegotiation, our work extends this understanding by exploring an additional dimension -- wo

Julian De Freitas, Noah Castelo, Bernd Schmitt, Miklos Sarvary

Humanoid robots are a form of embodied artificial intelligence (AI) that looks and acts more and more like humans. Powered by generative AI and advances in robotics, humanoid robots can speak and interact with humans rather naturally but are still easily recognizable as robots. But how will we treat humanoids when they seem indistinguishable from humans in a

Katsuki Muraoka, Naoto Kojiguchi, Junpei Ito, Daisaku Nogami

There remains debate over whether the accretion disk survives or is entirely disrupted after the nova eruption. In our previous paper, Muraoka et al. (2024, PASJ, 76, 293) have photometrically demonstrated that the surviving accretion disk was expanded close to the L1 point during the optical plateau stage and then drastically shrank to the tidal truncation

Rutwig Campoamor-Stursberg, Oscar Carballal, Francisco J. Herranz

We propose an adaptation of the notion of scaling symmetries for the case of Lie-Hamilton systems, allowing their subsequent reduction to contact Lie systems. As an illustration of the procedure, time-dependent frequency oscillators and time-dependent thermodynamic systems are analyzed from this point of view. The formalism provides a novel method for constr

Qi Jia, Xiaodian Chen, Shu Wang, Licai Deng

Previous studies of the Period--Luminosity relations (PLRs) of Delta Scuti ($\delta$ Sct) stars have focused on those with a single pulsation mode. However, for $\delta$ Sct stars with many different pulsation modes, classifying a single mode is difficult. In this study, an all-sky dataset is constructed using double-mode $\delta$ Sct stars from ZTF and OGLE

Andrei Niculae, Adrian Cosma, Emilian Radoi

Accurately mapping medical procedure names from healthcare providers to standardized terminology used by insurance companies is a crucial yet complex task. Inconsistencies in naming conventions lead to missclasified procedures, causing administrative inefficiencies and insurance claim problems in private healthcare settings. Many companies still use human re

Lea Enzi, Stefan Thonhauser

We study a stochastic differential game in a ruin theoretic environment. In our setting two insurers compete for market share, which is represented by a joint performance functional. Consequently, one of the insurers strives to maximize it, while the other seeks to minimize it. As a modelling basis we use classical surplus processes extended by dynamic reins

Remi Hendriks, Matthew Luckie, Mattijs Jonker, Raffaele Sommese

IP anycast replicates an address at multiple locations to reduce latency and enhance resilience. Due to anycast's crucial role in the modern Internet, earlier research introduced tools to perform anycast censuses. The first, iGreedy, uses latency measurements from geographically dispersed locations to map anycast deployments. The second, MAnycast2, uses anyc

Sai Venkata Ramana Ambadipudi, Albert Bae, Azam Gholami

Using multiparticle collision dynamics simulations, we investigate the swimming dynamics, orientational behavior, and hydrodynamic interactions of a model swimmer designed to mimic the isolated flagellar apparatus ($FA$) of Chlamydomonas reinhardtii. We represent the $FA$ as a chain of monomers connected by elastic springs, with two traveling waves originati

Yunkai Liang, Zhangyu Chen, Pengfei Zuo, Zhi Zhou

In large language model (LLM) serving systems, executing each request consists of two phases: the compute-intensive prefill phase and the memory-intensive decoding phase. To prevent performance interference between the two phases, current LLM serving systems typically adopt prefill-decoding disaggregation, where the two phases are split across separate machi

Alexei Kniazev

I present the results of echelle spectroscopy of a bright HII region in the irregular galaxy IC4662 and their comparison with results from long-slit spectroscopy of the same region. All observations were obtained with the standard spectrographs of the SALT telescope: (1) low and medium spectral resolution spectrograph RSS (R~800) and (2) echelle spectrograph

Tomoki Nakamigawa, Tadashi Sakuma

The pebble motion problem (PMP) asks whether one configuration of labeled pebbles on a graph can be transformed into another by moving pebbles to adjacent unoccupied vertices. It is a fundamental model of graph reconfiguration and is closely related to multi-agent path finding (MAPF). A central open problem since Kornhauser, Miller, and Spirakis (FOCS 1984)

Jun Cui

This study explores the impact of entrepreneurial motivations on ESG performance in Chinese stock exchange listed automobile companies. Using quantitative methods and empirical analysis via STATA software, the research examines baseline stability, endogeneity, heterogeneity, and mediation/moderation mechanisms. A sample of 50 firms from the Shanghai and Shen

Eberhard Klempt

Dmitri Diakonov has played a significant role in identifying the degrees of freedom underlying hadron spectroscopy. His contributions are discussed with a view on recent developments.

Baptiste Cerclé, Nathan Huguenin

This article is the second chapter of a two-part series dedicated to the mathematical study of the higher-spin symmetry enjoyed by the $\mathfrak{sl}_3$ boundary Toda Conformal Field Theory. Namely, based on a probabilistic definition of this model and building on the framework introduced in the first article of this series, we compute some singular vectors

David Fainsin, Antoine Debray, Ilya Karuseichyk, Mattia Walschaers

Large-scale operations in quantum networks require efficient sorting of desired paths between nodes. In this article, we consider entanglement routing, which involves establishing an entanglement link between specific nodes in a large network of bosonic nodes. The networks are continuous-variable graph states built from finite squeezing and passive linear op

Marlies Hafer, Alexander Marx

We consider the problem of estimating the expected causal effect $E[Y|do(X)]$ for a target variable $Y$ when treatment $X$ is set by intervention, focusing on continuous random variables. In settings without selection bias or confounding, $E[Y|do(X)] = E[Y|X]$, which can be estimated using standard regression methods. However, regression fails when systemati

Pankhuri Gupta, Kacho Imtiyaz Ali Khan, Akash Kumar, Rekha Agarwal

Spin-orbit torque (SOT) presents a promising avenue for energy-efficient spintronics devices, surpassing the limitations of spin transfer torque. While extensively studied in heavy metals, SOT in antiferromagnetic quantum materials remains largely unexplored. Here, we investigate SOT in epitaxial FeSn, a collinear antiferromagnet with a kagome lattice. FeSn

Moritz Werling, Rainer Faller, Wolfgang Betz, Daniel Straub

This paper describes the comprehensive safety framework that underpinned the development, release process, and regulatory approval of BMW's first SAE Level 3 Automated Driving System. The framework combines established qualitative and quantitative methods from the fields of Systems Engineering, Engineering Risk Analysis, Bayesian Data Analysis, Design of Exp

Yujie Shi, Alex Jie Yang, Sanhong Deng

This study investigates entropy's potential for analyzing scientific research patterns across disciplines. Originating from thermodynamics, entropy now measures uncertainty and diversity in information systems. We examine Shannon Entropy, Entropy Weight Method, Maximum Entropy Principle and structural entropy applications in scientific collaboration, knowled

Haojin Wang, Haitao Liu, Meng Ye, Yuanchang Li

Multiferroics are known to be classified into two types. However, type-I lacks sufficient magnetoelectric coupling and type-II lacks sufficient electric polarization, making both practically difficult. In this work, we explore the possibility of type-III multiferroics, where the origins of ferroelectricity and magnetism are highly intertwined but not causall

Henrik Christiansen, Takashi Maruyama, Federico Errica, Viktor Zaverkin

We present an end-to-end differentiable molecular simulation framework (DIMOS) for molecular dynamics and Monte Carlo simulations. DIMOS easily integrates machine-learning-based interatomic potentials and implements classical force fields including an efficient implementation of particle-mesh Ewald. Thanks to its modularity, both classical and machine-learni

Dingchen Yang, Bowen Cao, Anran Zhang, Weibo Gu

Multi-modal Large Langue Models (MLLMs) often process thousands of visual tokens, which consume a significant portion of the context window and impose a substantial computational burden. Prior work has empirically explored visual token pruning methods based on MLLMs' intermediate states (e.g., attention scores). However, they have limitations in precisely de