February 2025 arXiv papers — page 25

Amirhossein Bayat, Melika Emami, Rahim Tafazolli, Atta Quddus

Electrotactile feedback is a promising method for delivering haptic sensations, but challenges such as the naturalness of sensations hinder its adoption in commercial devices. In this study, we introduce a novel device that enables the exploration of complex stimulation signals to enhance sensation naturalness. We designed six stimulation signals with linear

Yusong Wang, Xinbai Li, Ziyang Li, Zebo Tang

Recent measurements by various experiments in ultra-peripheral collisions have observed spin-interference in $\rho^{0}$ photoproduction, marking a breakthrough in Fermi-scale quantum interference experiments. Building on this, STAR extended the measurement to hadronic heavy-ion collisions, where significant rescattering effects on $\rho^{0}$ mesons were expe

Piotr Sawicki, Marek Grześ, Dan Brown, Fabrício Góes

This study adapts the Consensual Assessment Technique (CAT) for Large Language Models (LLMs), introducing a novel methodology for poetry evaluation. Using a 90-poem dataset with a ground truth based on publication venue, we demonstrate that this approach allows LLMs to significantly surpass the performance of non-expert human judges. Our method, which levera

C. Basalti, G. Caldoni, S. Coppini, B. Gualandi

Research data management (RDM) strategies and practices play a pivotal role in adhering to the paradigms of reproducibility and transparency by enabling research sharing in accordance with the principles of Open Science. Discipline-specificity is an essential factor when understanding RDM declinations, to tailor a comprehensive support service and to enhance

V. D. Borisov, V. O. Yurovsky, I. A. Kudryashov

We introduce a novel diffusion model for the propagation of cosmic rays (CRs) that incorporates an anisotropic diffusion tensor of a general form within a realistically modeled large-scale Galactic magnetic field. The parameters of the model are consistent with the contemporary understanding of the large-scale Galactic magnetic field structure and the dynami

AK Yeoh, VH Hall-Chen, QT Pratt, BS Victor

We introduce a new approach to measure the magnetic pitch angle profile in tokamak plasmas with Doppler backscattering (DBS), a technique traditionally used for measuring flows and density fluctuations. The DBS signal is maximised when its probe beam's wavevector is perpendicular to the magnetic field at the cutoff location, independent of the density fluctu

Philippe Balbiani, Çigdem Gencer

We introduce an intuitionistic modal logic strictly contained in the intuitionistic modal logic IK and being an appropriate candidate for the title of ``minimal normal intuitionistic modal logic''.

M. L. H. Musa, Z. Z. Abidin, A. Annuar, D. A. A. Lee

Obscuration in active galactic nuclei (AGN) provides insights into the material surrounding the central engine. Compton-thick AGN (CTAGN), characterized by a column density of $N_{\mathrm{H}} \geq 1.5 \times 10^{24} \ \mathrm{cm}^{-2}$, are heavily obscured by dust and gas. While X-ray observations primarily determine this column density, the sub-mm obscurat

K. Bakke

We discuss the missing He-McKellar-Wilkens geometric quantum phase in Landau levels for a neutral particle with a permanent electric dipole moment in the presence of an infinity wall. We also discuss the influence of the missing He-McKellar-Wilkens geometric quantum phase on the energy levels of a neutral particle confined to a one-dimensional quantum ring.

X. Yang, L. Xu, S. Xiong, H. Rao

Optical biosensors based on micro-/nano-fibers are highly valuable for probing and monitoring liquid environments and bioactivity. Most of current optical biosensors, however, are still based on glass, semiconductors, or metallic materials, which might be not fully suited for biologically-relevant environments. Here, we introduce biocompatible and flexible m

Iliana Loi, Konstantinos Moustakas

Fatigue modeling is essential for motion synthesis tasks to model human motions under fatigued conditions and biomechanical engineering applications, such as investigating the variations in movement patterns and posture due to fatigue, defining injury risk mitigation and prevention strategies, formulating fatigue minimization schemes, and creating improved e

Vincent Foriel, Frantz Martinache, David Mary

Nulling interferometry is a promising technique for direct detection of exoplanets. However, the performance of current devices is limited by different perturbations sources and especially by its sensitivity to any phase aberrations. The work presented here attempts to overcome those limitations by using a four-telescopes nulling interferometer architecture,

Sheikh Moonsun Pervez, Saptarshi Mandal

We perform a systematic and exact study of Majorana fermion dynamics in the Kitaev-Heisenberg-$\Gamma$ model in a few finite-size clusters increasing in size up to twelve sites. We employ exact Jordan-Wigner transformations to evaluate certain measures of Majorana fermion correlation functions, which effectively capture matter and gauge Majorana fermion dyna

Satoshi Sunada, Tomoaki Niiyama, Kazutaka Kanno, Rin Nogami

The rapidly increasing computational demands for artificial intelligence (AI) have spurred the exploration of computing principles beyond conventional digital computers. Physical neural networks (PNNs) offer efficient neuromorphic information processing by harnessing the innate computational power of physical processes; however, training their weight paramet

Thi Lan Dinh, Wiebke Bennecke, G. S. Matthijs Jansen, D. Russell Luke

We report on the use of algorithms to avoid or move away from ``bad'' local minima in nonconvex optimization. Our study is phenomenological and empirical, focusing on the performance of cyclic projections, the cyclic relaxed Douglas-Rachford algorithm, and relaxed Douglas-Rachford splitting on the product space for orbital tomographic imaging from an

Yuri Sato, Kohta Murase, Yutaka Ohira, Susumu Inoue

In recent years, afterglow emission in the very-high-energy (VHE) band above 100 GeV has been clearly detected for at least five gamma-ray bursts (GRBs 180720B, 190114C, 190829A, 201216C and 221009A). For some of these VHE GRBs, we previously proposed a two-component jet model, consisting of two uniform jets with narrow and wide opening angles to explain the

Moshe Babaioff, Yiding Feng, Noam Manaker Morag

We consider the impact of fairness requirements on the social efficiency of truthful mechanisms for trade, focusing on Bayesian bilateral-trade settings. Unlike the full information case in which all gains-from-trade can be realized and equally split between the two parties, in the private information setting, equitability has devastating welfare implication

Tresor Y. Koffi, Youssef Mourchid, Mohammed Hindawi, Yohan Dupuis

Detecting impact where an individual makes contact with the ground within a fall event is crucial in fall detection systems, particularly for elderly care where prompt intervention can prevent serious injuries. The UP-Fall dataset, a key resource in fall detection research, has proven valuable but suffers from limitations in data accuracy and comprehensivene

Vu Tuan Truong, Long Bao Le

Diffusion models have emerged as state-of-the-art generative frameworks, excelling in producing high-quality multi-modal samples. However, recent studies have revealed their vulnerability to backdoor attacks, where backdoored models generate specific, undesirable outputs called backdoor target (e.g., harmful images) when a pre-defined trigger is embedded to

Ibrahim Nali, Attila Dénes, Abdessamad Tridane, Xueyong Zhou

This research gives a thorough examination of an HIV infection model that includes quiescent cells and immune response dynamics in the host. The model, represented by a system of ordinary differential equations, captures the complex interaction between the host's immune response and viral infection. The study focuses on the model's fundamental aspects, such

Jiebin Yan, Ziwen Tan, Yuming Fang, Jiale Rao

Omnidirectional image, also called 360-degree image, is able to capture the entire 360-degree scene, thereby providing more realistic immersive feelings for users than general 2D image and stereoscopic image. Meanwhile, this feature brings great challenges to measuring the perceptual quality of omnidirectional images, which is closely related to users' quali

Valeria Zelina Reyna Ortiz, Maciej Rybczynski, Zbigniew Wlodarczyk

The investigation of remnants associated with the QCD chiral critical point is a primary objective in high-energy ion collision experiments. Numerous studies indicate that a scaling relation between higher-order factorial moments of hadron multiplicity distributions and the second factorial moment may serve as a diagnostic tool for identifying the QCD critic

Rinske M. Alkemade, Rastko Sknepnek, Frank Smallenburg, Laura Filion

Machine learning (ML) strategies are opening the door to faster computer simulations, allowing us to simulate more realistic colloidal systems. Since the interactions in colloidal systems are often highly many-body, stemming from e.g. depletion and steric interactions, one of the challenges for these algorithms is capturing the many-body nature of these inte

Nahyeon Lee, Jongsoo Lim, Mina Choi, Hyeong-Chai Jeong

This study explores global video on demand content consumption patterns through a network-based approach. We used Netflix's 'TV-shows' ranking data, spanning 822 days across 71 countries, to construct a network where countries are represented as nodes and consumption similarities are reflected as link weights. By applying the Louvain algorithm, we identified

Norbert Bodendorfer

Accurate and reliable air pollution forecasting is crucial for effective environmental management and policy-making. llull-environment is a sophisticated and scalable forecasting system for air pollution, inspired by previous models currently operational in Madrid and Valladolid (Spain). It contains (among other key components) an encoder-decoder convolution

Shiyu Xiang, Ansen Zhang, Yanfei Cao, Yang Fan

Although Aligned Large Language Models (LLMs) are trained to refuse harmful requests, they remain vulnerable to jailbreak attacks. Unfortunately, existing methods often focus on surface-level patterns, overlooking the deeper attack essences. As a result, defenses fail when attack prompts change, even though the underlying "attack essence" remains the same. T

Ce Zhang, Heng Lu, Chen Yang, YuBin Zhang

Nanomechanical resonators driven by multifrequency signals combine the physics of mesoscopic vibrations and the technologies of radio communication. Their simplest property stems from their resonant response: they behave as filters, responding only to driving signals whose frequency range is contained within that of the mechanical response. While the respons

Lars Schroeder, Clara Stegehuis

The node2vec random walk has proven to be a key tool in network embedding algorithms. These random walks are tuneable, and their transition probabilities depend on the previous visited node and on the triangles containing the current and the previously visited node. Even though these walks are widely used in practice, most mathematical properties of node2vec

Anju Rani, Daniel O. Arroyo, Petar Durdevic

The effectiveness of zero-shot classification in large vision-language models (VLMs), such as Contrastive Language-Image Pre-training (CLIP), depends on access to extensive, well-aligned text-image datasets. In this work, we introduce two complementary data sources, one generated by large language models (LLMs) to describe the stages of fungal growth and ano

Pu Wang, Huaizhi Ma, Zhihua Zhang, Zhuoran Zheng

Accurate polyp segmentation remains challenging due to irregular lesion morphologies, ambiguous boundaries, and heterogeneous imaging conditions. While U-Net variants excel at local feature fusion, they often lack explicit mechanisms to model the dynamic evolution of segmentation confidence under uncertainty. Inspired by the interpretable nature of flow-base

Daniël M. H. van Gent

This document contains notes based on lectures given by Hendrik Lenstra at the PCMI summer school 2022. There are many problems in algebraic number theory which one would like to solve algorithmically, for example computation of the maximal order $\mathcal{O}$ of a number field, and the many problems that are most often stated only for $\mathcal{O}$, such as

Jin Cai, Bo Zhou

Let $G$ be a nontrivial graph with minimum degree $\delta$ and $k$ an integer with $k\ge 2$. In the literature, there are eigenvalue conditions that imply $G$ contains $k$ edge-disjoint spanning trees. We give eigenvalue conditions that imply $G$ contains $k$ edge-disjoint spanning trees and another forest $F$ with $|E(F)|>\frac{\delta-1}{\delta}(|V(G)|-1)$,

L. Beirão da Veiga, F. Dassi, S. Gómez

We carry out a stability and convergence analysis of a fully discrete scheme for the time-dependent Navier-Stokes equations resulting from combining an $H(\mathrm{div}, \Omega)$-conforming discontinuous Galerkin spatial discretization, and a discontinuous Galerkin time stepping scheme. Such a scheme is proven to be pressure robust and Reynolds semi-robust. S

Xiao-Ming Huang, Ying Zhao, Xiaowen Hao, Hua-You Xiang

Designing the high performance magneto or elastocaloric effect in NiMnIn alloys with spin-lattice coupling in a deep freezing temperature range of 200 K to 255 K is challenging due to the limited lattice entropy change and large negative contribution of magnetic entropy change during phase transitions. In this work, we systematically study the first order ma

E. A. Nesterova, S. B. Korolev

We propose a protocol for tridirectional quantum teleportation in continuous variables. A special feature of the protocol is the possibility to choose one of three scenarios: simultaneous exchange between three participants, exchange between any two participants, or the transfer of two states to a third participant. We use a cluster state in continuous varia

Lei Xiao, Shuo Yang, Wen Chen, Zibin Zheng

The non-fungible tokens (NFTs) market has evolved over the past decade, with NFTs serving as unique digital identifiers on a blockchain that certify ownership and authenticity. However, their high value also attracts attackers who exploit vulnerabilities in NFT smart contracts for illegal profits, thereby harming the NFT ecosystem. One notable vulnerability

Oliver Clarke, Alexander Milner

We introduce the package allMarkovBases for Macaulay2, which is used to compute all minimal Markov bases of a given toric ideal. The package builds on functionality of 4ti2 by producing the fiber graph of the toric ideal. The package uses this graph to compute other properties of the toric ideal such as its indispensable set of binomials as well as its unive

Kazuki Nakajima, Masanao Kodakari, Masaki Aida

Hypergraphs provide a fundamental framework for representing complex systems involving interactions among three or more entities. As empirical hypergraphs grow in size, characterizing their structural properties becomes increasingly challenging due to computational complexity and, in some cases, restricted access to complete data, requiring efficient samplin

Hamed Hellaoui, Matti Laitila, Markus Isomäki, Hua Chao

The upcoming generation of mobile telecommunication systems is expected to support new use cases, where the mobile network serves one or more IP subnetworks located behind the User Equipment (UEs). This would create new challenges for the mobile system to efficiently serve such behind-UE subnetworks, as the latter are commonly not visible to the mobile syste

Longxiang Fan, Shichang Song

We give a new proof of the Weyl-von Neumann-Berg theorem. Our proof improves Halmos' proof in 1972 by observing the fact that every compact set in the complex plane is the continuous image of a compact set in the real line.

Kirill Krasnov, Adam Shaw

As is very well-known, linearisation of the instanton equations on a 4-manifold gives rise to an elliptic complex of differential operators, the truncated (twisted) Hodge complex $\Lambda^0(\mathfrak{g}) \to \Lambda^1(\mathfrak{g})\to \Lambda^2_+(\mathfrak{g})$. Moreover, the linearisation of the full YM equations also fits into this framework, as it is give

Fengbin Guan, Zihao Yu, Yiting Lu, Xin Li

Video quality assessment tasks rely heavily on the rich features required for video understanding, such as semantic information, texture, and temporal motion. The existing video foundational model, InternVideo2, has demonstrated strong potential in video understanding tasks due to its large parameter size and large-scale multimodal data pertaining. Building

A. B. Swain, J. Kuttruff, J. Vorberger, P. Baum

Electron-hole pairs in semiconductors are essential for solar cells and fast electronic circuitry, but the competition between carrier transport and relaxation into heat limits the efficiency and speed. Here we use ultrafast electron diffraction with terahertz pulse compression to measure the electron-phonon decay rate in single-crystal silicon as a function

Zerui Li, Gengze Zhou, Haodong Hong, Yanyan Shao

Vision-and-Language Navigation (VLN) empowers agents to associate time-sequenced visual observations with corresponding instructions to make sequential decisions. However, generalization remains a persistent challenge, particularly when dealing with visually diverse scenes or transitioning from simulated environments to real-world deployment. In this paper,

Anastasios Nentidis, Charilaos Akasiadis, Angelos Charalambidis, Alexander Artikis

In Knowledge Graphs (KGs), where the schema of the data is usually defined by particular ontologies, reasoning is a necessity to perform a range of tasks, such as retrieval of information, question answering, and the derivation of new knowledge. However, information to populate KGs is often extracted (semi-) automatically from natural language resources, or

James Hefford, Matt Wilson

We use the Chu construction to functorially build BV-categories from duoidal categories, demonstrating that candidate models of BV-logic can be cofreely constructed from a fragment of a model of Retor\'e's sequencing operator. By using this construction to show that the strong Hyland envelope is a BV-category, we find a way to build a canonical model of spat

B. Fromont, J. De Rosny, R. Pascaud, N. Lebbe

Overcoming the diffraction limit, meaning focusing waves on a sub-wavelength scale, has received considerable attention for applications involving light and acoustics. Indeed, the intense focusing achieved enhances the interactions between waves and matter, and the improved spatial resolution opens up possibilities in fields such as imaging, detection and co

Yu Liu, Baoxiong Jia, Ruijie Lu, Junfeng Ni

Building articulated objects is a key challenge in computer vision. Existing methods often fail to effectively integrate information across different object states, limiting the accuracy of part-mesh reconstruction and part dynamics modeling, particularly for complex multi-part articulated objects. We introduce ArtGS, a novel approach that leverages 3D Gauss

Marcin Hoffmann

One of the main challenges associated with the implementation of an Open RAN User-Centric Cell-Free network is the appropriate formulation of serving clusters. This problem can be effectively solved using a proposed algorithm that leverages cooperation between xApp and rApp. Simulation results have shown that the proposed solution allows for a 16% increase i

Simon Brandhorst, Matthias Zach

We derive explicit equations for the Oguiso-Yu automorphism of minimum topological entropy on a complex Enriques surface. The approach is computer aided and makes use of elliptic fibrations.

Deepanshu Aggarwal, Rohit Narula, Sankalpa Ghosh

Supermoir\'e structures (SMS), formed by overlapping moir\'e-patterns in van der Waals heterostructures, display complex behaviour that lacks a comprehensive low-energy theoretical description. We demonstrate that these structures can form emergent fractals under specific conditions and identify the parameter space where this occurs in hexagonal trilateral S

M. D. Sreelakshmi, N. Sinthuja, N. Vishnu Priya, M. Senthilvelan

The nonlocal nonlinear evolution equations describe phenomena in which wave evolution is influenced by local and nonlocal spatial and temporal variables. These equations have opened up a new wave of physically important nonlinear evolution equations. Their solutions provide insights into the interplay between nonlinearity and nonlocality, making it a corners

Romuald A. Janik

We argue that the Ising model CFT can be used to obtain some clear insights into 3D (quantum) gravity with matter. We review arguments for the existence of its holographic description, and concentrate on the time dependence of perturbations of the theory at high temperature, which would correspond to throwing matter into a black hole in the dual picture. Apa

Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas

This paper utilizes the properties of type-based multiple access (TBMA) to investigate its effectiveness as a robust approach for over-the-air computation (AirComp) in the presence of Byzantine attacks, this is, adversarial strategies where malicious nodes intentionally distort their transmissions to corrupt the aggregated result. Unlike classical direct agg

Francisco S. Cuesta, Karim Achouri

The general approach in metasurface design is to find the unit-cell properties required to achieve a given functionality. This is usually done by modeling the metasurface as a combination of surface electric and magnetic polarization densities, whose parameters are determined by solving the generalized sheet transition conditions. This is a time consuming ta

Nils-Christian Kempke, Tim Kunt, Bassel Katamish, Charlie Vanaret

Shifting towards renewable energy sources and reducing carbon emissions necessitate sophisticated energy system planning, optimization, and extension. Energy systems optimization models (ESOMs) often form the basis for political and operational decision-making. ESOMs are frequently formulated as linear (LPs) and mixed-integer linear (MIP) problems. MIPs allo

M. Stangalini, G. Verth, V. Fedun, D. Perrone

In addition to sunspots, which represent the most easily visualized manifestation of solar magnetism, cutting-edge observations of the solar atmosphere have uncovered a plethora of magnetic flux tubes, down to the resolving power of modern high-resolution telescopes (a few tens of km), revealing how the Sun is a fully magnetized star. These magnetic elements

Lynda R Hutcheson, Maximilian Hartmann, Gergana D Borisova, Paul Birk

We investigate the time-dependent evolution of the dipole phase shift induced by strong-field ionization (SFI) using attosecond transient absorption spectroscopy (ATAS) for time-delays where the pump-probe pulses overlap. We study measured and calculated time-dependent ATA spectra of the ionic 4d-5p transition in xenon, and present the time-dependent line sh

Jaehyeon Son, Soochan Lee, Gunhee Kim

Recent studies have shown that Transformers can perform in-context reinforcement learning (RL) by imitating existing RL algorithms, enabling sample-efficient adaptation to unseen tasks without parameter updates. However, these models also inherit the suboptimal behaviors of the RL algorithms they imitate. This issue primarily arises due to the gradual update

Liangdong Liu, Zhitong Zheng, Cong Wang, Tianhuang Su

Large language models (LLMs) have wide applications in the field of natural language processing(NLP), such as GPT-4 and Llama. However, with the exponential growth of model parameter sizes, LLMs bring significant resource overheads. Low-bit quantization, as a key technique, reduces memory usage and computational demands by decreasing the bit-width of model p

Sainan Peng, Yudong Chen, Yang Li, Guangyu Fan

By employing two-color counter-rotating circularly polarized laser fields, we investigate the dynamics of electron recapture into Rydberg states under strong, ultrashort laser pulses, probed via coherent extreme-ultraviolet free-induction decay (XFID). Our study reveals significant distinctions between XFID and above-threshold high-order harmonic generation

Shogo Iwazaki

We study the noise-free Gaussian Process (GP) bandits problem, in which the learner seeks to minimize regret through noise-free observations of the black-box objective function lying on the known reproducing kernel Hilbert space (RKHS). Gaussian process upper confidence bound (GP-UCB) is the well-known GP-bandits algorithm whose query points are adaptively c

Abhishek Harikrishnan, Adrien Lopez, Bérengère Dubrulle

To address the possible occurrence of a Finite-Time Singularity (FTS) during the oblique reconnection of two vortex rings, Moffatt-Kimura (MK) (J. Fluid Mech., 2019a; J. Fluid Mech., 2019b) developed a simplified model based on the Biot-Savart law and claimed that the vorticity amplification $\omega_{\text{max}}/\omega_0$ becomes very large for vortex Reynol

Ben Goertzel

We present a conceptual framework for extending homomorphic encryption beyond arithmetic or Boolean operations into the domain of intuitionistic logic proofs and, by the Curry-Howard correspondence, into the domain of typed functional programs. We begin by reviewing well-known homomorphic encryption schemes for arithmetic operations, and then discuss the ada

Nahom Abishu Hayla, A. Mohammed Seid, Aiman Erbad, Tilahun M. Getu

Although multi-tier vehicular Metaverse promises to transform vehicles into essential nodes -- within an interconnected digital ecosystem -- using efficient resource allocation and seamless vehicular twin (VT) migration, this can hardly be achieved by the existing techniques operating in a highly dynamic vehicular environment, since they can hardly balance m

Taj Munir, Nagaiah Chamakuri, Gerald Warnecke

This paper introduces improved numerical techniques for addressing numerical boundary and interface coupling conditions in the context of diffusion equations in cellular biophysics or heat conduction problems in fluid-structure interactions. Our primary focus is on two critical numerical aspects related to coupling conditions: the preservation of the conserv

Jinbo Wang, Mingze Wang, Zhanpeng Zhou, Junchi Yan

Transformers consist of diverse building blocks, such as embedding layers, normalization layers, self-attention mechanisms, and point-wise feedforward networks. Thus, understanding the differences and interactions among these blocks is important. In this paper, we uncover a clear Sharpness Disparity across these blocks, which emerges early in training and in

Lusine Tsarukyan, Anahit Badalyan, Rafael Drampyan

A novel non-invasive microscopy technique for imaging and sizing of folded DNA molecules with the use of photovoltaic tweezers and phase-sensitive detection is elaborated and realized. This novel method is compared with the state-of-the-art method of visualization of DNA molecules by fluorescent microscopy technique which requires the labeling of the DNA by

Vinay Kulkarni, V. V. Reddy, Neha Maheshwari

This paper presents a novel radar signal detection pipeline focused on detecting large targets such as cars and SUVs. Traditional methods, such as Ordered-Statistic Constant False Alarm Rate (OS-CFAR), commonly used in automotive radar, are designed for point or isotropic target models. These may not adequately capture the Range-Doppler (RD) scattering patte

Boštjan Gabrovšek, Matic Simonič

We model proteins with intramolecular bonds, such as disulfide bridges, using the concept of bonded knots -- closed loops in three-dimensional space equipped with additional bonds that connect different segments of the knot. We extend the Kauffman bracket polynomial (which is closely related to the Jones polynomial) to bonded knots through the introduction o

Edgar Ivan Sanchez Medina, Kai Sundmacher

Predictive thermodynamic models are crucial for the early stages of product and process design. In this paper the performance of Graph Neural Networks (GNNs) embedded into a relatively simple excess Gibbs energy model, the extended Margules model, for predicting vapor-liquid equilibrium is analyzed. By comparing its performance against the established UNIFAC

Philippe Blondeel, Filip Van Utterbeeck, Ben Lauwens

Modelling and simulating mine countermeasures search missions performed by autonomous vehicles equipped with a sensor capable of detecting mines at sea is a challenging endeavour. The output of our stochastic optimal control implementation consists of an optimal trajectory in a square domain for the autonomous vehicle such that the total mission time is mini

Kun Chen-Hu, Kristian S. Jensen, Petar Popovski

The integration of quantum communication protocols over Ethernet networks is proposed, showing the potential of combining classical and quantum technologies for efficient, scalable quantum networking. By leveraging the inherent strengths of Ethernet, such as addressing, MAC layer functionality, and scalability; we propose a practical framework to support the

Yue-Liang Wu

A General Theory of the Standard Model (GSM) is built in a spin-related gravigauge spacetime, based on the conformal inhomogeneous spin gauge symmetry WS$_c$(1,3)=SP(1,3)$\rtimes$W$^{1,3}$$\rtimes$SP$_c$(1,1) and the scaling gauge symmetry SG(1), alongside the Standard Model symmetry U$_Y$(1)$\times$SU$_L$(2)$\times$SU(3)$_c$. This framework introduces novel

Sharmistha Chattopadhyay, Krishnamoorthi J, Anuj Kumar Upadhyay

The IceCube Neutrino Observatory is an optical Cherenkov detector instrumenting one cubic kilometer of ice at the South Pole. The Cherenkov photons emitted following a neutrino interaction are detected by digital optical modules deployed along vertical strings within the ice. The densely instrumented bottom central region of the IceCube detector, known as De

Weilin Chen, Ruichu Cai, Yuguang Yan, Zhifeng Hao

Long-term causal inference is an important but challenging problem across various scientific domains. To solve the latent confounding problem in long-term observational studies, existing methods leverage short-term experimental data. Ghassami et al. propose an approach based on the Conditional Additive Equi-Confounding Bias (CAECB) assumption, which asserts

Teng Lin, Yuyu Luo, Honglin Zhang, Jicheng Zhang

Multi-entity question answering (MEQA) represents significant challenges for large language models (LLM) and retrieval-augmented generation (RAG) systems, which frequently struggle to consolidate scattered information across diverse documents. While existing methods excel at single-document comprehension, they often struggle with cross-document aggregation,

Hui Feng, Yuntzu Yin, Emiliano Reynares, Jay Nanavati

Biomedical ontologies, which comprehensively define concepts and relations for biomedical entities, are crucial for structuring and formalizing domain-specific information representations. Biomedical code mapping identifies similarity or equivalence between concepts from different ontologies. Obtaining high-quality mapping usually relies on automatic generat

Greg Bowen, Simon Devitt

This paper is a general introduction to the t\={u}Q toolchain (https://github.com/QSI-BAQS/tuQ) and a discussion of its two main workflows, 'reduce and optimise' and 'draft and compile'. The t\={u}Q toolchain was designed to advance research in cluster-state computing and the workflows are presented as suggestions for how a researcher might use the tool. The

Jie He, Jennifer Neville, Mengting Wan, Longqi Yang

Large Language Models (LLMs) can enhance their capabilities as AI assistants by integrating external tools, allowing them to access a wider range of information. While recent LLMs are typically fine-tuned with tool usage examples during supervised fine-tuning (SFT), questions remain about their ability to develop robust tool-usage skills and can effectively

Jiachang Bi, Ruyi Zhang, Xiong Yao, Yanwei Cao

The advancement of semiconductor materials has played a crucial role in the development of electronic and optical devices. However, scaling down semiconductor devices to the nanoscale has imposed limitations on device properties due to quantum effects. Hence, the search for successor materials has become a central focus in the fields of materials science and

Cesare Carissimo, Marcin Korecki, Damian Dailisan

Varied real world systems such as transportation networks, supply chains and energy grids present coordination problems where many agents must learn to share resources. It is well known that the independent and selfish interactions of agents in these systems may lead to inefficiencies, often referred to as the `Price of Anarchy'. Effective interventions that

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The $\Xi_c^+ \pi^- \pi^+$ spectrum is investigated using proton-proton collisions at a center-of-mass energy of 13TeV, corresponding to an integrated luminosity of 5.4fb$^{-1}$, collected by the LHCb experiment during 2016--2018. Four states are observed with high significance, and their masses and widths are measured to be \begin{align*} m[\Xi_c(2815)^{+}]

Bram van Dartel, Marc Damie, Florian Hahn

Among all privacy attacks against Machine Learning (ML), membership inference attacks (MIA) attracted the most attention. In these attacks, the attacker is given an ML model and a data point, and they must infer whether the data point was used for training. The attacker also has an auxiliary dataset to tune their inference algorithm. Attack papers commonly s

Greg Bowen, Athena Caesura, Simon Devitt, Madhav Krishnan Vijayan

The algorithm-specific graph and circuit etching are two strategies for compiling a graph state to implement quantum computation. Benchmark testing exposed limitations to the proto-compiler, Jabalizer giving rise to Etch (https://github.com/QSI-BAQS/Etch), an open-source, circuit-etching tool for transpiling a quantum circuit to a graph state. The viability

Cesare Carissimo, Jan Nagler, Heinrich Nax

We investigate the dynamics of Q-learning in a class of generalized Braess paradox games. These games represent an important class of network routing games where the associated stage-game Nash equilibria do not constitute social optima. We provide a full convergence analysis of Q-learning with varying parameters and learning rates. A wide range of phenomena

Cristian Sestito, Ahmed J. Abdelmaksoud, Shady Agwa, Themis Prodromakis

The Von Neumann bottleneck, which relates to the energy cost of moving data from memory to on-chip core and vice versa, is a serious challenge in state-of-the-art AI architectures, like Convolutional Neural Networks' (CNNs) accelerators. Systolic arrays exploit distributed processing elements that exchange data with each other, thus mitigating the memory cos

D. Hareb, J. Martinet, B. Miramond

Achieving optimal semantic segmentation with frame-based vision sensors poses significant challenges for real-time systems like UAVs and self-driving cars, which require rapid and precise processing. Traditional frame-based methods often struggle to balance latency, accuracy, and energy efficiency. To address these challenges, we leverage event streams from

Heyao Wang, Ziran Zhao, Lingbo Qiao, Dalu Guo

Millimeter-wave (MMW) technology has been widely utilized in human security screening applications due to its superior penetration capabilities through clothing and safety for human exposure. However, existing methods largely rely on fixed polarization modes, neglecting the potential insights from variations in target echoes with respect to incident polariza

Qiancheng Xu, Yongqi Li, Heming Xia, Fan Liu

Tool learning has emerged as a promising direction by extending Large Language Models' (LLMs) capabilities with external tools. Existing tool learning studies primarily focus on the general-purpose tool-use capability, which addresses explicit user requirements in instructions. However, they overlook the importance of personalized tool-use capability, leadin

Romain Edmond Lacoste

This paper introduces Sparklen, a statistical learning toolkit for Hawkes processes in Python, designed to bring together efficiency and ease of use. The purpose of this package is to provide the Python community with a complete suite of cutting-edge tools specifically tailored for the study of exponential Hawkes processes, with a particular focus on highdim

Hongyi Cai, Jie Li, Mohammad Mahdinur Rahman, Wenzhen Dong

The effectiveness of instruction fine-tuning for Large Language Models is fundamentally constrained by the quality and efficiency of training datasets. This work introduces Low-Confidence Gold (LCG), a novel filtering framework that employs centroid-based clustering and confidence-guided selection for identifying valuable instruction pairs. Through a semi-su

A. Hu, Y. Cheng, L. Zhang, S. Morita

In Experimental Advanced Superconducting Tokamak (EAST tokamak) with tungsten divertors and molybdenum first wall, lithiumization and boronization have been frequently carried out to improve the plasma performance, in particular, in long pulse discharges. A study on impurity behaviors of lithium, boron and tungsten atoms/ions in the edge plasma is then cruci

Seung Uk Jang

Let $X_D^\ast$ be the non-singuar locus of the Markoff surface $X_D\colon x^2+y^2+z^2=xyz+D$ and consider the set of its $p$-adic integer points $X_D^\ast(\mathbb{Z}_p)$. It is known to Bourgain, Gamburd, and Sarnak that the modulo $p$ transitivity by algebraic automorphisms of $X_0^\ast$ implies minimality of $X_0^\ast(\mathbb{Z}_p)$ by algebraic automorphi

Siva Anantharaman, Sabine Frittella, Benjamin Nguyen

We introduce a logical framework named Distributed Labeled Tagged Transition System (DLTTS), using concepts from Probabilistic Automata, Probabilistic Concurrent Systems, and Probabilistic labelled transition systems. We show that DLTTS can be used to formally model how a given piece of private information P (e.g., a set of tuples) stored in a given database

Viktor Rogowski, Angelica Svalkvist, Matteo Maspero, Tomas Janssen

Background: Deep learning (DL)-based organ segmentation is increasingly used in radiotherapy, yet voxel-wise DL uncertainty maps are rarely presented to clinicians. Purpose: This study assessed how DL-generated uncertainty maps impact radiation oncologists during manual correction of prostate radiotherapy DL segmentations. Methods: Two nnUNet models were tra

Kim G. Larsen, Martin Zimmermann

Inspired by Martin Fr\"anzle's persistent and influential work on capturing and handling delay inherent to cyber-physical systems in the formal verification of such systems, we study timed games where controllable actions do not take effect immediately, but only after some delay, i.e., they are scheduled for later execution. We show that solving such games i

Patrick G. J. Irwin, Daniel D. Wenkert, Amy A. Simon, Emma Dahl

Using a newly developed `holistic' atmospheric model of the aerosol structure in Uranus's atmosphere, based upon observations made by HST/STIS, Gemini/NIFS and IRTF/SpeX from 2000 -- 2009, we make a new estimate the bolometric Bond albedo of Uranus during this time of $A^* = 0.338 \pm 0.011$, with a phase integral of $q^* = 1.36 \pm 0.03$. Then, using a simp

Jinyuan Chang, Qiao Hu, Zhentao Shi, Jia Zhang

Economic and financial models -- such as vector autoregressions, local projections, and multivariate volatility models -- feature complex dynamic interactions and spillovers across many time series. These models can be integrated into a unified framework, with high-dimensional parameters identified by moment conditions. As the number of parameters and moment

Margaret Li, Sneha Kudugunta, Luke Zettlemoyer

Modern foundation models rely heavily on using scaling laws to guide crucial training decisions. Researchers often extrapolate the optimal architecture and hyper parameters settings from smaller training runs by describing the relationship between, loss, or task performance, and scale. All components of this process vary, from the specific equation being fit