December 2024 arXiv papers — page 2

I. Kasik, I. Barton, M. Kamradek, O. Podrazky

Specialty optical fibres, usually the silica-based ones doped with rare-earth ions, have been heart of fibre amplifiers and lasers spread thanks to work of team of Sir David N. Payne started in 1980-ies of 20th century. Wavelength of their emission depends on used rare earth, on glass matrix in which the rare earths are incorporated, on fibre structure in ma

Antoni Wadowski, Anshul D. S. Parmar, Filip Kaśkosz, Jesper Byggmästar

Interatomic potentials are key to uncovering microscopic structure-property relationships, essential for multiscale simulations and high-throughput experiments. For metallic glasses, their disordered atomic structure makes the development of potentials particularly challenging, resulting in the scarcity of chemistry-specific parametrizations for this importa

Yi Zhang, Mohamadamin Rajabinezhad, Yichao Wang, Junbo Zhao

This paper introduces a novel, fully distributed control framework for DC microgrids, enhancing resilience against exponentially unbounded false data injection (EU-FDI) attacks. Our framework features a consensus-based secondary control for each converter, effectively addressing these advanced threats. To further safeguard sensitive operational data, a priva

Sebastian Jaskiewicz, Stephen Jones, Robert Szafron, Yannick Ulrich

The leading and next-to-leading order QCD predictions for Higgs boson pair production at hadron colliders suffer from a significant mass renormalisation scheme uncertainty related to the choice of the top-quark mass. The functional dependence of the result on the value of the intermediate quark mass can be understood in the high-energy limit using the Method

Asha V, Bhavanishankar K

Lung cancer is an extremely lethal disease primarily due to its late-stage diagnosis and significant mortality rate, making it the major cause of cancer-related demises globally. Machine Learning (ML) and Convolution Neural network (CNN) based Deep Learning (DL) techniques are primarily used for precise segmentation and classification of cancerous nodules in

Edgar Guzman, Robert D. Howe

The unpredictable nature of outdoor settings introduces numerous safety concerns, making hazard detection crucial for safe navigation. This paper introduces a novel system for sidewalk safety navigation utilizing a hybrid approach that combines a Variational Autoencoder (VAE) with a One-Class Support Vector Machine (OCSVM). The system is designed to detect a

Zhenpeng Huang, Xinhao Li, Jiaqi Li, Jing Wang

Multimodal Large Language Models (MLLMs) have significantly progressed in offline video understanding. However, applying these models to real-world scenarios, such as autonomous driving and human-computer interaction, presents unique challenges due to the need for real-time processing of continuous online video streams. To this end, this paper presents syste

Torey Hilbert, Steven MacEachern, Yuan Zhang

Recently, there has been growing concern about heavy-tailed and skewed noise in biological data. We introduce RobustPALMRT, a flexible permutation framework for testing the association of a covariate of interest adjusted for control covariates. RobustPALMRT controls type I error rate for finite-samples, even in the presence of heavy-tailed or skewed noise. T

Federica Giacchino, Giovanni La Mura, Stefano Ciprini, Dario Gasparrini

3C 216 is an extragalactic radio source classified as a compact steep spectrum (CSS) object, associated with the source 4FGL J0910.0+4257 detected by the Large Area Telescope (LAT) on board the Fermi Gamma-ray Space Telescope. The source exhibits extended radio structures as well as an inner relativistic jet. In general, jets accelerated by active galactic n

Yipeng Kang, Junqi Wang, Yexin Li, Mengmeng Wang

As large language models (LLMs) become increasingly integrated into critical applications, aligning their behavior with human values presents significant challenges. Current methods, such as Reinforcement Learning from Human Feedback (RLHF), typically focus on a limited set of coarse-grained values and are resource-intensive. Moreover, the correlations betwe

Aidan Botkin, Madeline L. Dawsey, David J. Hemmer, Matthew R. Just

We make an application of ideas from partition theory to a problem in multiplicative number theory. We propose a deterministic model of prime number distribution, from first principles related to properties of integer partitions, that naturally predicts the prime number theorem as well as the twin prime conjecture. The model posits that, for $n\geq 2$, $$p_{

Anton T. Than, Yasar Y. Atas, Abhijit Chakraborty, Jinglei Zhang

The quantum chromodynamics (QCD) phase diagram, which reveals the state of strongly interacting matter at different temperatures and densities, is key to answering open questions in physics, ranging from the behavior of particles in neutron stars to the conditions of the early universe. However, classical simulations of QCD face significant computational bar

Alan D. Miller

I propose a model of aggregation of intervals relevant to the study of legal standards of tolerance. Seven axioms: responsiveness, anonymity, continuity, strategyproofness, and three variants of neutrality are then used to prove several important results about a new class of aggregation methods called endpoint rules. The class of endpoint rules includes extr

Natália Bátorová, Stevan Gajović

Arithmetic-geometric mean sequences were already studied over real and complex numbers, and recently, Michael J. Griffin, Ken Ono, Neelam Saikia and Wei-Lun Tsai considered them over finite fields $\mathbb{F}_q$ such that $q \equiv 3 \pmod 4$. In this paper, we extend the definition of arithmetic-geometric mean sequences over $\mathbb{F}_q$ such that $q \equ

Antoni Kijowski, Sebastiano Nicolussi Golo, Ben Warhurst

We characterize smooth maps between sub-Riemannian Lie groups that commute with sub-Laplacians. We show they are sub-Riemannian conformal submersions. Our work clarifies the analysis initiated on Carnot groups in \cite{MR2363343}. In particular, we show that the sub-Laplacian in a Carnot group determines the sub-Riemannian structure.

Dennis Delali Kwesi Wayo, Leonardo Goliatt, Darvish Ganji

Photocatalytic water splitting has emerged as a sustainable pathway for hydrogen production, leveraging sunlight to drive chemical reactions. This review explores the integration of density functional theory (DFT) with machine learning (ML) to accelerate the discovery, optimization, and design of photocatalysts. DFT provides quantum-mechanical insights into

Xinhao Li, Yi Wang, Jiashuo Yu, Xiangyu Zeng

Long-context video modeling is critical for multimodal large language models (MLLMs), enabling them to process movies, online video streams, and so on. Despite its advances, handling long videos remains challenging due to the difficulty in efficiently understanding the extremely long video context. This paper aims to address this issue from aspects of model

Dennis Delali Kwesi Wayo, Vladislav Kudryashov, Mirat Karibayev, Gertrude Ellen Fynn

This study presents a comprehensive numerical analysis of a quantum-dot-engineered heterostructure, PbS:$Yb^{3+},Er^{3+}$/CuBiO, optimized for water splitting applications. Using density functional theory (DFT) coupled with machine learning, the study explores the electronic, optical, and catalytic properties of the material. The optimized PbS structure exhi

Xi Chen, Fa-Jie Wang, Zhen Bi, Zhi-Da Song

Ensembles that respect symmetries on average exhibit richer topological states than those in pure states with exact symmetries, leading to the concept of average symmetry-protected topological states (ASPTs). The free-fermion counterpart of ASPT is the so-called statistical topological insulator (STI) in disordered ensembles. In this work, we demonstrate the

Chengcheng Mai, Yuxiang Wang, Ziyu Gong, Hanxiang Wang

Document-level relation extraction (Doc-RE) aims to extract relations between entities across multiple sentences. Therefore, Doc-RE requires more comprehensive reasoning abilities like humans, involving complex cross-sentence interactions between entities, contexts, and external general knowledge, compared to the sentence-level RE. However, most existing Doc

Jonas Foglszinger, Andrej Denisenko, Georgy V. Astakhov, Lev Kazak

The ST2 center is an optically addressable point defect in diamond that facilitates spin initialization and readout. However, while this study presents the discovery of ST2 centers first observed in a natural diamond and provides a reliable technique for artificially creating them, its chemical structure remains unknown. To assess the potential of ST2, we ma

Tiange Luo, Ang Cao, Gunhee Lee, Justin Johnson

Despite recent advances in Vision-Language Models (VLMs), they may over-rely on visual language priors existing in their training data rather than true visual reasoning. To investigate this, we introduce ViLP, a benchmark featuring deliberately out-of-distribution images synthesized via image generation models and out-of-distribution Q&A pairs. Each question

Dimitris Bertsimas, Georgios Margaritis

In this paper, we explore the application of ChatGPT in the domain of Robust and Adaptive Robust Optimization. We demonstrate that with appropriate prompting, ChatGPT can be used to auto-formulate and solve simple Robust and Adaptive Optimization Problems. We first develop specialized informational prompts tailored to the domains of Adaptive and Robust Optim

Anders Martinsson, Raphael Steiner

We prove the following local strengthening of Shearer's classic bound on the independence number of triangle-free graphs: For every triangle-free graph $G$ there exists a probability distribution on its independent sets such that every vertex $v$ of $G$ is contained in a random independent set drawn from the distribution with probability $(1-o(1))\frac{\ln d

Ritwik Bhaduri, Siyuan Ma, Lucas Janson

Compositional data (i.e., data comprising random variables that sum up to a constant) arises in many applications including microbiome studies, chemical ecology, political science, and experimental designs. Yet when compositional data serve as covariates in a regression, the sum constraint renders every covariate automatically conditionally independent of th

Adrien Vacher, Omar Chehab, Anna Korba

Even in low dimensions, sampling from multi-modal distributions is challenging. We provide the first sampling algorithm for a broad class of distributions -- including all Gaussian mixtures -- with a query complexity that is polynomial in the parameters governing multi-modality, assuming fixed dimension. Our sampling algorithm simulates a time-reversed diffu

Suman Itani, Yibo Zhang, Jiadong Zang

Thermoelectric materials provide a sustainable way to convert waste heat into electricity. However, data-driven discovery and optimization of these materials are challenging because of a lack of a reliable database. Here we developed a comprehensive database of 7,123 thermoelectric compounds, containing key information such as chemical composition, structura

Daniel Sanchez, David Alfaya, Jaime Pizarroso

We present a new Python package called "motives", a symbolic manipulation package based on SymPy capable of handling and simplifying motivic expressions in the Grothendieck ring of Chow motives and other types of $\lambda$-rings. The package is able to manipulate and compare arbitrary expressions in $\lambda$-rings and, in particular, it contains explicit to

Hashmath Shaik, Alex Doboli

Large Language Models offer new opportunities to devise automated implementation generation methods that can tackle problem solving activities beyond traditional methods, which require algorithmic specifications and can use only static domain knowledge, like performance metrics and libraries of basic building blocks. Large Language Models could support creat

Mark E. Turiansky, Sai Mu, Lukas Razinkovas, Kamyar Parto

Chromium is a common transition-metal impurity that is easily incorporated during crystal growth. It is perhaps best known for giving rise to the 694.3 nm (1.786 eV) emission in Cr-doped Al$_2$O$_3$, exploited in ruby lasers. Chromium has also been found in monoclinic gallium oxide, a wide-bandgap semiconductor being pursued for power electronics. In this wo

Mingqi Gao, Yixin Liu, Xinyu Hu, Xiaojun Wan

Evaluating and ranking the capabilities of different LLMs is crucial for understanding their performance and alignment with human preferences. Due to the high cost and time-consuming nature of human evaluations, an automatic LLM bencher (i.e., an automatic evaluation framework that aims to rank LLMs based on their alignment with human preferences) is indispe

Prabhjot Kaur, Atul Singh Minhas, Chirag Kamal Ahuja, Anil Kumar Sao

Limited accessibility to high field MRI scanners (such as 7T, 11T) has motivated the development of post-processing methods to improve low field images. Several existing post-processing methods have shown the feasibility to improve 3T images to produce 7T-like images [3,18]. It has been observed that improving lower field (LF, <=1.5T) images comes with addit

Ahmad Mustapha, Hadi Al-Khansa, Hadi Al-Mubasher, Aya Mourad

Large Language Models (LLMs) have shown remarkable capabilities, not only in generating human-like text, but also in acquiring knowledge. This highlights the need to go beyond the typical Natural Language Processing downstream benchmarks and asses the various aspects of LLMs including knowledge and reasoning. Numerous benchmarks have been developed to evalua

Xavier Emery, Moreno Bevilacqua, Emilio Porcu

A huge literature in statistics and machine learning is devoted to parametric families of correlation functions, where the correlation parameters are used to understand the properties of an associated spatial random process in terms of smoothness and global or compact support. However, most of current parametric correlation functions attain only non-negative

Muhammad Sudipto Siam Dip, Mohammod Abdul Motin, Chandan Karmakar, Thomas Penzel

Objective: Automatic sleep scoring is crucial for diagnosing sleep disorders. Existing frameworks based on Polysomnography often rely on long sequences of input signals to predict sleep stages, which can introduce complexity. Moreover, there is limited exploration of simplifying representation learning in sleep scoring methods. Methods: In this study, we pro

Elias C. Rodrigues, Roney L. Thompson, Dário A. B. Oliveira, Roberto F. Ausas

This research employs Universal Differential Equations (UDEs) alongside differentiable physics to model viscoelastic fluids, merging conventional differential equations, neural networks and numerical methods to reconstruct missing terms in constitutive models. This study focuses on analyzing four viscoelastic models: Upper Convected Maxwell (UCM), Johnson-Se

Harit Vishwakarma, Alan Mishler, Thomas Cook, Niccolò Dalmasso

Large language models (LLMs) are empowering decision-making in several applications, including tool or API usage and answering multiple-choice questions (MCQs). However, incorrect outputs pose significant risks in high-stakes domains like healthcare and finance. To quantify LLM uncertainty and thereby mitigate these risks, recent works employ conformal predi

Pavan Kumar Meena, Rahul Verma, Arushi, Sonika Jangid

Superconductivity and nontrivial topology are highly sought-after phenomena in quantum materials. While many topological crystalline materials have been found to exhibit superconductivity, their presence in quasicrystals - materials with a unique aperiodic yet ordered structure - has remained largely unexplored. In this work, we report the discovery of super

Daniel P. Snowman

A BEG Hamiltonian is used to model an Ising spin glass with annealed vacancies on a hierarchical lattice. In addition to competing bilinear interactions, repulsive biquadratic interactions on the perimeter of our unit structures compete with attractive cross-link interactions. Ordering and transitions in this system are probed by generating several phase dia

FOOT Collaboration, R. Ridolfi, M. Toppi, A. Mengarelli

This paper presents the measurements of the angular differential cross sections for the forward production of He, Li, Be, B, C and N nuclei in the fragmentation process of a 400$\text{MeV/nucleon}$ $^{16}\text{O}$ beam interacting with a graphite target. Due to the limited data available in this energy regime, these measurements of nuclear fragmentation cros

Ye-Bing Zhang, Xin-Chi Zhou, Bao-Zong Wang, Xiong-Jun Liu

The fermionic t-J model has been widely recognized as a canonical model for broad range of strongly correlated phases, particularly the high-Tc superconductor. Simulating this model with controllable quantum platforms offers new possibilities to probe high-Tc physics, yet suffering challenges. Here we propose a novel scheme to realize a highly-tunable extend

Irina Rezvyakova

This is an article, published in Izvestiya: Mathematics, 2016, Volume 80, Issue 3, which complements arxiv:2411.18492

Qiwei Hu, Cong-Feng Qiao, Li-Ping Sun

Within the framework of nonrelativistic quantum chromodynamics, this study examines the electroproduction processes $e+p\to e+B_c+\overline{c}+b$, $e+p\to e+B_s+\overline{s}+b$, and $e+p\to e+D_s+\overline{c}+s$ at lepton-hadron colliders. The differential cross sections in $\cos\theta$ and $p_T^2$ at HERA are presented. The results indicate that the product

Mehrdad Salimnejad, Nikolaos Pappas, Marios Kountouris

In this paper, we address the problem of timely delivery of status update packets in a real-time communication system, where a transmitter sends status updates generated by a source to a receiver over an unreliable channel. The timestamps of transmitted and received packets are measured using separate clocks located at the transmitter and receiver, respectiv

Győző Kovács

The effect of the finite system size on the QCD phase diagram was studied with various momentum space constraints within a mean-field quark-meson model. On the one hand side, the choice of the scenario -- low-momentum cutoff and discretization with periodic or antiperiodic boundary conditions -- and the presence of the vacuum fluctuations were found to stron

Federico Gerbino, Guido Giachetti, Pierre Le Doussal, Andrea De Luca

We introduce a solvable model of a measurement-induced phase transition (MIPT) in a deterministic but chaotic dynamical system with a positive Lyapunov exponent. In this setup, an observer only has a probabilistic description of the system but mitigates chaos-induced uncertainty through repeated measurements. Using a minimal representation via a branching tr

Zeping Sui, Hien Quoc Ngo, Michail Matthaiou, Lajos Hanzo

Simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS)-aided cell-free massive multiple-input multiple-output (CF-mMIMO) systems are investigated under spatially correlated fading channels using realistic imperfect hardware. Specifically, the transceiver distortions, \textcolor{black}{time-varying phase noise, and RIS phase

Nour Dekhil, Adnan Rashid, Sofiene Tahar

We introduce a proof recommender system for the HOL4 theorem prover. Our tool is built upon a transformer-based model [2] designed specifically to provide proof assistance in HOL4. The model is trained to discern theorem proving patterns from extensive libraries of HOL4 containing proofs of theorems. Consequently, it can accurately predict the next tactic(s)

Takuma Nakamura, Dahyeon Lee, Jason Horng, Florent Lecocq

We investigate short pulse illumination of a high-speed extended-InGaAs photodiode at cryogenic temperatures towards its use in control and readout of superconducting qubits. First, we demonstrate high detector responsivity at 1550 nm illumination at 20 mK, a wavelength band unavailable to cryogenic standard InGaAs detectors due to the temperature-dependent

Tim Jenness, Stelios Voutsinas, Gregory P. Dubois-Felsmann, Andrei Salnikov

The IVOA Simple Image Access version 2 protocol defines an easy way to provide community access to a collection of data. At the Vera C. Rubin Observatory we currently enable ObsTAP access to our data holdings via an ObsCore export or view of our Data Butler repositories. This approach comes with some deployment constraints, such as requiring pgsphere and com

Fabrizio Colombo, Elodie Pozzi, Irene Sabadini, Brett D. Wick

This paper addresses the Corona problem for slice hyperholomorphic functions for a single quaternionic variable. While the Corona problem is well-understood in the context of one complex variable, it remains highly challenging in the case of several complex variables. The extension of the theory of one complex variable to several complex variables is not the

Adnan Rashid, Sa'ed Abed, Osman Hasan

The control of Biomedical Systems in Physical Human-Robot Interaction (pHRI) plays a pivotal role in achieving the desired behavior by ensuring the intended transfer function and stability of subsystems within the overall system. Traditionally, the control aspects of biomedical systems have been analyzed using manual proofs and computer based analysis tools.

Lu Yang

U(4) local transformations on the four Weyl spinors forming the isospin doublet of Dirac fermions are assumed as symmetries of the standard model. With the Lorentz transformations considered simultaneously, the symmetry group is enlarged in order to form a closed Lie algebra. In this framework, the chirality mixing gauge components with certain constraints c

Stefan Szeider

The MCP Solver bridges Large Language Models (LLMs) with symbolic solvers through the Model Context Protocol (MCP), an open-source standard for AI system integration. Providing LLMs access to formal solving and reasoning capabilities addresses their key deficiency while leveraging their strengths. Our implementation offers interfaces for constraint programmi

Md. Tarek Hasan, Arifa Akter, Mohammad Nazmush Shamael, Md Al Emran Hossain

Dropout is an effective strategy for the regularization of deep neural networks. Applying tabu to the units that have been dropped in the recent epoch and retaining them for training ensures diversification in dropout. In this paper, we improve the Tabu Dropout mechanism for training deep neural networks in two ways. Firstly, we propose to use tabu tenure, o

Amira Jemaa, Adnan Rashid, Sofiene Tahar

Explainable Artificial Intelligence (XAI) plays an important role in improving the transparency and reliability of complex machine learning models, especially in critical domains such as cybersecurity. Despite the prevalence of heuristic interpretation methods such as SHAP and LIME, these techniques often lack formal guarantees and may produce inconsistent l

Ben Nageris, Felipe Meneguzzi, Reuth Mirsky

Goal Recognition aims to infer an agent's goal from a sequence of observations. Existing approaches often rely on manually engineered domains and discrete representations. Deep Recognition using Actor-Critic Optimization (DRACO) is a novel approach based on deep reinforcement learning that overcomes these limitations by providing two key contributions. First

Giacomo Bartolucci, Daniel Maria Busiello, Matteo Ciarchi, Alberto Corticelli

``Pasta alla Cacio e pepe'' is a traditional Italian dish made with pasta, pecorino cheese, and pepper. Despite its simple ingredient list, achieving the perfect texture and creaminess of the sauce can be challenging. In this study, we systematically explore the phase behavior of Cacio e pepe sauce, focusing on its stability at increasing temperatures for va

Yating Liu, Claire Donnat

By representing documents as mixtures of topics, topic modeling has allowed the successful analysis of datasets across a wide spectrum of applications ranging from ecology to genetics. An important body of recent work has demonstrated the computational and statistical efficiency of probabilistic Latent Semantic Indexing (pLSI)-- a type of topic modeling -- i

M. A. P. Goncalves, M. Graf, M. Pasciak, J. Hlinka

This paper analyzes a peculiar phenomenon of non-reciprocal domain wall pairs and illustrate the implications in ab-initio-based atomistic computational experiments with (112)-oriented planar R180 domain walls within the canonical multiferroic ferroelectric crystal of BiFeO3. Results show that parallel walls on the opposite sides of a given domain within a s

Zijian Fang, Zongkai Liu, Chao Yu, Chaohao Hu

In this paper, we delve into the utilization of the negative momentum technique in constrained minimax games. From an intuitive mechanical standpoint, we introduce a novel framework for momentum buffer updating, which extends the findings of negative momentum from the unconstrained setting to the constrained setting and provides a universal enhancement to th

Cristina Tavares, Nathalia Nascimento, Paulo Alencar, Donald Cowan

The emergence of machine learning (ML) has led to a transformative shift in software techniques and guidelines for building software applications that support data analysis process activities such as data ingestion, modeling, and deployment. Specifically, this shift is impacting ML model selection, which is one of the key phases in this process. There have b

Frédéric Robert

We analyze the asymptotic pointwise behavior of families of solutions to the high-order critical equation $$P_\alpha u_\alpha=\Delta_g^k u_\alpha+\hbox{lot}=|u_\alpha|^{2^\star-2-\epsilon_\alpha} u_\alpha\hbox{ in }M$$ that behave like $$u_\alpha=u_0+B_\alpha+o(1)\hbox{ in }H_k^2(M)$$ where $B=(B_\alpha)_\alpha$ is a Bubble, also called a Peak. We give obstr

Ayoub Ben Chaliah, Hela Dellagi

Catastrophic forgetting remains a major challenge when adapting large language models (LLMs) to new tasks or domains. Conventional fine-tuning often overwrites existing knowledge, causing performance degradation on original tasks. We introduce Superposition in Transformers, a novel architecture that leverages autoencoders to superimpose the hidden representa

Yomal De Mel, Kasun Wickramasinghe, Nisansa de Silva, Surangika Ranathunga

Due to reasons of convenience and lack of tech literacy, transliteration (i.e., Romanizing native scripts instead of using localization tools) is eminently prevalent in the context of low-resource languages such as Sinhala, which have their own writing script. In this study, our focus is on Romanized Sinhala transliteration. We propose two methods to address

AmirHosein Rostami, Sepand Haghighi, Sadra Sabouri, Alireza Zolanvari

PyMilo is an open-source Python package that addresses the limitations of existing Machine Learning (ML) model storage formats by providing a transparent, reliable, and safe method for exporting and deploying trained models. Current formats, such as pickle and other binary formats, have significant problems, such as reliability, safety, and transparency issu

Madeleine Darbyshire, Elizabeth Sklar, Simon Parsons

Precision agriculture leverages data and machine learning so that farmers can monitor their crops and target interventions precisely. This enables the precision application of herbicide only to weeds, or the precision application of fertilizer only to undernourished crops, rather than to the entire field. The approach promises to maximize yields while minimi

Jeff Forshaw, Ruben Sandapen

Inspired by light-front holography, we compute the pion mass, charge radius, decay constant, electromagnetic form factor and electromagnetic transition form factor. To do so, we model the longitudinal quark dynamics using potentials due to 't Hooft and to Li & Vary. We find a longitudinal wavefunction that is rather more peaked about $x \sim 1/2$ than in pre

Cheng Yuan, Jian Jiang, Kunyi Yang, Lv Wu

Surgical video segmentation is critical for AI to interpret spatial-temporal dynamics in surgery, yet model performance is constrained by limited annotated data. The SAM2 model, pretrained on natural videos, offers potential for zero-shot surgical segmentation, but its applicability in complex surgical environments, with challenges like tissue deformation an

Shuai Zhang, Aliza Panjwani, Penghao Xiao, Maitrayee Ghosh

The structure and stability of iron near melting at multi-megabar pressures are of significant interest in high pressure physics and earth and planetary sciences. While the body-centered cubic (BCC) phase is generally recognized as unstable at lower temperatures, its stability relative to the hexagonal close-packed (HCP) phase at high temperatures (approxima

Kewei Zhou, Ziming Wang, Zhihao Chen, Xin Wang

This paper introduces a novel approach for achieving fixed-time tracking consensus control in multiagent systems (MASs). Departing from the reliance on traditional controllers, our innovative controller integrates modified tuning and Lyapunov functions to guarantee stability and convergence. Furthermore, we have implemented an event-triggered strategy aimed

Ke Yang, Volodymyr Kindratenko, ChengXiang Zhai

Training language models (LMs) and their application agents is increasingly costly due to large datasets and models, making test failures difficult to bear. Simplified language environments serve as primordial training and testing grounds, retaining essential commonsense and communication skills but in a more digestible form, potentially enhancing the learni

Jisun Baek, David Conlon, Joonkyung Lee

Given a graph $H$ and a natural number $n$, the extremal number $\mathrm{ex}(n, H)$ is the largest number of edges in an $n$-vertex graph containing no copy of $H$. In this paper, we obtain a general upper bound for the extremal number of generalised face-incidence graphs, a family which includes the standard face-incidence graphs of regular polytopes. This

Bálint Tóth

By synchronously coupling multiple Lorentz trajectories exploring the same environment consisting of randomly placed scatterers in R^3 we upgrade the annealed invariance principle proved in [C. Lutsko, B. T\'oth, Commun. Math. Phys. 379 589-632 (2020)] to quenched setting (that is, valid for almost all realizations of the environment) along sufficiently fast

Heron Caldas, A. L. Mota

The tricritical behavior in a class of one-dimensional (1D) field theories that exhibit spontaneous symmetry breaking at zero temperature and chemical potential is analyzed. In the Gross-Neveu (GN)-type models of massless fermions the discrete chiral symmetry is spontaneously broken. After doping, the symmetry is restored at a critical chemical potential. We

Keke Zhai

Currently, large models are prone to generating harmful content when faced with complex attack instructions, significantly reducing their defensive capabilities. To address this issue, this paper proposes a method based on constructing data aligned with multi-dimensional attack defense to enhance the generative security of large models. The core of our metho

Arda Bulut, Yusuf Sariyar, Giuseppe Negro, Livio Nicola Carenza

We numerically investigate the phase behavior of thick shells of cholesteric liquid crystals with tangential anchoring at the shell boundary. For achiral liquid crystal, we demonstrate a thickness-dependent transition from a configuration featuring four disclination line connecting the inner and outer surfaces to a state free of defect in the bulk, where eac

Santiago Radi

This article provides a method to calculate the fixed-point proportion of any iterated wreath product acting on a $d$-regular tree. Moreover, the method applies to a generalization of iterated wreath products acting on a $d$-regular tree, which are not groups. As an application of this generalization, a family of groups of finite type of depth $2$ acting on

Pedram Fekri, Mehrdad Zadeh, Javad Dargahi

The success rate of catheterization procedures is closely linked to the sensory data provided to the surgeon. Vision-based deep learning models can deliver both tactile and visual information in a sensor-free manner, while also being cost-effective to produce. Given the complexity of these models for devices with limited computational resources, research has

Yifan Xu, Xinhao Li, Yichun Yang, Desen Meng

Video understanding, including video captioning and retrieval, is still a great challenge for video-language models (VLMs). The existing video retrieval and caption benchmarks only include short descriptions, limits their ability of detailed video understanding evaluation. To address this problem, we present CaReBench, a testing benchmark for fine-grained vi

Chao-Qi Zhang, Jin Sun, Zhi-Peng Xing, Rui-Lin Zhu

Recently, the Belle II Collaboration reported the branching fraction $\mathcal{B}(B^+ \to K^+ \nu \bar{\nu})=(2.3\pm0.7)\times10^{-5}$ with a significance of $3.5\sigma$, which is $2.7\sigma$ above the SM expectation. Motivated by this measurement, we calculate this decay channel at the NLO and twist-3 level using the PQCD approach. By combining the lattice

Jiseok Chae, Chulhee Yun, Donghwan Kim

In minimax optimization, the extragradient (EG) method has been extensively studied because it outperforms the gradient descent-ascent method in convex-concave (C-C) problems. Yet, stochastic EG (SEG) has seen limited success in C-C problems, especially for unconstrained cases. Motivated by the recent progress of shuffling-based stochastic methods, we invest

Zhaoliang Wan, Yonggen Ling, Senlin Yi, Lu Qi

This paper addresses the scarcity of large-scale datasets for accurate object-in-hand pose estimation, which is crucial for robotic in-hand manipulation within the ``Perception-Planning-Control" paradigm. Specifically, we introduce VinT-6D, the first extensive multi-modal dataset integrating vision, touch, and proprioception, to enhance robotic manipulation.

Hernán Castro

In this article we study the quasi-linear equation \[\mathrm{div}\, \mathcal A(x,u,\nabla u)=\mathcal B(x,u,\nabla u)\quad \text{in }\Omega,\qquad u\in H^{1,p}_{loc}(\Omega;w_1dx)\] where $\mathcal A$ and $\mathcal B$ are functions satisfying $\mathcal A(x,u,\nabla u)\sim w_1(|\nabla u|^{p-2}\nabla u+|u|^{p-2}u)$ and $\mathcal B(x,u,\nabla u)\sim w_2(|\nabla

Liam Lonergan, Ibon Saratxaga, John Sloan, Oscar Maharog

This paper sets out the first web-based transcription system for the Irish language - Fotheidil, a system that utilises speech-related AI technologies as part of the ABAIR initiative. The system includes both off-the-shelf pre-trained voice activity detection and speaker diarisation models and models trained specifically for Irish automatic speech recognitio

Ilias Diakonikolas, Daniel M. Kane, Mingchen Ma

We study the problem of learning general (i.e., not necessarily homogeneous) halfspaces under the Gaussian distribution on $R^d$ in the presence of some form of query access. In the classical pool-based active learning model, where the algorithm is allowed to make adaptive label queries to previously sampled points, we establish a strong information-theoreti

Nermin Covic, Bakir Lacevic, Dinko Osmankovic, Tarik Uzunovic

In this paper, we present the main features of Dynamic Rapidly-exploring Generalized Bur Tree (DRGBT) algorithm, a sampling-based planner for dynamic environments. We provide a detailed time analysis and appropriate scheduling to facilitate a real-time operation. To this end, an extensive analysis is conducted to identify the time-critical routines and their

N. K. Bhadari, L. K. Dewangan, O. R. Jadhav, Ariful Hoque

Star clusters, including high-mass stars, form within hub-filament systems (HFSs). Observations of HFSs that remain unaffected by feedback from embedded stars are rare yet crucial for understanding the mass inflow process in high-mass star formation. Using the JWST NIRCAM images, Dewangan et al. 2024, reported that the high-mass protostar G11P1 is embedded i

Laura Fredrickson, Max Zimet

In this note, we prove a concrete variant of the twistor theorem of Hitchin--Karlhede--Lindstr\"om--Ro\v{c}ek which applies when one already has the real manifold on which one wishes to construct a hyper-K\"ahler structure, and so one does not need to construct it as a parameter space of twistor lines.

Alessandro T. Gifford, Domenic Bersch, Marie St-Laurent, Basile Pinsard

There is growing symbiosis between artificial and biological intelligence sciences: neural principles inspire new intelligent machines, which are in turn used to advance our theoretical understanding of the brain. To promote further collaboration between biological and artificial intelligence researchers, we introduce the 2025 edition of the Algonauts Projec

Rafał Filipów, Jacek Tryba

We present a few results about (non)pathology of submeasures and ideals.

Miro Miranda, Marcela Charfuelan, Andreas Dengel

In response to climate change, assessing crop productivity under extreme weather conditions is essential to enhance food security. Crop simulation models, which align with physical processes, offer explainability but often perform poorly. Conversely, machine learning (ML) models for crop modeling are powerful and scalable yet operate as black boxes and lack

Hitoshi Omori

In this article, the disjunction-free fragment of Ja\'skowski's discussive logic D2 in the language of classical logic is shown to be complete with respect to three- and four-valued semantics. As a byproduct, a rather simple axiomatization of the disjunction-free fragment of D2 is obtained. Some implications of this result are also discussed.

Hitoshi Omori, Jonas R. B. Arenhart

The present article examines a system of four-valued logic recently introduced by Oleg Grigoriev and Dmitry Zaitsev. In particular, besides other interesting results, we will clarify the connection of this system to related systems developed by Paul Ruet and Norihiro Kamide. By doing so, we discuss two philosophical problems that arise from making such conne

Hitoshi Omori, Jonas R. B. Arenhart

In this paper, we elaborate on the ordered-pair semantics originally presented by Matthew Clemens for LP (Priest's Logic of Paradox). For this purpose, we build on a generalization of Clemens semantics to the case of n-tuple semantics, for every n. More concretely, i) we deal with the case of a language with quantifiers, and ii) we consider philosophical imp

Norihiro Kamide

Gentzen-style sequent calculi and Gentzen-style natural deduction systems are introduced for a family (C-family) of connexive logics over Wansing's basic connexive logic C. The C-family is derived from C by incorporating the Peirce law, the law of excluded middle, and the generalized law of excluded middle. Theorems establishing equivalence between the propo

Jaime Sánchez-Barriga, Oliver J. Clark, Oliver Rader

Topological materials have gained significant attention in condensed matter physics due to their unique electronic and transport properties. Three-dimensional (3D) topological materials are characterized by robust electronic states that are protected by symmetries and exhibit peculiar spin textures. They offer a rich platform for for future information techn

Cheng-Syuan Wan

This work studies the proof theory of left (right) skew monoidal closed categories and skew monoidal bi-closed categories from the perspective of non-associative Lambek calculus. Skew monoidal closed categories represent a relaxed version of monoidal closed categories, where the structural laws are not invertible; instead, they are natural transformations wi

Satoru Niki, Hitoshi Omori

It is not uncommon for a logic to be invented multiple times, hinting at its robustness. This trend is followed also by the expansion BD+ of Belnap-Dunn logic by Boolean negation. Ending up in the same logic, however, does not mean that the semantic interpretations are always the same as well. In particular, different interpretations can bring us to differen

Norihiro Kamide, Sara Negri

A unified Gentzen-style framework for until-free propositional linear-time temporal logic is introduced. The proposed framework, based on infinitary rules and rules for primitive negation, can handle uniformly both a single-succedent sequent calculus and a natural deduction system. Furthermore, an equivalence between these systems, alongside with proofs of c