December 2023 arXiv papers — page 36

Patrick Carzon

At top collider energies where baryon stopping is negligible, the initial state of heavy ion collisions is overall charge neutral and predominantly composed of gluons. Nevertheless, there can also be significant local fluctuations of the baryon number, strangeness, and electric charge densities about zero, perturbatively corresponding to the production of qu

Alexandre Quesney

We consider the properad that governs the balanced infinitesimal bialgebras equipped with a coproduct of degree $1-d$. This properad naturally encodes a part of the structure of the pre-Calabi-Yau algebras of degree $d$. We compute the cobar construction of its Koszul dual coproperad and show that its gebras lie between the homotopy double Poisson gebras and

Sara Pucillo

Among the most iconic results of Run-1 and Run-2 of the LHC is the observation of enhanced production of (multi-)strange to non-strange particles, gradually rising from low-multiplicity to high-multiplicity pp or p--Pb collisions and reaching values close to those measured in peripheral Pb--Pb collisions. The observed behaviour cannot be quantitatively repro

Yevgeniy Men, Jonathan Fhima, Leo Anthony Celi, Lucas Zago Ribeiro

Diabetic retinopathy (DR) is a prevalent complication of diabetes associated with a significant risk of vision loss. Timely identification is critical to curb vision impairment. Algorithms for DR staging from digital fundus images (DFIs) have been recently proposed. However, models often fail to generalize due to distribution shifts between the source domain

Lizhou Fan, Wenyue Hua, Lingyao Li, Haoyang Ling

Complex reasoning ability is one of the most important features of current LLMs, which has also been leveraged to play an integral role in complex decision-making tasks. Therefore, the investigation into the reasoning capabilities of Large Language Models (LLMs) is critical: numerous benchmarks have been established to assess the reasoning abilities of LLMs.

Nathan Kaplan, Harold Polo

A semidomain is a subsemiring of an integral domain. One can think of a semidomain as an integral domain in which additive inverses are no longer required. A semidomain $S$ is additively reduced if $0$ is the only invertible element of the monoid $(S,+)$, while $S$ is additively atomic if the monoid $(S,+)$ is atomic (i.e., every non-invertible element $s \i

Patrick J. Stofanak, Cheng-Nian Xiao, Inanc Senocak

We observe the spontaneous onset of three-dimensional motion from a quiescent, purely conductive state of a stably stratified fluid in a V-shaped enclosure heated from below, which ultimately self-organizes into a two-dimensional steady state without any external forcing to the initial configuration. We identify a dominant three-dimensional instability throu

Nathaël Da Costa, Marvin Pförtner, Lancelot Da Costa, Philipp Hennig

Gaussian processes (GPs) are the most common formalism for defining probability distributions over spaces of functions. While applications of GPs are myriad, a comprehensive understanding of GP sample paths, i.e. the function spaces over which they define a probability measure, is lacking. In practice, GPs are not constructed through a probability measure, b

Léo Régnier, Maxim Dolgushev, Olivier Bénichou

We develop a comprehensive framework for analyzing full record statistics, covering record counts $M(t_1), M(t_2), \ldots$, and their corresponding attainment times $T_{M(t_1)}, T_{M(t_2)}, \ldots$, as well as the intervals until the next record. From this multiple-time distribution, we derive general expressions for various observables related to record dyn

Ivan Damnjanović, Nino Bašić, Tomaž Pisanski, Arjana Žitnik

A nut graph is a simple graph whose adjacency matrix has the eigenvalue zero with multiplicity one such that its corresponding eigenvector has no zero entries. It is known that there exist no cubic circulant nut graphs. A bicirculant (resp. tricirculant) graph is defined as a graph that admits a cyclic group of automorphisms having two (resp. three) orbits o

Brian C. Hall, Ching-Wei Ho, Jonas Jalowy, Zakhar Kabluchko

We start with a random polynomial $P^{N}(z)$ of degree $N$ with independent coefficients. We then consider a new polynomial $P_{t}^{N}$ obtained by $\lceil Nt\rceil$ applications of a fractional differential operator of the form $z^{a} (d/dz)^{b},$ where $a$ and $b$ are real numbers. When $b>0,$ we compute the limiting root distribution $\mu_{t}$ of $P_{t}^{

Karthik Bharath, Alexander Lewis, Akash Sharma, Michael V Tretyakov

Error bounds are derived for sampling and estimation using a discretization of an intrinsically defined Langevin diffusion with invariant measure $\text{d}\mu_\phi \propto e^{-\phi} \mathrm{dvol}_g $ on a compact Riemannian manifold. Two estimators of linear functionals of $\mu_\phi $ based on the discretized Markov process are considered: a time-averaging e

MacKenzie Carr, Eun-Kyung Cho, Nicholas Crawford, Vesna Iršič

An improper interval (edge) coloring of a graph $G$ is an assignment of colors to the edges of $G$ satisfying the condition that, for every vertex $v \in V(G)$, the set of colors assigned to the edges incident with $v$ forms an integral interval. An interval coloring is $k$-improper if at most $k$ edges with the same color all share a common endpoint. The mi

Shane Bergsma, Timothy Zeyl, Lei Guo

We propose SutraNets, a novel method for neural probabilistic forecasting of long-sequence time series. SutraNets use an autoregressive generative model to factorize the likelihood of long sequences into products of conditional probabilities. When generating long sequences, most autoregressive approaches suffer from harmful error accumulation, as well as cha

Cristina G. Fernandes, Guilherme Oliveira Mota, Nicolás Sanhueza-Matamala

We prove that in any $n$-vertex complete graph there is a collection $\mathcal{P}$ of $(1 + o(1))n$ paths that strongly separates any pair of distinct edges $e, f$, meaning that there is a path in $\mathcal{P}$ which contains $e$ but not $f$. Furthermore, for certain classes of $n$-vertex $\alpha n$-regular graphs we find a collection of $(\sqrt{3 \alpha + 1

Filippos Christianos, Georgios Papoudakis, Matthieu Zimmer, Thomas Coste

A key method for creating Artificial Intelligence (AI) agents is Reinforcement Learning (RL). However, constructing a standalone RL policy that maps perception to action directly encounters severe problems, chief among them being its lack of generality across multiple tasks and the need for a large amount of training data. The leading cause is that it cannot

Nico Potyka, Yuqicheng Zhu, Yunjie He, Evgeny Kharlamov

Large-language models (LLMs) can support a wide range of applications like conversational agents, creative writing or general query answering. However, they are ill-suited for query answering in high-stake domains like medicine because they are typically not robust - even the same query can result in different answers when prompted multiple times. In order t

A. Deepika Bollimpalli, P. Chris Fragile, W. Janosz Dewberry, Włodek Kluźniak

Many accreting black holes and neutron stars exhibit rapid variability in their X-ray light curves, termed quasi-periodic oscillations (QPOs). The most commonly observed type is the low-frequency ($\lesssim 10$ Hz), type-C QPO, while only a handful of sources exhibit high-frequency QPOs ($\gtrsim 60$ Hz). The leading model for the type-C QPO is Lense-Thirrin

Jonas Schmitt

Many of the most fundamental laws of nature can be formulated as partial differential equations (PDEs). Understanding these equations is, therefore, of exceptional importance for many branches of modern science and engineering. However, since the general solution of many PDEs is unknown, the efficient approximate solution of these equations is one of humanit

Wangda Zhang, Yanbin Wang, Kenneth A. Ross

The prefix sum operation is a useful primitive with a broad range of applications. For database systems, it is a building block of many important operators including join, sort and filter queries. In this paper, we study different methods of computing prefix sums with SIMD instructions and multiple threads. For SIMD, we implement and compare horizontal and v

Giulio Biroli, Alexander K. Hartmann, Marco Tarzia

A central theoretical issue at the core of the current research on many-body localization (MBL) consists in characterizing the statistics of rare long-range resonances in many-body eigenstates. This is of paramount importance to understand: (i) the critical properties of the MBL transition and the mechanism for its destabilization through quantum avalanches;

Subhaditya Bhattacharya, Sahabub Jahedi, Soumitra Nandi, Abhik Sarkar

We investigate flavour violating four Fermi Standard Model Effective Field Theory (SMEFT) operators of dimension-six that can be probed via $tc ~(\bar{t}c+t\bar{c})$ production at the multi-TeV muon collider. We study different FCNC and FCCC processes related to $B$, $B_s$, $K$ and $D$ decays and mixings, sensitive to these operators and constrain the corres

Honghao Fu, Zhiqi Shen, Jing Jih Chin, Hao Wang

Analyzing and reconstructing visual stimuli from brain signals effectively advances the understanding of human visual system. However, the EEG signals are complex and contain significant noise. This leads to substantial limitations in existing works of visual stimuli reconstruction from EEG, such as difficulties in aligning EEG embeddings with the fine-grain

Abhinav Arun, Ashish Dhiman, Mehul Soni, Yibei Hu

Financial reports offer critical insights into a company's operations, yet their extensive length typically spanning 30 40 pages poses challenges for swift decision making in dynamic markets. To address this, we leveraged finetuned Large Language Models (LLMs) to distill key indicators and operational metrics from these reports basis questions from the user.

Aiyinsi Zuo, Haixi Zhang, Zirui Li, Ce Zheng

Within the field of complicated multivariate time series forecasting (TSF), popular techniques frequently rely on intricate deep learning architectures, ranging from transformer-based designs to recurrent neural networks. However, recent findings suggest that simple Linear models can surpass sophisticated constructs on diverse datasets. These models directly

Martina Ferrillo, Maksym Ovchynnikov, Filippo Resnati, Albert De Roeck

Beam dump experiments proposed at the SPS are perfectly suited to explore the parameter space of models with long-lived particles, thanks to the combination of a large intensity with a high proton beam energy. In this paper, we study how the exploration power may be augmented further by installing a detector based on liquid argon time projection chamber tech

Max Ku, Dongfu Jiang, Cong Wei, Xiang Yue

In the rapidly advancing field of conditional image generation research, challenges such as limited explainability lie in effectively evaluating the performance and capabilities of various models. This paper introduces VIEScore, a Visual Instruction-guided Explainable metric for evaluating any conditional image generation tasks. VIEScore leverages general kn

S. Di Napoli, A. Román, A. M. Llois, M. H. Aguirre

$Ab$ $initio$ calculations show the presence of a strong magnetoelectric interfacial coupling in CaMnO$_3$ ultra-thin film grown on a strained BaTiO$_3$ ferroelectric film. This heterostructure presents a polarization driven magnetic transition from a G-type to an A-type antiferromagnetic structure. Together with this magnetic transition we find a metallic b

Yoan Fauvel, Julia S. Meyer, Manuel Houzet

In a Josephson junction, the transfer of Cooper pairs from one superconductor to the other one can be associated with the formation of Andreev bound states. In a Josephson junction made with a semiconducting nanowire, the spin degeneracy of these Andreev states can be broken thanks to the presence of spin-orbit coupling and a finite phase difference between

Freya Johnson, Frederic Rendell-Bhatti, Bryan D. Esser, Aisling Hussey

Antiferromagnets hosting structural or magnetic order that breaks time reversal symmetry are of increasing interest for 'beyond von Neumann computing' applications because the topology of their band structure allows for intrinsic physical properties, exploitable in integrated memory and logic function. One such group are the non-collinear antiferromagnets. E

Yuhao Chen, Chloe Wong, Hanwen Yang, Juan Aguenza

This study critically evaluates the efficacy of prompting methods in enhancing the mathematical reasoning capability of large language models (LLMs). The investigation uses three prescriptive prompting methods - simple, persona, and conversational prompting - known for their effectiveness in enhancing the linguistic tasks of LLMs. We conduct this analysis on

Zohreh Aliannejadi, Mehdi Alaeiyan, Alireza Gilani

A connected and nonempty graph A is defined as generalized t-edge distance-balanced, while for each edge f={\alpha}\{beta} the number of edges nearer to {\alpha} than \{beta} are equal to t-times of edges nearer to \{beta} than to {\alpha}, for t \in N, or vice versa. We determine some classes of such graphs. Moreover, we investigate edge-szeged index of the

Yin Luo, Qingchao Kong, Nan Xu, Jia Cao

As the latest advancements in natural language processing, large language models (LLMs) have achieved human-level language understanding and generation abilities in many real-world tasks, and even have been regarded as a potential path to the artificial general intelligence. To better facilitate research on LLMs, many open-source LLMs, such as Llama 2 and Fa

Lorenzo Valentini, Elena Bernardi, Enrico Paolini

The construction of preamble sequences for channel estimation by superposition of orthogonal pilots can improve performance of massive grant-free uplink from machine-type devices. In this letter, a technique is proposed to obtain full benefit from these "pilot mixtures" in presence of a base station with a massive number of antennas. The proposed technique c

Kun Yan, Lei Ji, Zeyu Wang, Yuntao Wang

In recent years, the integration of vision and language understanding has led to significant advancements in artificial intelligence, particularly through Vision-Language Models (VLMs). However, existing VLMs face challenges in handling real-world applications with complex scenes and multiple objects, as well as aligning their focus with the diverse attentio

Lara Bohnenblust, Harald Ita, Manfred Kraus, Johannes Schlenk

We compute the far-field time-domain waveform of the gravitational waves produced in the scattering of two spinning massive objects. The results include linear-in-spin ($S$) couplings and first-order gravitational corrections ($G^3$), and are valid for encounters in the weak-field regime. Employing a field-theory framework based on the scattering of massive

Benshuai Lyu

A flow decomposition method based on canonical correlation analysis is proposed in this paper to optimally dissect complex flows into mutually orthogonal modes that are ranked by their cross-correlation with an observable. It is particularly suitable for identifying the observable-correlated flow structures while effectively excluding those uncorrelated, eve

Bhoomika Rajput, Amit Kumar Mandal, Ashwani Pandey, C. S. Stalin

The correlation between optical and $\gamma$-ray flux variations in blazars reveals a complex behaviour. In this study, we present our analysis of the connection between changes in optical and $\gamma$-ray emissions in the blazar Ton 599 over a span of approximately 15 years, from August 2008 to March 2023. Ton 599 reached its highest flux state across the e

Shahin Honarvar, Mark van der Wilk, Alastair Donaldson

We present a method for systematically evaluating the correctness and robustness of instruction-tuned large language models (LLMs) for code generation via a new benchmark, Turbulence. Turbulence consists of a large set of natural language $\textit{question templates}$, each of which is a programming problem, parameterised so that it can be asked in many diff

Sarmed Wahab, Mohamed Suleiman, Faisal Shabbir, Nasim Shakouri Mahmoudabadi

This article deals with the study of predicting the confinement effect of carbon fiber reinforced polymers (CFRPs) on concrete cylinder strength using metaheuristics-based artificial neural networks. A detailed database of 708 CFRP confined concrete cylinders is developed from previously published research with information on 8 parameters including geometric

Benjamin Doyon, Friedrich Hübner, Takato Yoshimura

Deformations of many-body Hamiltonians by certain products of conserved currents, referred to as $T\bar{T}$-deformations, are known to preserve integrability. Generalised $T\bar{T}$-deformations, based on the complete space of pseudolocal currents, were suggested [B. Doyon, J, Durnin, T. Yoshimura, Scipost Physics 13, 072 (2022)] to give rise to integrable s

Alexandre Delory, Daniel A. Kiefer, Claire Prada, Fabrice Lemoult

Objective - Shear wave elastography has enriched ultrasound medical imaging with quantitative measurements of tissue stiffness. However, this method still suffers from some limitations due to viscoelasticity, guiding geometry or static deformations. Approach - To explore these limitations, a nearly-incompressible soft elastomer strip is chosen to mimic the m

Zahra Ghasemi Kooktapeh, Hakimeh Dustmohammadloo, Hooman Mehrdoost, Farivar Fatehi

Using a systematic review and meta-analysis, this study investigates the impact of the COVID-19 pandemic on job burnout among nurses. We review healthcare articles following the PRISMA 2020 guidelines and identify the main aspects and factors of burnout among nurses during the pandemic. Using the Maslach Burnout questionnaire, we searched PubMed, ScienceDire

Rongao Li, Jie Fu, Bo-Wen Zhang, Tao Huang

We introduce TACO, an open-source, large-scale code generation dataset, with a focus on the optics of algorithms, designed to provide a more challenging training dataset and evaluation benchmark in the field of code generation models. TACO includes competition-level programming questions that are more challenging, to enhance or evaluate problem understanding

Claudia Merger, Jasper Albers, Carsten Honerkamp, Moritz Helias

The susceptible-infected-recovered (SIR) model and its variants form the foundation of our understanding of the spread of diseases. Here, each agent can be in one of three states (susceptible, infected, or recovered), and transitions between these states follow a stochastic process. The probability of an agent becoming infected depends on the number of its i

Vito Dichio

This PhD thesis is essentially the story of a scientific idea, from what it has blossomed, how it has grown, what it might become. My ambition in writing has been to produce an original, coherent and compact narrative. It begins (1) with a discussion of the meaning, ambitions and circumstances of biological physics, as I understand them. Two background chapt

Andreas Habring, Martin Holler

This review provides an introduction to - and overview of - the current state of the art in neural-network based regularization methods for inverse problems in imaging. It aims to introduce readers with a solid knowledge in applied mathematics and a basic understanding of neural networks to different concepts of applying neural networks for regularizing inve

Vanessa Graber, Michele Ronchi, Celsa Pardo-Araujo, Nanda Rea

We combine pulsar population synthesis with simulation-based inference (SBI) to constrain the magnetorotational properties of isolated Galactic radio pulsars. We first develop a framework to model neutron star birth properties and their dynamical and magnetorotational evolution. We specifically sample initial magnetic field strengths, $B$, and spin periods,

Sam Alexander Martino, João Morado, Chenghao Li, Zhenghao Lu

Traditional clustering algorithms often struggle to capture the complex relationships within graphs and generalise to arbitrary clustering criteria. The emergence of graph neural networks (GNNs) as a powerful framework for learning representations of graph data provides new approaches to solving the problem. Previous work has shown GNNs to be capable of prop

Y. Zhang, A. Gaddie, H-V. Do, G. W. Biedermann

Optical tweezer arrays of neutral atoms provide a versatile platform for quantum simulation due to the range of interactions and Hamiltonians that can be realized and explored. We propose to simulate a two-component Bose-Hubbard model with power-law hopping using arrays of multilevel Rydberg atoms featuring resonant dipolar interactions. The diversity of sta

Lois Wong

Providing mental healthcare to individuals with limited English proficiency (LEP) remains a pressing problem within psychiatry. Because the majority of individuals trained in providing psychiatric care are English speakers, the quality of mental healthcare given to LEP patients is significantly lower than that provided for English speakers. The provision of

John Z. Zhang, Lukas Graf, Annesya Banerjee, Aaron Yeiser

Purpose: One of the major reasons that totally implantable cochlear microphones are not readily available is the lack of good implantable microphones. An implantable microphone has the potential to provide a range of benefits over external microphones for cochlear implant users including the filtering ability of the outer ear, cosmetics, and usability in all

Istvan David

Sustainability is becoming a key property of modern software systems. While there is a substantial and growing body of knowledge on engineering sustainable software, end-to-end frameworks that situate sustainability-related activities within the software delivery lifecycle are missing. In this article, we propose the SusDevOps framework that promotes sustain

Jakub Wiktor Both, Bergit Brattekås, Martin Fernø, Eirik Keilegavlen

Mixed-dimensional mathematical models for flow in fractured media have been prevalent in the modeling community for almost two decades, utilizing the explicit representation of fractures by lower-dimensional manifolds embedded in the surrounding porous media. In this work, for the first time, direct qualitative and quantitative comparisons of mixed-dimension

Megan Clark, Joseph Harms, Roman Vasyltsiv, Austin Sloop

Purpose: Ultra-fast scintillation imaging has been shown to provide a unique tool for spatio-temporal dosimetry of conventional cyclotron and synchrocyclotron pencil beam scanning (PBS) deliveries, indicating the potential use for characterization of ultra-UHDR PBS proton beams. The goal of this work is to introduce this novel concept and demonstrate its cap

Dong Wang

We analyse the hard edge limit of the Muttalib-Borodin ensembles with general potential, and show that the limiting correlation kernel found in the ensemble with linear potential is universal. We also prove the Plancherel-Rotach type asymptotics of the biorthogonal polynomials associated to the Muttalib-Borodin ensembles around zero, where the limits are giv

Xingyu Ni, Xuwen Chen, Cheng Yu, Bin Wang

In this study, we present the bicubic Hermite element method (BHEM), a new computational framework devised for the elastodynamic simulation of parametric thin-shell structures. The BHEM is constructed based on parametric quadrilateral Hermite patches, which serve as a unified representation for shell geometry, simulation, collision avoidance, as well as rend

Benedikt Schneider, Johannes Reuther, Matías G. Gonzalez, Björn Sbierski

We implement the temperature flow scheme first proposed by Honerkamp and Salmhofer in Phys.~Rev.~B 64, 184516 (2001) into the pseudo-Majorana functional renormalization group method for quantum spin systems. Since the renormalization group parameter in this approach is a physical quantity -- the temperature $T$ -- the numerical efficiency increases significa

Yacine Ikhlef, Alexi Morin-Duchesne

We propose a new family ${\sf Y}_{k,\ell,x,y,[z,w]}$ of modules over the enlarged periodic Temperley--Lieb algebra ${\sf{\cal E}PTL}_N(\beta)$. These modules are built from link states with two marked points, similarly to the modules ${\sf X}_{k,\ell,x,y,z}$ that we constructed in a previous paper. They however differ in the way that defects connect pairwise

Roman Höllwieser, Francesco Knechtli, Tomasz Korzec, Michael Peardon

We present a method for computing hybrid static quark-antiquark potentials in lattice QCD based on Laplace trial states. They are formed by eigenvector components of the covariant lattice Laplace operator and their covariant derivatives. The new method does not need complicated gauge link paths between the static quarks and makes off-axis separations easily

Augustin Parjadis, Quentin Cappart, Bistra Dilkina, Aaron Ferber

Lagrangian relaxation is a versatile mathematical technique employed to relax constraints in an optimization problem, enabling the generation of dual bounds to prove the optimality of feasible solutions and the design of efficient propagators in constraint programming (such as the weighted circuit constraint). However, the conventional process of deriving La

Amir Hosseini, Mehdi Alaeiyan, Zohreh Aliannejadi

A nonempty graph G is called generalized 3-distance-balanced, (3-GDB) whenever for every edge ab, |Wab|=3|Wba| or conversely. As well as a graph G is called generalized 3-nicely distance-balanced (3-GNDB) whenever for every edge ab of G, there exists a positive integer g, such that: |Wba|=gG. In this paper, we classify 3-GNDB graphs with, gG \in{1,2}.

Ziqiang Wu, Bingpeng Ma

Text-based person search aims to simultaneously localize and identify the target person based on query text from uncropped scene images, which can be regarded as the unified task of person detection and text-based person retrieval task. In this work, we propose a large-scale benchmark dataset named PRW-TPS-CN based on the widely used person search dataset PR

Yi-Han Iris Yin, Zhao Joseph Zhang, Jun Yang, Run-Chao Chen

Magnetar giant flares (MGFs), originating from noncatastrophic magnetars, share noteworthy similarities with some short gamma-ray bursts (GRBs). However, understanding their detailed origin and radiation mechanisms remains challenging due to limited observations. The discovery of MGF GRB 231115A, the second extragalactic MGF located in the Cigar galaxy at a

Haihao Lu, Jinwen Yang, Haodong Hu, Qi Huangfu

A recent GPU implementation of the Restarted Primal-Dual Hybrid Gradient Method for Linear Programming was proposed in Lu and Yang (2023). Its computational results demonstrate the significant computational advantages of the GPU-based first-order algorithm on certain large-scale problems. The average performance also achieves a level close to commercial solv

Alberto Bombardelli, Stefano Tonetta

The verification of asynchronous software components poses significant challenges due to the way components interleave and exchange input/output data concurrently. Compositional strategies aim to address this by separating the task of verifying individual components on local properties from the task of combining them to achieve global properties. This paper

Tanish Baranwal, Jan Lebert, Jan Christoph

Electrical waves in the heart form rotating spiral or scroll waves during life-threatening arrhythmias such as atrial or ventricular fibrillation. The wave dynamics are typically modeled using coupled partial differential equations, which describe reaction-diffusion dynamics in excitable media. More recently, data-driven generative modeling has emerged as an

Thibault Maurel-Oujia, Suhas S. Jain, Keigo Matsuda, Kai Schneider

Cluster and void formations are key processes in the dynamics of particle-laden turbulence. In this work, we assess the performance of various neural network models for synthesizing preferential concentration fields of particles in turbulence. A database of direct numerical simulations of homogeneous isotropic two-dimensional turbulence with one-way coupled

Jinpeng Liu, Wenxun Dai, Chunyu Wang, Yiji Cheng

Conventional text-to-motion generation methods are usually trained on limited text-motion pairs, making them hard to generalize to open-world scenarios. Some works use the CLIP model to align the motion space and the text space, aiming to enable motion generation from natural language motion descriptions. However, they are still constrained to generate limit

Georgios Pappas, Rong Zhou

We give a simple and uniform proof of a conjecture of Haines-Richarz characterizing the smooth locus of Schubert varieties in twisted affine Grassmannians. Our method is elementary and avoids any representation theoretic techniques, instead relying on a combinatorial analysis of tangent spaces of Schubert varieties.

Lluís Hernández-Navarro, Matthew Asker, Mauro Mobilia

Antimicrobial resistance to drugs (AMR), a global threat to human and animal health, is often regarded as resulting from cooperative behaviour. Moreover, microbes generally evolve in volatile environments that, together with demographic fluctuations (birth and death events), drastically alter population size and strain survival. Motivated by the need to bett

Michael Hite, Yannick Meurice

Ab-initio calculations of real-time evolution for lattice gauge theory have very interesting potential applications but present challenging computational aspects. We show that tensor renormalization group methods developed in the context of Euclidean-time lattice field theory can be applied to calculation of Trotterized evolution operators at real time. We d

Mingyuan Zhang, Huirong Li, Zhongang Cai, Jiawei Ren

Text-driven motion generation has achieved substantial progress with the emergence of diffusion models. However, existing methods still struggle to generate complex motion sequences that correspond to fine-grained descriptions, depicting detailed and accurate spatio-temporal actions. This lack of fine controllability limits the usage of motion generation to

Daniel Koutas, Elizabeth Bismut, Daniel Straub

We propose a novel Deep Reinforcement Learning (DRL) architecture for sequential decision processes under uncertainty, as encountered in inspection and maintenance (I&M) planning. Unlike other DRL algorithms for (I&M) planning, the proposed +RQN architecture dispenses with computing the belief state and directly handles erroneous observations instead. We app

Maurice A. de Gosson

We address the problem of the reconstruction of quantum covariance matrices using the notion of Lagrangian and symplectic polar duality introduced in previous work. We apply our constructions to Gaussian quantum states which leads to a non-trivial generalization of Pauli's reconstruction problem and we state a simple tomographic characterization of such stat

Enrico Trotti

The scalar glueball, the lightest state in the gluonic Yang-Mills (YM) sector of QCD, is stable in that framework. The scattering of two scalar glueballs is therefore a well defined process in YM, which can be studied with the tools of quantum field theory and partial wave analysis. By using a dilaton Lagrangian, which contains a single dimensionful paramete

Esrat F. Dulia, Mir S. Sabuj, Syed A. M. Shihab

Advanced Air Mobility (AAM) is an emerging transportation system that will enable the safe and efficient low altitude operations and applications of unmanned aircraft (e.g., passenger transportation and cargo delivery) in the national airspace. This system is currently under active research and development by NASA in collaboration with FAA, other federal par

Nicolas Bohm Agostini, Jude Haris, Perry Gibson, Malith Jayaweera

This paper addresses the need for automatic and efficient generation of host driver code for arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an important workload in various applications, including machine learning and scientific computing. While existing tools have focused on automating accelerator prototyping, little attention

Valérie Castin, Pierre Ablin, Gabriel Peyré

Self-attention and masked self-attention are at the heart of Transformers' outstanding success. Still, our mathematical understanding of attention, in particular of its Lipschitz properties - which are key when it comes to analyzing robustness and expressive power - is incomplete. We provide a detailed study of the Lipschitz constant of self-attention in sev

Victor Ceban, Mihai A. Macovei

We have investigated the phonon dynamics of a single-molecule embedded in a mechanical resonator made of an organic crystal. The whole system is placed in an optical resonator within the bad cavity limit. We have found that the optical control of the molecular population affects the phonon dynamics. Long-lived phonons are obtained when slowing-down the decay

Sandra Buob, Jonatan Höschele, Vasiliy Makhalov, Antonio Rubio-Abadal

The development of quantum-gas microscopes has brought novel ways of probing quantum degenerate many-body systems at the single-atom level. Until now, most of these setups have focused on alkali atoms. Expanding quantum-gas microscopy to alkaline-earth elements will provide new tools, such as SU(N)-symmetric fermionic isotopes or ultranarrow optical transiti

Nick Keepfer, Thomas Flynn, Nick Parker, Thomas Billam

We introduce a novel approach to the three-dimensional reconstruction of superfluid vortex filaments using deep convolutional neural networks. Superfluid vortices, quantum mechanical phenomena of immense scientific interest, are challenging to image due to their small dimensions and intricate topology. Here, we propose a deep-learning methodology that serves

Shane Bergsma, Timothy Zeyl, Javad Rahimipour Anaraki, Lei Guo

We present coarse-to-fine autoregressive networks (C2FAR), a method for modeling the probability distribution of univariate, numeric random variables. C2FAR generates a hierarchical, coarse-to-fine discretization of a variable autoregressively; progressively finer intervals of support are generated from a sequence of binned distributions, where each distribu

Aimeric Colléaux, David Langlois, Karim Noui

We classify all higher-order generalised Einstein-Maxwell Lagrangians that include terms linear in the curvature tensor and quadratic in the derivatives of the electromagnetic field strength tensor. Using redundancies due to the Bianchi identities, dimensionally dependent identities and boundary terms, we show that a general Lagrangian of this form can alway

Christopher Hoffman, Avi Levy, Elchanan Mossel

The stable matching problem has been the subject of intense theoretical and empirical study since the seminal 1962 paper by Gale and Shapley. The number of stable matchings for different systems of preferences has been studied in many contexts, going back to Donald Knuth in the 1970s. In this paper, we consider a family of distributions defined by the Mallow

Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wołczyk

Many complex tasks can be decomposed into simpler, independent parts. Discovering such underlying compositional structure has the potential to enable compositional generalization. Despite progress, our most powerful systems struggle to compose flexibly. It therefore seems natural to make models more modular to help capture the compositional nature of many ta

David de la Rosa, Antonio J Rivera, María J del Jesus, Francisco Charte

Photo-trapping cameras are widely employed for wildlife monitoring. Those cameras take photographs when motion is detected to capture images where animals appear. A significant portion of these images are empty - no wildlife appears in the image. Filtering out those images is not a trivial task since it requires hours of manual work from biologists. Therefor

S. Calder, Z. Y. Zhao, M. H. Upton, J. -Q. Yan

The pyrochlore osmate Ho2Os2O7 is a candidate material for a fragile J=0 local singlet ground state, however little is known regarding the single-ion behavior of either the Os or Ho ions. To address this we present polarized neutron powder diffraction (PNPD) and resonant inelastic x-ray scattering (RIXS) measurements that separately probe the local site beha

J. Gliozzo, G. Marinò, A. Bonometti, M. Frasca

The prediction of tumor progression and chemotherapy response has been recently tackled exploiting Tumor Infiltrating Lymphocytes (TILs) and the nuclear protein Ki67 as prognostic factors. Recently, deep neural networks (DNNs) have been shown to achieve top results in estimating Ki67 expression and simultaneous determination of intratumoral TILs score in bre

Jinwoo Go, Peng Chen

We consider optimal experimental design (OED) problems in selecting the most informative observation sensors to estimate model parameters in a Bayesian framework. Such problems are computationally prohibitive when the parameter-to-observable (PtO) map is expensive to evaluate, the parameters are high-dimensional, and the optimization for sensor selection is

Sofie Goethals, Sandra Matz, Foster Provost, Yanou Ramon

Our online lives generate a wealth of behavioral records -'digital footprints'- which are stored and leveraged by technology platforms. This data can be used to create value for users by personalizing services. At the same time, however, it also poses a threat to people's privacy by offering a highly intimate window into their private traits (e.g., their per

Nadia Qutob, Razieh Emami, Kung-Yi Su, Randall Smith

We make an in-depth analysis of different AGN jet models' signatures, inducing quiescence in galaxies with a halo mass of $10^{12} M_\odot$. Three jet models, including cosmic ray-dominant, hot thermal, and precessing kinetic jets, are studied at two energy flux levels each, compared to a jet-free, stellar feedback-only simulation. We examine the distributio

Ayoub Raji, Nicola Musiu, Alessandro Toschi, Francesco Prignoli

In this paper, we present a novel formulation to model the effects of a locked differential on the lateral dynamics of an autonomous open-wheel racecar. The model is used in a Model Predictive Controller in which we included a micro-steps discretization approach to accurately linearize the dynamics and produce a prediction suitable for real-time implementati

E. Ercolessi, R. Fioresi, T. Weber

In this expository paper we present a brief introduction to the geometrical modeling of some quantum computing problems. After a brief introduction to establish the terminology, we focus on quantum information geometry and ZX-calculus, establishing a connection between quantum computing questions and quantum groups, i.e. Hopf algebras.

Georgia Atkinson, Nick Wright, A. Stephen McGough, Per Berggren

In recent years generative adversarial networks (GANs) have been used to supplement datasets within the field of marine bioacoustics. This is driven by factors such as the cost to collect data, data sparsity and aid preprocessing. One notable challenge with marine bioacoustic data is the low signal-to-noise ratio (SNR) posing difficulty when applying deep le

Max Bergerhoff, Omar Elshehy, Stephan Kucera, Matthias Kreis

The quantum repeater cell is a basic building block for a quantum network, as it allows to overcome the distance limitations due to unavoidable fiber loss in direct transmission. We demonstrate the implementation of a quantum repeater cell, based on two free-space coupled $^{40}$Ca$^+$ ions in the same trap that act as quantum memories. We demonstrate the as

Emma Pierson, Divya Shanmugam, Rajiv Movva, Jon Kleinberg

Advances in large language models (LLMs) have driven an explosion of interest about their societal impacts. Much of the discourse around how they will impact social equity has been cautionary or negative, focusing on questions like "how might LLMs be biased and how would we mitigate those biases?" This is a vital discussion: the ways in which AI generally, a

Attilio Frangi, Alessio Colombo, Alessandra Vizzaccaro, Cyril Touzé

This paper presents the first application of the direct parametrisation method for invariant manifolds to a fully coupled multiphysics problem involving the nonlinear vibrations of deformable structures subjected to an electrostatic field. The formulation proposed is intended for model order reduction of electrostatically actuated resonating Micro-Electro-Me

Tin Nguyen, Peijie Chen, Anh Totti Nguyen

Traditional bird classifiers mostly rely on the visual characteristics of birds. Some prior works even train classifiers to be invariant to the background, completely discarding the living environment of birds. Instead, we are the first to explore integrating habitat information, one of the four major cues for identifying birds by ornithologists, into modern

Konstantinos Tsougkas

The spectral zeta function of the Laplacian on self-similar fractal sets has been previously studied and shown to meromorphically extend to the complex plane. In this work we establish under certain conditions a relationship between the logarithm of the determinant of the discrete graph Laplacian on the sequence of graphs approximating the fractal and the re