December 2024 arXiv papers — page 66

Tang-Kai Lee, Archana Mohandas

We study ancient solutions to discrete heat equations on some weighted graphs. On a graph of the form of a product with $\bb Z,$ we show that there are no non-trivial ancient solutions with polynomial growth. This result is parallel to the case of finite graphs, which is also discussed. Along the way, we prove a backward uniqueness result for solutions with

Annet Konings, Mariia Marinichenko, Oleksii Mikulenko, Subodh P. Patil

Primordial gravitational waves propagate almost unimpeded from the moment they are generated to the present epoch. Nevertheless, they are subject to convolution with a non-trivial transfer function. Within the standard thermal history, shifts in the temperature-redshift relation combine with damping effects by free streaming neutrinos to non-trivially proces

Antonia Seifert, Zachary G. Lane, Marco Galoppo, Ryan Ridden-Harper

We present a new, cosmologically model-independent, statistical analysis of the Pantheon+ type Ia supernovae spectroscopic dataset, improving a standard methodology adopted by Lane et al. We use the Tripp equation for supernova standardisation alone, thereby avoiding any potential correlation in the stretch and colour distributions. We compare the standard h

Sigal Gottlieb, Zachary J. Grant

High order strong stability preserving (SSP) time discretizations ensure the nonlinear non-inner-product strong stability properties of spatial discretizations suited for the stable simulation of hyperbolic PDEs. Over the past decade multiderivative time-stepping have been used for the time-evolution hyperbolic PDEs, so that the strong stability properties o

Chatchai Noytaptim, Xiao Zhong

Recently, the authors have proved the finiteness of common zeros of two iterated rational maps under some compositional independence assumptions. In this article, we advance towards a question of Hsia and Tucker on a Zariski non-density of common zeros of iterated morphisms on a variety. More precisely, we provide an affirmative answer in the case of H\'{e}n

Ben Simner, Alasdair Armstrong, Thomas Bauereiss, Brian Campbell

To manage exceptions, software relies on a key architectural guarantee, precision: that exceptions appear to execute between instructions. However, this definition, dating back over 60 years, fundamentally assumes a sequential programmers model. Modern architectures such as Arm-A with programmer-observable relaxed behaviour make such a naive definition inade

Jaume de Haro, Emilio Elizalde, Supriya Pan

Based on the Newtonian mechanics, in this article, we present a heuristic derivation of the Friedmann equations, providing an intuitive foundation for these fundamental relations in cosmology. Additionally, using the first law of thermodynamics and Euler's equation, we derive a set of equations that, at linear order, coincide with those obtained from the con

Abdelhak Djouadi, John Ellis, Jeremie Quevillon

We discuss ways to discriminate at hadron colliders between a quasi-bound toponium state and a pseudoscalar Higgs boson A, as predicted in many extensions of the Standard Model. We apply the discussion to the excess of t tbar threshold events recently observed at the LHC by the CMS collaboration \cite{CMS}, which could in principle be due to either possibili

Armaan Sharma, Mansur M. Arief

Growing concerns regarding environmental health have highlighted the aviation industry's impact and potential mitigation strategies. Previous research has indicated hydrogen's significant potential for reducing the industry's environmental impact, yet implementation challenges remain. Through analysis of light aircraft and military applications, we demonstra

Nils Berglund, Georgi S. Medvedev, Gideon Simpson

The Kuramoto model (KM) of $n$ coupled phase-oscillators is analyzed in this work. The KM on a Cayley graph possesses a family of steady state solutions called twisted states. Topologically distinct twisted states are distinguished by the winding number $q\in\mathbb{Z}$. These states are known to be stable for small enough $q$. In the presence of small noise

Chunyan Mu, Nima Motamed, Natasha Alechina, Brian Logan

There has been considerable work on reasoning about the strategic ability of agents under imperfect information. However, existing logics such as Probabilistic Strategy Logic are unable to express properties relating to information transparency. Information transparency concerns the extent to which agents' actions and behaviours are observable by other agent

Michael Hanks, Soovin Lee, Nicolo Lo Piparo, Shin Nishio

Bosonic codes have seen a resurgence in interest for applications as varied as fault tolerant quantum architectures, quantum enhanced sensing, and entanglement distribution. Cat codes have been proposed as low-level elements in larger architectures, and the theory of rotationally symmetric codes more generally has been significantly expanded in the recent li

Chang Ye, Gonzalo Mateos

We study blind deconvolution of signals defined on the nodes of an undirected graph. Although observations are bilinear functions of both unknowns, namely the forward convolutional filter coefficients and the graph signal input, a filter invertibility requirement along with input sparsity allow for an efficient linear programming reformulation. Unlike prior

Syuhei Iguro, Varun Mathur, Ian M. Shoemaker, Volodymyr Takhistov

We present a novel mechanism for the irreducible production of magnetic monopoles from interactions of cosmic rays and interstellar medium (ISM). Resulting monopoles drain energy from galactic magnetic fields, disrupting their formation and sustainability. We generalize conventional Parker bounds to monopoles with extended energy spectrum and, considering co

Matteo Della Rocca, Georgios Antoniou, Leonardo Gualtieri, Andrea Maselli

We investigate the gravitational wave emission from extreme mass ratio inspirals, key targets for the upcoming space-based detector LISA, considering the scenario where the lighter black hole in the binary is endowed by a long-lived, time-dependent scalar field configuration, known as a scalar wig. We develop a formalism to compute scalar perturbations for e

Erik D. Demaine, Martin L. Demaine, Markus Hecher, Rebecca Lin

We prove two results about transforming any convex polyhedron, modeled as a linkage L of its edges. First, if we subdivide each edge of L in half, then L can be continuously flattened into a plane. Second, if L is equilateral and we again subdivide each edge in half, then L can be reversed, i.e., turned inside-out. A linear number of subdivisions is optimal

Alexander Kolesnikov, André Susano Pinto, Michael Tschannen

In the past, normalizing generative flows have emerged as a promising class of generative models for natural images. This type of model has many modeling advantages: the ability to efficiently compute log-likelihood of the input data, fast generation and simple overall structure. Normalizing flows remained a topic of active research but later fell out of fav

Haotian Zheng, Jinke Ren, Yushan Sun, Ruichen Zhang

The recent advancements in large language models (LLMs) have significantly improved language understanding and generation capabilities. However, it is difficult to deploy LLMs on resource-constrained edge devices due to their high computational and storage resource demands. To address this issue, we propose a novel LLM model pruning method, namely structural

Federico Mazzone, Maarten Everts, Florian Hahn, Andreas Peter

Fully Homomorphic Encryption (FHE) enables operations on encrypted data, making it extremely useful for privacy-preserving applications, especially in cloud computing environments. In such contexts, operations like ranking, order statistics, and sorting are fundamental functionalities often required for database queries or as building blocks of larger protoc

King L. Ng, Luís H. Carnevale, Michał Klamka, Piotr Deuar

Deformed droplets are ubiquitous in various industrial applications, such as inkjet printing, lab-on-a-chip devices, and spray cooling, and can fundamentally affect the involved applications both favorably and unfavorably. Here, we employ many-body dissipative particle dynamics to investigate the oscillations of water droplets on a harmonically and horizonta

Adria Gómez-Valent, Joan Solà Peracaula

The standard cosmological model currently in force, aka $\Lambda$CDM, has been plagued with a variety of tensions in the last decade or so, which puts it against the wall. At the core of the $\Lambda$CDM we have a rigid cosmological term, $\Lambda$, for the entire cosmic history. Recently, the results from the DESI collaboration suggested the possibility tha

ATLAS Collaboration

A search for the production of three massive vector bosons, $VVZ (V=W, Z)$, in proton-proton collisions at $\sqrt{s} = 13$ TeV is performed using data with an integrated luminosity of $140$ fb$^{-1}$ recorded by the ATLAS detector at the Large Hadron Collider. Events produced in the leptonic final states $WWZ \to \ell\nu \ell\nu \ell \ell$ ($\ell=e, \mu$), $

Gangli Liu

The all pairs shortest path problem is a fundamental optimization problem in graph theory. We deal with re-calculating the all-pairs shortest path (APSP) matrix after a minor modification of a weighted dense graph, e.g., adding a node, removing a node, or updating an edge. We assume the APSP matrix for the original graph is already known. The graph can be di

Lily Chung, Erik D. Demaine, Martin L. Demaine, Markus Hecher

We analyze the problem of folding one polyhedron, viewed as a metric graph of its edges, into the shape of another, similar to 1D origami. We find such foldings between all pairs of Platonic solids and prove corresponding lower bounds, establishing the optimal scale factor when restricted to integers. Further, we establish that our folding problem is also NP

Lydia J Bardwell Speltz, Seung-Kyun Lee, Yunhong Shu, Matt A Bernstein

Purpose: To theoretically and experimentally study implant lead tip heating caused by radiofrequency (RF) power deposition in different wire configurations that contain loop(s). Methods: Maximum temperature rise caused by RF heating was measured at 1.5T on 20 insulated, capped wires with various loop and straight segment configurations. The experimental resu

Yuqing Wang, Shuhuai Ren, Zhijie Lin, Yujin Han

Autoregressive models have emerged as a powerful approach for visual generation but suffer from slow inference speed due to their sequential token-by-token prediction process. In this paper, we propose a simple yet effective approach for parallelized autoregressive visual generation that improves generation efficiency while preserving the advantages of autor

Zhuohao Yu, Weizheng Gu, Yidong Wang, Xingru Jiang

Large Language Models excel at code generation yet struggle with complex programming tasks that demand sophisticated reasoning. To bridge this gap, traditional process supervision relies on learned reward models requiring costly training data and suffering from reward misalignment, while outcome supervision fails for complex tasks needing coordinated interme

Rajendra Prasad Bhatt, Sumanta Chakraborty, Sukanta Bose

We derive the response, the real part of which provides the tidal Love numbers, for non-extremal as well as extremal Kerr black holes under generic tidal perturbations. Our results suggest that the static as well as dynamical (linear-in-frequency) Love numbers vanish for both Schwarzschild and slowly rotating (linear-in-angular momentum) Kerr black holes, un

Jnaneshwar Baslingker, Manjunath Krishnapur, Mokshay Madiman

We prove log-concavity of the lengths of the top rows of Young diagrams under Poissonized Plancherel measure. This is the first known positive result towards a 2008 conjecture of Chen that the length of the top row of a Young diagram under the Plancherel measure is log-concave. This is done by showing that the ordered elements of several discrete ensembles h

Qwen, :, An Yang, Baosong Yang

In this report, we introduce Qwen2.5, a comprehensive series of large language models (LLMs) designed to meet diverse needs. Compared to previous iterations, Qwen 2.5 has been significantly improved during both the pre-training and post-training stages. In terms of pre-training, we have scaled the high-quality pre-training datasets from the previous 7 trilli

Qiyang Sun, Yupei Li, Emran Alturki, Sunil Munthumoduku Krishna Murthy

As Artificial Intelligence (AI) continues to advance rapidly, Friendly AI (FAI) has been proposed to advocate for more equitable and fair development of AI. Despite its importance, there is a lack of comprehensive reviews examining FAI from an ethical perspective, as well as limited discussion on its potential applications and future directions. This paper a

Thomas F Burns, Tomoki Fukai, Christopher J Earls

Large language models (LLMs) demonstrate an impressive ability to utilise information within the context of their input sequences to appropriately respond to data unseen by the LLM during its training procedure. This ability is known as in-context learning (ICL). Humans and non-human animals demonstrate similar abilities, however their neural architectures d

Guido Arnone, Guillermo Cortiñas, Devarshi Mukherjee

We study homological invariants of the Steinberg algebra $\mathcal{A}_k(\mathcal{G})$ of an ample groupoid $\mathcal{G}$ over a commutative ring $k$. For $\mathcal{G}$ principal or Hausdorff with ${\mathcal{G}}^{\rm{Iso}}\setminus{\mathcal{G}}^{(0)}$ discrete, we compute Hochschild and cyclic homology of $\mathcal{A}_k(\mathcal{G})$ in terms of groupoid homo

Will Hide, Bram Petri

We prove that the set of limit points of the set of all spectral gaps of closed arithmetic hyperbolic surfaces equals $[0,\frac{1}{4}]$.

Filip Novotný, Marek Talíř, Emil Varga

Superfluid helium, the inviscid low-temperature phase of liquid \4He, enables investigation of flows with reduced dimensionality since, due to the vanishing viscosity, sub-micron flow channels can be constructed. In such strongly confined volumes filled with superfluid, the longitudinal acoustic wave is a coupled fluctuation of pressure and entropy density c

Yang Tian, Sizhe Yang, Jia Zeng, Ping Wang

Current efforts to learn scalable policies in robotic manipulation primarily fall into two categories: one focuses on "action," which involves behavior cloning from extensive collections of robotic data, while the other emphasizes "vision," enhancing model generalization by pre-training representations or generative models, also referred to as world models,

Peter Craig, Elias Aydi, Laura Chomiuk, Jay Strader

We present a systematic study of the $BVRI$ colours of novae over the course of their eruptions. Where possible, interstellar reddening was measured using the equivalent widths of Diffuse Interstellar Bands (DIBs). Some novae lack spectra with sufficient resolution and signal-to-noise ratios; therefore, we supplement as necessary with 3D and 2D dust maps. Ut

R. Gerstner

We show how arbitrary unit cells of periodic materials can be represented as graphs whose nodes represent atoms and whose weighted edges represent tunneling connections between atoms. Further, we present methods to calculate the band structure of a material with an arbitrary graphical representation, which allows one to study the Fermi level of the material

Lei Tan, Weihao Li, Pingyang Dai, Jie Chen

In the realm of Text-Based Person Search (TBPS), mainstream methods aim to explore more efficient interaction frameworks between text descriptions and visual data. However, recent approaches encounter two principal challenges. Firstly, the widely used random-based Masked Language Modeling (MLM) considers all the words in the text equally during training. How

Smitarani Mishra, Shaon Sahoo

Statistical formulations of thermodynamic entropy, such as those by Boltzmann and Gibbs, were originally developed for classical systems and are well understood in that context. However, the foundational aspects of quantum statistical mechanics remain an area of active debate and are yet to be fully understood. This work is motivated by the need to develop a

Shimiao Li

The growing threats of uncertainties, anomalies, and cyberattacks on power grids are driving a critical need to advance situational awareness which allows system operators to form a complete and accurate picture of the present and future state. Simulation and estimation are foundational tools in this process. However, existing tools lack the robustness and e

Fabio L. Braghin

Pseudoscalar and axial neutral and charged pion-constituent quark coupling constants are investigated with nondegenerate quark masses in different kinematical points, off shell and on shell pions and constituent quarks. By considering a large quark mass expansion of a quark determinant in the presence of local pion field and of constituent quark background c

Canon Sun, Joseph Maciejko

We present an extension of Landau's theory of phase transitions by incorporating the topology of the order parameter. When the order parameter comprises several components arising from multiplicity in the same irreducible representation of symmetry, it can possess a nontrivial topology and acquire a Berry phase under the variation of thermodynamic parameters

Nynke van Uffelen, Lode Lauwaert, Mark Coeckelbergh, Olya Kudina

In recent years, much research has been dedicated to uncovering the environmental impact of Artificial Intelligence (AI), showing that training and deploying AI systems require large amounts of energy and resources, and the outcomes of AI may lead to decisions and actions that may negatively impact the environment. This new knowledge raises new ethical quest

Niall T. Macpherson, Paul Merrikin, Ricardo Stuardo

G-structure techniques are used to construct broad classes of circle compactifications of Mink$_{D+1}$ solutions to Mink$_{D}$ embedded into type II supergravity for $D=1,...5$. Under a certain assumptions we show that the conditions that imply supersymmetry for Mink$_{D+1}$ imply those of the Mink$_{D}$ solution, but that Bianchi identities of the fluxes mu

Xiangsen Chen, Xuming Hu, Nan Tang

Retrieve-augmented generation (RAG) frameworks have emerged as a promising solution to multi-hop question answering(QA) tasks since it enables large language models (LLMs) to incorporate external knowledge and mitigate their inherent knowledge deficiencies. Despite this progress, existing RAG frameworks, which usually follows the retrieve-then-read paradigm,

Noemi Anau Montel, James Alvey, Christoph Weniger

Model misspecification analysis strategies, such as anomaly detection, model validation, and model comparison are a key component of scientific model development. Over the last few years, there has been a rapid rise in the use of simulation-based inference (SBI) techniques for Bayesian parameter estimation, applied to increasingly complex forward models. To

M. Deal, M. -J. Goupil, J. Philidet, M. S. Cunha

The glitch signatures in $r_{010}$ for F-type stars (higher amplitude and period of the oscillatory component) are very different from those of G-type stars. The aim of this work is to analyse the signatures of these glitches and understand the origin of the differences in these signatures between G-type and F-type stars. We fit the glitch signatures in the

João A. Leite, Olesya Razuvayevskaya, Carolina Scarton, Kalina Bontcheva

Disinformation, irrespective of domain or language, aims to deceive or manipulate public opinion, typically through employing advanced persuasion techniques. Qualitative and quantitative research on the weaponisation of persuasion techniques in disinformation has been mostly topic-specific (e.g., COVID-19) with limited cross-domain studies, resulting in a la

Chloé Gaudu

For over two decades, CORSIKA 7 and its previous versions have been the leading Monte Carlo code for simulating extensive air showers. However, its monolithic Fortran-based software design and hand-optimized code has created challenges for maintenance, adaptation to new computing paradigms, and extensions for more complex simulations. Addressing these limita

Donghyeop Lee, Euisung Park

Let $\Gamma \subset \mathbb{P}^n$ be a nondegenerate finite subscheme of degree $d$. Then the Castelnuovo-Mumford regularity ${\rm reg} ({\Gamma})$ of $\Gamma$ is at most $\left\lceil \frac{d-n-1}{t(\Gamma)} \right\rceil +2$ where $t(\Gamma)$ is the smallest integer such that $\Gamma$ admits a $(t+2)$-secant $t$-plane. In this paper, we show that ${\rm reg}

Stefanos Gkikas, Manolis Tsiknakis

The automatic estimation of pain is essential in designing an optimal pain management system offering reliable assessment and reducing the suffering of patients. In this study, we present a novel full transformer-based framework consisting of a Transformer in Transformer (TNT) model and a Transformer leveraging cross-attention and self-attention blocks. Elab

Chloé Gaudu, Maximilian Reininghaus, Felix Riehn

The field of air shower physics, dedicated to understanding the development of cosmic-ray interactions with the Earth's atmosphere, faces a significant challenge regarding the muon content of air showers observed by the Pierre Auger Observatory, and numerous other observatories. Thorough comparisons between extensive air shower (EAS) measurements and simulat

Tim Sainburg, Asaf Zorea

Extracting signals from noisy backgrounds is a fundamental problem in signal processing across a variety of domains. In this paper, we introduce Noisereduce, an algorithm for minimizing noise across a variety of domains, including speech, bioacoustics, neurophysiology, and seismology. Noisereduce uses spectral gating to estimate a frequency-domain mask that

Fabian Billert, Stefan Conrad

Determining the sustainability impact of companies is a highly complex subject which has garnered more and more attention over the past few years. Today, investors largely rely on sustainability-ratings from established rating-providers in order to analyze how responsibly a company acts. However, those ratings have recently been criticized for being hard to

Lakshika Vaishnav, Sakshi Singh, Kimberly A. Cornell

This paper investigates the impacts of the rapidly evolving landscape of generative Artificial Intelligence (AI) development. Emphasis is given to how organizations grapple with a critical imperative: reevaluating their policies regarding AI usage in the workplace. As AI technologies advance, ethical considerations, transparency, data privacy, and their impa

Philippe Brax, Emma Bruyère

We consider the effects of quartic self-interactions on the dynamics of a binary system due to a (nearly) massless scalar field conformally coupled to matter. We investigate the deviations from General Relativity at the conservative level and put a bound on the self-coupling $ \lambda \lesssim (\beta^2 G_N M_\odot^2)^{-1}$ where $\beta$ is the conformal coup

C. G. Palau, W. Wang, J. Han

We develop a method for constraining the potential of the Milky Way using stellar streams with a known progenitor. The method expresses the stream in angle-action coordinates and integrates the orbits of the stars backwards in time to obtain the stripping point positions of the stream stars relative to the cluster. In the potential that generated the stream,

ATLAS Collaboration

The high-luminosity phase of LHC operations (HL-LHC), will feature a large increase in simultaneous proton-proton interactions per bunch crossing up to 200, compared with a typical leveling target of 64 in Run 3. Such an increase will create a very challenging environment in which to perform charged particle trajectory reconstruction, a task crucial for the

Ian Hambleton, John Nicholson

Kreck and Schafer produced the first examples of stably diffeomorphic closed smooth 4-manifolds which are not homotopy equivalent. They were constructed by applying the doubling construction to 2-complexes over certain finite abelian groups of odd order. By extending their methods, we formulate a new homotopy invariant on the class of 4-manifolds arising as

Tom R. Hepworth, Daniel K. Ruttley, Fritz von Gierke, Philip D. Gregory

Rotational states of ultracold polar molecules possess long radiative lifetimes, microwave-domain coupling, and tunable dipolar interactions. The availability of numerous rotational states has inspired many proposed applications, including simulations of quantum magnetism, encodings of information in high-dimensional qudits, and synthetic dimensions with man

Wei Cheng, Jiahui Hong, Zhi-Xiang Zhu

For the non-monotone Hamilton-Jacobi equations of contact type, the associated Lax-Oleinik semiflow $(T_t, C(M))$ is expansive. In this paper, we provide qualitative estimates for both the lower and upper bounds of the topological entropy of the semiflow.

Haoran Liu, Youzhi Luo, Tianxiao Li, James Caverlee

We consider the conditional generation of 3D drug-like molecules with \textit{explicit control} over molecular properties such as drug-like properties (e.g., Quantitative Estimate of Druglikeness or Synthetic Accessibility score) and effectively binding to specific protein sites. To tackle this problem, we propose an E(3)-equivariant Wasserstein autoencoder

Simone Blasi

We revisit the study of light interacting with QCD axion domain walls from the perspective of the non-linear axion coupling to photons, $g(a) F \tilde F$, which encodes the effects related to the breaking of the axion shift symmetry including the well-known mixing with meson states. As the axion makes an $\mathcal{O}(1)$ excursion of its fundamental period a

Zihan Liu, Yang Chen, Mohammad Shoeybi, Bryan Catanzaro

In this paper, we introduce AceMath, a suite of frontier math models that excel in solving complex math problems, along with highly effective reward models capable of evaluating generated solutions and reliably identifying the correct ones. To develop the instruction-tuned math models, we propose a supervised fine-tuning (SFT) process that first achieves com

Alexander Wimmers, Fanny Böse, Leonard Göke

Recent pledges to triple global nuclear capacity by 2050 suggest a "nuclear renaissance," bolstered by unconventional reactor concepts such as sodium-cooled fast reactors, high-temperature reactors, and molten salt reactors. These technologies claim to address the challenges of today's high-capacity light-water reactors, i.e., cost overruns, delays, and soci

Sovik Roy, Aahaman Kalaiselvan, Chandrashekar Radhakrishnan, Md Manirul Ali

The practical success of quantum technology hinges on sustaining quantum coherence, which is vulnerable to environmental interactions causing decoherence. We investigate coherence in tripartite quantum systems under the influence of noisy environment. In this study, we explore the dynamics of the relative entropy of coherence for tripartite pure and mixed st

Joey Bonitati

This thesis investigates quantum algorithms for eigenstate preparation, with a focus on solving eigenvalue problems such as the Schrodinger equation by utilizing near-term quantum computing devices. These problems are ubiquitous in several scientific fields, but more accurate solutions are specifically needed as a prerequisite for many quantum simulation tas

Nico J. Guth, Oskar Vallhagen, Per Helander, Istvan Pusztai

Pellets of frozen material travelling into a magnetically confined fusion plasma are accelerated by the so-called pellet rocket effect. The non-uniform plasma heats the pellet ablation cloud asymmetrically, producing pressure-driven, rocket-like propulsion of the pellet. We present a semi-analytical model of this process by perturbing a spherically symmetric

Yunli Shao

Model predictive control has emerged as an effective approach for real-time optimal control of connected and automated vehicles. However, nonlinear dynamics of vehicle and traffic systems make accurate modeling and real-time optimization challenging. Learning-based control offer a promising alternative, as they adapt to environment without requiring an expli

Chao Liang, Carlo Cosentino, Alessio Merola, Maria Romano

Some recent papers have extended the concept of finite-time stability (FTS) to the context of 2D linear systems, where it has been referred to as finite-region stability (FRS). FRS methodologies make even more sense than the classical FTS approach developed for 1D-systems, since, typically, at least one of the state variables of 2D-systems is a space coordin

Zhu Liao, Nour Hezbri, Victor Quétu, Van-Tam Nguyen

Today, deep neural networks are widely used since they can handle a variety of complex tasks. Their generality makes them very powerful tools in modern technology. However, deep neural networks are often overparameterized. The usage of these large models consumes a lot of computation resources. In this paper, we introduce a method called \textbf{T}ill the \t

Xuwei Tan, Qian Zhao, Yanlan Liu, Xueru Zhang

Drought is one of the most destructive and expensive natural disasters, severely impacting natural resources and risks by depleting water resources and diminishing agricultural yields. Under climate change, accurately predicting drought is critical for mitigating drought-induced risks. However, the intricate interplay among the physical and biological driver

Jorge Íñiguez-González, Hugo Aramberri

The experimental demonstration of electric skyrmion bubbles and the recent prediction of their Brownian motion have brought topological ferroelectrics close to their magnetic counterparts. Electric bubbles (e-bubbles) could potentially be leveraged in applications for which magnetic skyrmions have been proposed (e.g., neuromorphic computing). Yet, we still l

Nicolaï Gouraud, Louis Lagardère, Olivier Adjoua, Thomas Plé

We introduce the Velocity Jumps approach, denoted as JUMP, a new class of Molecular dynamics integrators, replacing the Langevin dynamics by a hybrid model combining a classical Langevin diffusion and a piecewise deterministic Markov process, where the expensive computation of long-range pairwise interactions is replaced by a resampling of the velocities at

Bhupendra Acharya, Dominik Sautter, Muhammad Saad, Thorsten Holz

Social media platforms have become the hubs for various user interactions covering a wide range of needs, including technical support and services related to brands, products, or user accounts. Unfortunately, there has been a recent surge in scammers impersonating official services and providing fake technical support to users through these platforms. In thi

R. A. Dumer, M. Godoy

In this work, we employed the Ising model to identify phase transitions in a magnetic system where the degree distribution of the network follows a power-law and the connections are assortatively mixed. In the Ising model, the spins assume only two values, $\sigma = \pm 1$, and interact through ferromagnetic coupling $J$. The network is characterized by four

Tianyu Qiu, Yi Xie, Yun Xiong, Hao Niu

This paper explores how to enhance existing masked time-series modeling by randomly dropping sub-sequence level patches of time series. On this basis, a simple yet effective method named DropPatch is proposed, which has two remarkable advantages: 1) It improves the pre-training efficiency by a square-level advantage; 2) It provides additional advantages for

Hanzhi Jiang, Mike Blake, Anthony P. Thompson

The quantum extremal island rule allows us to compute the Page curves of Hawking radiation in semi-classical gravity. In this work, we study the connection between these calculations and the thermalisation of chaotic quantum many-body systems, using a coarse-grained description of entanglement dynamics known as the entanglement membrane. Starting from a doub

Antoine El-Hayek, Monika Henzinger, Jason Li

Dynamically maintaining the minimum cut in a graph $G$ under edge insertions and deletions is a fundamental problem in dynamic graph algorithms for which no conditional lower bound on the time per operation exists. In an $n$-node graph the best known $(1+o(1))$-approximate algorithm takes $\tilde O(\sqrt{n})$ update time [Thorup 2007]. If the minimum cut is

Trung Kiên Lê, Daniil M. Lukin, Charles Roques-Carmes, Aviv Karnieli

Light-matter interaction with squeezed vacuum has received much interest for the ability to enhance the native interaction strength between an atom and a photon with a reservoir assumed to have an infinite bandwidth. Here, we study a model of parametrically driven cavity quantum electrodynamics (cavity QED) for enhancing light-matter interaction while subjec

Aqeel Ahmed, Zackaria Chacko, Ina Flood, Can Kilic

We perform a model-independent analysis of the dimension-six terms that are generated in the low energy effective theory when a hidden sector that communicates with the Standard Model (SM) through a specific portal operator is integrated out. We work within the Standard Model Effective Field Theory (SMEFT) framework and consider the Higgs, neutrino and hyper

Uba K. Ubamanyu, Zheren Baizhikova, Jia-Liang Le, Roberto Ballarini

We present the results from a numerical investigation using the finite element method to study the buckling strength of near-perfect spherical shells containing a single, localized, Gaussian-dimple defect whose profile is systematically varied toward the limit of vanishing amplitude. In this limit, our simulations reveal distinct buckling behaviors for hemis

Dilara Abdel, Maxime Herda, Martin Ziegler, Claire Chainais-Hillairet

In this paper, we present the numerical analysis and simulations of a multi-dimensional memristive device model. Memristive devices and memtransistors based on two-dimensional (2D) materials have demonstrated promising potential for neuromorphic computing and next-generation memory technologies. Our charge transport model describes the drift-diffusion of ele

Flavio Bombacigno, Mariaveronica De Angelis, Carsten van de Bruck, William Giarè

Within the framework of hybrid metric-Palatini gravity, we incorporate non-localities introduced via the inverse of the d'Alembert operators acting on the scalar curvature. We analyse the dynamical structure of the theory and, adopting a scalar-tensor perspective, assess the stability conditions to ensure the absence of ghost instabilities. Focusing on a spe

Chiheb Ben Mahmoud, Louise A. M. Rosset, Jonathan R. Yates, Volker L. Deringer

Nuclear magnetic resonance (NMR) is a powerful spectroscopic technique that is sensitive to the local atomic structure of matter. Computational predictions of NMR parameters can help to interpret experimental data and validate structural models, and machine learning (ML) has emerged as an efficient route to making such predictions. Here, we systematically st

Jiuzu Hong, Huanhuan Yu

The coherence conjecture of Pappas and Rapoport, proved by Zhu, asserts the equality of dimensions for the global sections of a line bundle over a spherical Schubert variety in the affine Grassmannian and those of another line bundle over a certain union of Schubert varieties in a partial affine flag variety. In this paper, we enhance this equality of dimens

Qi Liu, Ming Xue, Matthew Radzihovsky, Xinwei Li

Balancing high sensitivity with a broad dynamic range is a fundamental challenge in measurement science, as improving one often compromises the other. While traditional quantum metrology has prioritized enhancing local sensitivity, a large dynamic range is crucial for applications such as atomic clocks, where extended phase interrogation times contribute to

Patrick T. Brandt, Sultan Alsarra, Vito J. D`Orazio, Dagmar Heintze

Conflict scholars have used rule-based approaches to extract information about political violence from news reports and texts. Recent Natural Language Processing developments move beyond rigid rule-based approaches. We review our recent ConfliBERT language model (Hu et al. 2022) to process political and violence related texts. The model can be used to extrac

Damian Clancy, John J. H. Stewart

In infectious disease modelling, the expected time from endemicity to extinction (of infection) may be analysed via WKB approximation, a method with origins in mathematical physics. The method is very general, but its uptake to date may have been limited by the practical difficulties of implementation. It is necessary to compute a trajectory of a (high dimen

Hallee E. Wong, Jose Javier Gonzalez Ortiz, John Guttag, Adrian V. Dalca

Medical researchers and clinicians often need to perform novel segmentation tasks on a set of related images. Existing methods for segmenting a new dataset are either interactive, requiring substantial human effort for each image, or require an existing set of previously labeled images. We introduce a system, MultiverSeg, that enables practitioners to rapidl

Ion Grama, Michael Nussbaum

We establish that a non-Gaussian nonparametric regression model is asymptotically equivalent to a regression model with Gaussian noise. The approximation is in the sense of Le Cam's deficiency distance $\Delta $; the models are then asymptotically equivalent for all purposes of statistical decision with bounded loss. Our result concerns a sequence of indepen

Johannes Flake, Robert Laugwitz, Sebastian Posur

We show that induction along a Frobenius extension of Hopf algebras is a Frobenius monoidal functor in great generality, in particular, for all finite-dimensional and all pointed Hopf algebras. As an application, we show that induction functors from unimodular Hopf subalgebras to small quantum groups at roots of unity are Frobenius monoidal functors and clas

A. Doff, João Paulo Pinheiro, C. A. de S. Pires

In this work, we introduce the minimal set of leptoquarks into the 3-3-1 model with right-handed neutrinos, capable of generating radiative masses for active neutrinos. As a main consequence, the standard neutrinos acquire small Majorana masses at the one-loop level, while right-handed (sterile) neutrinos obtain small Majorana masses at the two-loop level, n

Yajing Wang, Zongwei Luo, Jingzhe Wang, Zhanke Zhou

Prompt optimization automatically refines prompting expressions, unlocking the full potential of LLMs in downstream tasks. However, current prompt optimization methods are costly to train and lack sufficient interpretability. This paper proposes enhancing LLMs' reasoning performance by eliciting their causal inference ability from prompting instructions to c

G. Andrade-Miranda, K. Chatzipapas, J. D. Arias-Londoño, J. I. Godino-Llorente

The advances in the development of Facilitative Playbacks extracted from High-Speed videoendoscopic sequences of the vocal folds are hindered by a notable lack of publicly available datasets annotated with the semantic segmentations corresponding to the area of the glottal gap. This fact also limits the reproducibility and further exploration of existing res

Ahmad Biniaz, Anil Maheshwari, Joseph S. B. Mitchell, Saeed Odak

We study the problem of guarding the boundary of a simple polygon with a minimum number of guards such that each guard covers a contiguous portion of the boundary. First, we present a simple greedy algorithm for this problem that returns a guard set of size at most OPT + 1, where OPT is the number of guards in an optimal solution. Then, we present a polynomi

Xiang-Yu Wu, Han Gao, Bailey Forster, Charles Gale

We present the first theoretical study of the polarization of lepton pairs produced in $\sqrt{s_\mathrm{NN}} = 5.02$ TeV Pb+Pb collisions at the LHC, using next-to-leading order (NLO) dilepton emission rates. These calculations employ a multi-stage framework to simulate the evolution of relativistic heavy-ion collisions, and to explore the sensitivity of pol

Ming-Shau Liu, Nicholas Kamp, Carlos A. Argüelles

We report new constraints and sensitivities to heavy neutral leptons (HNLs) with transition magnetic moments, also known as dipole-portal HNLs. This is accomplished using data from the T2K ND280 near detector in addition to the projected three-year dataset of the upgraded ND280 detector. Dipole-portal HNLs have been extensively studied in the literature and

Zhifei Chen, Tianshuo Xu, Wenhang Ge, Leyi Wu

Rendering and inverse rendering are pivotal tasks in both computer vision and graphics. The rendering equation is the core of the two tasks, as an ideal conditional distribution transfer function from intrinsic properties to RGB images. Despite achieving promising results of existing rendering methods, they merely approximate the ideal estimation for a speci