December 2024 arXiv papers — page 179

Yi-Chen Wu, Hsien-Hsin Chou

Perovskite materials are highly promising for a range of optoelectronic applications including energy conversion technologies, owing to their high charge-carrier mobilities, adaptability of bandgap tuning, and exceptional light-harvesting capabilities. Yet, defects that arise during manufacturing often lead to performance limitations such as hindered efficie

Ruoqi Yu, Bikram Karmakar, Jessica Vandeleest, Eleanor Bimla Schwarz

Causal inference is vital for informed decision-making across fields such as biomedical research and social sciences. Randomized controlled trials (RCTs) are considered the gold standard for internal validity of inferences, whereas observational studies (OSs) often provide the opportunity for greater external validity. However, both data sources have inheren

Pouya Tanouri, Ryley Hill, Douglas Scott, Edward L. Chapin

Photometric redshifts (photo-z's) provide an efficient alternative to spectroscopic redshifts, enabling redshift estimation for large galaxy samples. However, traditional photo-z methods primarily rely on optical and near-infrared (OIR) photometry, which can struggle with dusty star-forming galaxies that are often faint in the OIR but bright at far-infrared

Diego Fallas Padilla, Mingjian Zhu, Han Pu

Quantum entanglement is an essential resource for quantum science and technology. However, entanglement detection and quantification, via typical entanglement measures such as linear entanglement entropy or negativity, can be a very challenging task. Here we propose a protocol to detect bipartite entanglement in a system of $N$ qubits inspired by the concept

Zhiheng Zhang, Zichen Wang

Network interference has attracted significant attention in the field of causal inference, encapsulating various sociological behaviors where the treatment assigned to one individual within a network may affect the outcomes of others, such as their neighbors. A key challenge in this setting is that standard causal inference methods often assume independent t

Lorenzo Agosta, Kersti Hermansson, Mikhail Dzugutov

The properties of liquid water are known to change drastically in confined geometries. A most interesting and intriguing phenomenon is that the diffusion of water is found to be strongly enhanced by the proximity of a hydrophobic confining wall relative to the bulk diffusion. We report a molecular dynamics simulation using a classical water model investigati

Yogesh Phalak, Hodjat Pendar

In this theoretical study, we present an analytical framework to investigate the slithering motion of snakes on flat surfaces. While previous studies have predominantly relied on numerical methods to identify optimal locomotion kinematics, such approaches are often sensitive to initial guesses and the number of kinematic parameters in the model. Here, we der

Ron A Soltz, Dhanush A Hangal, Aaron Angerami

We apply Bayesian techniques to compare a simple, empirical model for jet-quenching in heavy-ion collisions to centrality-dependent jet-$R_{AA}$ measured by ATLAS for Pb+Pb collisions at $\sqrt{s_{NN}}=5.02$~TeV. We find that the $R_{AA}$ values for central collisions are adequately described with a model for the mean $p_T$-dependent jet energy-loss using on

Sheng Xu, Amnon Balanov, Amit Singer, Tamir Bendory

Accurate orientation estimation is a crucial component of 3D molecular structure reconstruction, both in single-particle cryo-electron microscopy (cryo-EM) and in the increasingly popular field of cryo-electron tomography (cryo-ET). The dominant approach, which involves searching for the orientation that maximizes cross-correlation relative to given template

Víctor Blanco, Alberto Japón, Justo Puerto, Peter Zhang

In this paper we provide a novel mathematical optimization based methodology to perturb the features of a given observation to be re-classified, by a tree ensemble classification rule, to a certain desired class. The method is based on these facts: the most viable changes for an observation to reach the desired class do not always coincide with the closest d

Raimund Bürger, Claudio Muñoz, Sebastián Tapia

Jamitons are self-sustained traveling wave solutions that arise in certain second-order macroscopic models of vehicular traffic. A necessary condition for a jamiton to appear is that the local traffic density breaks the so-called sub-characteristic condition. This condition states that the characteristic velocity of the corresponding first-order Lighthill-Wh

D. J. Campbell, M. Frachet, V. Oliviero, T. Kurosawa

Strange metals challenge our understanding of charge transport in metals. Here, we investigate how the strange metal phase of La$_{2-x}$Sr$_x$CuO$_4$ is impacted by a field-induced glassy antiferromagnetic state. Using magnetic fields above 80 T, we discover a strong enhancement of the normal state magnetoresistance when entering the spin glass phase. We dem

Tim Vieira, Ben LeBrun, Mario Giulianelli, Juan Luis Gastaldi

Modern language models are internally -- and mathematically -- distributions over $\it{token}$ strings rather than $\it{character}$ strings, posing numerous challenges for programmers building user applications on top of them. For example, if a prompt is specified as a character string, it must be tokenized before passing it to the token-level language model

Ye Yuan, Can Chen, Christopher Pal, Xue Liu

In offline multi-objective optimization (MOO), we leverage an offline dataset of designs and their associated labels to simultaneously minimize multiple objectives. This setting more closely mirrors complex real-world problems compared to single-objective optimization. Recent works mainly employ evolutionary algorithms and Bayesian optimization, with limited

Juan Miguel Lopez Alcaraz, Wilhelm Haverkamp, Nils Strodthoff

Background: Liver diseases present a significant global health challenge and often require costly, invasive diagnostics. Electrocardiography (ECG), a widely available and non-invasive tool, can enable the detection of liver disease by capturing cardiovascular-hepatic interactions. Methods: We trained tree-based machine learning models on ECG features to dete

Gian Alix, Arian Haghparast, Manos Papagelis

Advances in tracking technologies have spurred the rapid growth of large-scale trajectory data. Building a compact collection of pathlets, referred to as a trajectory pathlet dictionary, is essential for supporting mobility-related applications. Existing methods typically adopt a top-down approach, generating numerous candidate pathlets and selecting a subse

J. Félix Salazar, Ana Laura García-Perciante, Olivier Sarbach

In this paper we derive a new first-order theory of relativistic dissipative fluids by adopting the trace-fixed particle frame. Whereas in a companion letter we show that this theory is hyperbolic, causal and stable at global equilibrium states, here we prove that the full nonlinear system of equations can be cast into a first-order quasilinear system which

J. Félix Salazar, Ana Laura García-Perciante, Olivier Sarbach

We propose a first-order theory of relativistic dissipative fluids in the trace-fixed particle frame, which is similar to Eckart's frame except that the temperature is determined by fixing the trace of the stress-energy tensor. Our theory is hyperbolic and causal provided a single inequality holds. For low wave numbers, the expected damped modes in the shear

Krzysztof Gołębiowski

The main aim of this article is to prove that for any continuous function $f \colon X \to X$, where $X$ is metrizable (or, more generally, for any family $\mathcal{F}$ of such functions, satisfying an additional condition), there exists a compatible metric $d$ on $X$ such that the $n$th iteration of $f$ (more generally, the composition of any $n$ functions f

Taehyeun Kim, Anouck Girard, Ilya Kolmanovsky

The paper considers a Constrained-Informed Neural Network (CINN) approximation for the Time Shift Governor (TSG), which is an add-on scheme to the nominal closed-loop system used to enforce constraints by time-shifting the reference trajectory in spacecraft rendezvous applications. We incorporate Kolmogorov-Arnold Networks (KANs), an emerging architecture in

Saurav Ghosh, Reshmi Mitra, Indranil Roy, Bidyut Gupta

Ensuring security for highly dynamic peer-to-peer (P2P) networks has always been a challenge, especially for services like online transactions and smart devices. These networks experience high churn rates, making it difficult to maintain appropriate access control. Traditional systems, particularly Role-Based Access Control (RBAC), often fail to meet the nee

Pio Ong, Max H. Cohen, Tamas G. Molnar, Aaron D. Ames

This paper presents a novel approach for synthesizing control barrier functions (CBFs) from high relative degree safety constraints: Rectified CBFs (ReCBFs). We begin by discussing the limitations of existing High-Order CBF approaches and how these can be overcome by incorporating an activation function into the CBF construction. We then provide a comparativ

Maximilian K. Baker, Timothy A. Davis, Freeke van de Voort, Ilaria Ruffa

The dominant processes by which galaxies replenish their cold gas reservoirs remain disputed, especially in massive galaxies. Stellar-gas kinematic misalignments offer an opportunity to study these replenishment processes. However, observed distributions of these misalignments conflict with current models of gas replenishment in early-type galaxies (ETGs), w

Yingtao Luo, Zhixun Li, Qiang Liu, Jun Zhu

Machine learning systems are notoriously prone to biased predictions about certain demographic groups, leading to algorithmic fairness issues. Due to privacy concerns and data quality problems, some demographic information may not be available in the training data and the complex interaction of different demographics can lead to a lot of unknown minority sub

Jacob A. Warshauer, Huyongqing Chen, Daniel Alejandro Bustamante Lopez, Qishuo Tan

Van der Waals magnets are an emerging material family for investigating light-matter interactions and spin-correlated excitations. Here, we report the discovery of a photo-induced state with a lifetime of 17 ps in the van der Waals antiferromagnet NiPS$_3$, which appears exclusively with resonant pumping at 1.476 eV in the antiferromagnetic state. The long-l

Xiyao Wang, Zhengyuan Yang, Linjie Li, Hongjin Lu

Despite significant advancements in vision-language models (VLMs), there lacks effective approaches to enhance response quality by scaling inference-time computation. This capability is known to be a core step towards the self-improving models in recent large language model studies. In this paper, we present Vision Value Model (VisVM) that can guide VLM infe

Andrii A. Chaika, Yelizaveta Kulynych, D. O. Oriekhov, Sergei G. Sharapov

The density of states and differential entropy per particle are analyzed for Dirac-like electrons in graphene subjected to a perpendicular magnetic field and an in-plane electric field. For comparison, the derived density of states is contrasted with the well-known case of nonrelativistic electrons in crossed magnetic and electric fields. The study considers

Behrad Moniri, Hamed Hassani

In this paper we study the asymptotics of linear regression in settings with non-Gaussian covariates where the covariates exhibit a linear dependency structure, departing from the standard assumption of independence. We model the covariates using stochastic processes with spatio-temporal covariance and analyze the performance of ridge regression in the high-

Dongping Fang, Lian Duan, Xiaojing Yuan, Allyn Klunder

Accurate prediction of medical conditions with straight past clinical evidence is a long-sought topic in the medical management and health insurance field. Although great progress has been made with machine learning algorithms, the medical community is still skeptical about the model accuracy and interpretability. This paper presents an innovative hierarchic

Luciana Ferrer, Odette Scharenborg, Tom Bäckström

Many development decisions affect the results obtained from ML experiments: training data, features, model architecture, hyperparameters, test data, etc. Among these aspects, arguably the most important design decisions are those that involve the evaluation procedure. This procedure is what determines whether the conclusions drawn from the experiments will o

Yinghe Qi, Zhenwei Xu, Filippo Coletti

The small-scale velocity gradient is connected to fundamental properties of turbulence at the large scales. By neglecting the viscous and nonlocal pressure Hessian terms, we derive a restricted Euler model for the turbulent flow along an undeformed free surface and discuss the associated stable/unstable manifolds. The model is compared with the data collecte

Artem Abanov, Shang-Shun Zhang, Andrey Chubukov

We analyze the dynamical pairing susceptibility $\chi_{pp} (\omega_m)$ at $T=0$ in a quantum-critical metal, where superconductivity emerges out of a non-Fermi liquid ground state once the pairing interaction exceeds a certain threshold. We obtain $\chi_{pp} (\omega_m)$ as the ratio of the fully dressed dynamical pairing vertex $\Phi (\omega_m)$ and the bare

Matthew Heydeman, Chiara Toldo

Supersymmetric rotating 1/16-BPS black holes in $AdS_4 \times S^7$ are expected to capture the average degeneracy of BPS states in the dual ABJM superconformal theory for given fixed charges. This has been successfully demonstrated for the superconformal index using complexified black hole metrics, but a naive Gibbons-Hawking calculation of the actual degene

Pierre Bousseyroux, Jean-Philippe Bouchaud

The eigenvalue spectrum of the sum of large random matrices that are mutually "free", i.e., randomly rotated, can be obtained using the formalism of R-transforms, with many applications in different fields. We provide a direct interpretation of the otherwise abstract additivity property of R-transforms for the sum in terms of a dynamical evolution of "partic

Matthew Heydeman, Chiara Toldo

For a variety of BPS black holes in string theory, the supersymmetric index has provided a microscopic validation of the Bekenstein-Hawking formula. In the near-BPS limit, a gravitational path integral analysis previously revealed the semiclassical spectrum is modified, having a large extremal degeneracy (consistent with the index) and a mass gap up to a con

Amílcar Branquinho, Juan E. F. Díaz, Ana Foulquié-Moreno, Hélder Lima

We provide necessary and sufficient conditions for the Hessenberg recurrence matrix associated with a system of multiple orthogonal polynomials to admit a factorisation as a product of bidiagonal matrices. Using the Gauss-Borel factorisation of the moment matrix, we show that the nontrivial entries of those bidiagonal matrices can be expressed in terms of co

Shreya Bhatia, Tarushi Gandhi, Dhruv Kumar, Pankaj Jalote

System testing is essential in any software development project to ensure that the final products meet the requirements. Creating comprehensive test cases for system testing from requirements is often challenging and time-consuming. This paper explores the effectiveness of using Large Language Models (LLMs) to generate test case designs from Software Require

Dennis Bonatsos, Andriana Martinou, S. K. Peroulis, D. Petrellis

The proxy-SU(3) symmetry predicts, in a parameter-free way, the collective deformation variables beta and gamma in even-even atomic nuclei away from closed shells based on the highest weight irreducible representations (irreps) of SU(3) in the relevant proton and neutron shells, which are the most symmetric irreps allowed by the Pauli principle and the short

L. Richarz, I. C. Skogvoll, E. Y. Tokle, K. A. Hunnestad

Domain walls in ferroelectric oxides provide fertile ground for the development of next-generation nanotechnology. Examples include domain-wall-based memory, memristors, and diodes, where the unusual electronic properties and the quasi-2D nature of the walls are leveraged to emulate the behavior of electronic components at ultra-small length scales. Here, we

A. J. Battisti, I. Shivaei, H. -J. Park, M. Decleir

The 2175{\AA} bump is a prominent absorption feature at ultraviolet (UV) wavelengths in dust extinction and attenuation curves. Understanding the relative strength of this feature is important for accurate dust corrections at both low- and high-redshift. This feature is postulated to arise from polycyclic aromatic hydrocarbon (PAH) dust grains; however, the

Chi Zhang, Janis Sprenger, Zhongjun Ni, Christian Berger

Predicting pedestrian crossing behavior is important for intelligent traffic systems to avoid pedestrian-vehicle collisions. Most existing pedestrian crossing behavior models are trained and evaluated on datasets collected from a single country, overlooking differences between countries. To address this gap, we compared pedestrian road-crossing behavior at u

Y. Chapovskyi, O. Kozachok, A. Petravchuk

Let $\mathbb{K}$ be an algebraically closed field of characteristic zero and $\mathbb{K}[x,y]$ the polynomial ring. The group $\text{SL}_{2}\left(\mathbb{K}[x,y]\right)$ of all matrices with determinant equal to $1$ over $\mathbb{K}[x,y]$ can not be generated by elementary matrices. The known counterexample was pointed out by P.M. Cohn. Conversely, A.A.Susli

Luis Morales-Navarro, Deborah A. Fields, Yasmin B. Kafai, Deepali Barapatre

Purpose: The purpose of this paper is to examine how a clinical interview protocol with failure artifact scenarios can capture changes in high school students' explanations of troubleshooting processes in physical computing activities. We focus on physical computing since finding and fixing hardware and software bugs is a highly contextual practice that invo

Faizuddin Ahmed, Ahmad Al-Badawi, İzzet Sakallı, Abdelmalek Bouzenadad

This paper aims to explore the quasinormal modes (QNMs) and effective potential profiles of massless and rotating BTZ black holes within the frameworks of $f(\mathcal{R})$ and Ricci-Inverse ($\mathcal{RI}$) modified gravity theories, which, while producing similar space-time structures, exhibit variations due to distinct cosmological constants, $\Lambda_m$.

Cheng-An Hsieh, Jing Zhang, Ava Yan

In the game development process, creating character animations is a vital step that involves several stages. Typically for 2D games, illustrators begin by designing the main character image, which serves as the foundation for all subsequent animations. To create a smooth motion sequence, these subsequent animations involve drawing the character in different

Alpar Türkoğlu, Berk Karabacakoğlu, Ali Emre Pusane

This paper suggests achieving diversity gains while utilizing low-denisty parity check (LDPC) codes in molecular communications. Intersymbol interference (ISI) causes a significant disadvantage in error performance for molecular communications. Even though decoding LDPC codes with soft decoding yields a considerable enhancement in the bit error rate (BER) cu

Mitsuaki Hirasawa, Masazumi Honda, Akira Matsumoto, Jun Nishimura

The spontaneous breaking of CP symmetry in 4D SU($N$) pure Yang-Mills theory at $\theta=\pi$ has recently attracted much attention in the context of the higher-form symmetry and the 't Hooft anomaly matching condition. Here we use Monte Carlo simulations to study the $N=2$ case, which is interesting since it is the case opposite to the large-$N$ limit, where

Jon Gutiérrez-Zaballa, Koldo Basterretxea, Javier Echanobe

Machine learning-based embedded systems employed in safety-critical applications such as aerospace and autonomous driving need to be robust against perturbations produced by soft errors. Soft errors are an increasing concern in modern digital processors since smaller transistor geometries and lower voltages give electronic devices a higher sensitivity to bac

Guy Barel, Oren Tsur, Dan Vilenchik

Stance detection plays a pivotal role in enabling an extensive range of downstream applications, from discourse parsing to tracing the spread of fake news and the denial of scientific facts. While most stance classification models rely on textual representation of the utterance in question, prior work has demonstrated the importance of the conversational con

Yifei Li

Integer division instruction is generally expensive in most architectures. If the divisor is constant, the division can be transformed into combinations of several inexpensive integer instructions. This article discusses the classic round-up variant of the fast unsigned division by constants algorithm, and provides full proof of its correctness and feasibili

Seungone Kim, Juyoung Suk, Xiang Yue, Vijay Viswanathan

Given the increasing use of synthetic data in language model (LM) post-training, an LM's ability to generate high-quality data has become nearly as crucial as its ability to solve problems directly. While prior works have focused on developing effective data generation methods, they lack systematic comparison of different LMs as data generators in a unified

Kwang Hak Kim, Mamadou Diagne, Miroslav Krstić

In safety-critical control, managing safety constraints with high relative degrees and uncertain obstacle dynamics pose significant challenges in guaranteeing safety performance. Robust Control Barrier Functions (RCBFs) offer a potential solution, but the non-smoothness of the standard RCBF definition can pose a challenge when dealing with multiple derivativ

Francesco Innocenti, Paul Kinghorn, Will Yun-Farmbrough, Miguel De Llanza Varona

We introduce JPC, a JAX library for training neural networks with Predictive Coding. JPC provides a simple, fast and flexible interface to train a variety of PC networks (PCNs) including discriminative, generative and hybrid models. Unlike existing libraries, JPC leverages ordinary differential equation solvers to integrate the gradient flow inference dynami

Dana R. Louie, Elijah Mullens, Lili Alderson, Ana Glidden

Water has proven to be ubiquitously detected in near-infrared (NIR) transmission spectroscopy observations of hot Jupiter atmospheres, including WASP-17b. However, previous analyses of WASP-17b's atmosphere based upon Hubble Space Telescope (HST) and Spitzer data could not constrain the water abundance, finding that sub-solar, super-solar and bimodal posteri

Marshall D. Allen, Vahid Attari, Brent Vela, James Hanagan

The spatial control of material placement afforded by metal additive manufacturing (AM) has enabled significant progress in the development and implementation of compositionally graded alloys (CGAs) for spatial property variation in monolithic structures. However, cracking and brittle phase formation have hindered CGA development, with limited research exten

Aaron Wang, Abhijith Gandrakota, Jennifer Ngadiuba, Vivekanand Sahu

Machine learning (ML) algorithms, particularly attention-based transformer models, have become indispensable for analyzing the vast data generated by particle physics experiments like ATLAS and CMS at the CERN LHC. Particle Transformer (ParT), a state-of-the-art model, leverages particle-level attention to improve jet-tagging tasks, which are critical for id

Harish S. Bhat, Hardeep Bassi, Christine M. Isborn

Consider the problem of determining the optimal applied electric field to drive a molecule from an initial state to a desired target state. For even moderately sized molecules, solving this problem directly using the exact equations of motion -- the time-dependent Schr\"odinger equation (TDSE) -- is numerically intractable. We present a solution of this prob

Pedram Khorsandi, Rushil Gupta, Mehrnaz Mofakhami, Simon Lacoste-Julien

Performative prediction is a framework accounting for the shift in the data distribution induced by the prediction of a model deployed in the real world. Ensuring rapid convergence to a stable solution where the data distribution remains the same after the model deployment is crucial, especially in evolving environments. This paper extends the Repeated Risk

Geoff Penington, Pratik Rath

Recently Dong, Rath and Kudler-Flam proposed a modified cosmic brane prescription for computing the R\'{e}nyi entropy $S_\alpha$ of a holographic system in the presence of multiple extremal surfaces. This prescription was found by assuming a diagonal approximation, where the R\'{e}nyi entropy is computed after first measuring the areas of all extremal surfac

Murray Moinester

We review experimental tests of three-flavor (u,d,s) chiral perturbation theory (ChPT). These include measurements of pion and kaon polarizabilities, the chiral anomaly amplitudes for processes such as $\gamma \rightarrow \pi\pi\pi$, $\gamma \rightarrow \pi\pi\eta$, and $\gamma \rightarrow KK\pi$; as well as the lifetimes of the neutral pion and eta. These o

Beatrice Foroni, Luca Merlo, Lea Petrella

In this paper we develop a novel hidden Markov graphical model to investigate time-varying interconnectedness between different financial markets. To identify conditional correlation structures under varying market conditions and accommodate stylized facts embedded in financial time series, we rely upon the generalized hyperbolic family of distributions with

Taeyeon Kim, Piljin Yi

The Noether procedure carries an inherent ambiguity due to the necessary local extension, no longer a symmetry, of the global symmetry. The gauging should fix the ambiguity once and for all, however, and, for translations, the general covariance demands us to use the Lie derivative. We argue that, with this alone and without any further tweaking, the Noether

Meltem Apaydin Ustun, Liang Xu, Bo Zeng, Xiaoning Qian

Automated hyperparameter search in machine learning, especially for deep learning models, is typically formulated as a bilevel optimization problem, with hyperparameter values determined by the upper level and the model learning achieved by the lower-level problem. Most of the existing bilevel optimization solutions either assume the uniqueness of the optima

Davide Bucciarelli, Nicholas Moratelli, Marcella Cornia, Lorenzo Baraldi

The task of image captioning demands an algorithm to generate natural language descriptions of visual inputs. Recent advancements have seen a convergence between image captioning research and the development of Large Language Models (LLMs) and Multimodal LLMs -- like GPT-4V and Gemini -- which extend the capabilities of text-only LLMs to multiple modalities.

Advait Mehla, Mansi M. Kasliwal, Viraj Karambelkar, Patrick Tisserand

Hydrogen-deficient Carbon (HdC) stars are a class of supergiants with anomalous chemical compositions, suggesting that they are remnants of CO-He white dwarf (WD) mergers. This class comprises two spectroscopically similar subclasses - dusty R Coronae Borealis (RCB) and dustless Hydrogen-deficient Carbon (dLHdC) stars. Both subclasses have a stark overabunda

Anxo Biasi, Patrick Gérard

This work makes analytic progress in the deterministic study of turbulence in Hamiltonian systems by identifying two types of energy cascade solutions and the corresponding large- and small-scale structures they generate. The first cascade represents condensate formation via a highly coherent process recently uncovered, while the second cascade, which has no

Devin J. Williams, Ivana Damjanov, Marcin Sawicki, Harrison Souchereau

Galaxies are predicted to assemble their stellar haloes through the accretion of stellar material from interactions with their cosmic environment. Observations that trace stellar halo buildup probe the processes that drive galaxy size and stellar mass growth. We investigate stellar halo assembly over $0.2 \leq z \leq 1.1$ in a mass-complete ($M_{\star} \geq

Robert-Jeron Reifert, Yasemin Karacora, Christina Chaccour, Aydin Sezgin

In this paper, we develop the first comprehensive tutorial on designing future 6G networks that synergistically integrate notions of resilience and criticality from the ground up. While resilience refers to the ability to absorb, adapt to, and recover from adversarial or challenging conditions, criticality indicates the degree of importance or urgency assign

Francisco R. Candón, Damiano F. G. Fiorillo, Giuseppe Lucente, Edoardo Vitagliano

Axions and other putative feebly interacting particles (FIPs) with a mass of tens to several hundreds of keVs can be produced in stellar cores with a Lorentz boost factor $E_a/m_a\lesssim 10$. Thus, starburst galaxies such as M82 are efficient factories of slow axions. Their decay $a\rightarrow\gamma\gamma$ would produce a large flux of X-ray photons, peakin

Terrence Pierre Jacques, Samuel Cupp, Leonardo R. Werneck, Samuel D. Tootle

Many astrophysical systems of interest to numerical relativity-such as rapidly rotating stars, black hole accretion disks, and core-collapse supernovae-exhibit near-symmetries. These systems generally consist of a strongly gravitating central object surrounded by an accretion disk, debris, and ejecta. Simulations can efficiently exploit the near-axisymmetry

Esha Bhatia, Sayan Chakrabarti, Sovan Chakraborty

The kinematics of the ultra-diffuse galaxy (UDG) NGC1052-DF44 is primarily influenced by the presence of dark matter (DM). In this paper, we conduct a contrasting kinematic study of DF44 within the alternative modified gravity framework. In comparison to NFW DM, we test three alternative gravity models viz Milgromian dynamics (MOND), characterized by a known

Zhang Meng-Han, Guo Xuan, Dao-Xin Yao

We present unconventional nodal crossings in a two-dimensional (2D) collinear altermagnet, which are enforced by crystal symmetries to lock spin polarization and valley degrees of freedom. The altermagnetism generate nonrelativistic spin-splitting in honeycomb antiferromagnets, guaranteeing novel band degeneracies between bands sharing identical spin configu

Falko Pientka, Inti Sodemann Villadiego

We investigate the propagation of electromagnetic waves through materials displaying a non-linear Hall effect. The coupled Maxwell-Boltzmann equations for traveling waves can be mapped onto ordinary differential equations that resemble those for the motion of a pendulum. In the weakly non-linear regime relevant for most experiments, we find that the polariza

Samuel J. Witte, Andrew Mummery

Light feebly-coupled bosonic particles can efficiently extract the rotational energy of rapidly spinning black holes on sub-astrophysical timescales via a phenomenon known as black hole superradiance. In the case of light axions, the feeble self-interactions of these particles can lead to a non-linear coupled evolution of many superradiant quasi-bound states

Tista Banerjee, Suchetan Das, K. Sengupta

We study the dynamics of entanglement asymmetry in periodically driven quantum systems. Using a periodically driven XY chain as a model for a driven integrable quantum system, we provide semi-analytic results for the behavior of the dynamics of the entanglement asymmetry, $\Delta S$, as a function of the drive frequency. Our analysis identifies special drive

Kohei Inayoshi, Shigeo S. Kimura, Hirofumi Noda

The James Webb Space Telescope (JWST) observations enable the exploration of active galactic nuclei (AGNs) with broad-line emission in the early universe. Despite their clear radiative and morphological signatures of AGNs in rest-frame optical bands, complementary evidence of AGN activity - such as X-ray emission and UV/optical variability - remains rarely d

Kaleb Anderson, Thomas C. Gehrman, Pearl Sandick, Kuver Sinha

The blue loop stage of intermediate mass stars has been called a "magnifying glass", where even seemingly small effects in prior stages of evolution, as well as assumptions about stellar composition, rotation, and convection, produce discernible changes. As such, blue loops, and especially the existence and properties of Cepheids, can serve as a laboratory w

David P. Bennett, Aparna Bhattacharya, Jean-Philippe Beaulieu, Naoki Koshimoto

We present high angular resolution imaging from the {\sl Hubble Space Telescope} combined with adaptive optics imaging results from the {\sl Keck}-II telescope to determine the mass of the OGLE-2012-BLG-0563L host star and planet to be $M_{\rm host} = 0.801\pm 0.033M_\odot$ and $M_{\rm planet} = 1.116 \pm 0.087 M_{\rm Jupiter}$, respectively, located at a di

Max Geier, Frederik Nathan

We propose a simple circuit architecture for a dissipatively error corrected Gottesman-Kitaev-Preskill (GKP) qubit. The device consists of a electromagnetic resonator with impedance $h/2e^2\approx 12.91\,{\rm k}\Omega$ connected to a Josephson junction with a voltage bias oscillating at twice the resonator frequency. For large drive amplitudes, the circuit i

Philipp Kempski, Dongzi Li, Drummond B. Fielding, Eliot Quataert

Intermittent magnetic structures are a plausible candidate for explaining cosmic-ray (CR) diffusion rates derived from observed CR energy spectra. Independently, studies of extreme scattering events (ESEs) of radio quasars and pulsar scintillation have hinted that very straight, large-aspect-ratio, magnetic current sheets may be responsible for the localized

Cesar A. Gallegos, Shengtao Jiang, Steven R. White, A. L. Chernyshev

The phase diagram of the $S\!=\!1/2$ easy-axis triangular-lattice $J_1\!-\!J_2$ model is investigated using the density-matrix renormalization group and analytical insights. We find a significant spin-liquid region extending from the Heisenberg limit and residing between the Y phase-known as the magnetic analogue of the "supersolid"-and collinear stripe phas

Pasquale Marra

I found an extended duality (triality) between Dirac fermions in periodic spacetime metrics, nonrelativistic fermions in gauge fields (e.g., Harper-Hofstadter model), and in periodic scalar fields on a lattice (e.g., Aubry-Andr\'e model). This indicates an unexpected equivalence between spacetime metrics, gauge fields, and scalar fields on the lattice, which

Samuel Awelewa, Maxim Dzero

We revisit certain aspects of a problem concerning the influence of carrier scattering induced by magnetic impurities in metals on their superconducting properties. Superconductivity is assumed to be driven by strong electron-phonon interaction. We use the self-consistent solution of the Nagaoka equations for the scattering matrix together with the Migdal-El

Uri Keshet, Kuan-Chou Hou

Galaxy-cluster virial (structure-formation accretion) shock observations are shown to imply $\gtrsim1\%$ magnetization of a layer extending $\gtrsim10^{16}$ Debye lengths downstream, challenging the modelling of high Alfv\'en-Mach collisionless shocks. Unlike similar shocks in supernova remnants or relativistic shocks in $\gamma$-ray burst afterglows, where

H. R. Stacey, M. Kaasinen, C. M. O'Riordan, J. P. McKean

The nuclear structure of dusty star-forming galaxies is largely unexplored but harbours critical information about their structural evolution. Here, we present long-baseline Atacama Large (sub-)Millimetre Array (ALMA) continuum observations of a gravitationally lensed dusty star-forming galaxy at $z=2.78$. We use a pixellated lens modelling analysis to recon

Asher Berlin, Surjeet Rajendran, Harikrishnan Ramani, Erwin H. Tanin

Millicharged particles are generic in theories of dark sectors. A cosmic or local abundance of them may be produced by the early universe, stellar environments, or the decay or annihilation of dark matter/dark energy. Furthermore, if such particles are light, these production channels result in a background of millicharged radiation. We show that light-shini

J. Vega-Ferrero, F. Buitrago, J. Fernández-Iglesias, S. Raji

Stellar disk truncations, also referred to as galaxy edges, are key indicators of galactic size, determined by the radial location of the gas density threshold for star formation. Accurately measuring galaxy sizes for millions of galaxies is essential for understanding the physical processes driving galaxy evolution over cosmic time. In this study, we aim to

Zhenhao Song, Tessa Cookmeyer, Leon Balents

We study the driven-dissipative Bose-Hubbard model with all-to-all hopping and subject to incoherent pumping and decay, as is naturally probed in several recent experiments on excitons in WS2/WSe2 moir\'e systems, as well as quantum simulators. By positing a particular form of coupling to the environment, we derive the Lindblad jump operators and show that,

Matilda Delgado, Damian van de Heisteeg, Sanjay Raman, Ethan Torres

We argue that the finiteness of quantum gravity amplitudes in fully compactified theories (at least in supersymmetric cases) leads to a bottom-up prediction for the existence of non-trivial dualities. In particular, finiteness requires the moduli space of massless fields to be compactifiable, meaning that its volume must be finite or at least grow no faster

Panos Betzios, Ioannis D. Gialamas, Olga Papadoulaki

We show how certain types of magnetic asymptotically Anti-de Sitter Euclidean wormholes can catalyze the onset of inflation. These wormholes can be embedded as saddle point solutions of General Relativity coupled to the Standard Model, the inflaton being identified with the Higgs particle. Our scenario is based on the assumption that the quantum effective po

Kyung-Su Kim, Veit Elser

We propose a universal kinetic mechanism for a half-metallic ferromagnet -- a metallic state with full spin polarization -- arising from strong on-site Coulomb repulsions between particles that exhibit constrained one-dimensional (1D) dynamics. We illustrate the mechanism in the context of a solvable model on a Lieb lattice in which doped electrons have 1D m

Johannes Mitscherling, Alexander Avdoshkin, Joel E. Moore

The importance of simple geometrical invariants, such as the Berry curvature and quantum metric, constructed from the Bloch states of a crystal has become well-established over four decades of research. More complex aspects of geometry emerge in properties linking multiple bands, such as optical responses. In the companion work [arXiv:2409.16358], we identif

Hao Geng

Local operators are the basic observables in quantum field theory which encode the physics observed by a local experimentalist. However, when gravity is dynamical, diffeomorphism symmetries are gauged which apparently obstructs a sensible definition of local operators, as different locations in spacetime are connected by these gauged symmetries. This conside

Phum Siriviboon, Chu-Liang Fu, Michael Landry, Ryotaro Okabe

Characterizing quantum materials is essential for understanding their microscopic interactions and advancing quantum technology. X-ray photon correlation spectroscopy (XPCS) with coherent X-ray sources offers access to higher-order correlations, but its theoretical basis, the Siegert relation, is derived from dynamical light scattering with independent class

Hesamodin Mohammadian, Griffin Higgins, Samuel Ansong, Roozbeh Razavi-Far

Control Flow Graphs and Function Call Graphs have become pivotal in providing a detailed understanding of program execution and effectively characterizing the behavior of malware. These graph-based representations, when combined with Graph Neural Networks (GNN), have shown promise in developing high-performance malware detectors. However, challenges remain d

Amir Bar, Gaoyue Zhou, Danny Tran, Trevor Darrell

Navigation is a fundamental skill of agents with visual-motor capabilities. We introduce a Navigation World Model (NWM), a controllable video generation model that predicts future visual observations based on past observations and navigation actions. To capture complex environment dynamics, NWM employs a Conditional Diffusion Transformer (CDiT), trained on a

Bingjie Song, Xin Huang, Ruting Xie, Xue Wang

We present Style3D, a novel approach for generating stylized 3D objects from a content image and a style image. Unlike most previous methods that require case- or style-specific training, Style3D supports instant 3D object stylization. Our key insight is that 3D object stylization can be decomposed into two interconnected processes: multi-view dual-feature a

Qitao Zhao, Shubham Tulsiani

Inferring the 3D structure underlying a set of multi-view images typically requires solving two co-dependent tasks -- accurate 3D reconstruction requires precise camera poses, and predicting camera poses relies on (implicitly or explicitly) modeling the underlying 3D. The classical framework of analysis by synthesis casts this inference as a joint optimizati

Hirotsugu Fujii, Kohei Fujikura, Yoshio Kikukawa, Takuya Okuda

We study the lattice Schwinger model by combining the variational uniform matrix product state (VUMPS) algorithm with a gauge-invariant matrix product ansatz that locally enforces the Gauss law constraint. Both the continuum and lattice versions of the Schwinger model with $\theta=\pi$ are known to exhibit first-order phase transitions for the values of the

Ruili Feng, Han Zhang, Zhantao Yang, Jie Xiao

We present The Matrix, the first foundational realistic world simulator capable of generating continuous 720p high-fidelity real-scene video streams with real-time, responsive control in both first- and third-person perspectives, enabling immersive exploration of richly dynamic environments. Trained on limited supervised data from AAA games like Forza Horizo