December 2024 arXiv papers — page 163

Julien Flamant, Xavier Luciani, Sebastian Miron, Yassine Zniyed

Multidimensional quaternion arrays (often referred to as "quaternion tensors") and their decompositions have recently gained increasing attention in various fields such as color and polarimetric imaging or video processing. Despite this growing interest, the theoretical development of quaternion tensors remains limited. This paper introduces a novel multilin

Kaiyuan Chen, Kush Hari, Trinity Chung, Michael Wang

Cloud robotics enables robots to offload complex computational tasks to cloud servers for performance and ease of management. However, cloud compute can be costly, cloud services can suffer occasional downtime, and connectivity between the robot and cloud can be prone to variations in network Quality-of-Service (QoS). We present FogROS2-FT (Fault Tolerant) t

Daniel R. Lester, Michael G. Trefry, Guy Metcalfe

Many random flows, including 2D unsteady and stagnation-free 3D steady flows, exhibit non-trivial braiding of pathlines as they evolve in time or space. We show that these random flows belong to a pathline braiding \emph{universality class} that quantitatively links dispersion and chaotic stirring, meaning that the Lyapunov exponent can be estimated from the

Arkadii Slinko

The most studied class of Condorcet domains (acyclic sets of linear orders) is the class of peak-pit domains of maximal width. It has a number of combinatorial representations by such familiar combinatorial objects like rhombus tilings and arrangements of pseudolines. Arrow's single-peaked domains are peak-pit but do not have maximal width. We suggest how to

Bardia Baraeinejad, Maryam Forouzesh, Saba Babaei, Yasin Naghshbandi

In the last few decades, several wearable devices have been designed to monitor respiration rate in an effort to capture pulmonary signals with higher accuracy and reduce patients' discomfort during use. In this article, we present the design and implementation of a device for real-time monitoring of respiratory system movements. When breathing, the circumfe

T. Beck, A. Gade, B. A. Brown, Y. Utsuno

High-resolution in-beam $\gamma$-ray spectroscopy was used to study excited states of the neutron-deficient nucleus $^{32}$Ar populated in fast-beam induced four- and six-nucleon removal reactions from $^{36,38}$Ca. One new $\gamma$-ray transition and indications for an additional two were found, allowing for a glimpse at the level scheme beyond the known $2

Shuhao Ma, Yu Cao, Ian D. Robertson, Chaoyang Shi

Accurate understanding of muscle activation and muscle forces plays an essential role in neuro-rehabilitation and musculoskeletal disorder treatments. Computational musculoskeletal modeling has been widely used as a powerful non-invasive tool to estimate them through inverse dynamics using static optimization, but the inherent computational complexity result

Arijit Das, Minh-Binh Tran

This article introduces a novel numerical approach, based on Finite Volume Techniques, for studying fully nonlinear coagulation-fragmentation models, where both the coagulation and fragmentation components of the collision operator are nonlinear. The models come from $3-$wave kinetic equations, a pivotal framework in wave turbulence theory. Despite the impor

Laurin M. Gray, Katherine L. Rhode, Catrina M. Hamilton-Drager, Tiffany Picard

Investigating the angular momentum evolution of pre-main sequence (PMS) stars provides important insight into the interactions between Sun-like stars and their protoplanetary disks, and the timescales that govern disk dissipation and planet formation. We present projected rotational velocities (v sin i values) of 254 T Tauri stars (TTSs) in the ~3 Myr-old op

Ananya Mohapatra, Eric G. Blackman

The origin of magnetic white dwarfs (MWDs) has been a long-standing puzzle. Proposed origin mechanisms have included: fossil fields frozen in from the progenitor convective core; a dynamo in the progenitor envelope; crystallization dynamos in sufficiently cool white dwarfs; and merger-accretion disk dynamos from white dwarf-white dwarf mergers or tidally shr

Brittany A. Erickson

In this work we explore the fidelity of numerical approximations to the analytic spectra of hyperbolic partial differential equation systems with variable coefficients. We are particularly interested in the ability of discrete methods to accurately discover sources of physical instabilities. By considering the perturbed equations that arise in linearized pro

Maria Cuellar

This article examines the overlooked risk of false negative errors arising from eliminations in forensic firearm comparisons. While recent reforms in forensic science have focused on reducing false positives, eliminations--often based on class characteristics or intuitive judgments--receive little empirical scrutiny despite their potential to exclude true so

Ritoban Kundu, Peter X. K. Song

Social network interference induces complex dependencies where a unit's outcome is influenced not only by its own exposure and mediator but also by those of connected neighbors. In such settings, a significant challenge lies in distinguishing direct exposure effects from interference-driven spillover effects, and further separating these from indirect effect

Jacob L. Fine, Alan M. Moses

The RNA World hypothesis predicts that self-replicating RNAs evolved before DNA genomes and coded proteins. Despite widespread support for the RNA World, self-replicating RNAs have yet to be identified in a natural context, leaving a key 'missing link' for this explanation of the origin of life. Inspired by recent work showing that condensates of charged pol

Celestine Lalengmawia, R. Zosiamliana, Bernard Lalroliana, Lalhum Hima

Pb-based perovskites are considered to be the most efficient materials for energy harvest. However, real-time application is limited because of their toxicity. As a result, lead-free perovskites that offer similar advantages are potential alternatives. Here, we have chosen LiSnX$_3$ (X = Cl, Br, and I) for further calculation and explore its possibilities fo

Sindhu Boddu, Arindam Mukherjee

This paper presents a robust approach for object detection in aerial imagery using the YOLOv5 model. We focus on identifying critical objects such as ambulances, car crashes, police vehicles, tow trucks, fire engines, overturned cars, and vehicles on fire. By leveraging a custom dataset, we outline the complete pipeline from data collection and annotation to

Jinwei Tang, Jiayin Qin, Kiran Thorat, Chen Zhu-Tian

With Large Language Models (LLMs) recently demonstrating impressive proficiency in code generation, it is promising to extend their abilities to Hardware Description Language (HDL). However, LLMs tend to generate single HDL code blocks rather than hierarchical structures for hardware designs, leading to hallucinations, particularly in complex designs like Do

Shiming Zheng, E. S. Khramtsov, I. V. Ignatiev

A microscopic model of a heterostructure with a quantum well (QW) is proposed to study the exciton behavior in an external electric field. The effect of an electric field ranging from 0 to 6 kV/cm applied to the GaAs/AlGaAs QW structure in the growth direction is studied for several QWs of various widths up to 100 nm. The three-dimensional Schr\"odinger equa

Tomasz Goliński, Praful Rahangdale, Alice Barbora Tumpach

In this paper we examine various approaches to the notion of Poisson manifold in the context of Banach manifolds. Existing definitions are presented and differences between them are explored and illustrated with examples.

Aníbal Silva, André Restivo, Moisés Santos, Carlos Soares

Generative modeling for tabular data has recently gained significant attention in the Deep Learning domain. Its objective is to estimate the underlying distribution of the data. However, estimating the underlying distribution of tabular data has its unique challenges. Specifically, this data modality is composed of mixed types of features, making it a non-tr

Ori Friesen, Cecily Kolko, Nick Layman, Kate Lorenzen

The generalized distance matrix of a graph is a matrix in which the $(i,j)$th entry is a function, $f$, of the distance between vertex $i$ and vertex $j$. Depending on the choice of $f$, this family of matrices includes both the adjacency matrix and the traditional distance matrix. We present a cospectral construction for the generalized distance matrix akin

Andy Rosenbaum, Pegah Kharazmi, Ershad Banijamali, Lu Zeng

We present CALICO, a method to fine-tune Large Language Models (LLMs) to localize conversational agent training data from one language to another. For slots (named entities), CALICO supports three operations: verbatim copy, literal translation, and localization, i.e. generating slot values more appropriate in the target language, such as city and airport nam

Mohamed BenSalah, Salih Tatar

In this paper, we study an inverse problem for identifying the initial value in a space-time fractional diffusion equation from the final time data. We show the identifiability of this inverse problem by proving the existence of its unique solution with respect to the final observed data. It is proved that the inverse problem is an ill-posed problem. Namely,

Himanshu Mittal, Suvramalya Basak, Anjali Gautam

Violence detection in surveillance videos is a critical task for ensuring public safety. As a result, there is increasing need for efficient and lightweight systems for automatic detection of violent behaviours. In this work, we propose an effective method which leverages human skeleton key-points to capture inherent properties of violence, such as rapid mov

Valdemar Farré, Juan C. Estrada-Jiménez, José D. Vega Sánchez, Juan A. Vasquez-Peralvo

In recent years, the fifth-generation (5G) mobile network has been developed worldwide to remarkably improve network performance and spectral efficiency. Very recently, reconfigurable intelligent surfaces (RISs) technology has emerged as an innovative solution for controlling the propagation medium of the forthcoming sixth-generation (6G) networks. Specifica

Enrico Herrmann, Murat Kologlu, Ian Moult

Despite tremendous progress in our understanding of scattering amplitudes in perturbative (super-) gravity, much less is known about other asymptotic observables, such as correlation functions of detector operators. In this paper, we initiate the study of detector operators and their correlation functions in perturbative quantum gravity. Inspired by recent p

Kamel Ourabah

Non-Maxwellian distributions are commonly observed across a wide range of systems and scales. While direct observations provide the strongest evidence for these distributions, they also manifest indirectly through their influence on processes and quantities that strongly depend on the energy distribution, such as reaction rates. In this paper, we investigate

Celestine Lalengmawia, Zosiamliana Renthlei, Shivraj Gurung, Lalhriat Zuala

Wide bandgap semiconductors (WBGs) are predicted to be the potential materials for energy generation and storing. In this work, we used density functional theory (DFT) that incorporates generalized gradient approximation (GGA) and meta-generalized gradient approximation (mGGA) methods to explore the various properties of the LiSnCl3 and LiSnBr3 perovskites.

Ganesh Subramaniam, Avik De, Tee-How Loo, Yong Kheng Goh

The symmetric teleparallel theory offers an alternative gravitational formulation which can elucidate events in the early and late universe without requiring the physical existence of dark matter or dark energy. In this formalism, $f(Q, C)$ gravity has been recently introduced by incorporating the boundary term $C$ with the non-metricity scalar $Q$. In this

Evangelos Afxonidis, Andreas Karch, Chitraang Murdia

{In 1+1 dimensional conformal field theory with a boundary the boundary contribution to the entanglement entropy is determined by a single number $g$ effectively counting the boundary degrees of freedom. In contrast, in 1+1 dimensional interface CFTs the corresponding quantity is a non-trivial {\it function} depending on the position of the interval relative

Rakshit Jain, Matthew Roddy, Vishakha Gupta, Benjamin Huang

Quantized anomalous Hall effects (QAHEs) occur in remarkable electronic states which possess not only quantized Hall signals but in some cases regions of dissipationless electron transport. The initial demonstrations of a QAHE in a magnetically-doped topological insulator (TI) required temperatures below 100 mK, and since then a major focus of the field has

John Carlton, Valerie Gibson, Tim Kovachy, Christopher McCabe

Terrestrial long-baseline atom interferometer experiments are emerging as powerful tools for probing new fundamental physics, including searches for dark matter and gravitational waves. In the frequency range relevant to these signals, gravity gradient noise (GGN) poses a significant challenge. While previous studies for vertical instruments have focused on

L. A. Lessa, G. J. Olmo

The field equations of static, spherically symmetric geometries generated by anisotropic fluids is investigated with the aim of better understanding the relation between the matter and the emergence of minimal area throats, like in wormhole and black bounce scenarios. Imposing some simplifying restrictions on the matter, which amounts to considering nonlinea

R. Tamang, Shivraj Gurung, D. P. Rai, Samy Brahimi

Recently, a new magnetic phase, termed altermagnetism, has caught the attention of the magnetism and spintronics community. This newly discovered magnetic phenomenon differs from traditional ferromagnetism and antiferromagnetic. It generally lacks net magnetization and is characterized by unusual non-relativistic spin-splitting and broken time-reversal symme

Tali Palma, Valeria Coenda, Gustavo Baume, Carlos Feinstein

Context. Understanding the formation and evolution of star clusters in the Milky Way requires precise identification of clusters that form binary or multiple systems. Such systems offer valuable insight into the dynamical processes and interactions that influence cluster evolution. Aims. This study aims to identify and classify star clusters in the Milky Way

Ajneet Dhillon, Sayantan Roy Chowdhury

Let $X$ be a smooth geometrically connected projective curve of genus at least 2 over a field of characteristic zero. We compute the essential dimension of the moduli stack of symplectic bundles over $X$. Unlike the case of vector bundles, we are able to precisely compute the essential dimension as the generic gerbe of the moduli stack has period 2 over it's

Sudip Kumar Saha, Maria N. Gastiasoro, Jonathan Ruhman, Avraham Klein

Superconductivity in doped SrTiO$_3$ has remained an enduring mystery for over 50 years. The material's status as a ``quantum" ferroelectric metal, characterized by a soft polar mode, suggests that quantum criticality could play a pivotal role in the emergence of its superconducting state. We show that the system is amenable to a strong coupling (Eliashberg)

Nicola Marchili, Gunther Witzel, Margo F. Aller

An in-depth analysis of variability has been carried out on the 2 GHz and 8 GHz light curves from the impressive database of the US Navy's extragalactic source monitoring program at the Green Bank Interferometer (GBI), complemented by UMRAO light curves for selected sources. The data have been inspected in a search for one-year periodic patterns. Variations

Michael Walther, Nils Schöneberg, Solène Chabanier, Eric Armengaud

We present the Lyssa suite of high-resolution cosmological simulations of the Lyman-$\alpha$ forest designed for cosmological analyses. These 18 simulations have been run using the Nyx code with $4096^3$ hydrodynamical cells in a 120 Mpc ($\sim$ 81Mpc/h) comoving box and individually provide sub-percent level convergence of the Lyman-$\alpha$ forest 1d flux

Zixuan Peng, Crystal L. Martin, Zirui Chen, Drummond B. Fielding

We study the physical origins of outflowing cold clouds in a sample of 14 low-redshift dwarf ($M_{\ast} \lesssim 10^{10}$ $M_{\odot}$) galaxies from the COS Legacy Archive Spectroscopic SurveY (CLASSY) using Keck/ESI data. Outflows are traced by broad (FWHM ~ 260 $\rm{km}$ $\rm{s^{-1}}$) and very-broad (VB; FWHM ~ 1200 $\rm{km}$ $\rm{s^{-1}}$) velocity compo

John Soltis, Michelle Ntampaka, Benedikt Diemer, John ZuHone

The mass accretion rate of galaxy clusters is a key factor in determining their structure, but a reliable observational tracer has yet to be established. We present a state-of-the-art machine learning model for constraining the mass accretion rate of galaxy clusters from only X-ray and thermal Sunyaev-Zeldovich observations. Using idealized mock observations

Keisi Kacanja, Alexander H. Nitz

Most observed neutron stars have masses around 1.4 $M_\odot$, consistent with current formation mechanisms. To date, no sub-solar mass neutron star has been observed. Observing a low-mass neutron star would be a significant milestone, providing crucial constraints on the nuclear equation of state, unveiling a new population of neutron stars, and advancing th

Michael Gnewuch, Klaus Ritter, Robin Rüßmann

We study integration and $L^2$-approximation in the worst-case setting for deterministic linear algorithms based on function evaluations. The underlying function space is a reproducing kernel Hilbert space with a Gaussian kernel of tensor product form. In the infinite-variate case, for both computational problems, we establish matching upper and lower bounds

Mario Collura, Jacopo De Nardis, Vincenzo Alba, Guglielmo Lami

We introduce an efficient method to quantify nonstabilizerness in fermionic Gaussian states, overcoming the long-standing challenge posed by their extensive entanglement. Using a perfect sampling scheme based on an underlying determinantal point process, we compute the Stabilizer Renyi Entropies (SREs) for systems with hundreds of qubits. Benchmarking on ran

Yunkun Wang, Yue Zhang, Zhen Qin, Chen Zhi

Large language models face intrinsic limitations in coding with APIs that are unseen in their training corpora. As libraries continuously evolve, it becomes impractical to exhaustively retrain LLMs with new API knowledge. This limitation hampers LLMs from solving programming problems which require newly introduced or privately maintained libraries. Inspired

Guillaume Bossard, Axel Kleinschmidt, Ergin Sezgin

We revisit six-dimensional (1,0) supergravity coupled to nT tensor multiplets and Yang-Mills fields for nT>1 for which no covariant action exists. We construct the action in the Henneaux-Teitelboim approach and in the presence of a gauge anomaly. We moreover obtain the supersymmetric Green-Schwarz counterterm for the gravitational anomaly for arbitrary matte

Harry Addison, Chris Frohmaier, Kate Maguire, Robert C. Nichol

Early-time spectroscopy of supernovae (SNe), acquired within days of explosion, yields crucial insights into their outermost ejecta layers, facilitating the study of their environments, progenitor systems, and explosion mechanisms. Recent efforts in early discovery and follow-up of SNe have shown the potential insights that can be gained from early-time spec

F. Rizzuti, F. Matteucci, P. Molaro, G. Cescutti

Recent observations by JWST have revealed supersolar $^{14}$N abundances in galaxies at very high redshift. On the other hand, these galaxies show subsolar metallicity. The observed N/O ratios are difficult to reproduce in the framework of chemical evolution models for the Milky Way. Our aim is to reproduce these high N/O ratios with chemical evolution model

Antonio Delgado, Seth Koren

We identify $m_{12}^2$ as a spurion of non-invertible Peccei-Quinn symmetry in the type II 2HDM with gauged quark flavor. Thus a UV theory which introduces quark color-flavor monopoles can naturally realize alignment without decoupling and can furthermore revive the Weinberg-Wilczek axion. As an example we consider the $SU(9)$ theory of color-flavor unificat

Alireza Rashedi, Mehri Ebrahimi, Yunhu Huang, Matt J. Rudd

We report the fabrication and optical characterization of an air-suspended photonic crystal nanobeam cavity in yttrium-iron-garnet (YIG) realized by focused-ion-beam milling. YIG's combination of low optical loss and ferrimagnetism makes it highly attractive for quantum technologies, yet prior work has largely been focused on millimeter-scale spheres and sim

C. Groeneveld, R. J. van Weeren, A. Botteon, R. Cassano

Some galaxy clusters contain non-thermal synchrotron emitting plasma permeating the intracluster medium (ICM). The spectral properties of this radio emission are not well characterized at decameter wavelengths ({\nu} < 30 MHz), primarily due to the severe corrupting effects of the ionosphere. Using a recently developed calibration strategy, we present LOFAR

Benjamín Grinstein, Xiaochuan Lu, Carlos Miró, Pablo Quílez

Accidental symmetries in effective field theories can be established by computing and comparing Hilbert series. This invites us to study them with the tools of invariant theory. Applying this technology, we spotlight three classes of accidental symmetries that hold to all orders for non-derivative interactions. They are broken by derivative interactions and

Rong-Jun Fu, Rudi Rahn, Ding Yu Shao, Wouter J. Waalewijn

Modern collider phenomenology requires unprecedented precision for the theoretical predictions, for which slicing techniques provide an essential tool at next-to-next-to-leading order (NNLO) in the strong coupling. The most popular slicing variable is based on the transverse momentum $q_T$ of a color-singlet final state, but its generalization to final state

Heng-Yu Chen, Nick Dorey, Sanefumi Moriyama, Rishi Mouland

We establish a precise correspondence between the giant graviton expansion of the superconformal index of field theories in $D\leq 4$, and the master volume formalism of Gauntlett, Martelli and Sparks (GMS) which determines the near horizon geometries of certain BPS black holes and black strings in supergravity. We focus on 4d $\mathcal{N}=1$ superconformal

B. Hovis-Afflerbach, Y. Götberg, A. Schootemeijer, J. Klencki

Stars stripped of their hydrogen-rich envelopes through binary interaction are thought to be responsible for both hydrogen-poor supernovae and the hard ionizing radiation observed in low-$Z$ galaxies. A population of these stars was recently observed for the first time, but their prevalence remains unknown. In preparation for such measurements, we estimate t

Lening Wang, Wenzhao Zheng, Dalong Du, Yunpeng Zhang

4D driving simulation is essential for developing realistic autonomous driving simulators. Despite advancements in existing methods for generating driving scenes, significant challenges remain in view transformation and spatial-temporal dynamic modeling. To address these limitations, we propose a Spatial-Temporal simulAtion for drivinG (Stag-1) model to reco

Susung Hong, Johanna Karras, Ricardo Martin-Brualla, Ira Kemelmacher-Shlizerman

Recent advancements in text-based diffusion models have accelerated progress in 3D reconstruction and text-based 3D editing. Although existing 3D editing methods excel at modifying color, texture, and style, they struggle with extensive geometric or appearance changes, thus limiting their applications. To this end, we propose Perturb-and-Revise, which makes

Chen Geng, Yunzhi Zhang, Shangzhe Wu, Jiajun Wu

We study the problem of generating temporal object intrinsics -- temporally evolving sequences of object geometry, reflectance, and texture, such as a blooming rose -- from pre-trained 2D foundation models. Unlike conventional 3D modeling and animation techniques that require extensive manual effort and expertise, we introduce a method that generates such as

Hee Jae Kim, Kathakoli Sengupta, Masaki Kuribayashi, Hernisa Kacorri

People who are blind perceive the world differently than those who are sighted, which can result in distinct motion characteristics. For instance, when crossing at an intersection, blind individuals may have different patterns of movement, such as veering more from a straight path or using touch-based exploration around curbs and obstacles. These behaviors m

Hyesu Lim, Jinho Choi, Jaegul Choo, Steffen Schneider

Adapting foundation models for specific purposes has become a standard approach to build machine learning systems for downstream applications. Yet, it is an open question which mechanisms take place during adaptation. Here we develop a new Sparse Autoencoder (SAE) for the CLIP vision transformer, named PatchSAE, to extract interpretable concepts at granular

Hidir Yesiltepe, Tuna Han Salih Meral, Connor Dunlop, Pinar Yanardag

In this work, we propose the first motion transfer approach in diffusion transformer through Mixture of Score Guidance (MSG), a theoretically-grounded framework for motion transfer in diffusion models. Our key theoretical contribution lies in reformulating conditional score to decompose motion score and content score in diffusion models. By formulating motio

Tuna Han Salih Meral, Hidir Yesiltepe, Connor Dunlop, Pinar Yanardag

Text-to-video models have demonstrated impressive capabilities in producing diverse and captivating video content, showcasing a notable advancement in generative AI. However, these models generally lack fine-grained control over motion patterns, limiting their practical applicability. We introduce MotionFlow, a novel framework designed for motion transfer in

Jiahua Dong, Tong Wu, Rui Qian, Jiaqi Wang

The 3D contrastive learning paradigm has demonstrated remarkable performance in downstream tasks through pretraining on point cloud data. Recent advances involve additional 2D image priors associated with 3D point clouds for further improvement. Nonetheless, these existing frameworks are constrained by the restricted range of available point cloud datasets,

Ian A. Leahy, Anthony D. Rice, Jocienne N. Nelson, Herve Ness

Low carrier densities in topological semimetals (TSMs) enable the exploration of novel magnetotransport in the quantum limit (QL). Recent findings consistent with 3D quasi-quantum Hall effect (QQHE) have positioned TSMs as promising platforms for exploring 3D quantum Hall transport, but the lack of tunability in the Fermi level has thus far limited the abili

Fay Borhani, Arnab Seth, Itamar Kimchi

We show that certain crystalline topological defects in the gapless Kitaev honeycomb spin liquid model generate a chirality and Majorana fermion orbital magnetization that depends in a universal manner on their emergent flux. Focusing on 5-7 dislocations as building blocks, consisting of pentagon and heptagon disclinations, we identify the Kitaev bond label

Zhe Chen, Weiyun Wang, Yue Cao, Yangzhou Liu

We introduce InternVL 2.5, an advanced multimodal large language model (MLLM) series that builds upon InternVL 2.0, maintaining its core model architecture while introducing significant enhancements in training and testing strategies as well as data quality. In this work, we delve into the relationship between model scaling and performance, systematically ex

Hanqing Zhu, Zhenyu Zhang, Wenyan Cong, Xi Liu

Large language models (LLMs) are notoriously memory-intensive during training, particularly with the popular AdamW optimizer. This memory burden necessitates using more or higher-end GPUs or reducing batch sizes, limiting training scalability and throughput. To address this, various memory-efficient optimizers have been proposed to reduce optimizer memory us

Krzysztof Maziarz, Guoqing Liu, Hubert Misztela, Austin Tripp

Chemical synthesis remains a critical bottleneck in the discovery and manufacture of functional small molecules. AI-based synthesis planning models could be a potential remedy to find effective syntheses, and have made progress in recent years. However, they still struggle with less frequent, yet critical reactions for synthetic strategy, as well as hallucin

Zied Ammari, Andrew Rout, Vedran Sohinger

In this paper, we are concerned with the study of statistical equilibria for focusing nonlinear Schr\"odinger and Hartree equations on the d-dimensional torus when d=1,2,3. Due to the focusing nature of the nonlinearity in these PDEs, Gibbs measures have to be appropriately localized. First, we show that these local Gibbs measures are stationary solutions fo

Junzhe Zhu, Yuanchen Ju, Junyi Zhang, Muhan Wang

Dense 3D correspondence can enhance robotic manipulation by enabling the generalization of spatial, functional, and dynamic information from one object to an unseen counterpart. Compared to shape correspondence, semantic correspondence is more effective in generalizing across different object categories. To this end, we present DenseMatcher, a method capable

Michael Hanna, Aaron Mueller

Autoregressive transformer language models (LMs) possess strong syntactic abilities, often successfully handling phenomena from agreement to NPI licensing. However, the features they use to incrementally process language inputs are not well understood. In this paper, we fill this gap by studying the mechanisms underlying garden path sentence processing in LM

Rafael Aoude, Donal O'Connell, Matteo Sergola

We obtain the Hawking spectrum by exponentiating a series of Feynman diagrams describing a scalar field scattering through a collapse background. Our approach is rooted in semiclassical methods of scattering amplitudes which have recently been developed for application to gravitational-wave physics. The diagrams we encounter do not compute a standard amplitu

Hongyi Xiao, Harol Torres, Achim Sack, Thorsten Pöschel

Understanding swimming in soft yielding media is challenging due to their complex deformation response to the swimmer's motion. We experimentally show that a scallop-inspired swimmer with reciprocally flapping wings generates locomotion in granular matter. This disagrees with the scallop theorem prohibiting reciprocal swimming in a liquid when its inertia is

Kevin Murphy

This manuscript gives a big-picture, up-to-date overview of the field of (deep) reinforcement learning and sequential decision making, covering value-based methods, policy-based methods, model-based methods, multi-agent RL, LLMs and RL, and various other topics (e.g., offline RL, hierarchical RL, intrinsic reward). It also includes some code snippets for tra

XENON Collaboration, E. Aprile, J. Aalbers, K. Abe

Radiogenic neutrons emitted by detector materials are one of the most challenging backgrounds for the direct search of dark matter in the form of weakly interacting massive particles (WIMPs). To mitigate this background, the XENONnT experiment is equipped with a novel gadolinium-doped water Cherenkov detector, which encloses the xenon dual-phase time project

Ziyi Wu, Aliaksandr Siarohin, Willi Menapace, Ivan Skorokhodov

Real-world videos consist of sequences of events. Generating such sequences with precise temporal control is infeasible with existing video generators that rely on a single paragraph of text as input. When tasked with generating multiple events described using a single prompt, such methods often ignore some of the events or fail to arrange them in the correc

Hoang Ky Nguyen

In A&A 412, 35 (2003) Blanchard, Douspis, Rowan-Robinson, and Sarkar (BDRS) slightly modified the primordial fluctuation spectrum and produced an excellent fit to WMAP's CMB power spectrum for an Einstein-de Sitter (EdS) universe, bypassing dark energy. Curiously, they obtained a Hubble value of $H_0\approx46$, in sharp conflict with the canonical range $H_0

Victor Gonzalez, Harold Polo, Pedro Rodriguez

A semidomain is a subsemiring of an integral domain. Within this class, a unique factorization semidomain (UFS) is characterized by the property that every nonzero, nonunit element can be factored into a product of finitely many prime elements. In this paper, we investigate the localization of semidomains, focusing specifically on UFSs. We demonstrate that t

Nicholas J. Boyer, Christopher Shepard, Ruiyi Zhou, Jianhang Xu

We present an application of our new theoretical formulation of quantum dynamics, moment propagation theory (MPT) (Boyer et al., J. Chem. Phys. 160, 064113 (2024)), for employing machine-learning techniques to simulate the quantum dynamics of electrons. In particular, we use real-time time-dependent density functional theory (RT-TDDFT) simulation in the gaug

Haya Samaana, Diego Elias Costa, Emad Shihab, Ahmad Abdellatif

Background. In modern software development, the use of external libraries and packages is increasingly prevalent, streamlining the software development process and enabling developers to deploy feature-rich systems with little coding. While this reliance on reusing code offers substantial benefits, it also introduces serious risks for deployed software in th

Matthäus Schulik, James Owen

Hydrodynamic outflows, such as those observed escaping close-in gas giant planets, are not isothermal in structure. Their highly ionized nature allows them to cool adiabatically at distances beyond several planetary radii. The contrast between the hottest gas temperatures at around 10,000K and the coldest at around 1,000K triggers an excess population of the

Shuhei Yonehara

The notion of a Jacobi manifold is a natural generalization of that of a Poisson manifold. A Jacobi manifold has a natural foliation in which each leaf has either a contact structure or a locally conformal symplectic structure. In this paper, we study a characteristic class called the Godbillon-Vey class for Jacobi manifolds with regular foliation and expres

Xiangyu Han, Zhen Jia, Boyi Li, Yan Wang

Photorealistic simulators are essential for the training and evaluation of vision-centric autonomous vehicles (AVs). At their core is Novel View Synthesis (NVS), a crucial capability that generates diverse unseen viewpoints to accommodate the broad and continuous pose distribution of AVs. Recent advances in radiance fields, such as 3D Gaussian Splatting, ach

Ruiqi Zhang, Brandon Motes, Shaun Tan, Yongli Lu

We demonstrate a machine learning (ML) approach that accurately predicts the current-voltage behavior of 3D/2D-structured (FAMA)Pb(IBr)3/OABr hybrid organic-inorganic halide perovskite (HOIP) solar cells under AM1.5 illumination. Our neural network algorithm is trained on measured responses from several hundred HOIP solar cells, using three simple optical me

Qian Long, Zhi Li, Ran Gong, Ying Nian Wu

Collaboration is a cornerstone of society. In the real world, human teammates make use of multi-sensory data to tackle challenging tasks in ever-changing environments. It is essential for embodied agents collaborating in visually-rich environments replete with dynamic interactions to understand multi-modal observations and task specifications. To evaluate th

Brandon B. Le

This paper investigates the complex dynamics and fractal attractors that arise in a 60-dimensional ring lattice system of electrically coupled nonchaotic Rulkov neurons. While networks of chaotic Rulkov neurons have been widely studied, systems of nonchaotic Rulkov neurons have not been extensively explored due to the piecewise complexity of the nonchaotic R

Qiaolin Qin, Roozbeh Aghili, Heng Li, Ettore Merlo

Log parsing has been a long-studied area in software engineering due to its importance in identifying dynamic variables and constructing log templates. Prior work has proposed many statistic-based log parsers (e.g., Drain), which are highly efficient; they, unfortunately, met the bottleneck of parsing performance in comparison to semantic-based log parsers,

Manuel Suárez-Rodríguez, Fernando De Juan, Ivo Souza, Marco Gobbi

Ohm's law has been a cornerstone of electronics since its experimental discovery. This law establishes that in a conductive system, the voltage is directly proportional to the current. Even when time-reversal symmetry is disrupted, leading to the emergence of magnetoresistance and Hall effects, the linear relationship between voltage and current remains inta

Fnu Neha, Deepshikha Bhati, Deepak Kumar Shukla, Md Amiruzzaman

Object detection is a fundamental task in computer vision and image understanding, with the goal of identifying and localizing objects of interest within an image while assigning them corresponding class labels. Traditional methods, which relied on handcrafted features and shallow models, struggled with complex visual data and showed limited performance. The

Javier Muñoz, Álvaro Huertas-García, Carlos Martí-González, Enrique De Miguel Ambite

The opaque nature of transformer-based models, particularly in applications susceptible to unethical practices such as dark-patterns in user interfaces, requires models that integrate uncertainty quantification to enhance trust in predictions. This study focuses on dark-pattern detection, deceptive design choices that manipulate user decisions, undermining a

Aravind Asok

We discuss elements of a social history of the theory of projective modules over commutative rings. We attempt to study the question: how did the theory of projective modules become one of "mainstream" focus in mathematics? To do this, we begin in what one might call the pre-history of projective modules, describing the mathematical culture into which the no

Daniel Harman, Ashton Palacios, Philip Lundrigan, Willie K. Harrison

Side channels have become an essential component of many modern information-theoretic schemes. The emerging field of cross technology communications (CTC) provides practical methods for creating intentional side channels between existing communications technologies. This paper describes a theoretical foundation for one such, recently proposed, CTC scheme: Gh

Saransh Kumar Gupta, Lipika Dey, Partha Pratim Das, Geeta Trilok-Kumar

This paper presents a novel approach to compute food composition data for Indian recipes using a knowledge graph for Indian food (FKG[.]in) and LLMs. The primary focus is to provide a broad overview of an automated food composition analysis workflow and describe its core functionalities: nutrition data aggregation, food composition analysis, and LLM-augmente

Vicenç Méndez, Rosa Flaquer-Galmés, Arnab Pal

We study the occupation time statistics for non-Markovian random walkers based on the formalism of the generalized master equation for the Continuous-Time Random Walk. We also explore the case when the random walker additionally undergoes a stochastic resetting dynamics. We derive and solve the backward Feynman-Kac equation to find the characteristic functio

Luis F. Alday, Gaston Giribet, Tobias Hansen

We consider tree-level scattering amplitudes for four string tachyons on $AdS_3 \times {\cal N}$ with pure NSNS fluxes. We show that in a small curvature expansion, properly defined, the amplitudes take the form of a genus zero integral given by the Virasoro-Shapiro integrand with the extra insertion of single valued multiple polylogarithms. This is the same

Boyu Zhou, Saikat Guha, Christos N. Gagatsos

We address the estimation problem of the separation of two arbitrarily close incoherent point sources from the quantum Bayesian point of view, i.e., when a prior probability distribution function (PDF) on the separation is available. For the non-dispalced and displaced half-Gaussian prior PDF, we compare the performance of SPADE and direct imaging (DI) with

Luca Masserano, Abdul Fatir Ansari, Boran Han, Xiyuan Zhang

How to best develop foundational models for time series forecasting remains an important open question. Tokenization is a crucial consideration in this effort: what is an effective discrete vocabulary for a real-valued sequential input? To address this question, we develop WaveToken, a wavelet-based tokenizer that allows models to learn complex representatio

Xiaohui Chen, Satya Narayan Shukla, Mahmoud Azab, Aashu Singh

How well can Multimodal Large Language Models (MLLMs) understand composite images? Composite images (CIs) are synthetic visuals created by merging multiple visual elements, such as charts, posters, or screenshots, rather than being captured directly by a camera. While CIs are prevalent in real-world applications, recent MLLM developments have primarily focus

Wei Leong Tee, Xiaohui Fan, Feige Wang, Jinyi Yang

Variability is a fundamental signature for active galactic nuclei (AGN) activity, and serve as an unbiased indicator for rapid instability happened near the center supermassive black hole (BH). Previous studies showed that AGN variability does not have strong redshift evolution, and scales with their bolometric luminosity and BH mass, making it a powerful pr

Salih Tatar, Mohamed BenSalah

In this paper, we study simultaneous determination of the strain hardening exponent, the shear modulus and the yield stress in an inverse problem. First, we analyze the direct and the inverse problems. Then we formulate the inverse problem in the Bayesian framework. After solving the direct problem by an iterative approach, we propose a numerical method base