October 2023 arXiv papers — page 116

Sebastian Olano, Debaditya Raychaudhury, Lei Song

We study the singularities of secant varieties of smooth projective varieties using methods from birational geometry when the embedding line bundle is sufficiently positive. More precisely, we study the Du Bois complex of secant varieties and its relationship with the sheaves of differential forms. Through this analysis, we give a necessary and sufficient co

Natalia A. Viana Bedoya, Daciberg Lima Gonçalves

In this paper we characterize primitive branched coverings with minimal defect over the projective plane with respect to the properties decomposable and indecomposable. This minimality is achieved when the covering surface is also the projective plane, which corresponds to the last case to be solved. As a consequence, we have extended the family of realisati

G. L. Verschuur, J. T. Schmelz

Gaussian decomposition of HI4PI profiles was done for two regions along high velocity Complex M, the first with corresponding H-alpha emission and the second without. In the former, we detected the Critical Ionization Velocity (CIV) signature, a line width of 25 km/s, of H-alpha. In low-velocity gas, the CIV effect ionizes the atoms and produces the signatur

Pranay Manocha, Donald Williamson, Adam Finkelstein

Perceptual evaluation constitutes a crucial aspect of various audio-processing tasks. Full reference (FR) or similarity-based metrics rely on high-quality reference recordings, to which lower-quality or corrupted versions of the recording may be compared for evaluation. In contrast, no-reference (NR) metrics evaluate a recording without relying on a referenc

Manuel Albrizzio

We consider the action on $\mathbb{F}_2^n$ by cyclic permutations ($\mathbb{Z}/n\mathbb{Z}$). Two elements $x, y\in \mathbb{F}_2^n$ are in the same orbit if they are cyclic shifts of each other. Cryptographic properties of rotation symmetric Boolean functions can be efficiently computed using the square matrix $_n\mathcal{A}$, the construction of which uses

Azar I. Ahmadov, Azza A. Alshehri, Abdel Nasser Tawfik

The mass spectrum of different meson particles is generated using an effective Lagrangian of the extended linear-sigma model (eLSM) for scalar and pseudoscalar meson fields and quark flavors, up, down, strange, and charm. Analytical formulas for the masses of scalar, pseudoscalar, vector, and axialvector meson states are derived assuming global chiral symmet

Guanru Feng, Dawei Lu, Jun Li, Tao Xin

People are witnessing quantum computing revolutions nowadays. Progress in the number of qubits, coherence times and gate fidelities are happening. Although quantum error correction era has not arrived, the research and development of quantum computing have inspired insights and breakthroughs in quantum technologies, both in theories and in experiments. In th

Yuting Wu, Ziyu Wang, Wei D. Lu

Decoder-only Transformer models such as GPT have demonstrated exceptional performance in text generation, by autoregressively predicting the next token. However, the efficacy of running GPT on current hardware systems is bounded by low compute-to-memory-ratio and high memory access. Process-in-memory (PIM) architectures can minimize off-chip data movement an

Daniel Suen, Yen-Chi Chen

Multivariate bounded discrete data arises in many fields. In the setting of dementia studies, such data is collected when individuals complete neuropsychological tests. We outline a modeling and inference procedure that can model the joint distribution conditional on baseline covariates, leveraging previous work on mixtures of experts and latent class models

Maxwell Joseph Jacobson, Yexiang Xue

Design generation requires tight integration of neural and symbolic reasoning, as good design must meet explicit user needs and honor implicit rules for aesthetics, utility, and convenience. Current automated design tools driven by neural networks produce appealing designs but cannot satisfy user specifications and utility requirements. Symbolic reasoning to

Ahmed Khalil, Robert Piechocki, Raul Santos-Rodriguez

In this paper we introduce learnable lattice vector quantization and demonstrate its effectiveness for learning discrete representations. Our method, termed LL-VQ-VAE, replaces the vector quantization layer in VQ-VAE with lattice-based discretization. The learnable lattice imposes a structure over all discrete embeddings, acting as a deterrent against codebo

Álvaro Pé de la Riva, Carmen Rodrigo, Francisco J. Gaspar, James H. Adler

In this work, a local Fourier analysis is presented to study the convergence of multigrid methods based on additive Schwarz smoothers. This analysis is presented as a general framework which allows us to study these smoothers for any type of discretization and problem. The presented framework is crucial in practice since it allows one to know a priori the an

K. Werner

Ultrarelativistic heavy-ion collisions will first realize many nucleon-nucleon scatterings, happening instantaneously and therefore necessarily in parallel, due to the short collision time. An appropriate quantum mechanical tool to treat that problem is S-matrix theory, and it has been known for a long time how to derive a simple geometric probabilistic pict

George Brooks, William Linz

For a $k$-uniform hypergraph $\mathcal{H}$, the \emph{codegree squared sum} $\text{co}_2(\mathcal{H})$ is the square of the $\ell_2$-norm of the codegree vector of $\mathcal{H}$, and for a family $\mathscr{F}$ of $k$-uniform hypergraphs, the codegree squared extremal number $\text{exco}_2(n, \mathscr{F})$ is the maximum codegree squared sum of a hypergraph o

N. Emelianova, N. Khusnutdinov

We consider the two planes at zero temperature with isotropic conductivity that are in relative lateral motion with velocity $v$ and inter-plane distance $a$. Two models of conductivity are taken into account -- the constant and frequency-dependent Drude models. The normal (perpendicular to planes) Casimir force is analysed in detail for two systems -- i) tw

Małgorzata Bednarska-Bzdȩga

Consider the following Ramsey game played on the edge set of $K_{\mathbb N}$. In every round, Builder selects an edge and Painter colours it red or blue. Builder's goal is to force Painter to create a red copy of a path $P_k$ on $k$ vertices or a blue copy of $P_n$ as soon as possible. The online (size) Ramsey number $\tilde{r}(P_k,P_n)$ is the number of rou

Thomas Donlon, Heidi Jo Newberg, Robyn Sanderson, Emily Bregou

The Milky Way's (MW) inner stellar halo contains an [Fe/H]-rich component with highly eccentric orbits, often referred to as the "last major merger." Hypotheses for the origin of this component include Gaia-Sausage/Enceladus (GSE), where the progenitor collided with the MW proto-disk 8-11 Gyr ago, and the Virgo Radial Merger (VRM), where the progenitor colli

Claudio Gómez-Gonzáles, Alexander J. Sutherland, Jesse Wolfson

Resolvent degree is an invariant measuring the complexity of algebraic and geometric phenomena, including the complexity of finite groups. To date, the resolvent degree of a finite simple group $G$ has only been investigated when $G$ is a cylic group; an alternating group; a simple factor of a Weyl group of type $E_6$, $E_7$, or $E_8$; or $\operatorname{PSL}

William K. Black, August E. Evrard

Using the photometric population prediction method {\bf Red Dragon}, we characterize the Red Sequence (RS) and Blue Cloud (BC) of DES galaxies in the COSMOS field. Red Dragon (RD) uses a redshift-evolving, error-corrected Gaussian mixture model to detail the distribution of photometric colors, smoothly parameterizing the two populations with relative weights

Sahil Girhepuje

This research delves into the reduction of machine learning model bias through Ensemble Learning. Our rigorous methodology comprehensively assesses bias across various categorical variables, ultimately revealing a pronounced gender attribute bias. The empirical evidence unveils a substantial gender-based wage prediction disparity: wages predicted for males,

Alex Feiner

Let $K$ be a number field, let $v$ be a finite place of $K$, let $f\in K[z]$ be a degree $d\geqslant2$ polynomial with $v|d$, and let $a\in K$. We show that if $f$ is postcritically bounded and has potential good reduction with respect to $v$, then the arboreal representation associated to the pair $(f,a)$ is either finite or infinitely wildly ramified above

Ricky Ini Liu, Michael Tang

The algebra of quasisymmetric functions QSym and the shuffle algebra of compositions Sh are isomorphic as graded Hopf algebras (in characteristic zero), and isomorphisms between them can be specified via shuffle bases of QSym. We use the notion of infinitesimal characters to characterize shuffle bases, and we establish a universal property for Sh in the cate

Syed Eqbal Alam, Dhirendra Shukla, Shrisha Rao

We develop an iterative differentially private algorithm for client selection in federated settings. We consider a federated network wherein clients coordinate with a central server to complete a task; however, the clients decide whether to participate or not at a time step based on their preferences -- local computation and probabilistic intent. The algorit

Thomas Weighill

We prove that for a metric space $X$ and a finite group $G$ acting on $X$ by isometries, if $X$ coarsely embeds into a Hilbert space, then so does the quotient $X/G$. A crucial step towards our main result is to show that for any integer $k > 0$ the space of unordered $k$-tuples of points in Hilbert space, with the $1$-Wasserstein distance, itself coarsely e

Yuanwei Bin, George Huang, Robert Kunz, Xiang I A Yang

The constants and functions in Reynolds-averaged Navier Stokes (RANS) turbulence models are coupled. Consequently, modifications of a RANS model often negatively impact its basic calibrations, which is why machine-learned augmentations are often detrimental outside the training dataset. A solution to this is to identify the degrees of freedom that do not aff

Yuanwei Bin, George I. Park, Yu Lv, Xiang I. A. Yang

We examine and benchmark the emerging idea of applying the large-eddy simulation (LES) formalism to unconventionally coarse grids where RANS would be considered more appropriate at first glance. We distinguish this idea from very-large-eddy-simulation (VLES) and detached-eddy-simulation (DES), which require switching between RANS and LES formalism. LES on RA

Peng E S Chen, Yuanwei Bin, Xiang I A Yang, Yipeng Shi

Assessing the compliance of a white-box turbulence model with known turbulent knowledge is straightforward. It enables users to screen conventional turbulence models and identify apparent inadequacies, thereby allowing for a more focused and fruitful validation and verification. However, comparing a black-box machine-learning model to known empirical scaling

Logan H. Jones, Svea Hernandez, Linda J. Smith, Bethan L. James

We present the first version release of SESAMME, a public, Python-based full spectrum fitting tool for Simultaneous Estimates of Star-cluster Age, Metallicity, Mass, and Extinction. SESAMME compares an input spectrum of a star cluster to a grid of stellar population models with an added nebular continuum component, using Markov chain Monte Carlo (MCMC) metho

Yuxiang Gao, Shiming Lei, Eleanor M. Clements, Yichen Zhang

The intrinsic anomalous Hall effect (AHE) has been reported in numerous ferromagnetic (FM) Weyl semimetals. However, AHE in the antiferromagnetic (AFM) or paramagnetic (PM) state of Weyl semimetals has been rarely observed experimentally, and only in centrosymmetric materials. Different mechanisms have been proposed to establish the connection between the AH

Oliver H. Wang

By work of Kirby-Siebenmann \cite{KirbySiebenmann} and Kervaire-Milnor \cite{KervaireMilnor}, there are only finitely many smooth manifolds homeomorphic to a given closed topological manifold. A construction involving Whitehead torsion shows this is not the case equivariantly for smooth finite group actions on a product $M\times I$ (see \cite[p. 262-266]{Bro

Sina Elahimanesh, Shayan Salehi, Sara Zahedi Movahed, Lisa Alazraki

In the wake of the post-pandemic era, marked by social isolation and surging rates of depression and anxiety, conversational agents based on digital psychotherapy can play an influential role compared to traditional therapy sessions. In this work, we develop a voice-capable chatbot in Farsi to guide users through Self-Attachment (SAT), a novel, self-administ

Ravi Mangal, Klas Leino, Zifan Wang, Kai Hu

Over the years, researchers have developed myriad attacks that exploit the ubiquity of adversarial examples, as well as defenses that aim to guard against the security vulnerabilities posed by such attacks. Of particular interest to this paper are defenses that provide provable guarantees against the class of $\ell_p$-bounded attacks. Certified defenses have

Hongchao Zhang, Junlin Wu, Yevgeniy Vorobeychik, Andrew Clark

Control Barrier Functions (CBFs) are a popular approach for safe control of nonlinear systems. In CBF-based control, the desired safety properties of the system are mapped to nonnegativity of a CBF, and the control input is chosen to ensure that the CBF remains nonnegative for all time. Recently, machine learning methods that represent CBFs as neural network

Kim H. Pham, Scott K. Cushing

Superionic conductors, or solid-state ion-conductors surpassing 0.01 S/cm in conductivity, can enable more energy dense batteries, robust artificial ion pumps, and optimized fuel cells. However, tailoring superionic conductors require precise knowledge of ion migration mechanisms that are still not well understood, due to limitations set by available spectro

Debangshu Banerjee, Aditya Gopalan

Parametric, feature-based reward models are employed by a variety of algorithms in decision-making settings such as bandits and Markov decision processes (MDPs). The typical assumption under which the algorithms are analysed is realizability, i.e., that the true values of actions are perfectly explained by some parametric model in the class. We are, however,

David M. Kaplan, David M. Blei

We develop a quantitative method to assess the style of American poems and to visualize a collection of poems in relation to one another. Qualitative poetry criticism helped guide our development of metrics that analyze various orthographic, syntactic, and phonemic features. These features are used to discover comprehensive stylistic information from a poem'

Mohammadjavad Ebrahimi, Uday V. Shanbhag, Farzad Yousefian

We consider a class of hierarchical multi-agent optimization problems over networks where agents seek to compute an approximate solution to a single-stage stochastic mathematical program with equilibrium constraints (MPEC). MPECs subsume several important problem classes including Stackelberg games, bilevel programs, and traffic equilibrium problems, to name

Andrew Swan, Jay Farihi, Kate Y. L. Su, Steven J. Desch

This letter reports the first JWST spectroscopy of a white dwarf debris disk, giving a preliminary assessment of the salient features, and recommendations for future observations. The polluted and dusty star WD 0145+234 experienced a major collisional event in its circumstellar disk in 2018, accompanied by an infrared outburst, and subsequently a gradual dec

Aude Gehrmann-De Ridder, Christian T Preuss, Ciaran Williams

We present next-to-leading order perturbative QCD predictions for four-jet-like event-shape observables in hadronic Higgs decays. To this end, we take into account two Higgs-decay categories: involving either the Yukawa-induced decay to a $b\bar{b}$ pair or the loop-induced decay to two gluons via an effective Higgs-gluon-gluon coupling. We present results f

Brian Punsly

A recent article on high-resolution 86 GHz observations with the Global Millimeter VLBI Array, the phased Atacama Large Millimeter/submillimeter Array, and the Greenland Telescope describes the detection of a limb-brightened cylindrical jet, $25 \mu\rm{as}< z< 100 \mu\rm{as}$, where $z$ is the axial displacement from the supermassive black hole in the sky pl

Sydney Petz, Marshall C. Johnson, Anusha Pai Asnodkar, Ji Wang

Most ultra hot Jupiters (UHJs) show evidence of temperature inversions, in which temperature increases with altitude over a range of pressures. Temperature inversions can occur when there is a species that absorbs the stellar irradiation at a relatively high level of the atmospheres. However, the species responsible for this absorption remains unidentified.

Matias Moreno

We study a Newtonian model which allows us to describe some extremely flat objects in galactic dynamics. This model is described by a partial differential equation system called Vlasov-Poisson, whose solutions describe the temporal evolution of a collisionless particle system in the phase space, subject to a self interacting gravitational potential. We treat

Carlos Dominguez, Jon Ander Campos, Eneko Agirre, Gorka Azkune

Neural information retrieval requires costly annotated data for each target domain to be competitive. Synthetic annotation by query generation using Large Language Models or rule-based string manipulation has been proposed as an alternative, but their relative merits have not been analysed. In this paper, we compare both methods head-to-head using the same n

Arindam Basu, Amit Chakraborty, Nilanjana Kumar, Soumya Sadhukhan

We study the boosted dark matter (BDM) scenario in a two-component model. We consider a neutrinophilic two-Higgs doublet model ($\nu$2HDM), which consists of one extra Higgs doublet and a light right-handed neutrino. This model is extended with a light ($\sim 10$~MeV) singlet scalar DM $\phi_3$, which is stabilized under an extra dark $Z_2^{\rm DM}$ symmetry

Seth Seidel, Da Yang

Humid air is lighter than dry air at the same temperature and pressure because the molecular weight of water vapor is less than that of dry air. This effect is known as vapor buoyancy (VB). In this work we use experiments in an idealized general circulation model (GCM) to show that VB warms the tropical free troposphere and leads to a significant increase in

Yufei Liu, Manzhou Li, Qin Ma

This study proposes a method based on lightweight convolutional neural networks (CNN) and generative adversarial networks (GAN) for apple ripeness and damage level detection tasks. Initially, a lightweight CNN model is designed by optimizing the model's depth and width, as well as employing advanced model compression techniques, successfully reducing the mod

Oussama Alyounes, Miguel Altamirano Cabrera, Dzmitry Tsetserukou

The growing demand for electric vehicles requires the development of automated car charging methods. At the moment, the process of charging an electric car is completely manual, and that requires physical effort to accomplish the task, which is not suitable for people with disabilities. Typically, the effort in the automation of the charging task research is

Matthew D. Koslovsky, Andee Kaplan, Victoria A. Terranova, Mevin B. Hooten

Measurement error in multinomial data is a well-known and well-studied inferential problem that is encountered in many fields, including engineering, biomedical and omics research, ecology, finance, official statistics, and social sciences. Methods developed to accommodate measurement error in multinomial data are typically equipped to handle false negatives

Olivier Gauthé, Frédéric Mila

Using state of the art tensor network computations combined with spin wave theory, we compute the finite temperature phase diagram of the spin 1/2 $J_1-J_2$ Heisenberg model on the square lattice with ferromagnetic $J_1 < 0$ and antiferromagnetic $J_2 > 0$. We localize the first order line originating from the first order zero temperature point as well as th

Hyungjoo Chae, Yongho Song, Kai Tzu-iunn Ong, Taeyoon Kwon

Human-like chatbots necessitate the use of commonsense reasoning in order to effectively comprehend and respond to implicit information present within conversations. Achieving such coherence and informativeness in responses, however, is a non-trivial task. Even for large language models (LLMs), the task of identifying and aggregating key evidence within a si

Saikat Chakraborty, Shuvendu K. Lahiri, Sarah Fakhoury, Madanlal Musuvathi

Synthesizing inductive loop invariants is fundamental to automating program verification. In this work, we observe that Large Language Models (such as gpt-3.5 or gpt-4) are capable of synthesizing loop invariants for a class of programs in a 0-shot setting, yet require several samples to generate the correct invariants. This can lead to a large number of cal

Noa Tuval, Alain Hertz, Tsvi Kuflik

The initial interaction of a user with a recommender system is problematic because, in such a so-called cold start situation, the recommender system has very little information about the user, if any. Moreover, in collaborative filtering, users need to share their preferences with the service provider by rating items while in content-based filtering there is

Yingjie Hu, Gengchen Mai, Chris Cundy, Kristy Choi

Social media messages posted by people during natural disasters often contain important location descriptions, such as the locations of victims. Recent research has shown that many of these location descriptions go beyond simple place names, such as city names and street names, and are difficult to extract using typical named entity recognition (NER) tools.

B. Tripathi, P. W. Terry, A. E. Fraser, E. G. Zweibel

Turbulence in three dimensions ($3$D) supports vortex stretching that has long been known to accomplish energy transfer to small scales. Moreover, net energy transfer from large-scale, forced, unstable flow-gradients to smaller scales is achieved by gradient-flattening instability. Despite such enforcement of energy transfer to small scales, it is shown here

Yunsheng Zhang

We present the Incremental Generative Monte Carlo (IGMC) method, designed to measure uncertainty in deep neural networks using deep generative approaches. IGMC iteratively trains generative models, adding their output to the dataset, to compute the posterior distribution of the expectation of a random variable. We provide a theoretical guarantee of the conve

Utkarsh Patel, Pratik Adarsh, Sudhanwa Patra, Purushottam Sahu

We explore the connection between low-scale CP-violating Dirac phase~$(\delta)$ and high-scale leptogenesis in a Left-Right Symmetric Model (LRSM) with scalar bidoublet and doublets. The fermion sector of the model is extended with one sterile neutrino~$(S_L)$ per generation to implement a double seesaw mechanism in the neutral fermion mass matrix. The doubl

Maya Okawa, Ekdeep Singh Lubana, Robert P. Dick, Hidenori Tanaka

Modern generative models exhibit unprecedented capabilities to generate extremely realistic data. However, given the inherent compositionality of the real world, reliable use of these models in practical applications requires that they exhibit the capability to compose a novel set of concepts to generate outputs not seen in the training data set. Prior work

Sebastian Bieringer, Gregor Kasieczka, Maximilian F. Steffen, Mathias Trabs

MALA is a popular gradient-based Markov chain Monte Carlo method to access the Gibbs-posterior distribution. Stochastic MALA (sMALA) scales to large data sets, but changes the target distribution from the Gibbs-posterior to a surrogate posterior which only exploits a reduced sample size. We introduce a corrected stochastic MALA (csMALA) with a simple correct

Sylvain Ribault, Ioannis Tsiares

We find a formula for the Virasoro fusion kernel at $c=25$, in terms of the connection coefficients of the Painlev\'e VI differential equation. Our formula agrees numerically with previously known integral representations of the kernel. The derivation of our formula relies on a duality $c\to 26-c$ that is obeyed by the shift equations for the fusion and modu

Sergio E. Aguilar-Gutierrez, Pablo Bueno, Pablo A. Cano, Robie A. Hennigar

We study various aspects of higher-curvature theories of gravity built from contractions of the metric, the Riemann tensor and the covariant derivative, $\mathcal{L}(g^{ab},R_{abcd},\nabla_a)$. We characterise the linearized spectrum of these theories and compute the modified Newton potential in the general case. Then, we present the first examples of Genera

Elie Hammou

The analysis and the interpretation of the LHC data require a precise determination of Parton Distribution Functions (PDFs) in order to detect reliably potential signs of new physics. I present a systematic study designed to assess the risk of absorbing, and thus missing, signals from heavy new physics in the PDFs parameterisation during the High-Luminosity

Steffani M. Grondin, Jeremy J. Webb, James M. M. Lane, Joshua S. Speagle

This work presents the Globular cluster Extra-tidal Mock Star (GEMS) catalogue of extra-tidal stars and binaries created via three-body dynamical encounters in globular cluster cores. Using the particle-spray code Corespray, we sample N=50,000 extra-tidal stars and escaped recoil binaries for 159 Galactic globular clusters. Sky positions, kinematics, stellar

Raphael Zöller, Matthias Kluge, Benjamin Staiger, Ralf Bender

In this study, we compare the structural parameters of ultra-diffuse galaxies (UDGs) to those of other dwarf galaxies and investigate whether UDGs form a distinct population. We observed deep $u'$-, $g'$-, and $r'$-band images (maximum limiting surface brightness [3$\sigma$, $10"\times10"$] $u'$ and $g'$: $\mathrm{\approx 30\,mag\,arcsec^{-2}}$; $r'$: $\math

Sihan Yuan, Risa H. Wechsler, Yunchong Wang, Mithi A. C. de los Reyes

Emission line galaxies (ELGs) are now the preeminent tracers of large-scale structure at z>0.8 due to their high density and strong emission lines, which enable accurate redshift measurements. However, relatively little is known about ELG evolution and the ELG-halo connection, exposing us to potential modeling systematics in cosmology inference using these s

David Robinson, Camille Avestruz, Nickolay Y. Gnedin

Gas cooling and heating functions play a crucial role in galaxy formation. But, it is computationally expensive to exactly compute these functions in the presence of an incident radiation field. These computations can be greatly sped up by using interpolation tables of pre-computed values, at the expense of making significant and sometimes even unjustified a

Zihao Li, Zheng Cai, Fengwu Sun, Johan Richard

We report galaxy MACS0416-Y3 behind the lensing cluster MACSJ0416.1--2403 as a tentative rotating disk at $z=8.34$ detected through its [OIII]$\lambda5007$ emission in JWST NIRCam wide-field slitless spectroscopic observations. The discovery is based on our new grism dynamical modeling methodology for JWST NIRCam slitless spectroscopy, using the data from ``

Elia Turco, Markus Aapro, Somesh C. Ganguli, Nils Krane

The Kondo effect describes the scattering of conduction electrons by magnetic impurities, manifesting as an electronic resonance at the Fermi energy with a distinctive temperature evolution. In this letter, we present a critical evaluation of the current methodology employed to demonstrate Kondo behavior in transport measurements, underscoring the limitation

Govert Nijs, Bruno Scheihing-Hitschfeld, Xiaojun Yao

We study the generalized gluon distribution that governs the dynamics of quarkonium inside a non-Abelian thermal plasma characterizing its dissociation and recombination rates. This gluon distribution can be written in terms of a correlation function of two chromoelectric fields connected by an adjoint Wilson line. We formulate and calculate this object in $

Chi Sun, Jacob Linder

Localized spins of single atoms adsorbed on surfaces have been proposed as building blocks for spintronics and quantum computation devices. However, identifying a way to achieve current-induced switching of spins with very low dissipation is an outstanding challenge with regard to practical applications. Here, we show that the indirect exchange interaction b

Shyamgopal Karthik, Karsten Roth, Massimiliano Mancini, Zeynep Akata

Given an image and a target modification (e.g an image of the Eiffel tower and the text "without people and at night-time"), Compositional Image Retrieval (CIR) aims to retrieve the relevant target image in a database. While supervised approaches rely on annotating triplets that is costly (i.e. query image, textual modification, and target image), recent res

B. T. Bolin, M. Ghosal, R. Jedicke

The rotational properties of $\sim$10~m-scale asteroids are poorly understood with only a few measurements. Additionally, collisions or thermal recoil can spin their rotations to periods less than a few seconds obfuscating their study due to the observational cadence imposed by the long read-out times of charge-coupled device imagers. We present a method to

Sudeep Dasari, Mohan Kumar Srirama, Unnat Jain, Abhinav Gupta

Visual representation learning hold great promise for robotics, but is severely hampered by the scarcity and homogeneity of robotics datasets. Recent works address this problem by pre-training visual representations on large-scale but out-of-domain data (e.g., videos of egocentric interactions) and then transferring them to target robotics tasks. While the f

Christophe Prange, Jin Tan

In the well-known book of Lions [{\em Mathematical topics in fluid mechanics. Incompressible models}, 1996], global existence results of finite energy weak solutions of the inhomogeneous incompressible Navier-Stokes equations (INS) were proved without assuming positive lower bounds on the initial density, hence allowing for vacuum. Uniqueness, regularity and

Aureliano M. Robles-Pérez, José Carlos Rosales

We characterise the numerical semigroups with a monotone Ap\'ery set (MANS-semigroups for abbreviate). Moreover, we describe the families of MANS-semigroups when we set the multiplicity and the ratio.

Guillaume Blanc

In this paper, we study invariant Poisson processes of lines (i.e, bi-infinite geodesics) in the $3$-regular tree. More precisely, there exists a unique (up to multiplicative constant) locally finite Borel measure on the space of lines that is invariant under graph automorphisms, and we consider two Poissonian ways of playing with this invariant measure. Fir

Utkarsh A. Mishra, Shangjie Xue, Yongxin Chen, Danfei Xu

Long-horizon tasks, usually characterized by complex subtask dependencies, present a significant challenge in manipulation planning. Skill chaining is a practical approach to solving unseen tasks by combining learned skill priors. However, such methods are myopic if sequenced greedily and face scalability issues with search-based planning strategy. To addres

Canyu Zhang, Xiaoguang Li, Qing Guo, Song Wang

Implicit representation of an image can map arbitrary coordinates in the continuous domain to their corresponding color values, presenting a powerful capability for image reconstruction. Nevertheless, existing implicit representation approaches only focus on building continuous appearance mapping, ignoring the continuities of the semantic information across

Ofer Busani, Timo Seppäläinen, Evan Sorensen

This paper studies the large scale limits of multi-type invariant distributions and Busemann functions of planar stochastic growth models in the Kardar-Parisi-Zhang (KPZ) class. We identify a set of sufficient hypotheses for convergence of multi-type invariant measures of last-passage percolation (LPP) models to the stationary horizon (SH), which is the uniq

Marcos Barrios, Marcelo Lanzilotta, Gustavo Mata

In this survey, we review the fundamental properties of the Igusa-Todorov functions, the $\phi$-dimension, the $\psi$-dimension and their generalizations.

Shuxiang Zhou, Enda Xiao, Hao Ma, Krzysztof Gofryk

Computing thermal transport from first-principles in UO$_2$ is complicated due to the challenges associated with Mott physics. Here we use irreducible derivative approaches to compute the cubic and quartic phonon interactions in UO$_2$ from first-principles, and we perform enhanced thermal transport computations by evaluating the phonon Green's function via

Jack Harrison, Hariom Jani, Junxiong Hu, Manohar Lal

Lensless coherent x-ray imaging techniques have great potential for high-resolution imaging of magnetic systems with a variety of in-situ perturbations. Despite many investigations of ferromagnets, extending these techniques to the study of other magnetic materials, primarily antiferromagnets, is lacking. Here, we demonstrate the first (to our knowledge) stu

Charalampos Charitos, Ioannis Papadoperakis, Georgios Tsapogas

A new metric on the open 2-dimensional unit disk is defined making it a geodesically complete metric space whose geodesic lines are precisely the Euclidean straight lines. Moreover, it is shown that the unit disk with this new metric is not isometric to any hyperbolic model of constant negative curvature, nor to any convex domain in R2 equipped with its Hilb

Hossein B. Jond

This paper considers a differential game approach to the predecessor-following vehicle platoon control problem without and with collision avoidance. In this approach, each vehicle tries to minimize the performance index (PI) of its control objective, which is reaching consensual velocity with the predecessor vehicle while maintaining a small inter-vehicle di

Geri Skenderi, Luigi Capogrosso, Andrea Toaiari, Matteo Denitto

Auxiliary tasks facilitate learning in situations where data is scarce or the principal task of interest is extremely complex. This idea is primarily inspired by the improved generalization capability induced by solving multiple tasks simultaneously, which leads to a more robust shared representation. Nevertheless, finding optimal auxiliary tasks is a crucia

Anket Patil, Dhairya Shah, Abhishek Shah, Mokshit Gala

Regarding the rising number of people suffering from mental health illnesses in today's society, the importance of mental health cannot be overstated. Wearable sensors, which are increasingly widely available, provide a potential way to track and comprehend mental health issues. These gadgets not only monitor everyday activities but also continuously record

Biyuan Liu, Huaixin Chen, Kun Li, Michael Ying Yang

Change detection plays a fundamental role in Earth observation for analyzing temporal iterations over time. However, recent studies have largely neglected the utilization of multimodal data that presents significant practical and technical advantages compared to single-modal approaches. This research focuses on leveraging {pre-event} digital surface model (D

Iuliia Kotseruba, John K. Tsotsos

To further advance driver monitoring and assistance systems, it is important to understand how drivers allocate their attention, in other words, where do they tend to look and why. Traditionally, factors affecting human visual attention have been divided into bottom-up (involuntary attraction to salient regions) and top-down (driven by the demands of the tas

I. V. Artamkin

A collection of vectors in a real vector space is called a unimodular system if any of its maximal linearly independent subsets generates the same free abelian group. This notion is closely connected with totally unimodular matrices: rows or columns of a totally unimodular matrix form a unimodular system and the matrix of coefficients of expansions of all ve

Etienne Chevalier, Yadh Hafsi, Vathana Ly Vath

The primary objective of this paper is to conceive and develop a new methodology to detect notable changes in liquidity within an order-driven market. We study a market liquidity model which allows us to dynamically quantify the level of liquidity of a traded asset using its limit order book data. The proposed metric holds potential for enhancing the aggress

Shubhadip Nayak, Sohom Das, Poulami Bag, Tanwi Debnath

We numerically examine the driven transport of an overdamped self-propelled particle through a two-dimensional array of circular obstacles. A detailed analysis of transport quantifiers (mobility and diffusivity) has been performed for two types of channels, {\it channel I} and {\it channel II}, that respectively correspond to the parallel and diagonal drives

Christopher Liaw, Aranyak Mehta, Wennan Zhu

We study the efficiency of non-truthful auctions for auto-bidders with both return on spend (ROS) and budget constraints. The efficiency of a mechanism is measured by the price of anarchy (PoA), which is the worst case ratio between the liquid welfare of any equilibrium and the optimal (possibly randomized) allocation. Our first main result is that the first

V. Girard-Alcindor, H. Jacob, M. Assié, D. Beaumel

MUGAST is a state-of-the-art silicon array combining trapezoidal and square shaped double-sided silicon strip detectors (DSSD) to four MUST2 telescopes. Coupled to a {\gamma}-ray spectrometer, the excellent angular coverage and compacity of the MUGAST array make it an ideal tool for the study of transfer reactions. It is a first step toward the development o

Austin Tripp, Krzysztof Maziarz, Sarah Lewis, Marwin Segler

Retrosynthesis is the task of planning a series of chemical reactions to create a desired molecule from simpler, buyable molecules. While previous works have proposed algorithms to find optimal solutions for a range of metrics (e.g. shortest, lowest-cost), these works generally overlook the fact that we have imperfect knowledge of the space of possible react

Wern Ng, Yongqiang Wen, Max Attwood, Daniel C Jones

Masers, the microwave analogues of lasers, have seen a renaissance owing to the discovery of gain media that mase at room-temperature and zero-applied magnetic field. However, despite the ease with which the devices can be demonstrated under ambient conditions, achieving the ubiquity and portability which lasers enjoy has to date remained challenging. We pre

M. Islam, N. d'Ambrumenil, D. D. Khalyavin, P. Manuel

We investigate the magnetic properties of the monoclinic D-type $\rm{Er_2Si_2O_7}$ with a distorted honeycomb lattice using powder and single crystal neutron scattering techniques, as well as single crystal magnetisation measurements. The powder neutron diffraction shows that below the ordering temperature, $T_{\rm N}=1.85$ K, the compound forms a ${\bf q}=0

Austin Tripp, José Miguel Hernández-Lobato

Generating molecules, both in a directed and undirected fashion, is a huge part of the drug discovery pipeline. Genetic algorithms (GAs) generate molecules by randomly modifying known molecules. In this paper we show that GAs are very strong algorithms for such tasks, outperforming many complicated machine learning methods: a result which many researchers ma

Nikhil Kandpal, Krishna Pillutla, Alina Oprea, Peter Kairouz

Fine-tuning is a common and effective method for tailoring large language models (LLMs) to specialized tasks and applications. In this paper, we study the privacy implications of fine-tuning LLMs on user data. To this end, we consider a realistic threat model, called user inference, wherein an attacker infers whether or not a user's data was used for fine-tu

Chufan Gao, Xulin Fan, Jimeng Sun, Xuan Wang

Relation extraction aims to classify the relationships between two entities into pre-defined categories. While previous research has mainly focused on sentence-level relation extraction, recent studies have expanded the scope to document-level relation extraction. Traditional relation extraction methods heavily rely on human-annotated training data, which is

Andrea Cappelletti

We study the categorical-algebraic properties of the semi-abelian variety $\ell \mathbb{G}rp$ of lattice-ordered groups. In particular, we show that this category is fiber-wise algebraically cartesian closed, arithmetical, and strongly protomodular. Moreover, we observe that $\ell \mathbb{G}rp$ is not action accessible, despite the good behaviour of centrali

Peng Li, Yeye He, Dror Yashar, Weiwei Cui

Language models, such as GPT-3.5 and ChatGPT, demonstrate remarkable abilities to follow diverse human instructions and perform a wide range of tasks. However, when probing language models using a range of basic table-understanding tasks, we observe that today's language models are still sub-optimal in many table-related tasks, likely because they are pre-tr