March 2023 arXiv papers — page 123

Guanrui Li, Giuseppe Loianno

Autonomous Micro Aerial Vehicles (MAVs) such as quadrotors equipped with manipulation mechanisms have the potential to assist humans in tasks such as construction and package delivery. Cables are a promising option for manipulation mechanisms due to their low weight, low cost, and simple design. However, designing control and planning strategies for cable me

Bryan Lim, Manon Flageat, Antoine Cully

The synergies between Quality-Diversity (QD) and Deep Reinforcement Learning (RL) have led to powerful hybrid QD-RL algorithms that have shown tremendous potential, and brings the best of both fields. However, only a single deep RL algorithm (TD3) has been used in prior hybrid methods despite notable progress made by other RL algorithms. Additionally, there

Yichen Li, Kaichun Mo, Yueqi Duan, He Wang

Shape assembly composes complex shapes geometries by arranging simple part geometries and has wide applications in autonomous robotic assembly and CAD modeling. Existing works focus on geometry reasoning and neglect the actual physical assembly process of matching and fitting joints, which are the contact surfaces connecting different parts. In this paper, w

Shouryya Ray

I point out that Gross-Neveu theory with SO(3) isospin in three spacetime dimensions -- proposed recently, for instance, as an effective description of the N\'eel transition in certain spin-orbital liquids -- also hosts quantum criticality of a more exotic kind. The ordered phase breaks SO(3) spontaneously, but the SO(3)-N\'eel order parameter vanishes. The

Hans Hon Sang Chan, David Muñoz Ramo, Nathan Fitzpatrick

We adapt a recent advance in resource-frugal quantum signal processing - the Quantum Eigenvalue Transform with Unitary matrices (QET-U) - to explore non-unitary imaginary time evolution on early fault-tolerant quantum computers using exactly emulated quantum circuits. We test strategies for optimising the circuit depth and the probability of successfully pre

Theodore Jacobson, Tin Sulejmanpasic

We formulate $U(1)_k$ Chern-Simons theory on a Euclidean spacetime lattice using the modified Villain approach. Various familiar aspects of continuum Chern-Simons theory such as level quantization, framing, the discrete 1-form symmetry and its 't Hooft anomaly, as well as the electric charge of monopole operators are manifest in our construction. The key tec

Zahari Kassabov, Maeve Madigan, Luca Mantani, James Moore

We assess the impact of top quark production at the LHC on global analyses of parton distributions (PDFs) and of Wilson coefficients in the SMEFT, both separately and in the framework of a joint interpretation. We consider the broadest top quark dataset to date containing all available measurements based on the full Run II luminosity. First, we determine the

Benjamin Koch, Enrique Muñoz

In this homage to Einstein's 144th birthday we propose a novel quantization prescription, where the paths of a path-integral are not random, but rather solutions of a geodesic equation in a random background. We show that this change of perspective can be made mathematically equivalent to the usual formulations of non-relativistic quantum mechanics. To concl

Sarah Kubiak, Andrew Vanderburg, Juliette Becker, Bruce Gary

WD 1856+534 b (or WD 1856 b for short) is the first known transiting planet candidate around a white dwarf star. WD 1856 b is about the size of Jupiter, has a mass less than about 12 Jupiter masses, and orbits at a distance of about 2% of an astronomical unit. The formation and migration history of this object is still a mystery. Here, we present constraints

Quentin Bonnefoy, Lawrence Hall, Claudio Andrea Manzari, Christiane Scherb

We propose theories of a complete mirror world with parity (P) solving the strong CP problem. P exchanges the entire Standard Model (SM) with its mirror copy. We derive bounds on the two new mass scales that arise: $v'$ where parity and mirror electroweak symmetry are spontaneously broken, and $v_3$ where the color groups break to the diagonal strong interac

Hamed Shirzad, Ameya Velingker, Balaji Venkatachalam, Danica J. Sutherland

Graph transformers have emerged as a promising architecture for a variety of graph learning and representation tasks. Despite their successes, though, it remains challenging to scale graph transformers to large graphs while maintaining accuracy competitive with message-passing networks. In this paper, we introduce Exphormer, a framework for building powerful

Shuai Yang, Liming Jiang, Ziwei Liu, Chen Change Loy

Recent advances in face manipulation using StyleGAN have produced impressive results. However, StyleGAN is inherently limited to cropped aligned faces at a fixed image resolution it is pre-trained on. In this paper, we propose a simple and effective solution to this limitation by using dilated convolutions to rescale the receptive fields of shallow layers in

Yunzhong Hou, Stephen Gould, Liang Zheng

Multiview camera setups have proven useful in many computer vision applications for reducing ambiguities, mitigating occlusions, and increasing field-of-view coverage. However, the high computational cost associated with multiple views poses a significant challenge for end devices with limited computational resources. To address this issue, we propose a view

Elena Manjavacas, Paulo A. Miles-Paez, Theodora Karalidi, Johanna M. Vos

Recent atmospheric models for brown dwarfs suggest that the existence of clouds in substellar objects is not needed to reproduce their spectra, nor their rotationally-induced photometric variability, believed to be due to the heterogeneous cloud coverage of brown dwarf atmospheres. Cloud-free atmospheric models also predict that their flux should not be pola

Alex Woodfinden, Will J. Percival, Seshadri Nadathur, Hans A. Winther

We present the cosmological implications of measurements of void-galaxy and galaxy-galaxy clustering from the Sloan Digital Sky Survey (SDSS) Main Galaxy Sample (MGS), Baryon Oscillation Spectroscopic Survey (BOSS), and extended BOSS (eBOSS) luminous red galaxy catalogues from SDSS Data Release 7, 12, and 16, covering the redshift range $0.07 < z < 1.0$. We

Nuwan Yapa, Kévin Fossez, Sebastian König

The study of open quantum systems (OQSs), i.e., systems interacting with an environment, impacts our understanding of exotic nuclei in low-energy nuclear physics, hadrons, cold-atom systems, or even noisy intermediate-scale quantum computers. Such systems often exhibit resonance states characterized by energy positions and dispersions (or decay widths), the

Hong-Xing Yu, Michelle Guo, Alireza Fathi, Yen-Yu Chang

Photorealistic object appearance modeling from 2D images is a constant topic in vision and graphics. While neural implicit methods (such as Neural Radiance Fields) have shown high-fidelity view synthesis results, they cannot relight the captured objects. More recent neural inverse rendering approaches have enabled object relighting, but they represent surfac

Manon Flageat, Bryan Lim, Antoine Cully

With the development of fast and massively parallel evaluations in many domains, Quality-Diversity (QD) algorithms, that already proved promising in a large range of applications, have seen their potential multiplied. However, we have yet to understand how to best use a large number of evaluations as using them for random variations alone is not always effec

Robert Irvine, Douglas Boubert, Vyas Raina, Adian Liusie

The emergence of pretrained large language models has led to the deployment of a range of social chatbots for chitchat. Although these chatbots demonstrate language ability and fluency, they are not guaranteed to be engaging and can struggle to retain users. This work investigates the development of social chatbots that prioritize user engagement to enhance

Felix Truger, Johanna Barzen, Marvin Bechtold, Martin Beisel

Due to low numbers of qubits and their error-proneness, Noisy Intermediate-Scale Quantum (NISQ) computers impose constraints on the size of quantum algorithms they can successfully execute. State-of-the-art research introduces various techniques addressing these limitations by utilizing known or inexpensively generated approximations, solutions, or models as

C. Pulsoni, O. Gerhard, S. M. Fall, M. Arnaboldi

Mass and angular momentum are key parameters of galaxies. Their co-evolution establishes an empirical relation between the specific stellar angular momentum j* and the stellar mass M* that depends on morphology. In this work, we measure j* in a sample of 32 early type galaxies (ETGs) from the ePN.S survey, using full 2D kinematic information out to a mean 6R

Alexander Arbieto, Andrés M. López, Elias Rego, Yeison Sánchez

In this work we study the existence of singular flows satisfying shadowing-like properties. More precisely, we prove that if C1 -vector field on a closed manifold induces a chain-recurrent flow containing an attached hyperbolic singularity of stable or unstable index-one, then this flow cannot satisfy the shadowing property. If the manifold is non-compact, t

Tongjia Zheng, Qing Han, Hai Lin

State estimation of robotic systems is essential to implementing feedback controllers, which usually provide better robustness to modeling uncertainties than open-loop controllers. However, state estimation of soft robots is very challenging because soft robots have theoretically infinite degrees of freedom while existing sensors only provide a limited numbe

Muhammad Saad Saeed, Shah Nawaz, Muhammad Haris Khan, Muhammad Zaigham Zaheer

With the rapid growth of social media platforms, users are sharing billions of multimedia posts containing audio, images, and text. Researchers have focused on building autonomous systems capable of processing such multimedia data to solve challenging multimodal tasks including cross-modal retrieval, matching, and verification. Existing works use separate ne

C. Marshall, K. Setoodehnia, G. C. Cinquegrana, J. H. Kelly

The star to star anticorrelation of sodium and oxygen {is} a defining feature of globular clusters, but, to date, the astrophysical site responsible for this unique chemical signature remains unknown. Sodium enrichment within these clusters depends sensitively on reaction rate of the sodium destroying reactions $^{23}$Na$(p, \gamma)$ and $^{23}$Na$(p, \alpha

Allan Borodin, Christodoulos Karavasilis

We consider the problem of online interval scheduling on a single machine, where intervals arrive online in an order chosen by an adversary, and the algorithm must output a set of non-conflicting intervals. Traditionally in scheduling theory, it is assumed that intervals arrive in order of increasing start times. We drop that assumption and allow for interva

Alexander Guttridge, Daniel K. Ruttley, Archie C. Baldock, Rosario González-Férez

We demonstrate Rydberg blockade due to the charge-dipole interaction between a single Rb atom and a single RbCs molecule confined in optical tweezers. The molecule is formed by magnetoassociation of a Rb+Cs atom pair and subsequently transferred to the rovibrational ground state with an efficiency of 91(1)\%. Species-specific tweezers are used to control the

William Thompson, Falk Herwig, Paul R. Woodward, Huaqing Mao

Recent photometric observations of massive stars have identified a low-frequency power excess which appears as stochastic low-frequency variability in light curve observations. We present the oscillation properties of high resolution hydrodynamic simulations of a 25 $\mathrm{M}_\odot$ star performed with the PPMStar code. The model star has a convective core

Jiahan Zhang, Dayong Tian

In the case of an imbalance between positive and negative samples, hard negative mining strategies have been shown to help models learn more subtle differences between positive and negative samples, thus improving recognition performance. However, if too strict mining strategies are promoted in the dataset, there may be a risk of introducing false negative s

Rita Touma, Arthur Le Ber, Michel Campillo, Alexandre Aubry

Imaging the structure of major fault zones is essential for our understanding of crustal deformations and their implications on seismic hazards. Investigating such complex regions presents several issues, including the variation of seismic velocity due to the diversity of geological units and the cumulative damage caused by earthquakes. Conventional migratio

John B Friedlander, Henryk Iwaniec

In this work and its sister paper [5] we give a new proof of the famous Linnik theorem bounding the least prime in an arithmetic progression. Using sieve machinery in both papers, we are able to dipense with the log-free zero density bounds and the repulsion property of exceptional zeros, two deep innovations begun by Linnik and reelied on in earlier proofs.

Manan Tomar, Riashat Islam, Matthew E. Taylor, Sergey Levine

Informational parsimony provides a useful inductive bias for learning representations that achieve better generalization by being robust to noise and spurious correlations. We propose \textit{information gating} as a way to learn parsimonious representations that identify the minimal information required for a task. When gating information, we can learn to r

Tuğrulcan Elmas, Stephane Selim, Célia Houssiaux

Social media posts may go viral and reach large numbers of people within a short period of time. Such posts may threaten the public dialogue if they contain misleading content, making their early detection highly crucial. Previous works proposed their own metrics to annotate if a tweet is viral or not in order to automatically detect them later. However, suc

Ulysse Najar, Victor Barolle, Paul Balondrade, Mathias Fink

As light travels through a disordered medium such as biological tissues, it undergoes multiple scattering events. This phenomenon is detrimental to in-depth optical microscopy, as it causes a drastic degradation of contrast, resolution and brightness of the resulting image beyond a few scattering mean free paths. However, the information about the inner refl

Ángel Javier Alonso, Michael Kerber

We study the decomposition of zero-dimensional persistence modules, viewed as functors valued in the category of vector spaces factorizing through sets. Instead of working directly at the level of vector spaces, we take a step back and first study the decomposition problem at the level of sets. This approach allows us to define the combinatorial notion of ro

Mohadeseh Feshanjerdi, Amir Ali Masoudi, Peter Grassberger, Mahdiyeh Ebrahimi

We study percolation on the sites of a finite lattice visited by a generalized random walk of finite length with periodic boundary conditions. More precisely, consider Levy flights and walks with finite jumps of length $>1$ (like knight's move random walks (RW) in 2 dimensions and generalized knight's move RW in 3d). In these walks, the visited sites do not

Anna Büttner, Anton Plietzsch, Mehrnaz Anvari, Frank Hellmann

The paper is published in Chaos. Please refer to the Chaos version from now on. Anna B\"uttner, Anton Plietzsch, Mehrnaz Anvari, Frank Hellmann; A framework for synthetic power system dynamics. Chaos 1 August 2023; 33 (8): 083120. https://doi.org/10.1063/5.0155971 Information on power grids is confidential and thus real data is often inaccessible. This neces

A. N. Lasenby, M. P. Hobson, W. E. V. Barker

We investigate recent claims that gravitomagnetic effects in linearised general relativity can explain flat and rising rotation curves, such as those observed in galaxies, without the need for dark matter. If one models a galaxy as an axisymmetric, stationary, rotating, non-relativistic and pressureless 'dust' of stars in the gravitoelectromagnetic (GEM) for

Antonin Paquette-Rufiange, Serge Prudhomme, Marc Laforest

Numerical predictions of quantities of interest measured within physical systems rely on the use of mathematical models that should be validated, or at best, not invalidated. Model validation usually involves the comparison of experimental data (outputs from the system of interest) and model predictions, both obtained at a specific validation scenario. The d

Matteo Ciardi, Fabio Cinti, Giuseppe Pellicane, Santi Prestipino

Confinement can have a considerable effect on the behavior of particle systems, and is therefore an effective way to discover new phenomena. A notable example is a system of identical bosons at low temperature under an external field mimicking an isotropic bubble trap, which constrains the particles to a portion of space close to a spherical surface. Using P

Aidan Herderschee, Radu Roiban, Fei Teng

We compute the next-to-leading order term in the scattering waveform of uncharged black holes in classical general relativity and of half-BPS black holes in $\mathcal{N}=8$ supergravity. We propose criteria, generalizing explicit calculations at next-to-leading order, for determining the terms in amplitudes that contribute to local observables. For general r

Andreas Brandhuber, Graham R. Brown, Gang Chen, Stefano De Angelis

Using a heavy-mass effective field theory (HEFT), we study gravitational-wave emission in the scattering of two spinless black holes or neutron stars of arbitrary masses at next-to-leading order in the Post-Minkowskian expansion. We compute the contributions to the one-loop scattering amplitude with four scalars and one graviton which are relevant to the cal

Bernardo Morcego, Wenjie Yin, Sjoerd Boersma, Eldert van Henten

Greenhouse is an important protected horticulture system for feeding the world with enough fresh food. However, to maintain an ideal growing climate in a greenhouse requires resources and operational costs. In order to achieve economical and sustainable crop growth, efficient climate control of greenhouse production becomes essential. Model Predictive Contro

Mert Kayaalp, Yunus Inan, Visa Koivunen, Emre Telatar

We consider the problem of information aggregation in federated decision making, where a group of agents collaborate to infer the underlying state of nature without sharing their private data with the central processor or each other. We analyze the non-Bayesian social learning strategy in which agents incorporate their individual observations into their opin

M. Gessner, A. Smerzi

We derive lower bounds on the variance of estimators in quantum metrology by choosing test observables that define constraints on the unbiasedness of the estimator. The quantum bounds are obtained by analytical optimization over all possible quantum measurements and estimators that satisfy the given constraints. We obtain hierarchies of increasingly tight bo

M. L. Hamadouche, A. C. Carnall, R. J. McLure, J. S. Dunlop

We present a spectro-photometric study of a mass-complete sample of quiescent galaxies at $1.0 < z < 1.3$ with $\mathrm{log_{10}}(M_{\star}/\mathrm{M_{\odot}}) \geq 10.3$ drawn from the VANDELS survey, exploring the relationship between stellar mass, age and star-formation history. Within our sample of 114 galaxies, we derive a stellar-mass vs stellar-age re

Richard S. J. Tol

Nobel laureates cluster together. 696 of the 727 winners of the Nobel Prize in physics, chemistry, medicine, and economics belong to one single academic family tree. 668 trace their ancestry to Emmanuel Stupanus, 228 to Lord Rayleigh (physics, 1904). Craig Mello (medicine, 2006) counts 51 Nobelists among his ancestors. Chemistry laureates have the most Nobel

Ryan J. French, Thomas J. Bogdan, Roberto Casini, Alfred G. de Wijn

The Visible Spectro-Polarimeter (ViSP) of the NSF Daniel K. Inouye Solar Telescope (DKIST) collected its Science Verification data on May 7-8, 2021. The instrument observed multiple layers of a sunspot atmosphere simultaneously, in passbands of Ca-II 397 nm (H-line), Fe-I 630 nm, and Ca-II 854 nm, scanning the region with a spatial sampling of 0.041" and ave

Rupert L. Frank, Ari Laptev, Larry Read

We derive weighted versions of the Cwikel-Lieb-Rozenblum inequality for the Schr\"odinger operator in two dimensions with a nontrivial Aharonov-Bohm magnetic field. Our bounds capture the optimal dependence on the flux and we identify a class of long-range potentials that saturate our bounds in the strong coupling limit. We also extend our analysis to the tw

Keisuke Yazawa, John Hayden, Jon-Paul Maria, Wanlin Zhu

Ferroelectric polarization switching is one common example of a process that occurs via nucleation and growth, and understanding switching kinetics is crucial for applications such as ferroelectric memory. Here we describe and interpret anomalous switching dynamics in the wurtzite nitride thin film ferroelectrics Al0.7Sc0.3N and Al0.94B0.06N using a general

Sebastian Forster, Gramoz Goranci, Yasamin Nazari, Antonis Skarlatos

Designing approximate all-pairs distance oracles in the fully dynamic setting is one of the central problems in dynamic graph algorithms. Despite extensive research on this topic, the first result breaking the $O(\sqrt{n})$ barrier on the update time for any non-trivial approximation was introduced only recently by Forster, Goranci and Henzinger [SODA'21] wh

Kayla D. Davie, Howard C. Elman

We explore the features of two methods of stabilization, aggregation and supremizer methods, for reduced-order modeling of parametrized optimal control problems. In both methods, the reduced basis spaces are augmented to guarantee stability. For the aggregation method, the reduced basis approximation spaces for the state and adjoint variables are augmented i

Russell D. Marroquin, Viacheslav Sadykov, Alexander Kosovichev, Irina N. Kitiashvili

The flux of energetic particles originating from the Sun fluctuates during the solar cycles. It depends on the number and properties of Active Regions (ARs) present in a single day and associated solar activities, such as solar flares and coronal mass ejections (CMEs). Observational records of the Space Weather Prediction Center (SWPC NOAA) enable the creati

Hege Michiels, An Vandebosch, Stijn Vansteelandt

When choosing estimands and estimators in randomized clinical trials, caution is warranted as intercurrent events, such as - due to patients who switch treatment after disease progression, are often extreme. Statistical analyses may then easily lure one into making large implicit extrapolations, which often go unnoticed. We will illustrate this problem of im

Martin W. van Mourik, Elias Zapusek, Pavel Hrmo, Lukas Gerster

We demonstrate a novel experimental toolset that enables irreversible multi-qubit operations on a quantum platform. To exemplify our approach, we realize two elementary nonunitary operations: the OR and NOR gates. The electronic states of two trapped $^{40}$Ca$^{+}$ ions encode the logical information, and a co-trapped $^{88}$Sr$^{+}$ ion provides the irreve

David Audretsch, Christian Fisch, Chiara Franzoni, Paul P. Momtaz

The first-ever article published in Research Policy was Casimir's (1971) advocacy of academic freedom in light of the industry's increasing influence on research in universities. Half a century later, the literature attests to the dearth of work on the role of academic freedom for innovation. To fill this gap, we employ instrumental variable techniques to id

Johannes Sjöstrand, Martin Vogel

We study the small singular values of the $2$-dimensional semiclassical differential operator $P = 2\,\mathrm{e}^{-\phi/h}\circ hD_{\overline{z}}\circ \mathrm{e}^{\phi/h}$ on $S^1+iS^1$ and on $S^1+i\mathbb{R}$ where $\phi$ is given by $\sin y$ and by $y^3/3$, respectively. The key feature of this model is the fact that we can pinpoint precisely where in pha

Jie Zhou, Xianshuai Cao, Wenhao Li, Lin Bo

Multi-scenario & multi-task learning has been widely applied to many recommendation systems in industrial applications, wherein an effective and practical approach is to carry out multi-scenario transfer learning on the basis of the Mixture-of-Expert (MoE) architecture. However, the MoE-based method, which aims to project all information in the same feature

Shreya Shankar, Labib Fawaz, Karl Gyllstrom, Aditya G. Parameswaran

Machine learning (ML) models in production pipelines are frequently retrained on the latest partitions of large, continually-growing datasets. Due to engineering bugs, partitions in such datasets almost always have some corrupted features; thus, it's critical to detect data issues and block retraining before downstream ML model accuracy decreases. However, i

João Penedo, João Pulido

We analyse the sensitivity of the Deep Underground Neutrino Experiment (DUNE) to a sterile neutrino, combining information from both the Near Detector (ND) and the Far Detector (FD). DUNE's sterile exclusion reach is affected by taking into account the information on the neutrino production point, in contrast to assuming a point-like neutrino source. Visible

Andrea Di Carli, Robbie Cruickshank, Matthew Mitchell, Arthur La Rooij

We experimentally investigate the stability of a quantum gas with repulsive interactions in an optical 1D lattice subjected to periodic driving. Excitations of the gas in the lowest lattice band are analyzed across the complete stability diagram, from slow to fast driving frequencies and from weak to strong driving strengths. To interpret our results, we exp

Roberto Di Mari, Zsuzsa Bakk, Jennifer Oser, Jouni Kuha

We propose a two-step estimator for multilevel latent class analysis (LCA) with covariates. The measurement model for observed items is estimated in its first step, and in the second step covariates are added in the model, keeping the measurement model parameters fixed. We discuss model identification, and derive an Expectation Maximization algorithm for eff

Paul Burkhardt, David G. Harris

We consider the problem of counting 4-cycles ($C_4$) in an undirected graph $G$ of $n$ vertices and $m$ edges (in bipartite graphs, 4-cycles are also often referred to as $\textit{butterflies}$). Most recently, Wang et al. (2019, 2022) developed algorithms for this problem based on hash tables and sorting the graph by degree. Their algorithm takes $O(m\bar\d

Alberto Manzano, Gonzalo Ferro, Álvaro Leitao, Carlos Vázquez

In this work we present an alternative methodology to the standard Quantum Accelerated Monte Carlo (QAMC) applied to derivatives pricing. Our pipeline benefits from the combination of a new encoding protocol, referred to as the direct encoding, and a amplitude estimation algorithm, the modified Real Quantum Amplitude Estimation (mRQAE) algorithm. On the one

Zahra Atashgahi, Xuhao Zhang, Neil Kichler, Shiwei Liu

Feature selection that selects an informative subset of variables from data not only enhances the model interpretability and performance but also alleviates the resource demands. Recently, there has been growing attention on feature selection using neural networks. However, existing methods usually suffer from high computational costs when applied to high-di

Marin Scalbert, Maria Vakalopoulou, Florent Couzinié-Devy

In Self-Supervised Learning (SSL), models are typically pretrained, fine-tuned, and evaluated on the same domains. However, they tend to perform poorly when evaluated on unseen domains, a challenge that Unsupervised Domain Generalization (UDG) seeks to address. Current UDG methods rely on domain labels, which are often challenging to collect, and domain-spec

Prahlad Sharma

We obtain the exponent of distribution $1/2+1/30$ for the ternary divisor function $d_3$ to square-free and prime power moduli, improving the previous results of Fouvry--Kowalski--Michel, Heath-Brown, and Friedlander--Iwaniec. The key input is certain estimates on bilinear sums with $GL(2)$ coefficients obtained using the delta symbol approach.

Michał Kosiba

This paper is devoted to proving the general {\L}ojasiewicz inequality, in both the definable and subanalytic cases, under the most relaxed assumptions. It means that we drop the usual continuity and compactness assumptions. In the second part of the paper we concentrate on the {\L}ojasiewicz inequality for multifunctions and apply it to the natural multifun

Enderson Falcón-Gómez, Adrián Amor-Martín, Valentín De La Rubia, Gabriel Santamaría-Botello

In this manuscript, we present an alternative method for calculating null geodesics in General Static Isotropic Metrics in General Relativity and Extended Theories of Gravity. By applying a conformal transformation, we are able to consider an analogue gravity model, where curvature is encoded in the dielectric and magnetic properties of a medium. In other wo

Wei-Kuo Chen, Heejune Kim, Arnab Sen

We study the L\'evy spin glass model, a fully connected model on $N$ vertices with heavy-tailed interactions governed by a power law distribution of order $0<\alpha<2.$ Our investigation is divided into three cases $0<\alpha<1$, $\alpha=1$, and $1<\alpha<2.$ When $1<\alpha<2,$ we identify a high temperature regime, in which the limit and fluctuation of the f

Senyu Qi, Wei-Min Gu, Tuan Yi, Zhi-Xiang Zhang

The time-domain (TD) surveys of the Large Sky Area Multi-Object Fiber Spectroscopic Telescope (LAMOST) yield high-cadence radial velocities, paving a new avenue to study binary systems including compact objects. In this work, we explore LAMOST TD spectroscopic data of four K2 plates and present a sample of six single-lined spectroscopic binaries that may con

Ramy Rashad, Andrea Brugnoli, Federico Califano, Erwin Luesink

In this paper we formulate the theory of nonlinear elasticity in a geometrically intrinsic manner using exterior calculus and bundle-valued differential forms. We represent kinematics variables, such as velocity and rate-of-strain, as intensive vector-valued forms while kinetics variables, such as stress and momentum, as extensive covector-valued pseudo-form

Madeline Oh, Maya Fishbach, Chase Kimball, Vicky Kalogera

In their most recent observing run, the LIGO-Virgo-KAGRA (LVK) Collaboration observed gravitational waves (GWs) from compact binary mergers with highly asymmetric mass ratios, including both binary black holes (BBHs) and neutron star--black holes (NSBHs). It appears that NSBHs with mass ratios $q\simeq0.2$ are more common than equally asymmetric BBHs, but th

Nathaniel Moore Glaser, Zsolt Kira

This paper addresses the task of joint multi-agent perception and planning, especially as it relates to the real-world challenge of collision-free navigation for connected self-driving vehicles. For this task, several communication-enabled vehicles must navigate through a busy intersection while avoiding collisions with each other and with obstacles. To this

Carlos Lassance, Stéphane Clinchant

This paper describes our participation in the 2022 TREC NeuCLIR challenge. We submitted runs to two out of the three languages (Farsi and Russian), with a focus on first-stage rankers and comparing mono-lingual strategies to Adhoc ones. For monolingual runs, we start from pretraining models on the target language using MLM+FLOPS and then finetuning using the

I. Vidana, A. Feijoo, M. Albaladejo, J. Nieves

We have conducted a study of the femtoscopic correlation functions for the $D^0D^{*+}$ and $D^+D^{*0}$ channels that build the $T_{cc}$ state. We develop a formalism that allows us to factorize the scattering amplitudes outside the integrals in the formulas, and the integrals involve the range of the strong interaction explicitly. For a source of size of 1 f

Liu Chen, Michael Deisher, Munir Georges

This paper describes an end-to-end (E2E) neural architecture for the audio rendering of small portions of display content on low resource personal computing devices. It is intended to address the problem of accessibility for vision-impaired or vision-distracted users at the hardware level. Neural image-to-text (ITT) and text-to-speech (TTS) approaches are re

Bolian Li, Ruqi Zhang

Long-tailed classification poses a challenge due to its heavy imbalance in class probabilities and tail-sensitivity risks with asymmetric misprediction costs. Recent attempts have used re-balancing loss and ensemble methods, but they are largely heuristic and depend heavily on empirical results, lacking theoretical explanation. Furthermore, existing methods

Lewis D Griffin, Bennett Kleinberg, Maximilian Mozes, Kimberly T Mai

Two studies tested the hypothesis that a Large Language Model (LLM) can be used to model psychological change following exposure to influential input. The first study tested a generic mode of influence - the Illusory Truth Effect (ITE) - where earlier exposure to a statement (through, for example, rating its interest) boosts a later truthfulness test rating.

Flavia Bonomo-Braberman, Eric Brandwein, Fabiano S. Oliveira, Moysés S. Sampaio

Interval graphs and proper interval graphs are well known graph classes, for which several generalizations have been proposed in the literature. In this work, we study the (proper) thinness, and several variations, for the classes of cographs, crowns graphs and grid graphs. We provide the exact values for several variants of thinness (proper, independent, co

Angelica Liguori, Luciano Caroprese, Marco Minici, Bruno Veloso

In real-world scenario, many phenomena produce a collection of events that occur in continuous time. Point Processes provide a natural mathematical framework for modeling these sequences of events. In this survey, we investigate probabilistic models for modeling event sequences through temporal processes. We revise the notion of event modeling and provide th

Sayantan Choudhury, Sudhakar Panda, M. Sami

We present a detailed exposition on the prospects of the formation of Primordial Black Holes (PBHs) during Slow Roll (SR) to Ultra Slow Roll (USR) sharp transitions in the framework of single-field inflation. We use an effective field theory (EFT) approach in order to keep the analysis model-independent and applicable to both the canonical and non-canonical

Will Johnson, Jinhe Ye

If $C$ is a curve over $\mathbb{Q}$ with genus at least $2$ and $C(\mathbb{Q})$ is empty, then the class of fields $K$ of characteristic 0 such that $C(K) = \varnothing$ has a model companion, which we call $C\mathrm{XF}$. The theory $C\mathrm{XF}$ is not complete, but we characterize the completions. Using $C\mathrm{XF}$, we produce examples of fields with

Danilo Nikolić, Bayan Karimi, Diego Subero Rengel, Jukka P. Pekola

We propose a mesoscopic thermometer for ultrasensitive detection based on the proximity effect in superconductor-normal metal (SN) heterostructures. The device is based on the zero-bias anomaly due to the inelastic Cooper pair tunneling in an SNIS junction (I stands for an insulator) coupled to an ohmic electromagnetic (EM) environment. The theoretical model

Dorian Baudry, Kazuya Suzuki, Junya Honda

In this paper we propose a general methodology to derive regret bounds for randomized multi-armed bandit algorithms. It consists in checking a set of sufficient conditions on the sampling probability of each arm and on the family of distributions to prove a logarithmic regret. As a direct application we revisit two famous bandit algorithms, Minimum Empirical

Si-An Chen, Chun-Liang Li, Nate Yoder, Sercan O. Arik

Real-world time-series datasets are often multivariate with complex dynamics. To capture this complexity, high capacity architectures like recurrent- or attention-based sequential deep learning models have become popular. However, recent work demonstrates that simple univariate linear models can outperform such deep learning models on several commonly used a

Andrea Barbon, Angelo Ranaldo

By investigating nonfungible tokens (NFTs), we provide the first systematic study of retail investor behavior through asset bubbles. Given that NFTs are recorded in public blockchains, we are able to track investor behavior over time, leading to the identification of numerous price run-ups and crashes. Our study reveals that agent-level variables, such as in

Gorka Muñoz-Gil, Andrea López-Incera, Lukas J. Fiderer, Hans J. Briegel

The foraging behavior of animals is a paradigm of target search in nature. Understanding which foraging strategies are optimal and how animals learn them are central challenges in modeling animal foraging. While the question of optimality has wide-ranging implications across fields such as economy, physics, and ecology, the question of learnability is a topi

Harrison LaBollita, Alexander Hampel, Jonathan Karp, Antia S. Botana

Using a density-functional theory plus dynamical mean-field theory methodology, we compute the many-body electronic structure and optical conductivity of NdNiO$_{2}$ under the influence of large scattering rates on the Nd($5d$) bands and including dynamical interactions on the Nd($5d$) orbitals with shifts of the Nd-Ni $d$-level energy difference. We find a

Rodrigo A. González, Koen Tiels, Tom Oomen

Sampling in control applications is increasingly done non-equidistantly in time. This includes applications in motion control, networked control, resource-aware control, and event-based control. Some of these applications, like the ones where displacement is tracked using incremental encoders, are driven by signals that are only measured when their values cr

Xianggang Yu, Mutian Xu, Yidan Zhang, Haolin Liu

Being data-driven is one of the most iconic properties of deep learning algorithms. The birth of ImageNet drives a remarkable trend of "learning from large-scale data" in computer vision. Pretraining on ImageNet to obtain rich universal representations has been manifested to benefit various 2D visual tasks, and becomes a standard in 2D vision. However, due t

Jamie Mullineaux, Takoua Jendoubi, Baptiste Leurent

The spread of COVID-19 has brought challenges to health, social and economic systems around the world. With little to no prior immunity in the global population transmission has been driven primarily by human interaction. However, as with common respiratory illnesses such as the flu it's suggested that COVID-19 may become seasonal as immunity grows. Yet the

Yunguan Fu, Yiwen Li, Shaheer U. Saeed, Matthew J. Clarkson

Recently, denoising diffusion probabilistic models (DDPM) have been applied to image segmentation by generating segmentation masks conditioned on images, while the applications were mainly limited to 2D networks without exploiting potential benefits from the 3D formulation. In this work, we studied the DDPM-based segmentation model for 3D multiclass segmenta

Eduardo Rodriguez, Gabe G. Plunk

The condition of quasi-isodynamicity is derived to second order in the distance from the magnetic axis. We do so using a formulation of omnigenity that explicitly requires the balance between the radial particle drifts at opposite bounce points of a magnetic well. This is a physically intuitive alternative to the integrated condition involving distances betw

Wei Xiao, Christos G. Cassandras, Calin A. Belta

It has been shown that optimizing quadratic costs while stabilizing affine control systems to desired (sets of) states subject to state and control constraints can be reduced to a sequence of Quadratic Programs (QPs) by using Control Barrier Functions (CBFs) and Control Lyapunov Functions (CLFs). In this paper, we employ machine learning techniques to ensure

Fabio Bernasconi, Iacopo Brivio, Stefano Filipazzi

We show that mixed-characteristic and equi-characteristic small deformations of 3-dimensional canonical (resp. terminal) singularities with perfect residue field of characteristic $p>5$ are canonical (resp. terminal). We discuss applications to arithmetic and geometric families of 3-dimensional Fano varieties and minimal models with canonical singularities.

Kei Ota, Devesh K. Jha, Hsiao-Yu Tung, Joshua B. Tenenbaum

Humans rely on touch and tactile sensing for a lot of dexterous manipulation tasks. Our tactile sensing provides us with a lot of information regarding contact formations as well as geometric information about objects during any interaction. With this motivation, vision-based tactile sensors are being widely used for various robotic perception and control ta

Abolfath Hosseinzadeh, Seyed Akbar Jafari

We use Boltzmann theory to study the semi-classical dynamics of electrons in a two-dimensional (2D) tilted Dirac material in which the tilt varies in space. The spatial variation of the tilt parameter induces a non-trivial spacetime geometry on the background of which the electrons roam about. As the first manifestation of graivto-electric phenomena, we find

Chris Kapulkin, Udit Mavinkurve

We develop a robust foundation for studying the fundamental group(oid) in discrete homotopy theory, including: equivalent definitions and basic properties, the theory of covering graphs, and the discrete version of the Seifert-van Kampen theorem.

Douglas D. Novaes, Leandro A. Silva

The cyclicity problem, crucial in analyzing planar vector fields, consists in estimating the number of limit cycles emanating from monodromic singularities. Traditionally, this estimation relies on Lyapunov coefficients. However, in nonsmooth systems, besides the limit cycles bifurcating by varying the Lyapunov coefficients, monodromic singularities on the s