March 2023 arXiv papers — page 2

Andrea Bacilieri, Pablo Austudillo-Estevez

There is a large consensus on the fundamental role of firm-level supply chain networks in macroeconomics. However, data on supply chains at the fine-grained, firm level are scarce and frequently incomplete. For listed firms, some commercial datasets exist but only contain information about the existence of a trade relationship between two companies, not the

T. J. Davidge

Information extracted from the GAIA Data Release 3 is used to examine the stellar contents within projected separations of 10 parsecs from eight close binary systems that are either classical W Serpentis systems or related objects. The goal is to search for remnant star clusters or moving groups with proper motions that are similar to those of the binaries.

Anthony Tang, Nathan Li, Benjamin Price, Alexander Mamishev

Dielectric barrier discharge (DBD) plasma actuators can generate a wall jet without moving parts by interacting with ionized and neutral molecules in an electric field. The coupling between electrohydrodynamic (EHD), turbulence, inertial and viscous effects in the flow boundary layer remains poorly understood and requires investigation. We present an experim

Nadia Nahar, Haoran Zhang, Grace Lewis, Shurui Zhou

Incorporating machine learning (ML) components into software products raises new software-engineering challenges and exacerbates existing challenges. Many researchers have invested significant effort in understanding the challenges of industry practitioners working on building products with ML components, through interviews and surveys with practitioners. Wi

Hans Gersbach, Akaki Mamageishvili, Fikri Pitsuwan

Systems and blockchains often have security vulnerabilities and can be attacked by adversaries, with potentially significant negative consequences. Therefore, infrastructure providers increasingly rely on bug bounty programs, where external individuals probe the system and report any vulnerabilities (bugs) in exchange for rewards (bounty). We develop a simpl

Carlos Mendez, Fabio Santos, Gabriel Gonçalves

Bubble columns are present in several applications, such as chemical and biochemical reactors and petrochemical and environmental engineering industries. This variety of applications is why understanding the bubble columns' dynamics is essential. This paper aims to describe a 2D bubble column system by a data-driven method to comprehend its dynamics better.

Wenzhi Hong, Hugh Sparks, Chris Dunsby

The technique of remote refocusing is used in optical microscopy to provide rapid axial scanning without mechanically perturbing the sample and in techniques such as oblique plane microscopy that build on remote refocusing to image a tilted plane within the sample. The magnification between the pupils of the primary (O1) and secondary (O2) microscope objecti

Alexander Dombowsky, David B. Dunson

Bayesian clustering typically relies on mixture models, with each component interpreted as a different cluster. After defining a prior for the component parameters and weights, Markov chain Monte Carlo (MCMC) algorithms are commonly used to produce samples from the posterior distribution of the component labels. The data are then clustered by minimizing the

Michael D. Himes, Joseph Harrington, Atilim Gunes Baydin

Characterizing exoplanetary atmospheres via Bayesian retrievals requires assuming some chemistry model, such as thermochemical equilibrium or parameterized abundances. The higher-resolution data offered by upcoming telescopes enables more complex chemistry models within retrieval frameworks. Yet, many chemistry codes that model more complex processes like ph

Tamaz Kereselidze, Irakli Noselidze, Zaal Machavariani

For a quasi-molecular mechanism of cosmological recombination, a scheme of calculation based on a rigorous quantum-mechanical approach is elaborated. The probability of free-bound radiative transition into an excited state of a quasi-molecule temporarily formed by a colliding electron and two nearest neighboring protons is derived in a closed algebraic form.

Lauren M. Weiss, Howard Isaacson, Andrew W. Howard, Benjamin J. Fulton

Despite the importance of Jupiter and Saturn to Earth's formation and habitability, there has not yet been a comprehensive observational study of how giant exoplanets correlate with the architectural properties of close-in, sub-Neptune-sized exoplanets. This is largely because transit surveys are particularly insensitive to planets at orbital separations >1

Johannes Köhler, Ferdinand Geuss, Melanie N. Zeilinger

We investigate model predictive control (MPC) formulations for linear systems subject to i.i.d. stochastic disturbances with bounded support and chance constraints. Existing stochastic MPC formulations with closed-loop guarantees can be broadly classified in two separate frameworks: i) using robust techniques; ii) feasibility preserving algorithms. We invest

Corey Jones

For a net of C*-algebras on a discrete metric space, we introduce a bimodule version of the DHR tensor category and show it is an invariant of quasi-local algebras under isomorphisms with bounded spread. For abstract spin systems on a lattice $L\subseteq \mathbb{R}^{n}$ satisfying a weak version of Haag duality, we construct a braiding on these categories. A

V. S. Manko, I. M. Mejía, C. I. Ramos, E. Ruiz

In the present paper we study the singularity structure of the exterior field of neutron stars with the aid of the four-parameter exact solution of the Einstein-Maxwell equations. The complete analysis of this problem in the generic case becomes possible due to the implementation of the novel analytical approach to the resolution of the singularity condition

K. Victor Sam Moses Babu, Pratyush Chakraborty, Mayukha Pal

The rapid growth of wind power generation has led to increased interest in understanding and mitigating the adverse effects of wind turbine wakes and forced oscillations in wind farms. In this paper, we model a wind farm consisting of three wind turbines connected to a distribution system. Forced oscillations due to wind shear and tower shadow are injected i

Vikas Aragam, Sonia Paban, Robert Rosati

The detection of a primordial stochastic gravitational wave background has the potential to reveal unprecedented insights into the early universe, and possibly into the dynamics of inflation. Generically, UV-complete inflationary models predict an abundance of light scalars, so any inflationary stochastic background may well be formed in a model with several

Michele Capovilla-Searle, Keiko Kawamuro, Rebecca Sorsen

Using Birman, Ko, and Lee's left canonical form of a braid, we characterize almost strongly quasipositive braids and give estimates of the fractional Dehn twist coefficient.

Alessandro Russo, N. Sukumar

The choice of stabilization term is a critical component of the virtual element method (VEM). However, the theory of VEM provides only asymptotic guidance for selecting the stabilization term, which ensures convergence as the mesh size approaches zero, but does not provide a unique prescription for its exact form. Thus, the selection of a suitable stabilizat

Robert Ferrando, Laurent Pagnier, Robert Mieth, Zhirui Liang

This paper addresses the challenge of efficiently solving the optimal power flow problem in real-time electricity markets. The proposed solution, named Physics-Informed Market-Aware Active Set learning OPF (PIMA-AS-OPF), leverages physical constraints and market properties to ensure physical and economic feasibility of market-clearing outcomes. Specifically,

Junyi Chai, Xiaoqian Wang

Adversarial training has been shown to be reliable in improving robustness against adversarial samples. However, the problem of adversarial training in terms of fairness has not yet been properly studied, and the relationship between fairness and accuracy attack still remains unclear. Can we simultaneously improve robustness w.r.t. both fairness and accuracy

Colin S. Beam

Selecting an evaluation metric is fundamental to model development, but uncertainty remains about when certain metrics are preferable and why. This paper introduces the concept of *resolving power* to describe the ability of an evaluation metric to distinguish between binary classifiers of similar quality. This ability depends on two attributes: 1. The metri

Xiang Zhang, Taoyue Wang, Xiaotian Li, Huiyuan Yang

Contrastive learning has shown promising potential for learning robust representations by utilizing unlabeled data. However, constructing effective positive-negative pairs for contrastive learning on facial behavior datasets remains challenging. This is because such pairs inevitably encode the subject-ID information, and the randomly constructed pairs may pu

Khandaker Foysal Haque, Milin Zhang, Francesco Restuccia

Recent advances in Wi-Fi sensing have ushered in a plethora of pervasive applications in home surveillance, remote healthcare, road safety, and home entertainment, among others. Most of the existing works are limited to the activity classification of a single human subject at a given time. Conversely, a more realistic scenario is to achieve simultaneous, mul

Antonija Utrobicic, Yannis Angelis, Stephan Aune, Jonathan Bortfeldt

The PICOSEC Micromegas precise timing detector is based on a Cherenkov radiator coupled to a semi-transparent photocathode and a Micromegas amplification structure. The first proof of concept single-channel small area prototype was able to achieve time resolution below 25 ps. One of the crucial aspects in the development of the precise timing gaseous detecto

Ethan Akin

A directed graph $R^{\circ}$ on a set $X$ is a set of ordered pairs of distinct points called \emph{arcs}. It is a tournament when every pair of distinct points is connected by an arc in one direction or the other (and not both). We can describe a tournament $R \subset X \times X$ as a total, antisymmetric relation, i.e. $R \cup R^{-1} = X \times X$ and $R \

Noah Stier, Baptiste Angles, Liang Yang, Yajie Yan

Dense 3D reconstruction from RGB images traditionally assumes static camera pose estimates. This assumption has endured, even as recent works have increasingly focused on real-time methods for mobile devices. However, the assumption of a fixed pose for each image does not hold for online execution: poses from real-time SLAM are dynamic and may be updated fol

I. Yu. Rybak, C. J. A. P. Martins, Patrick Peter, E. P. S. Shellard

We consider the evolution of current-carrying cosmic string networks described by the charge-velocity-dependent one scale (CVOS) model beyond the linear equation of state regime, specifically focusing on the Witten superconducting model. We find that, generically, for almost chiral currents, the network evolution reduces dynamically to that of the linear cas

Troy Nakagawa, Erik Poulin, Talbot Rueppel, Zhisong Chen

This study investigates the effect of thermal modification on the flexural properties, transverse fracture energy, and hardness of western hemlock, a material which is finding increasing applications in construction. Flexure tests on specimens featuring longitudinal and transverse grains showed that thermal modification at 167C slightly improves the flexural

Alexander Munteanu, Simon Omlor, David Woodruff

We improve upon previous oblivious sketching and turnstile streaming results for $\ell_1$ and logistic regression, giving a much smaller sketching dimension achieving $O(1)$-approximation and yielding an efficient optimization problem in the sketch space. Namely, we achieve for any constant $c>0$ a sketching dimension of $\tilde{O}(d^{1+c})$ for $\ell_1$ reg

Muhammad S. Battikh, Artem Lensky

Batch effects in high-dimensional Cytometry by Time-of-Flight (CyTOF) data pose a challenge for comparative analysis across different experimental conditions or time points. Traditional batch normalization methods may fail to preserve the complex topological structures inherent in cellular populations. In this paper, we present a residual neural network-base

Mohammadi Kiarash, Zhao He, Mengyao Zhai, Frederick Tung

In many real-world settings, the critical class is rare and a missed detection carries a disproportionately high cost. For example, tumors are rare and a false negative diagnosis could have severe consequences on treatment outcomes; fraudulent banking transactions are rare and an undetected occurrence could result in significant losses or legal penalties. In

Asier Zabalo, Massimiliano Stengel

We present an accurate and computationally efficient first-principles methodology to calculate the natural optical activity. Our approach is based on the long-wave density-functional perturbation theory and includes self-consistent field (SCF) terms naturally in the formalism, which are found to be of crucial importance. The final result is expressed exclusi

Homa Esfahanizadeh, Adam Yala, Rafael G. L. D'Oliveira, Andrea J. D. Jaba

Allowing organizations to share their data for training of machine learning (ML) models without unintended information leakage is an open problem in practice. A promising technique for this still-open problem is to train models on the encoded data. Our approach, called Privately Encoded Open Datasets with Public Labels (PEOPL), uses a certain class of random

Bogdan Mazoure, Jake Bruce, Doina Precup, Rob Fergus

Sequential decision-making agents struggle with long horizon tasks, since solving them requires multi-step reasoning. Most reinforcement learning (RL) algorithms address this challenge by improved credit assignment, introducing memory capability, altering the agent's intrinsic motivation (i.e. exploration) or its worldview (i.e. knowledge representation). Ma

Konrad Jałowiecki, Paulina Lewandowska, Łukasz Pawela

We introduce PyQBench, an innovative open-source framework for benchmarking gate-based quantum computers. PyQBench can benchmark NISQ devices by verifying their capability of discriminating between two von Neumann measurements. PyQBench offers a simplified, ready-to-use, command line interface (CLI) for running benchmarks using a predefined parametrized Four

Marcus DuPont, Andrew MacFadyen, Re'em Sari

Synchrotron and inverse Compton emission successfully explain the observed spectra of gamma-ray burst (GRB) afterglows. It is thought that most GRBs are products of extremely relativistic outflows and the afterglow marks the interaction of that ejecta with the surrounding matter. Faster decay of afterglow light curves at late times is indicative of non-spher

Dolev Bashi, Tsevi Mazeh, Simchon Faigler

Previous studies pointed out that many observed samples of short-period binaries display a cutoff period, $P_{\rm cut}$, such that almost all binaries with periods shorter than $P_{\rm cut}$ have circular orbits. This feature is probably due to long-term circularization processes induced by tidal interaction between the two stars of each binary. It seemed as

P. A. Palicio, E. Spitoni, A. Recio-Blanco, F. Matteucci

Context: In the last years, a significant number of works have focused on finding analytic solutions for the chemical enrichment models of galactic systems, including the Milky Way. Some of these solutions, however, cannot account for the enrichment produced by Type Ia SNe due to the presence of the delay time distributions (DTDs) in the models. Aims: We pre

S. Kovalenko, A. S. de Jesus, A. R. Zerwekh, Y. M. Oviedo-Torres

The Standard Model (SM) has no flavor-changing neutral current (FCNC) processes at the tree level. Therefore, processes featuring FCNC in new physics are tightly constrained by data. Typically, the lower bounds on the scale of new physics obtained from $K-\bar{K}$ or $B-\bar{B}$ mixing lie well above 10 TeV, surpassing the reach of current and future collide

Fan Deng, Xiaoming Tao, Pengxiang Wei, Shiyin Wei

Data-driven method for Structural Health Monitoring (SHM), that mine the hidden structural performance from the correlations among monitored time series data, has received widely concerns recently. However, missing data significantly impacts the conduction of this method. Missing data is a frequently encountered issue in time series data in SHM and many othe

Tapas Kumar Pal, Arnob Ray, Sayantan Nag Chowdhury, Dibakar Ghosh

Since Galileo's time, the pendulum has evolved into one of the most exciting physical objects in mathematical modeling due to its vast range of applications for studying various oscillatory dynamics, including bifurcations and chaos, under various interests. This well-deserved focus aids in comprehending various oscillatory physical phenomena that can be red

A. L. Cherchiglia, G. De Conto, C. C. Nishi

One simple way to lower the scale of the seesaw mechanism that generates neutrino masses is to attribute part of their smallness to a suppressed vacuum expectation value of a second Higgs doublet as in the neutrinophilic 2HDM or in the type IB seesaw model. On that structure we add one charged singlet scalar to induce a chirally enhanced contribution to $(g-

Louise Breuval, Adam G. Riess, Lucas M. Macri, Siyang Li

We present a low-dispersion period-luminosity relation (PL) based on 154 Cepheids in Messier 33 (M33) with Hubble Space Telescope (HST) photometry from the PHATTER survey. Using high-quality ground-based light curves, we recover Cepheid phases and amplitudes for multi-epoch HST data and we perform template fitting to derive intensity-averaged mean magnitudes

E. Parlanti, S. Carniani, A. Pallottini, M. Cignoni

High-redshift galaxies are expected to be more turbulent than local galaxies because of their smaller size and higher star formation and thus stronger feedback from star formation, frequent mergers events, and gravitational instabilities. However, this scenario has recently been questioned by the observational evidence of a few galaxies at z~4-5 with a gas v

Darcy A. Newmark, Austin Schneider

We explore a novel method for measuring the average temperature of the $\nu_x$ component in Type-II core-collapse supernovae. By measuring neutral current incoherent neutrino-Argon interactions in DUNE we can obtain spectral information for the combination of all active neutrino species. Combining this all-neutrino spectral information with detailed charged

Ting-Tung Wang, Zi Yang Meng

It is expected that the Gross-Neveu-Yukawa (GNY) chiral Ising transition of $N$ Majorana (or $N_f=N/4$ four-component Dirac) fermions coupled with scalar field in (2+1)D will be the first fermionic quantum critical point that various methods such as conformal bootstrap [1], perturbative renormalization group [2] and quantum Monte Carlo (QMC) simulations [3],

M. C. Rodriguez, Ignacio F. Ranea-Sandoval, C. Chirenti, D. Radice

The future detection of gravitational waves (GWs) from a galactic core-collapse supernova will provide information on the physics inside protoneutron stars (PNS). In this work, we apply three different classification methods for the PNS non-radial oscillation modes: Cowling classification, Generalized Cowling Nomenclature (GCN), and a Classification Based on

Anja Butter, Michael Krämer, Silvia Manconi, Kathrin Nippel

About a third of the $\gamma$-ray sources detected by the Fermi Large Area Telescope (Fermi-LAT) remain unidentified, and some of these could be exotic objects such as dark matter subhalos. We present a search for these sources using Bayesian neural network classification methods applied to the latest 4FGL-DR3 Fermi-LAT catalog. We first simulate the $\gamma

J. Sebastian Pineda, Jackie Villadsen

Observing magnetic star-planet interactions (SPI) offers promise for determining magnetic fields of exoplanets. Models of sub-Alfv\'enic SPI predict that terrestrial planets in close-in orbits around M~dwarfs can induce detectable stellar radio emission, manifesting as bursts of strongly polarized coherent radiation observable at specific planet orbital posi

A. A. Burkov, Michael Smith, Alexander Hickey, Ivar Martin

Weyl fermions possess the property of spin-momentum locking: the expectation value of the spin is parallel or antiparallel to the momentum at any given point in the Brillouin zone in the vicinity of a Weyl node. This is a direct consequence of the fact that Weyl nodes are monopoles of the Berry curvature, and in this sense an expression of the nontrivial Wey

Luigi Bellafronte, Sally Dawson, Pier Paolo Giardino

Effective field theory tools are essential for exploring non-Standard Model physics at the LHC in the absence of the discovery of new light particles. Predictions for observables are typically made at the lowest order in the QCD and electroweak expansions in the Standard Model effective field theory (SMEFT) and often ignore the effects of flavor. Here, we pr

Hao Song, Nathanan Tantivasadakarn, Wilbur Shirley, Michael Hermele

Fracton order describes novel quantum phases of matter that host quasiparticles with restricted mobility, and thus lies beyond the existing paradigm of topological order. In particular, excitations that cannot move without creating multiple excitations are called fractons. Here we address a fundamental open question -- can the notion of self-exchange statist

Hamza Ahmed, Fabian Ruehle

We study the complex structure moduli dependence of the scalar Laplacian eigenmodes for one-parameter families of Calabi-Yau $n$-folds in P^{n+1}. It was previously observed that some eigenmodes get lighter while others get heavier as a function of these moduli, which leads to eigenvalue crossing. We identify the cause for this behavior for the torus. We the

Naoto Inoue, Kotaro Kikuchi, Edgar Simo-Serra, Mayu Otani

Creative workflows for generating graphical documents involve complex inter-related tasks, such as aligning elements, choosing appropriate fonts, or employing aesthetically harmonious colors. In this work, we attempt at building a holistic model that can jointly solve many different design tasks. Our model, which we denote by FlexDM, treats vector graphic do

Xiao Zhou, Yujie Zhong, Zhen Cheng, Fan Liang

Object re-identification (ReID) aims to find instances with the same identity as the given probe from a large gallery. Pairwise losses play an important role in training a strong ReID network. Existing pairwise losses densely exploit each instance as an anchor and sample its triplets in a mini-batch. This dense sampling mechanism inevitably introduces positi

Shashank Tripathi, Lea Müller, Chun-Hao P. Huang, Omid Taheri

Estimating 3D humans from images often produces implausible bodies that lean, float, or penetrate the floor. Such methods ignore the fact that bodies are typically supported by the scene. A physics engine can be used to enforce physical plausibility, but these are not differentiable, rely on unrealistic proxy bodies, and are difficult to integrate into exist

Natalia Osorio-Clavijo, Omaira González-Martín, Sebastián F. Sánchez-Sánchez, Matteo Guainazzi

A complete demographic of active galactic nuclei (AGN) is essential to understand the evolution of the Universe. Optical surveys estimate the population of AGN in the local Universe to be of $\sim$ 4%. However, these results could be biased towards bright sources, not affected by the host galaxy attenuation. An alternative method for detecting these objects

Andrea Valassi, Taylor Childers, Laurence Field, Stephan Hageböck

The matrix element (ME) calculation in any Monte Carlo physics event generator is an ideal fit for implementing data parallelism with lockstep processing on GPUs and vector CPUs. For complex physics processes where the ME calculation is the computational bottleneck of event generation workflows, this can lead to large overall speedups by efficiently exploiti

Yu Jia, Jia-Yue Zhang

We investigate the soft behavior of the tree-level Rutherford scattering process. We consider two types of Rutherford scattering, a low-energy massless point-like projectile (say, a spin-${1\over 2}$ or spin-$0$ electron) to hit a static massive composite target particle carrying various spins (up to spin-$2$), and a slowly-moving light projectile hits a hea

Sam Bond-Taylor, Chris G. Willcocks

This paper introduces $\infty$-Diff, a generative diffusion model defined in an infinite-dimensional Hilbert space, which can model infinite resolution data. By training on randomly sampled subsets of coordinates and denoising content only at those locations, we learn a continuous function for arbitrary resolution sampling. Unlike prior neural field-based in

Muyuan Chen, Michael F. Schmid, Wah Chiu

Cryogenic electron microscopy is widely used in structural biology, but its resolution is often limited by the dynamics of the macromolecule. Here, we developed a refinement protocol based on Gaussian mixture models that integrates particle orientation and conformation estimation, and improves the alignment for flexible domains of protein structures. We demo

Arjun Majumdar, Karmesh Yadav, Sergio Arnaud, Yecheng Jason Ma

We present the largest and most comprehensive empirical study of pre-trained visual representations (PVRs) or visual 'foundation models' for Embodied AI. First, we curate CortexBench, consisting of 17 different tasks spanning locomotion, navigation, dexterous, and mobile manipulation. Next, we systematically evaluate existing PVRs and find that none are univ

Mohamed Mehdaoui

This paper provides a first attempt to incorporate the massive discontinuous changes in the spatio-temporal dynamics of epidemics. Namely, we propose an extended class of epidemic models, governed by coupled stochastic semilinear partial differential equations, driven by pure-jump L\'evy noise. Based on the considered type of incidence functions, by virtue o

Suad Krilašević, Sergio Grammatico

We present a singular perturbation theory applicable to systems with hybrid boundary layer systems and hybrid reduced systems {with} jumps from the boundary layer manifold. First, we prove practical attractivity of an adequate attractor set for small enough tuning parameters and sufficiently long time between almost all jumps. Second, under mild conditions o

Miguel Fernandez-Cortizas, Martin Molina, Pedro Arias-Perez, Rafael Perez-Segui

The development of autonomous aerial systems, particularly for multi-robot configurations, is a complex challenge requiring multidisciplinary expertise. Unlike ground robotics, aerial robotics has seen limited standardization, leading to fragmented development efforts. To address this gap, we introduce Aerostack2, a comprehensive, open-source ROS 2 based fra

J. Kluson, B. Matous

We find covariant canonical formalism for Weyl invariant gravity. We discuss constraint structure of this theory and its gauge fixed form.

Jérôme R. Simons

We generalise the inference procedure for eigenvectors of symmetrizable matrices of Tyler (1981) to that of invariant and singular subspaces of non-diagonalizable matrices. Wald tests for invariant vectors and $t$-tests for their individual coefficients perform well in simulations, despite the matrix being not symmetric. Using these results, it is now possib

Ximeng Sun, Pengchuan Zhang, Peizhao Zhang, Hardik Shah

Large Vision-Language Foundation Models (VLFM), such as CLIP, ALIGN and Florence, are trained on large-scale datasets of image-caption pairs and achieve superior transferability and robustness on downstream tasks, but they are difficult to use in many practical applications due to their large size, high latency and fixed architectures. Unfortunately, recent

Iva Laginja, Raphaël Pourcelot

We revive a cross-platform focal-plane wavefront sensing and control algorithm originally released in 1980 and show that it can provide significant contrast improvements over conventional control methods on coronagraphic instruments. Its simplicity makes it applicable to various coronagraph models and we demonstrate it on a classical Lyot coronagraph and a p

Honglu Zhou, Roberto Martín-Martín, Mubbasir Kapadia, Silvio Savarese

Our goal is to learn a video representation that is useful for downstream procedure understanding tasks in instructional videos. Due to the small amount of available annotations, a key challenge in procedure understanding is to be able to extract from unlabeled videos the procedural knowledge such as the identity of the task (e.g., 'make latte'), its steps (

David A. Simon, Michele Cappellari, Johanna Hartke

The massive elliptical galaxy M87 has been the subject of several supermassive black hole mass measurements from stellar dynamics, gas dynamics, and recently the black hole shadow by the Event Horizon Telescope (EHT). This uniquely positions M87 as a benchmark for alternative black hole mass determination methods. Here we use stellar kinematics extracted fro

David Lindemann, Andrew Swann

We classify hyperbolic polynomials in two real variables that admit a transitive action on some component of their hyperbolic level sets. Such surfaces are called special homogeneous surfaces, and they are equipped with a natural Riemannian metric obtained by restricting the negative Hessian of their defining polynomial. Independent of the degree of the poly

Casey Brinkman, Keyan Gootkin, Rena A. Lee, Grey Murphree

We observe neither life beyond Earth, nor moons around exoplanets, despite the prevalence of Earth-like planets across the galaxy. We suggest Moonfall as a possible mechanism to explain both simultaneously.

Julian Togelius, Georgios N. Yannakakis

Are you an AI researcher at an academic institution? Are you anxious you are not coping with the current pace of AI advancements? Do you feel you have no (or very limited) access to the computational and human resources required for an AI research breakthrough? You are not alone; we feel the same way. A growing number of AI academics can no longer find the m

Andrea Failla, Salvatore Citraro, Giulio Rossetti

Recent advances in network science have resulted in two distinct research directions aimed at augmenting and enhancing representations for complex networks. The first direction, that of high-order modeling, aims to focus on connectivity between sets of nodes rather than pairs, whereas the second one, that of feature-rich augmentation, incorporates into a net

Meng-Na Tang, Yong-Hui Lin, Feng-Kun Guo, Christoph Hanhart

The internal structure of the charm-strange mesons $D_{s0}^*(2317)$ and $D_{s1}(2460)$ are subject of intensive studies. Their widths are small because they decay dominantly through isospin-breaking hadronic channels $D_{s0}^*(2317)^+\to D_s^+\pi^0$ and $D_{s1}(2460)^+\to D_s^{*+}\pi^0$. The $D_{s1}(2460)$ can also decay into the hadronic final states $D_s^+

Chi-Fang Chen, Michael J. Kastoryano, Fernando G. S. L. Brandão, András Gilyén

Preparing ground states and thermal states is essential for simulating quantum systems on quantum computers. Despite the hope for practical quantum advantage in quantum simulation, popular state preparation approaches have been challenged. Monte Carlo-style quantum Gibbs samplers have emerged as an alternative, but prior proposals have been unsatisfactory du

Akifumi Kira, Nobuo Terajima, Yasuhiko Watanabe, Hirotaka Yamamoto

The logistics industry in Japan is facing a severe shortage of labor. Therefore, there is an increasing need for joint transportation allowing large amounts of cargo to be transported using fewer trucks. In recent years, the use of artificial intelligence and other new technologies has gained wide attention for improving matching efficiency. However, it is d

Mohamed-Amine Chadi, Hajar Mousannif

This paper presents a review of the field of reinforcement learning (RL), with a focus on providing a comprehensive overview of the key concepts, techniques, and algorithms for beginners. RL has a unique setting, jargon, and mathematics that can be intimidating for those new to the field or artificial intelligence more broadly. While many papers review RL in

Jakob Robnik, Uroš Seljak

Stochastic sampling algorithms such as Langevin Monte Carlo are inspired by physical systems in a heat bath. Their equilibrium distribution is the canonical ensemble given by a prescribed target distribution, so they must balance fluctuation and dissipation as dictated by the fluctuation-dissipation theorem. In contrast to the common belief, we show that the

Ke-Hui Yu, Xiao-Yang Jiao, Li-Jing Jin

We developed an inductive energy participation ratio (IEPR) method and a streamlined procedure for simulating and verifying superconducting quantum chips. These advancements are increasingly vital in the context of large-scale, fault-tolerant quantum computing. Our approach efficiently extracts the key linear and nonlinear characteristic parameters, as well

Shan Lin, Yuheng Zhi, Michael C. Yip

Without ground truth supervision, self-supervised depth estimation can be trapped in a local minimum due to the gradient-locality issue of the photometric loss. In this paper, we present a framework to enhance depth by leveraging semantic segmentation to guide the network to jump out of the local minimum. Prior works have proposed to share encoders between t

Peter Sziklai, Zsuzsa Weiner

In this paper we discuss a result similar to the polynomial version of the Alon-F\"uredi theorem. We prove that if you want to cover the vertices of the $n$-dimensional unit cube, except those of weight at most $r$ then you need an algebraic surface of degree at least $n-r$.

Jason T. Wright

I solve the problem of nomenclature of planets, stars, and moons, and in doing so repair two of the IAU's blunders. Drawing and improving upon foundational work by Chen & Kipping, I describe a single, physics-based taxonomy that christens all objects in hydrostatic equilibrium as "stars," a category that contains several subcategories based on the relevant p

Tomasz Krajewski, Marek Lewicki, Mateusz Zych

Terminal velocity reached by bubble walls in first order phase transitions is an important parameter determining both primordial gravitational-wave spectrum and production of baryon asymmetry in models of electroweak baryogenesis. We developed a numerical code to study the real-time evolution of expanding bubbles and investigate how their walls reach station

Riccardo Bellan, Saptaparna Bhattacharya, Giacomo Boldrini, Flavia Cetorelli

We present the first parton-level study of anomalous effects in triboson production in both fully and semi-leptonic channels in proton-proton collisions at 13 TeV at the Large Hadron Collider (LHC). The sensitivity to anomalies induced by a minimal set of bosonic dimension-6 operators from the Warsaw basis is evaluated with specific analyses for each final s

Ilya V. Kuzichev, Ivan Y. Vasko, Anton V. Artemyev, Stuart D. Bale

Spacecraft observations showed that electron heat conduction in the solar wind is probably regulated by whistler waves, whose origin and efficiency in electron heat flux suppression is actively investigated. In this paper, we present Particle-In-Cell simulations of a combined whistler heat flux and temperature anisotropy instability that can operate in the s

Philipp Nacke, Florian Otterpohl, Michael Thorwart, Peter Nalbach

Dephasing in quantum systems is typically the result of its interaction with environmental degrees of freedom. We investigate within a spin-boson model the influence of a super-Ohmic environment on the dynamics of a quantum two-state system. A super-Ohmic enviroment, thereby, models typical bulk phonons which are a common disturbance for solid state quantum

A. Hijano, F. S. Bergeret, F. Giazotto, A. Braggio

Recent studies have shown the potential for bipolar thermoelectricity in superconducting tunnel junctions with asymmetric energy gaps. The thermoelectric performance of these systems is significantly impacted by the inverse proximity effects present in the normal-superconducting bilayer, which is utilized to adjust the gap asymmetry in the junction. Here, we

Alexander G. Reisach, Myriam Tami, Christof Seiler, Antoine Chambaz

Additive Noise Models (ANMs) are a common model class for causal discovery from observational data and are often used to generate synthetic data for causal discovery benchmarking. Specifying an ANM requires choosing all parameters, including those not fixed by explicit assumptions. Reisach et al. (2021) show that sorting variables by increasing variance ofte

Chuangguan Ye, Hongyuan Zhu, Bo Zhang, Tao Chen

In recent years, research on few-shot learning (FSL) has been fast-growing in the 2D image domain due to the less requirement for labeled training data and greater generalization for novel classes. However, its application in 3D point cloud data is relatively under-explored. Not only need to distinguish unseen classes as in the 2D domain, 3D FSL is more chal

Federico Celi, Giacomo Baggio, Fabio Pasqualetti

This paper presents a novel approach for solving the pole placement and eigenstructure assignment problems through data-driven methods. By using open-loop data alone, the paper shows that it is possible to characterize the allowable eigenvector subspaces, as well as the set of feedback gains that solve the pole placement problem. Additionally, the paper prop

Anton Iliashenko

In this paper we use the Weitzenb\"ock formulas to get information about the Betti numbers of compact nearly $G_2$ and compact nearly K\"{a}hler $6$-manifolds. First, we establish estimates on two curvature-type self adjoint operators on particular spaces assuming bounds on the sectional curvature. Then using the Weitzenb\"ock formulas on harmonic forms, we

Maximilian Reichert, Quntao Zhuang, Jeffrey H. Shapiro, Roberto Di Candia

We propose a hetero-homodyne receiver for quantum illumination (QI) target detection. Unlike prior QI receivers, it uses a cascaded positive operator-valued measurement (POVM) that does not require a quantum interaction between QI's returned radiation and its stored idler. When used without sequential detection its performance matches the 3 dB quantum advant

Jacopo Angeletti, Haowei Shi, Theerthagiri Lakshmanan, David Vitali

Entanglement is vulnerable to degradation in a noisy sensing scenario, but surprisingly, the quantum illumination protocol has demonstrated that its advantage can survive. However, designing a measurement system that realizes this advantage is challenging since the information is hidden in the weak correlation embedded in the noise at the receiver side. Rece

Xiaochen Zheng, Xingyu Chen, Manuel Schürch, Amina Mollaysa

Contrastive learning methods have shown an impressive ability to learn meaningful representations for image or time series classification. However, these methods are less effective for time series forecasting, as optimization of instance discrimination is not directly applicable to predicting the future state from the historical context. To address these lim

Jonathan Utterson, Radek Erban

Considering interatomic potential $U({\mathbf q})$ where ${\mathbf q} = [{\mathbf q}_1, {\mathbf q}_2, \dots, {\mathbf q}_N] \in {\mathbb R}^{3N}$ is a vector describing positions, $\mathbf{q}_i \in {\mathbb R}^3$, it is shown that $U$ can be defined as a function of the interatomic distance variables $r_{ij} = |{\mathbf q}_i - {\mathbf q}_j |$, provided tha

Deyan P. Mihaylov, Serguei Ossokine, Alessandra Buonanno, Hector Estelles

We present pySEOBNR, a Python package for gravitational-wave (GW) modeling developed within the effective-one-body (EOB) formalism. The package contains an extensive framework to generate state-of-the-art inspiral-merger-ringdown waveform models for compact-object binaries composed of black holes and neutron stars. We document and demonstrate how to use the

Sergio A. Ortega, Miguel A. Martin-Delgado

Quantum walks are promising tools based on classical random walks, with plenty of applications such as many variants of optimization. Here we introduce the semiclassical walks in discrete time, which are algorithms that combines classical and quantum dynamics. Specifically, a semiclassical walk can be understood as a classical walk where the transition matri

Ovidiu Racorean

Recent works suggest that quantum theory may support a unification of the notions of space and time, thus treating the spatial and temporal quantum correlations equally. Specifically, the partial transposition of the maximally entangled state of two quantum systems at one time exactly matches the temporal quantum correlations of one quantum system that evolv