May 2023 arXiv papers — page 154

Mohamed Abid, Arman Afrasiyabi, Ihsen Hedhli, Jean-François Lalonde

Generally, image-to-image translation (i2i) methods aim at learning mappings across domains with the assumption that the images used for translation share content (e.g., pose) but have their own domain-specific information (a.k.a. style). Conditioned on a target image, such methods extract the target style and combine it with the source image content, keepin

Alex Cohen

We prove that if a fractal set in $\mathbb{R}^d$ avoids lines in a certain quantitative sense, which we call line porosity, then it has a fractal uncertainty principle. The main ingredient is a new higher dimensional Beurling-Malliavin multiplier theorem.

Waltraut Wustmann, Kevin Daniel Osborn

Superconducting logic is fast and energy-efficient relative to CMOS, but also fundamental studies are needed to scale up circuits for greater utility. Recently, ballistic shift registers for single-flux quanta (SFQ) bits were shown in simulation to allow high-efficiency superconducting gates. However, these gates are unpowered such that the bits slow after e

William Herzberg, Andreas Hauptmann, Sarah J. Hamilton

Reconstruction of tomographic images from boundary measurements requires flexibility with respect to target domains. For instance, when the system equations are modeled by partial differential equations the reconstruction is usually done on finite element (FE) meshes, allowing for flexible geometries. Thus, any processing of the obtained reconstructions shou

Sagar Silva Pratapsi, Lorenzo Buffoni, Stefano Gherardini

Quantum computers are operated by external driving fields, such as lasers, microwaves or transmission lines, that execute logical operations on multi-qubit registers, leaving the system in a pure state. However, the drive and the logical system might become correlated in such a way that, after tracing out the degrees of freedom of the driving field, the outp

Maria Beatrice Pozzetti, Konstantinos Tsouvalas

We prove that a word hyperbolic group whose Gromov boundary properly contains a $2$-sphere cannot admit a projective Anosov representation into $\mathsf{Sp}_{2m}(\mathbb{C})$, $m\in \mathbb{N}$. We also prove that a word hyperbolic group which admits a projective Anosov representation into $\mathsf{Sp}_{2m}(\mathbb{R})$ is virtually a free group or virtually

Soumik Mohian, Christoph Csallner

Locating a specific mobile application screen from existing repositories is restricted to basic keyword searches, such as Google Image Search, or necessitates a complete query screen image, as in the case of Swire. However, interactive partial sketch-based solutions like PSDoodle have limitations, including inaccuracy and an inability to consider text appear

Woojung Bae, Michael J. Daniels, Michael G. Perri

We propose a new Bayesian non-parametric (BNP) method for estimating the causal effects of mediation in the presence of a post-treatment confounder. We specify an enriched Dirichlet process mixture (EDPM) to model the joint distribution of the observed data (outcome, mediator, post-treatment confounders, treatment, and baseline confounders). The proposed BNP

Uladzimir Khasianevich, Dominik Stöckinger, Hyejung Stöckinger-Kim, Johannes Wünsche

We consider the full flavor structure of the $S_1$ leptoquark model and derive conservative constraints on the elements of the left- and right-handed coupling matrices. We focus on the cases where the muon $g-2$ deviation is explained by muon couplings to the top-quark or to the charm-quark or to all up-type quarks. The most significant constraints arise fro

Qinan Wang, Anika Goel, Luc Dessart, Ori D. Fox

A growing number of supernovae (SNe) are now known to exhibit evidence for significant interaction with a dense, pre-existing, circumstellar medium (CSM). SNe Ibn comprise one such class that can be characterised by both rapidly evolving light curves and persistent narrow He I lines. The origin of such a dense CSM in these systems remains a pressing question

Nicolas Zilberstein, Ashutosh Sabharwal, Santiago Segarra

We propose a solution for linear inverse problems based on higher-order Langevin diffusion. More precisely, we propose pre-conditioned second-order and third-order Langevin dynamics that provably sample from the posterior distribution of our unknown variables of interest while being computationally more efficient than their first-order counterpart and the no

Matteo Nerini, Shanpu Shen, Hongyu Li, Bruno Clerckx

Recently, beyond diagonal reconfigurable intelligent surface (BD-RIS) has been proposed to generalize conventional RIS. BD-RIS has a scattering matrix that is not restricted to being diagonal and thus brings a performance improvement over conventional RIS. While different BD-RIS architectures have been proposed, it still remains an open problem to develop a

A. T. Bajkova, A. A. Smirnov, V. V. Bobylev

The work is devoted to the analysis of the influence of the galactic bar on the orbital motion of globular clusters in the central region of the Galaxy. For this task, 45 globular clusters were selected, 34 of which belong to the bulge/bar and 11 to the disk. The most accurate astrometric data from the Gaia satellite (Vasiliev and Baumgardt, 2021), as well a

Stephen Gismondi

This is a tribute to my dear life-long friend, mentor and colleague Ted Swart. It includes anecdotal stories and memories of our times together, and also includes a new academic contribution in his honour, Teds polytope. Tweeks made to the Birkhoff polytope Bn endow Teds polytope Tn({\epsilon}) with a special tunable parameter {\epsilon} = {\epsilon}(n). Obs

Rongzhi Zhang, Jiaming Shen, Tianqi Liu, Jialu Liu

Knowledge distillation is a popular technique to transfer knowledge from large teacher models to a small student model. Typically, the student learns to imitate the teacher by minimizing the KL divergence of its output distribution with the teacher's output distribution. In this work, we argue that such a learning objective is sub-optimal because there exist

Jong Gwang Kim

We introduce a new form of Lagrangian and propose a simple first-order algorithm for nonconvex optimization with nonlinear equality constraints. We show the algorithm generates bounded dual iterates, and establish the convergence to KKT points under standard assumptions. The key features of the method are: (i) it does not require boundedness assumptions on t

Fabio Benatti, Francesca Gebbia, Stefano Pisoni

We discuss the generation and the long-time persistence of entanglement in open two-qubit systems whose reduced dissipative dynamics is not apriori engineered but is instead subjected to filtering and Markovian feedback. In particular, we analytically study 1.) whether the latter operations may enhance the environment capability of generating entanglement at

Denis D. Patterson, Simon A. Levin, A. Carla Staver, Jonathan D. Touboul

Spatial systems with heterogeneities are ubiquitous in nature, from precipitation, temperature and soil gradients controlling vegetation growth to morphogen gradients controlling gene expression in embryos. Such systems, generally described by nonlinear dynamical systems, often display complex parameter dependence and exhibit bifurcations. The dynamics of he

Srijay Deshpande, Fayyaz Minhas, Nasir Rajpoot

Generating realistic tissue images with annotations is a challenging task that is important in many computational histopathology applications. Synthetically generated images and annotations are valuable for training and evaluating algorithms in this domain. To address this, we propose an interactive framework generating pairs of realistic colorectal cancer h

Ryan Hardesty Lewis, Junfeng Jiao

Language models are not accurate in numerical problems. Their architecture does not allow for anything less than a probabilistic next word. This paper introduces ComputeGPT: an approach of creating a chat model able to answer computational problems through running on-demand code. ComputeGPT converts each question to relevant code, runs the code, and returns

Wenxiang Ying, Michael A. D. Taylor, Pengfei Huo

We present a microscopic theory that aims to explain the vibrational strong coupling (VSC) modified reaction rate constant. The analytic theory is based on a mechanistic conjecture that cavity modes promote the transition from the ground state to the vibrational excited state of the reactant, which is the rate-limiting step of the reaction. The theory explai

Ayako A. Hasegawa, Daisuke Inoue, Mitsuaki Akiyama

In human factor fields such as human-computer interaction (HCI) and psychology, researchers have been concerned that participants mostly come from WEIRD (Western, Educated, Industrialized, Rich, and Democratic) countries. This WEIRD skew may hinder understanding of diverse populations and their cultural differences. The usable privacy and security (UPS) fiel

Somin Wadhwa, Silvio Amir, Byron C. Wallace

Relation extraction (RE) is the core NLP task of inferring semantic relationships between entities from text. Standard supervised RE techniques entail training modules to tag tokens comprising entity spans and then predict the relationship between them. Recent work has instead treated the problem as a \emph{sequence-to-sequence} task, linearizing relations b

Benjamin J. B. Deutschmann, Maximilian Graber, Thomas Wilding, Klaus Witrisal

Geometric environment information aids future distributed radio infrastructures in providing services, such as ultra-reliable communication, positioning, and wireless power transfer (WPT). An a priori known environment model cannot always be assumed in practice. This paper investigates the capabilities of detecting specularly reflecting surfaces in a bistati

Xiangru Tang, Andrew Tran, Jeffrey Tan, Mark Gerstein

This paper presents our contribution to the MEDIQA-2023 Dialogue2Note shared task, encompassing both subtask A and subtask B. We approach the task as a dialogue summarization problem and implement two distinct pipelines: (a) a fine-tuning of a pre-trained dialogue summarization model and GPT-3, and (b) few-shot in-context learning (ICL) using a large languag

Giovanni Molica Bisci, Alejandro Ortega, Luca Vilasi

In this paper, by variational and topological arguments based on linking and $\nabla$-theorems, we prove the existence of multiple solutions for the following nonlocal problem with mixed Dirichlet-Neumann boundary data, $$ \left\{ \begin{array}{lcl} (-\Delta)^su=\lambda u+f(x,u) & &\text{in } \Omega, \\[2pt] \mkern+39mu u=0& &\text{on } \Sigma_{\mathcal{D}},

Luis M. Briceño-Arias, Cristóbal Vivar-Vargas

In this paper we provide an explicit expression for the proximity operator of a perspective of any proper lower semicontinuous convex function defined on a Hilbert space. Our computation enhances and generalizes known formulae for the case when the Fenchel conjugate of the convex function has open domain or when it is radial. We provide several examples of n

Joanna Jureczko

We prove under ZFC that in each extremally disconnected compact space there exists a non-limit point of any countable discrete subset.

Joanna Jureczko

The main result of this paper is to show that for any compact space $X$ and any family $\{f_\alpha \colon \alpha< 2^\kappa, f_\alpha \colon X \stackrel{onto}{\longrightarrow} \beta \kappa\}$ of open mappings there exists a point $x \in X$ such that for each $\alpha< 2^\kappa$ either $f_\alpha(x)$ belongs to $\kappa$ or $f_\alpha(x)$ is a weak $P_\kappa$-poin

Shmuel Balberg, Gilad Yassur

Centers of galaxies host both a supermassive black hole and a dense stellar cluster. Such an environment should lead to stellar collisions, possibly at very high velocities so that the total energy involved is of the same order as supernovae explosions. We present a simplified numerical analysis of the destructive stellar collision rate in a cluster similar

Zihan Miao, Anh Nguyen, Tian An Wong

We prove a first Kronecker limit formula for cofinite discrete subgroups of SL$(2,\mathbb{C})$, also called Kleinian groups, generalizing a method of Goldstein over SL$(2,\mathbb R)$. The proof uses the Fourier expansion of Eisenstein series, leading to an analogue of the logarithm of the Dedekind eta function, and whose transformation law produces a functio

Seunghwan Lee, Yifeng Jiang, C. Karen Liu

Existing digital human models approximate the human skeletal system using rigid bodies connected by rotational joints. While the simplification is considered acceptable for legs and arms, it significantly lacks fidelity to model rich torso movements in common activities such as dancing, Yoga, and various sports. Research from biomechanics provides more detai

Momchil Yordanov, Raphael d'Andrimont, Laura Martinez-Sanchez, Guido Lemoine

Crop classification via deep learning on ground imagery can deliver timely and accurate crop-specific information to various stakeholders. Dedicated ground-based image acquisition exercises can help to collect data in data scarce regions, improve control on timing of collection, or when study areas are to small to monitor via satellite. Automatic labelling i

Eliana Rodrigues, Emerson de Melo, Gülin Ercan

Let $F$ be a nilpotent group acted on by a group $H$ via automorphisms and let the group $G$ admit the semidirect product $FH$ as a group of automorphisms so that $C_G(F) = 1$. We prove that the order of $\gamma_\infty(G)$, the rank of $\gamma_\infty(G)$ are bounded in terms of the orders of $\gamma_{\infty}(C_G(H))$ and $H$, the rank of $\gamma_{\infty}(C_G

Tsvetan R. Yordanov, Ameen Abu-Hanna, Anita CJ Ravelli, Iacopo Vagliano

Availability of diagnostic codes in Electronic Health Records (EHRs) is crucial for patient care as well as reimbursement purposes. However, entering them in the EHR is tedious, and some clinical codes may be overlooked. Given an in-complete list of clinical codes, we investigate the performance of ML methods on predicting the complete ones, and assess the a

B. Riaz, W. -F. Thi, M. N. Machida

We present results from the first molecular line survey to search for the fundamental complex organic molecule, methanol (CH$_{3}$OH), in 14 Class 0/I proto-brown dwarfs (proto-BDs). IRAM 30-m observations over the frequency range of 92-116 GHz and 213-280 GHz have revealed emission in 14 CH$_{3}$OH transition lines, at upper state energy level, E$_{upper}\s

Josh Magnus Ludan, Yixuan Meng, Tai Nguyen, Saurabh Shah

Large Language Models (LLMs) are so powerful that they sometimes learn correlations between labels and features that are irrelevant to the task, leading to poor generalization on out-of-distribution data. We propose explanation-based finetuning as a general approach to mitigate LLMs' reliance on spurious correlations. Unlike standard finetuning where the mod

Kaushik Roy, Tarun Garg, Vedant Palit, Yuxin Zi

A fundamental question in natural language processing is - what kind of language structure and semantics is the language model capturing? Graph formats such as knowledge graphs are easy to evaluate as they explicitly express language semantics and structure. This study evaluates the semantics encoded in the self-attention transformers by leveraging explicit

Arumoy Shome, Luis Cruz, Arie van Deursen

Visualisations drive all aspects of the Machine Learning (ML) Development Cycle but remain a vastly untapped resource by the research community. ML testing is a highly interactive and cognitive process which demands a human-in-the-loop approach. Besides writing tests for the code base, bulk of the evaluation requires application of domain expertise to genera

Davide Gerosa, Matthew Mould

This short document illustrates QLUSTER: a toy model for populations of binary black holes in dense astrophysical environments. QLUSTER is a simple tool to investigate the occurrence and properties of hierarchical black-hole mergers detectable by gravitational-wave interferometers. QLUSTER is not meant to rival the complexity of state-of-the-art population s

Rylee Alanza Lyman

The main result of this paper is that the outer automorphism group of a free product of finite groups and cyclic groups is semistable at infinity (provided it is one ended) or semistable at each end. In a previous paper, we showed that the group of outer automorphisms of the free product of two nontrivial finite groups with an infinite cyclic group has infin

Hubert Etienne, François Charton

We combine philosophical theories with quantitative analyses of online data to propose a sophisticated approach to social media influencers. Identifying influencers as communication systems emerging from a dialectic interactional process between content creators and in-development audiences, we define them mainly using the composition of their audience and t

Osamu Fukushima, Ryusuke Hamazaki

We elucidate how the presence of higher-form symmetries affects the dynamics of thermalization in isolated quantum systems. Under reasonable assumptions, we analytically show that a $p$-form symmetry in a $(d+1)$-dimensional quantum field theory leads to the breakdown of the eigenstate thermalization hypothesis for many nontrivial $(d-p)$-dimensional observa

Eunice Yiu, Eliza Kosoy, Alison Gopnik

Much discussion about large language models and language-and-vision models has focused on whether these models are intelligent agents. We present an alternative perspective. We argue that these artificial intelligence models are cultural technologies that enhance cultural transmission in the modern world, and are efficient imitation engines. We explore what

Prashanth Amireddy, Srikanth Srinivasan, Madhu Sudan

We study the question of local testability of low (constant) degree functions from a product domain $S_1 \times \dots \times {S}_n$ to a field $\mathbb{F}$, where ${S_i} \subseteq \mathbb{F}$ can be arbitrary constant sized sets. We show that this family is locally testable when the grid is "symmetric". That is, if ${S_i} = {S}$ for all i, there is a probabi

M. Fabbrichesi, R. Floreanini, E. Gabrielli, L. Marzola

The violation of the Bell inequality is one of the hallmarks of quantum mechanics and can be used to rule out local deterministic alternative descriptions. We utilize the data analysis published by the LHCb collaboration on the helicity amplitudes for the decay $B^0\to J/\psi \,K^*(892)^0$ to compute the entanglement among the polarizations of the final vect

Mykola Makhortykh, Eve M. Zucker, David J. Simon, Daniel Bultmann

The memorialization of mass atrocities such as war crimes and genocides facilitates the remembrance of past suffering, honors those who resisted the perpetrators, and helps prevent the distortion of historical facts. Digital technologies have transformed memorialization practices by enabling less top-down and more creative approaches to remember mass atrocit

Scott Lucchini, Elena D'Onghia, J. Alfonso L. Aguerri

The distribution of moving groups in the solar neighborhood has been used to constrain dynamical properties of the Milky Way for decades. The kinematic bimodality between the main mode (Hyades, Pleiades, Coma Berenices, and Sirius) and Hercules can be explained by two different bar models -- via the outer Lindblad resonance of a bar with a high pattern speed

Hsiu-Chung Yeh, Achim Rosch, Aditi Mitra

The stability and dynamics of almost strong zero and $\pi$ modes in weakly non-integrable Floquet spin chains are investigated. Such modes can also be viewed as localized Majorana modes at the edge of a topological superconductor. Perturbation theory in the strength of integrability-breaking interaction $J_z$ is employed to estimate the decay rates of these

Minyoung Kim, Timothy Hospedales

We propose a novel hierarchical Bayesian approach to Federated Learning (FL), where our model reasonably describes the generative process of clients' local data via hierarchical Bayesian modeling: constituting random variables of local models for clients that are governed by a higher-level global variate. Interestingly, the variational inference in our Bayes

Phillip Howard, Junlin Wang, Vasudev Lal, Gadi Singer

Comparative knowledge (e.g., steel is stronger and heavier than styrofoam) is an essential component of our world knowledge, yet understudied in prior literature. In this paper, we harvest the dramatic improvements in knowledge capabilities of language models into a large-scale comparative knowledge base. While the ease of acquisition of such comparative kno

Philipp Johannes Schubert, Rangoli Saxena, Joergen Kornfeld

High-throughput 2D and 3D scanning electron microscopy, which relies on automation and dependable control algorithms, requires high image quality with minimal human intervention. Classical focus and astigmatism correction algorithms attempt to explicitly model image formation and subsequently aberration correction. Such models often require parameter adjustm

Ken Sekimoto

The martingale characterizes a kind of fairness or unbiased nature of the stochastic process which is associated with another stochastic process. If $x_t$ evolves according to the Langevin equation whose mean drift is $a_t$ as function of $x_t,$ and that $a_t$ as induced stochastic process is martingale in turn associated with the former process, then we sho

Jarle Sogn, Stefan Takacs

We consider the linearized elasticity equation, discretized with multi-patch Isogeometric Analysis. A standard discretization error analysis is based on Korn's inequality, which degrades for certain geometries, such as long and thin cantilevers. This phenomenon is known as geometry locking. We observe that high-order methods, like Isogeometric Analysis is be

Fabiola Fortuna, Xabier Marcano, Marcela Marín, Pablo Roig

We consider charged lepton flavor violating transitions mediated by the diphoton effective interactions $\ell_i\ell_j\gamma\gamma$ and explore which processes can probe them better. Our analysis includes single and double radiative decays, $\ell_i\to\ell_j\gamma(\gamma)$, as well as $\ell_i\to\ell_j$ conversions in nuclei for all possible flavor combinations

Dante Bigi, Sandro Mächler

We compute the effects of a finite $W$ boson mass on the inclusive $b\rightarrow c \ell \nu$ decay rate and the semileptonic moments. To this end we keep terms of $\mathcal{O}\left(q^2/m_W^2 \right)$ when integrating out the $W$ boson in the Weak Effective Theory. In the third hadronic invariant mass moment such corrections reach the $0.5\%$ level but they a

R. Rodrigues, T. Rodrigues, L. Campo-Deaño

The objective of this work is to characterise the onset of laterally asymmetric flow of viscoelastic solutions around a confined microfluidic cylinder, which was encountered in a recent study [Rodrigues et al., $\textit{J. Non-Newton. Fluid Mech.}$ $\textbf{289}$, 104406 (2020)]. To this end, two non-Newtonian fluids were employed in the same micro-geometry.

Peng Lu, Ahmad Rashid, Ivan Kobyzev, Mehdi Rezagholizadeh

Regularization techniques are crucial to improving the generalization performance and training efficiency of deep neural networks. Many deep learning algorithms rely on weight decay, dropout, batch/layer normalization to converge faster and generalize. Label Smoothing (LS) is another simple, versatile and efficient regularization which can be applied to vari

Marco de Cesare, Roberto Oliveri

We study the accretion of a Schwarzschild black hole due to spherically symmetric perturbations sourced by a minimally coupled massless scalar field. The backreaction of the black hole to low-frequency ingoing scalar waves is computed analytically as a second-order perturbative effect, using matched asymptotic expansions to relate the behaviour of the scalar

Han Yan, Xian Chen, Alejandro Torres-Orjuela

The possibility of forming gravitational-wave sources with high center-of-mass (c.m.) velocities in the vicinity of supermassive black holes requires us to develop a method of deriving the waveform in the observer's frame. Here we show that in the limit where the c.m. velocity is high but the relative velocities of the components of the source are small, we

Mikhail Al'perin, Alexander V. Osipov

In this paper, we have obtained a generalization of the Grothendieck's theorem for the space of continuous mappings $C_{\lambda,\mu}(X,Y)$ where $Y$ is a complete uniform space with the uniformity $\mu$ endowed with the topology of uniform convergence on the family $\lambda$ of subsets of $X$. A new topological game is defined - the Asanov-Velichko game, whi

Ashish Dhiman

Machine Learning has invariantly found its way into various Credit Risk applications. Due to the intrinsic nature of Credit Risk, quantifying the uncertainty of the predicted risk metrics is essential, and applying uncertainty-aware deep learning models to credit risk settings can be very helpful. In this work, we have explored the application of a scalable

Ruilong Li, Hang Gao, Matthew Tancik, Angjoo Kanazawa

Optimizing and rendering Neural Radiance Fields is computationally expensive due to the vast number of samples required by volume rendering. Recent works have included alternative sampling approaches to help accelerate their methods, however, they are often not the focus of the work. In this paper, we investigate and compare multiple sampling approaches and

Munan Gong, Ka-Wai Ho, James M. Stone, Eve C. Ostriker

Chemistry plays a key role in many aspects of astrophysical fluids. Atoms and molecules are agents for heating and cooling, determine the ionization fraction, serve as observational tracers, and build the molecular foundation of life. We present the implementation of a chemistry module in the publicly available magneto-hydrodynamic code Athena++. We implemen

Liron Barak, Itay M. Bloch, Ana M. Botti, Mariano Cababie

Millicharged particles appear in several extensions of the Standard Model, but have not yet been detected. These hypothetical particles could be produced by an intense proton beam striking a fixed target. We use data collected in 2020 by the SENSEI experiment in the MINOS cavern at the Fermi National Accelerator Laboratory to search for ultra-relativistic mi

Cai Zhou, Xiyuan Wang, Muhan Zhang

Relational pooling is a framework for building more expressive and permutation-invariant graph neural networks. However, there is limited understanding of the exact enhancement in the expressivity of RP and its connection with the Weisfeiler Lehman hierarchy. Starting from RP, we propose to explicitly assign labels to nodes as additional features to improve

Pau Batlle, Yifan Chen, Bamdad Hosseini, Houman Owhadi

We introduce a priori Sobolev-space error estimates for the solution of nonlinear, and possibly parametric, PDEs using Gaussian process and kernel based methods. The primary assumptions are: (1) a continuous embedding of the reproducing kernel Hilbert space of the kernel into a Sobolev space of sufficient regularity; and (2) the stability of the differential

Richard Luo, Austin Peng, Heidi Yap, Koby Beard

Video summarization has become an increasingly important task in the field of computer vision due to the vast amount of video content available on the internet. In this project, we propose a new method for natural language query based joint video summarization and highlight detection using multi-modal transformers. This approach will use both visual and audi

Jason P. Bell, Wade Hindes, Xiao Zhong

We improve known estimates for the number of points of bounded height in semigroup orbits of polarized dynamical systems. In particular, we give exact asymptotics for generic semigroups acting on the projective line. The main new ingredient is the Wiener-Ikehara Tauberian theorem, which we use to count functions in semigroups of bounded degree.

Tsang Keung Chan, Alejandro Benitez-Llambay, Tom Theuns, Carlos Frenk

An ionization front (I-front) that propagates through an inhomogeneous medium is slowed down by self-shielding and recombinations. We perform cosmological radiation hydrodynamics simulations of the I-front propagation during the epoch of cosmic reionization. The simulations resolve gas in minihalos (halo mass $10^4\lesssim M_h[{\rm M}_\odot]\lesssim 10^8)$ t

Camille Aron, Éric Brunet, Aditi Mitra

Quenched disorder slows down the scrambling of quantum information. Using a bottom-up approach, we formulate a kinetic theory of scrambling in a correlated metal near a superconducting transition, following the scrambling dynamics as the impurity scattering rate is increased. Within this framework, we rigorously show that the butterfly velocity $v$ is bounde

J. A. Aguilar-Saavedra, E. Arganda, F. R. Joaquim, R. M. Sandá Seoane

The MUST (Mass Unspecific Supervised Tagging) method has proven to be successful in implementing generic jet taggers capable of discriminating various signals over a wide range of jet masses. We implement the MUST concept by using eXtreme Gradient Boosting (XGBoost) classifiers instead of neural networks (NNs) as previously done. We build both fully-generic

Hamza Jnane, Jonathan Steinberg, Zhenyu Cai, H. Chau Nguyen

Classical shadows enable us to learn many properties of a quantum state $\rho$ with very few measurements. However, near-term and early fault-tolerant quantum computers will only be able to prepare noisy quantum states $\rho$ and it is thus a considerable challenge to efficiently learn properties of an ideal, noise free state $\rho_{id}$. We consider error m

Cecilia Sgalletta, Giuliano Iorio, Michela Mapelli, M. Celeste Artale

Galactic binary neutron stars (BNSs) are a unique laboratory to probe the evolution of BNSs and their progenitors. Here, we use a new version of the population synthesis code SEVN to evolve the population of Galactic BNSs, by modeling the spin up and down of pulsars self-consistently. We analyze the merger rate $\mathcal{R}_{\rm MW}$, orbital period $P_{\rm

Brayden Ware, Abhinav Deshpande, Dominik Hangleiter, Pradeep Niroula

Demonstrations of quantum computational advantage and benchmarks of quantum processors via quantum random circuit sampling are based on evaluating the linear cross-entropy benchmark (XEB). A key question in the theory of XEB is whether it approximates the fidelity of the quantum state preparation. Previous works have shown that the XEB generically approximat

Vicente Estrada-Carpenter, Casey Papovich, Ivelina Momcheva, Gabriel Brammer

Quiescent galaxies having more compact morphologies than star-forming galaxies has been a consistent result in the field of galaxy evolution. What is not clear is at what point this divergence happens, i.e. when do quiescent galaxies become compact, and how big of a role does the progenitor effect play in this result? Here we aim to model the morphological a

Souvik Banerjee, Pablo Basteiro, Rathindra Nath Das, Moritz Dorband

We propose the information-theoretic quantity of geometric quantum discord (GQD) as an indicator of the factorization properties of a given quantum system. In particular, we show how non-vanishing discord implies that the corresponding partition function does not factorize, both for generic pure states and the thermofield double state as a state with a known

Sarang Gopalakrishnan

We exploit the duality between quantum channels and sequentially generated states to construct families of highly entangled states that undergo phase transitions. These highly entangled states can be sequentially generated by collecting the emitted radiation from an open quantum system. In the dual perspective, the open system is regarded as a quantum-state-

Felix Winterer, Fabian R. Geisenhof, Noelia Fernandez, Anna M. Seiler

Nontrivial interacting phases can emerge in elementary materials. As a prime example, continuing advances in device quality have facilitated the observation of a variety of spontaneous quantum Hall-like states, a cascade of Stoner-like magnets, and an unconventional superconductor in bilayer graphene. Its natural extension, rhombohedral trilayer graphene is

Sean Bruton, Claudia Scarlata, Francesco Haardt, Matthew J. Hayes

We investigate the impact of field-to-field variation, deriving from cosmic variance, in measured Lyman-$\alpha$ emitter (LAE) luminosity functions (LFs) and this variation's impact on inferences of the neutral fraction of the intergalactic medium (IGM) during reionization. We post-process a z=7 IGM simulation to populate the dark matter halos with LAEs. The

Rodolfo Montez

We introduce a new imaging analysis technique to study the spatial distribution of the X-ray emission from the hot bubble of planetary nebula BD+30 3639. Hot bubble emission is typically photon-starved, thus limiting the methods for spatial-spectral analysis, however, this new technique uses the statistics of photon energies across the nebula to identify spa

Shahar Hod

It is proved, using the curved line element of a spherically symmetric charged object in general relativity and the Schwinger discharge mechanism of quantum field theory, that the orbital periods $T_{\infty}$ of test particles around central compact objects as measured by flat-space asymptotic observers are fundamentally bounded from below. The lower bound o

Mark Van Raamsdonk, Chris Waddell

The potential energy from a time-dependent scalar field provides a possible explanation for the observed cosmic acceleration. In this paper, we investigate how data from supernova and bary acoustic oscillation surveys constrain the possible evolution of a single scalar field over the period of time (roughly half the age of the universe) for which these data

Patrick M. Lenggenhager, Joseph Maciejko, Tomáš Bzdušek

Wave functions on periodic lattices are commonly described by Bloch band theory. Besides Abelian Bloch states labeled by a momentum vector, hyperbolic lattices support non-Abelian Bloch states that have so far eluded analytical treatments. By adapting the solid-state-physics notions of supercells and zone folding, we devise a method for the systematic constr

Alessandro Trinca, Raffaella Schneider, Rosa Valiante, Luca Graziani

We use the Cosmic Archaeology Tool (CAT) semi-analytical model to explore the contribution of Population (Pop) III/II stars and active galactic nuclei (AGNs) to the galaxy UV luminosity function (LF) evolution at $4 \leq z \leq 20$. We compare in particular with recent JWST data in order to explore the apparent tension between observations and theoretical mo

Andrea Gaspert, Pietro Giampa, Navin McGinnis, David E. Morrissey

Direct searches for dark matter with large-scale noble liquid detectors have become sensitive enough to detect the coherent scattering of local neutrinos. This will become a very challenging background to dark matter discovery in planned future detectors. For dark matter with mass above 10 GeV, the dominant neutrino backgrounds on the Earth are atmospheric n

Yann Gouttenoire, Tomer Volansky

Cosmological first-order phase transitions (1stOPTs) are said to be strongly supercooled when the nucleation temperature is much smaller than the critical temperature. These are often encountered in theories that admit a nearly scale-invariant potential, for which the bounce action decreases only logarithmically with temperature. During supercooled 1stOPTs t

Nils Quetschlich, Lukas Burgholzer, Robert Wille

In order to implement a quantum computing application, problem instances must be encoded into a quantum circuit and then compiled for a specific platform. The lengthy compilation process is a key bottleneck in this workflow, especially for problems that arise repeatedly with a similar yet distinct structure (each of which requires a new compilation run thus

Amy Lin, Jason Y. Zhang, Deva Ramanan, Shubham Tulsiani

We address the task of estimating 6D camera poses from sparse-view image sets (2-8 images). This task is a vital pre-processing stage for nearly all contemporary (neural) reconstruction algorithms but remains challenging given sparse views, especially for objects with visual symmetries and texture-less surfaces. We build on the recent RelPose framework which

Jinyu Li, Chenxu Luo, Xiaodong Yang

In order to deal with the sparse and unstructured raw point clouds, LiDAR based 3D object detection research mostly focuses on designing dedicated local point aggregators for fine-grained geometrical modeling. In this paper, we revisit the local point aggregators from the perspective of allocating computational resources. We find that the simplest pillar bas

Marek Lewicki, Piotr Toczek, Ville Vaskonen

We study the formation of primordial black holes (PBHs) in strongly supercooled first-order phase transitions. The mechanism is based on the presence of remnants dominated by the false vacuum that scale slower with the expansion of the Universe than their surroundings where this energy was already converted into radiation. We compute the PBH formation from t

Junyu Chen, Jie An, Hanjia Lyu, Christopher Kanan

Assessing the artness of AI-generated images continues to be a challenge within the realm of image generation. Most existing metrics cannot be used to perform instance-level and reference-free artness evaluation. This paper presents ArtScore, a metric designed to evaluate the degree to which an image resembles authentic artworks by artists (or conversely pho

Irene S. Gabashvili

The conversational artificial-intelligence (AI) technology ChatGPT has become one of the most widely used natural language processing tools. With thousands of published papers demonstrating its applications across various industries and fields, ChatGPT has sparked significant interest in the research community. Reviews of primary data have also begun to emer

A. Castro-González, O. D. S. Demangeon, J. Lillo-Box, C. Lovis

Small planets located at the lower mode of the bimodal radius distribution are generally assumed to be composed of iron and silicates in a proportion similar to that of the Earth. However, recent discoveries are revealing a new group of low-density planets that are inconsistent with that description. We intend to confirm and characterize the TESS planet cand

Michael Pinsker, Clemens Schindler

The set of increasing functions on the rational numbers, equipped with the composition operation, naturally forms a topological semigroup with respect to the topology of pointwise convergence in which a sequence of increasing functions converges if and only if it is eventually constant at every argument. We develop new techniques to prove there is no other P

GiBaik Sim, Frank Pollmann, Johannes Knolle

The identification of microscopic models describing the low-energy properties of correlated materials has been a central goal of spectroscopic measurements. We demonstrate how 2D non-linear spectroscopy can be used to distinguish effective spin models whose linear responses show similar behavior. Motivated by recent experiments on the quasi-1D Ising magnet C

Sicheng Yang, Zhiyong Wu, Minglei Li, Zhensong Zhang

The art of communication beyond speech there are gestures. The automatic co-speech gesture generation draws much attention in computer animation. It is a challenging task due to the diversity of gestures and the difficulty of matching the rhythm and semantics of the gesture to the corresponding speech. To address these problems, we present DiffuseStyleGestur

Bruce M. Kapron, Koosha Samieefar

Computational aspects of solution notions such as Nash equilibrium have been extensively studied, including settings where the ultimate goal is to find an equilibrium that possesses some additional properties. Furthermore, in order to address issues of tractability, attention has been given to approximate versions of these problems. Our work extends this dir

Flavien Léger, Pierre-Cyril Aubin-Frankowski

We present a new class of gradient-type optimization methods that extends vanilla gradient descent, mirror descent, Riemannian gradient descent, and natural gradient descent. Our approach involves constructing a surrogate for the objective function in a systematic manner, based on a chosen cost function. This surrogate is then minimized using an alternating

Lucas Johns

This paper responds to suggestions that the standard approach to collective neutrino oscillations leaves out potentially important quantum many-body correlations. Arguments in favor of this idea have been based on calculations that, on close scrutiny, offer no evidence either way. Inadequacies of the usual quantum-kinetic formalism are not currently supporte