October 2024 arXiv papers — page 21

Fardous Hasan, Hazrat Ali, Hasan Asyari Arief

Non-linear convection-reaction-diffusion (CRD) partial differential equations (PDEs) are crucial for modeling complex phenomena in fields such as biology, ecology, population dynamics, physics, and engineering. Numerical approximation of these non-linear systems is essential due to the challenges of obtaining exact solutions. Traditionally, the Galerkin fini

Souvik Sadhukhan, Mustansir Barma, Saroj Kumar Nandi

Many physical systems, including some examples of active matter, granular assemblies, and biological systems, show fluctuation-dominated phase ordering (FDPO), where macroscopic fluctuations coexist with long-range order. Most of these systems are out of equilibrium. By contrast, a recent work has analytically demonstrated that an equilibrium one-dimensional

Joseph Damilola Akinyemi, Kolawole John Adebayo

As the global food security landscape continues to evolve, the need for accurate and reliable crop disease diagnosis has never been more pressing. To address global food security concerns, we extend the widely used PlantVillage dataset with additional apple leaf disease classes, enhancing diversity and complexity. Experimental evaluations on both original an

B. D. Lam, S. Ma, I. Kovalenko, P. Wang

Pulmonary embolism (PE) is a leading cause of preventable in-hospital mortality. Advances in diagnosis, risk stratification, and prevention can improve outcomes. There are few large publicly available datasets that contain PE labels for research. Using the MIMIC-IV database, we extracted all available radiology reports of computed tomography pulmonary angiog

Zhaochong An, Guolei Sun, Yun Liu, Runjia Li

Few-shot 3D point cloud segmentation (FS-PCS) aims at generalizing models to segment novel categories with minimal annotated support samples. While existing FS-PCS methods have shown promise, they primarily focus on unimodal point cloud inputs, overlooking the potential benefits of leveraging multimodal information. In this paper, we address this gap by intr

Young Hyun Cho, Will Wei Sun

With the growing demand for personalized assortment recommendations, concerns over data privacy have intensified, highlighting the urgent need for effective privacy-preserving strategies. This paper presents a novel framework for privacy-preserving dynamic assortment selection using the multinomial logit (MNL) bandits model. Our approach employs a perturbed

Zaniar Sharifi, Khabat Soltanian, Ali Amiri

Neural Architecture Search (NAS) methods autonomously discover high-accuracy neural network architectures, outperforming manually crafted ones. However, The NAS methods require high computational costs due to the high dimension search space and the need to train multiple candidate solutions. This paper introduces LCoDeepNEAT, an instantiation of Lamarckian g

Timothy Li, Shannon Starr

We consider multifold convolutions of a combinatorial sequence $(a_n)_{n=0}^{\infty}$: namely, for each $k \in \N$ the $k$-fold convolution is $\mathcal{M}^{(k)}_n(\boldsymbol{a}) = \sum_{j_1+\dots+j_k=n} a_{j_1} \cdots a_{j_k}$. Let $C_n$ be the Catalan numbers, and let $B_n$ be the central binomial coefficients. Then for random Dyck paths or simple random

Chih-Chien Erich Wang, Jiun-Huei Proty Wu

With physical quantum computers becoming increasingly accessible, research on their applications across various fields has advanced rapidly. In this paper, we present the first study of quantum cosmology conducted on physical quantum computers, employing a newly proposed Hybrid Quantum-Classical (HQC) algorithm rather than the commonly used Variational Quant

Egberto Selerio

This research focuses on decentralized wastewater treatment (DEWAT) technologies for the Philippines that is motivated by the limited suitable wastewater treatment infrastructure in the country. A multi-criteria analysis (MCA), using the Analytic Hierarchy Process (AHP) and Delphi method, was employed to evaluate DEWAT technologies based on life cycle costs

J. M. R. Teixeira, C. A. O. Henriques, P. A. O. C. Silva, R. D. P. Mano

Noble gas radiation detectors with optical readout are gaining popularity in fields like astrophysics and particle physics due to their ability to produce both ionization and scintillation signals in response to ionizing radiation interaction. In addition, the amplification of primary ionization signals can be achieved by promoting secondary scintillation in

Yanlin Zhou, Manshi Limbu, Xuan Wang, Daigo Shishika

Team Coordination on Graphs with Risky Edges (\textsc{tcgre}) is a recently proposed problem, in which robots find paths to their goals while considering possible coordination to reduce overall team cost. However, \textsc{tcgre} assumes that the \emph{entire} environment is available to a \emph{homogeneous} robot team with \emph{ubiquitous} communication. In

Arman Oganisian, Joseph Hogan, Edwin Sang, Allison DeLong

Like many chronic diseases, human immunodeficiency virus (HIV) is managed over time at regular clinic visits. At each visit, patient features are assessed, treatments are prescribed, and a subsequent visit is scheduled. There is a need for data-driven methods for both predicting retention and recommending scheduling decisions that optimize retention. Predict

Kexun Zhang, Shang Zhou, Danqing Wang, William Yang Wang

Sampling is a basic operation in many inference-time algorithms of large language models (LLMs). To scale up inference efficiently with a limited compute, it is crucial to find an optimal allocation for sample compute budgets: Which sampling configurations (model, temperature, language, etc.) do we use? How many samples do we generate in each configuration?

Giulia Pagnini, Paola Di Matteo, Misha Haywood, Alessandra Mastrobuono-Battisti

The peculiar Galactic globular cluster $\omega$ Centauri (NGC 5139) has drawn attention for its unique features - such as a high stellar mass and a broad distribution of chemical elements - that have led to the hypothesis that it might be the nuclear remnant of an ancient dwarf galaxy accreted by the Milky Way (MW), potentially bringing along its own globula

David Garzón Ramos, Sabine Hauert

Framing an issue as a puzzle, problem, or mess is an illustrative approach to characterizing the issue's complexity within organizational theory and systems thinking. We use this approach to characterize the issue of designing collective behaviors for robot swarms and discuss how various research goals have shaped the current state of the field. We contextua

Josh Alman, Alexandr Andoni, Hengjie Zhang

We study the average-case version of the Orthogonal Vectors problem, in which one is given as input $n$ vectors from $\{0,1\}^d$ which are chosen randomly so that each coordinate is $1$ independently with probability $p$. Kane and Williams [ITCS 2019] showed how to solve this problem in time $O(n^{2 - \delta_p})$ for a constant $\delta_p > 0$ that depends on

Ankan Mullick, Sombit Bose, Abhilash Nandy, Gajula Sai Chaitanya

In task-oriented dialogue systems, intent detection is crucial for interpreting user queries and providing appropriate responses. Existing research primarily addresses simple queries with a single intent, lacking effective systems for handling complex queries with multiple intents and extracting different intent spans. Additionally, there is a notable absenc

Rochelle E. Tractenberg

Artificial Intelligence (AI) is a field that utilizes computing and often, data and statistics, intensively together to solve problems or make predictions. AI has been evolving with literally unbelievable speed over the past few years, and this has led to an increase in social, cultural, industrial, scientific, and governmental concerns about the ethical dev

Magnus Carlson, Jakob Stix

Let $K$ be a sub-$p$-adic field. We show that the functor sending a finite type $K$-scheme to its \'etale topos is fully faithful after localizing at the class of universal homeomorphisms. This generalizes a result of Voevodsky, who proved the analogous theorem for fields finitely generated over $\mathbb{Q}$. Our proof relies on Mochizuki's Hom-theorem in an

Eshta Bhardwaj, Harshit Gujral, Siyi Wu, Ciara Zogheib

Data curation is a field with origins in librarianship and archives, whose scholarship and thinking on data issues go back centuries, if not millennia. The field of machine learning is increasingly observing the importance of data curation to the advancement of both applications and fundamental understanding of machine learning models - evidenced not least b

Haiyi Mao, Romain Lopez, Kai Liu, Jan-Christian Hütter

The study of cells and their responses to genetic or chemical perturbations promises to accelerate the discovery of therapeutic targets. However, designing adequate and insightful models for such data is difficult because the response of a cell to perturbations essentially depends on its biological context (e.g., genetic background or cell type). For example

Jihyun Park, Andrey Sarantsev

We model time series of VIX (monthly average) and monthly stock index returns. We use log-Heston model: logarithm of VIX is modeled as an autoregression of order 1. Our main insight is that normalizing monthly stock index returns (dividing them by VIX) makes them much closer to independent identically distributed Gaussian. The resulting model is mean-reverti

Hala Hawashin

Despite significant advances in quantum computing across various domains, research on applying quantum approaches to language compositionality - such as modeling linguistic structures and interactions - remains limited. This gap extends to the integration of quantum language data with real-world data from sources like images, video, and audio. This thesis ex

Jiaqi Wu, Simin Chen, Zehua Wang, Wei Chen

As the volume of image data grows, data-oriented cloud computing in Internet of Video Things (IoVT) systems encounters latency issues. Task-oriented edge computing addresses this by shifting data analysis to the edge. However, limited computational power of edge devices poses challenges for executing visual tasks. Existing methods struggle to balance high mo

Francesco Andreoli, Charlie-Ray Mann, Alexander A. High, Darrick E. Chang

Arrays of atomic emitters have proven to be a promising platform to manipulate and engineer optical properties, due to their efficient cooperative response to near-resonant light. Here, we theoretically investigate their use as an efficient metalens. We show that, by spatially tailoring the (sub-wavelength) lattice constants of three consecutive two-dimensio

Thomas C. Abbott, Andrew V. Zwaniga, Charanjot Brar, Victoria M. Kaspi

We present frb-voe, a publicly available software package that enables radio observatories to broadcast fast radio burst (FRB) alerts to subscribers through low-latency virtual observatory events (VOEvents). We describe a use-case of frb-voe by the Canadian Hydrogen Intensity Mapping Experiment Fast Radio Burst (CHIME/FRB) Collaboration, which has broadcast

Carlos G. Boiza, Mariam Bouhmadi-López

We analyse the cosmological evolution of a generalised axion-like field that drives the late-time acceleration of the Universe. This model can exhibit tracking behaviour, which alleviates the coincidence problem. The cosmological perturbations are carried within a multi-fluid approach where the scalar field is described by a non-adiabatic fluid, i.e., one wh

Elena Tomasetti, Michele Moresco, Carmela Lardo, Andrea Cimatti

We explore the reliability and robustness in measuring the age, metallicity and mass of a sample of old Milky Way globular clusters (GCs) from their integrated light, setting the stage for using GCs as cosmic clocks at high redshift. We analyse 77 GCs from the WAGGS project, first by measuring Lick indices and spectroscopic breaks with PyLick, then performin

Johannes M. Henn, Jungwon Lim, William J. Torres Bobadilla

We compute analytically the three-loop correlation function of the local operator $\text{tr} \, \phi^3$ inserted into three on-shell states, in maximally supersymmetric Yang-Mills theory. The result is expressed in terms of Chen iterated integrals. We also present our result using generalised polylogarithms, and evaluate them numerically, finding agreement w

Mireille Soergel, Nicolas Vaskou

In this article we describe the centres of all Dyer groups. We also give a complete classification of when a Dyer group $D(\Gamma)$ is hyperbolic or acylindricality hyperbolic, with conditions that can easily be read on the Dyer graph $\Gamma$.

Shashank Kumar Ojha, Pratap Pal, Sergei Prokhorenko, Sajid Husain

Pattern formation in spin systems with continuous-rotational symmetry (CRS) provides a powerful platform to study emergent complex magnetic phases and topological defects in condensed-matter physics. However, its understanding and correlation with unconventional magnetic order along with high-resolution nanoscale imaging is challenging. Here, we employ scann

Steve Benford, Rachael Garrett, Eike Schneiders, Paul Tennent

We explore transdisciplinary collaborations between artists and roboticists across a portfolio of artworks. Brendan Walker's Broncomatic was a breath controlled mechanical rodeo bull ride. Blast Theory's Cat Royale deployed a robot arm to play with a family of three cats for twelve days. Different Bodies is a prototype improvised dance performance in which d

Gyusam Chang, Jiwon Lee, Donghyun Kim, Jinkyu Kim

Recent advances in 3D object detection leveraging multi-view cameras have demonstrated their practical and economical value in various challenging vision tasks. However, typical supervised learning approaches face challenges in achieving satisfactory adaptation toward unseen and unlabeled target datasets (\ie, direct transfer) due to the inevitable geometric

Ankit Ravish, Akshay Tejwani, Piduguralla Manaswini, Sathya Peri

Blockchain technology is booming up the digital world in recent days and thus paved a way for creating separate blockchain network for various industries. This technology is characterized by its distributed, decentralized, and immutable ledger system which serves as a fundamental platform for managing smart contract transactions (SCTs). However, these self-e

Stephen Chung, Scott Niekum, David Krueger

As reinforcement learning agents become increasingly deployed in real-world scenarios, predicting future agent actions and events during deployment is important for facilitating better human-agent interaction and preventing catastrophic outcomes. This paper experimentally evaluates and compares the effectiveness of future action and event prediction for thre

J. Martin Berglund, Michael Drewsen, Christiane P. Koch

Sympathetic cooling of molecular ions through the Coulomb interaction with laser-cooled atomic ions is an efficient tool to prepare translationally cold molecules without, ideally, affecting the internal state of the molecular ions. However, the electric field due to the Coulomb interaction may induce rotational transitions that change the purity of initiall

Adrian Garret Gabriel, Alaa Alameer Ahmad, Shankar Kumar Jeyakumar

Advancements in Large Language Models (LLMs) are revolutionizing the development of autonomous agentic systems by enabling dynamic, context-aware task decomposition and automated tool selection. These sophisticated systems possess significant automation potential across various industries, managing complex tasks, interacting with external systems to enhance

Josselin Somerville Roberts, Tony Lee, Chi Heem Wong, Michihiro Yasunaga

We introduce Image2Struct, a benchmark to evaluate vision-language models (VLMs) on extracting structure from images. Our benchmark 1) captures real-world use cases, 2) is fully automatic and does not require human judgment, and 3) is based on a renewable stream of fresh data. In Image2Struct, VLMs are prompted to generate the underlying structure (e.g., LaT

Alessandra Rizzo

In this paper, we study Hamiltonian operators which are sum of a first order operator and of a Poisson tensor, in two spatial independent variables. In particular, a complete classification of these operators is presented in two and three components, analyzing both the cases of degenerate and non degenerate leading coefficients.

Chenyu Gao, Michael E. Kim, Karthik Ramadass, Praitayini Kanakaraj

Estimated brain age from magnetic resonance image (MRI) and its deviation from chronological age can provide early insights into potential neurodegenerative diseases, supporting early detection and implementation of prevention strategies. Diffusion MRI (dMRI) presents an opportunity to build an earlier biomarker for neurodegenerative disease prediction becau

Zhengbo Zhou, Degan Hao, Dooman Arefan, Margarita Zuley

In breast cancer detection and diagnosis, the longitudinal analysis of mammogram images is crucial. Contemporary models excel in detecting temporal imaging feature changes, thus enhancing the learning process over sequential imaging exams. Yet, the resilience of these longitudinal models against adversarial attacks remains underexplored. In this study, we pr

Gaiane Panina, Timur Shamazov, Maksim Turevskii

Let $ E \xrightarrow[\text{}]{\pi} B$ be an oriented circle bundle over an oriented closed surface $B$. A quasisection is a smooth surface ${Q}$ (either closed or bordered) mapped by a generic smooth mapping $q$ to $E$ such that $\pi\circ q({Q})=B$. In the paper we derive a local formula for the Euler number, that is, we show that Euler number (Euler class)

Parisa Hatami, Richard Annan, Luis Urias Miranda, Jane Gorman

Identifying mutations of SARS-CoV-2 strains associated with their phenotypic changes is critical for pandemic prediction and prevention. We compared an explainable convolutional neural network (CNN) approach and the traditional genome-wide association study (GWAS) on the mutations associated with WHO labels of SARS-CoV-2, a proxy for virulence phenotypes. We

Clayton Bromley, Alexander Moore, Amar Saini, Douglas Poland

Contemporary state-of-the-art video object segmentation (VOS) models compare incoming unannotated images to a history of image-mask relations via affinity or cross-attention to predict object masks. We refer to the internal memory state of the initial image-mask pair and past image-masks as a working memory buffer. While the current state of the art models p

Parvathi Kooloth, Jian Lu, Yi Huang, Derek DeSantis

We devise a pattern-aware feedback framework for representing the forced climate response using a suite of Green's function experiments with solar radiation perturbations. By considering the column energy balance, a comprehensive linear response function (CLRF) forimportant climate variables and feedback quantities such as moist static energy, sea surface te

Simranpreet Kaur, Daniele Viganò, Víctor J. S. Béjar, Álvaro Sánchez Monge

Scallop-shell stars, a recently discovered class of young M dwarfs, show complex optical light curves that are characterized by periodic dips as well as other features that are stable over tens to hundreds of rotation cycles. The origin of these features is not well-understood. 2MASS J05082729$-$2101444 is a $\sim$25 Myr old scallop-shell star that was ident

Alexander H. Liu, Qirui Wang, Yuan Gong, James Glass

Neural Audio Codecs, initially designed as a compression technique, have gained more attention recently for speech generation. Codec models represent each audio frame as a sequence of tokens, i.e., discrete embeddings. The discrete and low-frequency nature of neural codecs introduced a new way to generate speech with token-based models. As these tokens encod

Pratap Pal, Jonathon L. Schad, Anuradha M. Vibhakar, Shashank Kumar Ojha

Deterministic control of coupled ferroelectric and antiferromagnetic orders remains a central challenge in multiferroics, limiting their integration into functional magnetoelectrics and magnonic-devices. (111)pc BiFeO3 with a robust single spin cycloid, offers direct magnetoelectric-coupling and a platform for efficient spin transport, yet multi-magnetic dom

Viet Cuong Nguyen, Mohammad Taher, Dongwan Hong, Vinicius Konkolics Possobom

The rapid evolution of Large Language Models (LLMs) presents a promising solution to the global shortage of mental health professionals. However, their alignment with essential counseling competencies remains underexplored. We introduce CounselingBench, a novel NCMHCE-based benchmark evaluating 22 general-purpose and medical-finetuned LLMs across five key co

Jijia Yang, Sen Peng, Xiaohua Jia

In practical application, the widespread deployment of diffusion models often necessitates substantial investment in training. As diffusion models find increasingly diverse applications, concerns about potential misuse highlight the imperative for robust intellectual property protection. Current protection strategies either employ backdoor-based methods, int

Shehu AbdusSalam, Xin Gao, George K. Leontaris, Pramod Shukla

Given the huge size of the generic four-dimensional scalar potentials arising from the type II supergravities based on toroidal orientifolds, it is even hard to analytically solve the extremization conditions, and therefore the previous studies have been mainly focused on taking some numerical approaches. In this work, using the so-called {\it axionic flux p

Benjamin Castle, Assaf Hasson

Generalizing previous work on algebraically closed valued fields (ACVF) and o-minimal fields, we study strongly minimal relics of real closed valued fields (RCVF), and more generally T-convex expansions of o-minimal fields. Our main result (replicating the o-minimal setting) is that non-locally modular strongly minimal definable relics of T-convex fields mus

Kamal Thapa, Sathyanarayana Paladugu, Oleg D. Lavrentovich

Nematic liquid crystals exhibit nanosecond electro-optic response to an applied electric field which modifies the degree of orientational order without realigning the molecular orientation. However, this nanosecond electrically-modified order parameter (NEMOP) effect requires high driving fields, on the order of 100 V/um for a modest birefringence change of

Alexander R. Its, Kenta Miyahara, Maxim L. Yattselev

Motivated by the simplest case of tt*-Toda equations, we study the large and small $x$ asymptotics for $x>0$ of real solutions of the sinh-Godron Painlev\'e III($D_6$) equation. These solutions are parametrized through the monodromy data of the corresponding Riemann-Hilbert problem. This unified approach provides connection formulae between the behavior at t

S. S. Agaev, K. Azizi, H. Sundu

Spectroscopic parameters and decays of the exotic tensor meson $T$ with content $bc \overline{b}\overline{c}$ are explored in the context of the diquark-antidiquark model. We treat it as a state built of axial-vector diquark $b^{T}C\gamma _{\mu }c$ and antidiquark $\overline{b}\gamma _{\nu }C \overline{c}^{T}$, where $C$ is the charge conjugation matrix. The

Ali Saeizadeh, Miead Tehrani-Moayyed, Davide Villa, J. Gordon Beattie

Accurate channel modeling in real-time faces remarkable challenge due to the complexities of traditional methods such as ray tracing and field measurements. AI-based techniques have emerged to address these limitations, offering rapid, precise predictions of channel properties through ground truth data. This paper introduces an innovative approach to real-ti

Jan Behrends, Benjamin Béri

The surface code, one of the leading candidates for quantum error correction, is known to protect encoded quantum information against stochastic, i.e., incoherent errors. The protection against coherent errors, such as from unwanted gate rotations, is however understood only for special cases, such as rotations about the $X$ or $Z$ axes. Here we consider gen

Nicholas A. Corbin, Arijit Sarkar, Jacquelien M. A. Scherpen, Boris Kramer

We present a scalable tensor-based approach to computing input-normal/output-diagonal nonlinear balancing transformations for control-affine systems with polynomial nonlinearities. This transformation is necessary to determine the states that can be truncated when forming a reduced-order model. Given a polynomial representation for the controllability and ob

Pavel Drozdov, Giorgio Gubbiotti

In this paper, we characterize all discrete-time systems in quasi-standard form admitting coalgebra symmetry with respect to the Lie--Poisson algebra $\mathfrak{h}_{6}$. The outcome of this study is a family of systems depending on an arbitrary function of three variables, playing the r\^ole of the potential. Moreover, using a direct search approach, we clas

Bevin Huang, Ethan G. Arnault, Woochan Jung, Caleb Fried

Single photon detectors (SPDs) are essential technology in quantum science, quantum network, biology, and advanced imaging. To detect the small quantum of energy carried in a photon, conventional SPDs rely on energy excitation across either a semiconductor bandgap or superconducting gap. While the energy gap suppresses the false-positive error, it also sets

Melanie Ferreri

Starting with an inclusion-exclusion proof of a combinatorial identity, a direct bijection can be produced using recursive subtraction (sometimes with a direct combinatorial description). We apply this method to identities for generalized Wilf equivalences among consecutive patterns in inversion sequences, giving direct bijective proofs of some generalized W

Mahan Mohseni, Iann Cunha, Daniel Miravet, Alina Wania Rodrigues

This work presents steps toward the design of Majorana zero modes (MZM) in InAsP quantum dots (QD) embedded in an InP semiconducting nanowire in contact with a p-type superconductor described by the Kitaev Hamiltonian. The single particle spectrum is obtained from million atom atomistic calculations with QNANO and many-electron spectra using exact diagonaliz

Yue Chen, Robert Shrock

We present exact calculations of the $q$-state Potts model partition functions and the equivalent Tutte polynomials for chain graphs comprised of $m$ repeated hammock subgraphs $H_{e_1,...,e_r}$ connected with line graphs of length $e_g$ edges, such that the chains have open or cyclic boundary conditions (BC). Here, $H_{e_1,...,e_r}$ is a hammock (series-par

John Fullerton, Charudatta Phatak

Three-dimensional magnetic nanostructures are an emerging platform capable of creating complex topological magnetic fields. The control of localized nanoscale magnetic fields is seen to be of importance for diverse areas from bio-applications such as drug delivery, nanoscale magnetic resonance imaging, as well as condensed matter physics such as particle tra

W. Ishibashi

An increasing number of exoplanets have been discovered in the Milky Way galaxy, which is also known to harbour a super-massive black hole (Sagittarius A*) at its centre. Here, we investigate how the central black hole (BH) activity may affect the evolution of exoplanets in our Galaxy. Accreting BHs emit high-energy radiation -- extreme ultraviolet and X-ray

Mauro Cabrera-Gadea, Cecilia Mateu, Pau Ramos

The outskirts of the Milky Way disc have been known to be warped since the late 1950s. Although various stellar populations have shown an underlying warped distribution, the relation between the age of the population and the warp they trace remains an open question. Our goal in this work is to detect the presence of the warp in the RR Lyrae (RRL) population

Federico Bernini, Pietro d'Avenia

We introduce a fractional magnetic pseudorelativistic operator for a general fractional order $s\in(0,1)$. First we define a suitable functional setting and we prove some fundamental properties. Then we show the behavior of the operator as $s \nearrow 1$ obtaining some results \`a la Bourgain-Brezis-Mironescu and removing the singularity from the integral de

Jimmy Gammell, Anand Raghunathan, Kaushik Roy

Supervised deep learning has emerged as an effective tool for carrying out power side-channel attacks on cryptographic implementations. While increasingly-powerful deep learning-based attacks are regularly published, comparatively-little work has gone into using deep learning to defend against these attacks. In this work we propose a technique for identifyin

Tal Adi, Jordan Flitter, Ely D. Kovetz

Early dark energy (EDE) is one of the leading models proposed to resolve the perplexing Hubble tension. Despite extensive scrutiny and testing against various observables, conclusive constraints remain elusive as we await new data. In this paper, we study the impact of EDE on the 21cm signal, a powerful probe of cosmic dawn, and the epoch of reionization. Fi

Seigo Kikura, Hayato Goto, Takao Aoki

We propose a method for generating optical cat states in propagating pulses based on cavity quantum electrodynamics (QED). This scheme uses multiple four-level systems (4LSs) inside an optical cavity as a light source. Time-modulating driving stimulates it to produce a superposition of coherent states entangled with the 4LSs. The postselection of an appropri

Hieu Le, Federico Stella, Benoit Guillard, Pascal Fua

Unsigned Distance Functions (UDFs) can be used to represent non-watertight surfaces in a deep learning framework. However, UDFs tend to be brittle and difficult to learn, in part because the surface is located exactly where the UDF is non-differentiable. In this work, we show that Gradient Distance Functions (GDFs) can remedy this by being differentiable at

Jack Y. Araz, Vinicius Mikuni, Felix Ringer, Nobuo Sato

At high-energy collider experiments, generative models can be used for a wide range of tasks, including fast detector simulations, unfolding, searches of physics beyond the Standard Model, and inference tasks. In particular, it has been demonstrated that score-based diffusion models can generate high-fidelity and accurate samples of jets or collider events.

Michele Ginolfi, Filippo Mannucci, Francesco Belfiore, Alessandro Marconi

The era of large-scale astronomical surveys demands innovative approaches for rapid and accurate analysis of extensive spectral data, and a promising direction in which to address this challenge is offered by machine learning. Here, we introduce a new pipeline, M-TOPnet (Multi-Task network Outputting Probabilities), which employs a convolutional neural netwo

Daneshvar Amrollahi, Mathias Preiner, Aina Niemetz, Andrew Reynolds

In many applications, SMT solvers are utilized to solve similar or identical tasks over time. Significant variations in performance due to small changes in the input are not uncommon and lead to frustration for users. This sort of stability problem represents an important usability challenge for SMT solvers. We introduce an approach for mitigating the stabil

Zohar Nussinov, Michael C. Ogilvie, Laurin Pannullo, Robert D. Pisarski

The phase diagram of QCD may contain a moat regime in a large region of temperature $T$ and chemical potential $\mu\neq0$. A moat regime is characterized by quasiparticle moatons (pions) whose energy is minimal at nonzero spatial momentum. At $\mu\neq 0$, higher mass dimension operators play a critical role in a moat regime. At dimension six, there are nine

Jacob L. Scott, Zhongtian Dong, Taejoon Kim, Kyoungchul Kong

In recent years, quantum computing has drawn significant interest within the field of high-energy physics. We explore the potential of quantum algorithms to resolve the combinatorial problems in particle physics experiments. As a concrete example, we consider top quark pair production in the fully hadronic channel at the Large Hadron Collider. We investigate

Jofre Abellanet-Vidal, Guillem Müller-Rigat, Grzegorz Rajchel-Mieldzioć, Anna Sanpera

Quantum states that remain separable (i.e., not entangled) under any global unitary transformation are known as absolutely separable and form a convex set. Despite extensive efforts, the complete characterization of this set remains largely unknown. In this work, we employ linear maps and their inverses to derive new sufficient analytical conditions for abso

Ian Low, Zhewei Yin

We present universal relations between entanglement entropy, which quantifies the quantum correlation between subsystems, and the elastic cross section, which is the primary observable for high energy particle scattering, by employing a careful formulation of wave packets for the incoming particles. For 2-to-2 elastic scattering with no initial entanglement

Jing Shu, Bin Xu, Yuan Xu

We propose a novel dark matter detection scheme by leveraging quantum coherence across a network of multiple quantum sensors. This method effectively eliminates incoherent background noise, thereby significantly enhancing detection sensitivity. This is achieved by performing a series of basis transformation operations, allowing the coherent signal to be expr

Sebastian Leontica, Andrew G. Green

This work presents a method for studying low-energy physics in highly correlated magnetic systems using the matrix product state (MPS) manifold. We adapt the spin-wave approach, which has been very successful in modeling certain low-entanglement magnetic materials, to systems where the ground state is better represented by an MPS, such as the S = 1 Affleck-K

Paul Wittmer, Carlo Ewerz

We report real-time simulations of far-from-equilibrium dynamics of a holographic superfluid in three dimensions. The holographic duality maps a strongly coupled superfluid to a weakly coupled theory with gravity in a higher-dimensional curved space which we study numerically. Starting from configurations of dense tangles of quantized vortex lines, the super

David Cyncynates, Olivier Simon

In this Letter, we motivate the fact that couplings between a scalar field and the Standard Model with strengths $10^{-6}(m_\phi/{\rm eV})^{-1/4}$ relative to gravity yield the total measured cosmological dark matter abundance over a broad mass range of $10^{-12}$ to $10^{14}\ \rm{eV}$. Remarkably, this result holds with minimal sensitivity to whether the sc

Evan Scannapieco, Liubin Pan, Edward Buie, Marcus Brüggen

Supersonic turbulence occurs in many environments, particularly in astrophysics. In the crucial case of isothermal turbulence, the probability density function (PDF) of the logarithmic density, $s$, is well measured, but a theoretical understanding of the processes leading to this distribution remains elusive. We investigate these processes using Lagrangian

Amir H. Khoram, Francesco Belfiore

Chemical abundances are key tracers of the cycle of baryons driving the evolution of galaxies. Most measurements of interstellar medium (ISM) abundance and metallicity gradients in galaxies are based, however, on model-dependent strong-line methods. Direct chemical abundances can be obtained via the detection of weak auroral lines, but such lines are too fai

Qifeng Huang, Jing Wang, Xuchen Lin, Se-Heon Oh

Galaxy interactions can significantly affect the star formation in galaxies, but it remains a challenge to achieve a consensus on the star formation rate (SFR) enhancement in galaxy pairs. Here, we investigate the SFR enhancement of gas-rich galaxy pairs detected by the Widefield ASKAP L-band Legacy All-sky Blind surveY (WALLABY). We construct a sample of 27

Jannis Gebhard, Aleksas Mazeliauskas, Adam Takacs

In this work, we perform computations of inclusive jet, and semi-inclusive jet-hadron cross sections for minimum bias oxygen-oxygen collisions at RHIC and LHC collision energies. We compute the no-quenching baseline for the jet nuclear modification factor $R_\mathrm{AA}$ and jet-, and hadron-triggered semi-inclusive nuclear modification factors $I_\mathrm{AA

Matthew J. Fahey, Izzy. L. Garland, Brooke. D. Simmons, William C. Keel

Active galactic nucleus (AGN) growth in disk-dominated, merger-free galaxies is poorly understood, largely due to the difficulty in disentangling the AGN emission from that of the host galaxy. By carefully separating this emission, we examine the differences between AGNs in galaxies hosting a (possibly) merger-grown, classical bulge, and AGNs in secularly gr

Gautham N. Sabhahit, Jorick S. Vink

While stellar expansion after core-hydrogen exhaustion related to thermal imbalance has been documented for decades, the physical phenomenon of stellar inflation that occurs close to the Eddington limit has only come to the fore in recent years. We aim to elucidate the differences between these physical mechanisms for stellar radius enlargement, especially a

Benjamin Basso, Lance J. Dixon, Alexander G. Tumanov

We study the three-point form factor of the length-three half-BPS operator ($\textrm{Tr}\,\phi^3$) in planar $\mathcal{N}=4$ Super-Yang-Mills theory, using analyticity and integrability methods. We find that the functions describing the form factor in perturbation theory live in the same restrictive space of multiple polylogarithms as the one describing the

Justin Bopp, Ore Gottlieb

Most black holes (BHs) formed in collapsing stars have low spin, though some are expected to acquire a magnetic accretion disk during the collapse. While such BH disks can launch magnetically driven winds, their physics and observational signatures have remained unexplored. We present global 3D general relativistic magnetohydrodynamic simulations of collapsi

Iosif Bena, Yixuan Li, Severin Lüst

Flux compactifications that give three- or four-dimensional Anti de Sitter vacua with a parametrically small negative cosmological constant are claimed to be ubiquitous in String Theory. However, the 1+1 and 2+1 dimensional CFT duals to such vacua should have very large central charges and rather unusual properties. We construct brane configurations that sou

Yixin Zhang, Yang Zhang

We propose a mechanism for insulating ferromagnetism in the honeycomb Hubbard model of semiconductor moir\'e superlattices. The ferromagnetism emerges at critical charge transfer regime, stabilizing the quantum anomalous Hall state without Hund's coupling. We further note the ferromagnetic exchange applies to general charge transfer systems when breaking par

Michael Zhang, Kimberly Paragas, Jacob L. Bean, Joseph Yeung

We present the 2.4--5.0 \um JWST/NIRCam emission spectrum of HD 189733b, along with an independent re-reduction of the previously published transmission spectrum at the same wavelengths. We use an upgraded version of PLanetary Atmospheric Tool for Observer Noobs (PLATON) to retrieve atmospheric parameters from both geometries. In transit, we obtain [M/H]=$0.

Erwin T. Lau, Ákos Bogdán, Daisuke Nagai, Nico Cappelluti

The recent tension in the value of the cosmological parameter $S_8 \equiv \sigma_8(\Omega_M/0.3)^{1/2}$, which represents the amplitude of the matter density fluctuations of the universe, has not been resolved. In this work, we present constraints on $S_8$ with the X-ray angular power spectra of clusters and groups measured with the half-sky map from the eRO

Tisyagupta Pyne, Ravinder K. Banyal, C. Swastik, Ayanabha De

The habitability of a planet is influenced by both its parent star and the properties of its local stellar neighborhood. Potential threats to habitability from the local stellar environment mainly arise from two factors: cataclysmic events such as powerful stellar explosions and orbital perturbations induced by close stellar encounters. Among the 4,500+ exop

Guillermo Torres, Andrew F. Boden, John D. Monnier, Gerard T. van Belle

We report high-resolution spectroscopic monitoring and long-baseline interferometric observations with the PTI of the 215-day binary system HD 174881 (K1 II-III), composed of two giant stars. The system is spatially resolved with the PTI, as well as in archival measurements with the CHARA Array. Our analysis of these observations, along with an analysis of t

Lukas Koch

Ideally, all analyses of normally distributed data should include the full covariance information between all data points. In practice, the full covariance matrix between all data points is not always available. Either because a result was published without a covariance matrix, or because one tries to combine multiple results from separate publications. For

Murtaza Dalal, Min Liu, Walter Talbott, Chen Chen

Sim2real for robotic manipulation is difficult due to the challenges of simulating complex contacts and generating realistic task distributions. To tackle the latter problem, we introduce ManipGen, which leverages a new class of policies for sim2real transfer: local policies. Locality enables a variety of appealing properties including invariances to absolut

Jaydeep Datta, Abhay Deshpande, Dmitri E. Kharzeev, Charles Joseph Naïm

Recently, it was discovered that the proton structure at high energies exhibits maximal entanglement. This leads to a simple relation between the proton's parton distributions and the entropy of hadrons produced in high-energy inelastic interactions that has been experimentally confirmed. In this letter, we extend this approach to the production of jets. Her