April 2024 arXiv papers — page 2

Kedron Silsbee

Radial drift of solid particles in the protoplanetary disk is often invoked as a threat to planet formation, as it removes solid material from the disk before it can be assembled into planets. However, it may also concentrate solids at particular locations in the disk, thus accelerating the coagulation process. Planetesimals are thought to drift much faster

Caroline C. McGrouther, Aaditya V. Rangan, Arianna Di Florio, Jeremy A. Elman

Bipolar Disorder (BD) is a complex disease. It is heterogeneous, both at the phenotypic and genetic level, although the extent and impact of this heterogeneity is not fully understood. In this paper, we leverage recent advances in heterogeneity analysis to look for genetically-driven subgroups (i.e., biclusters) within the broad phenotype of Bipolar Disorder

Nathaniel Haines, Conor Goold

Averaging predictions from multiple competing inferential models frequently outperforms predictions from any single model, providing that models are optimally weighted to maximize predictive performance. This is particularly the case in so-called $\mathcal{M}$-open settings where the true model is not in the set of candidate models, and may be neither mathem

Chongyang Shi, Yuheng Bu, Jie Fu

The paper studies information-theoretic opacity, an information-flow privacy property, in a setting involving two agents: A planning agent who controls a stochastic system and an observer who partially observes the system states. The goal of the observer is to infer some secret, represented by a random variable, from its partial observations, while the goal

Skylar Chan, Pranav Kulkarni, Paul H. Yi, Vishwa S. Parekh

Quantum machine learning (QML) has the potential for improving the multi-label classification of rare, albeit critical, diseases in large-scale chest x-ray (CXR) datasets due to theoretical quantum advantages over classical machine learning (CML) in sample efficiency and generalizability. While prior literature has explored QML with CXRs, it has focused on b

Andrei-Marius Avram, Andreea Iuga, George-Vlad Manolache, Vlad-Cristian Matei

This work introduces HistNERo, the first Romanian corpus for Named Entity Recognition (NER) in historical newspapers. The dataset contains 323k tokens of text, covering more than half of the 19th century (i.e., 1817) until the late part of the 20th century (i.e., 1990). Eight native Romanian speakers annotated the dataset with five named entities. The sample

Alexander Demin, Yuriy Dorn, Aleksandr Katrutsa, Daniil Kazantsev

Optimal page replacement is an important problem in efficient buffer management. The range of replacement strategies known in the literature varies from simple but efficient FIFO-based algorithms to more accurate but potentially costly methods tailored to specific data access patterns. The principal issue in adopting a pattern-specific replacement logic in a

Alessandro Lella, Eike Ravensburg, Pierluca Carenza, M. C. David Marsh

In this paper, we explore the phenomenology of massive Axion-Like Particles (ALPs) coupled to quarks and gluons, dubbed 'QCD ALPs', with an emphasis on the associated low-energy observables. ALPs coupled to gluons and quarks not only induce nuclear interactions at scales below the QCD-scale, relevant for ALP production in supernovae (SNe), but naturally also

Souvik Dey, Rafael Holanda, Cleto B. Miranda-Neto

Our purpose in this work is multifold. First, we provide general criteria for the finiteness of the projective and injective dimensions of a finite module $M$ over a (commutative) Noetherian ring $R$. Second, in the other direction, we investigate the impact of the finiteness of certain homological dimensions of $M$ if $R$ is local, mainly when $R$ is Cohen-

A. V. Berezin, A. M. Fedotov

We consider a setup to detect stimulated photon-photon scattering using high-power lasers. Signal photons are emitted from an overlap of the incoming intense laser pulses focused in vacuum from three sides. We derive and justify a general approximate analytical formula for the angular distribution and total yield of such signal photons in terms of the parame

Calarina Muslimani, Matthew E. Taylor

To create useful reinforcement learning (RL) agents, step zero is to design a suitable reward function that captures the nuances of the task. However, reward engineering can be a difficult and time-consuming process. Instead, human-in-the-loop RL methods hold the promise of learning reward functions from human feedback. Despite recent successes, many of the

Zhan Li, Jiayang Chen, Yongmeng Sua, Zhaohui Ma

We demonstrate an invertible all-optical gate on chip, with the roles of control and signal switchable by slightly adjusting their relative arrival time at the gate. It is based on quantum Zeno blockade driven by sum-frequency generation in a periodic-poled lithium niobate microring resonator. For two nearly-identical nanosecond pulses, the later arriving pu

H. Adami, M. M. Sheikh-Jabbari, V. Taghiloo

We develop the framework that reveals the intrinsic conserved stress tensor and current associated with the null infinity of a three-dimensional ($3d$) asymptotically flat spacetime. These are, respectively, canonical conjugates of degenerate metric and Ehresmann connection of the boundary Carrollian geometry. Their conservation reproduces the Bondi-mass and

Georgios Darivianakis, Angelos Georghiou, Soroosh Shafiee, John Lygeros

Designing policies for a network of agents is typically done by formulating an optimization problem where each agent has access to state measurements of all the other agents in the network. Such policy designs with centralized information exchange result in optimization problems that are typically hard to solve, require establishing substantial communication

Viviane Alfradique, Tiago Castro, Valerio Marra, Miguel Quartin

Gravitational lensing is a crucial tool for exploring cosmic phenomena, providing insights into galaxy clustering, dark matter, and dark energy. Given the substantial computational demands of $N$-body simulations, approximate methods like $\texttt{PINOCCHIO}$ and $\texttt{turboGL}$ have been proposed as viable alternatives for simulating lensing probability

Jason D. Chadwick, Christopher Kang, Joshua Viszlai, Sophia Fuhui Lin

Fault-tolerant quantum computation relies on the assumption of time-invariant, sufficiently low physical error rates. However, current superconducting quantum computers suffer from frequent disruptive noise events, including cosmic ray impacts and shifting two-level system defects. Several methods have been proposed to mitigate these issues in software, but

Jialiang Wei, Anne-Lise Courbis, Thomas Lambolais, Binbin Xu

Graphical User Interfaces (GUIs) are central to app development projects. App developers may use the GUIs of other apps as a means of requirements refinement and rapid prototyping or as a source of inspiration for designing and improving their own apps. Recent research has thus suggested retrieving relevant GUI designs that match a certain text query from sc

Devi Klein, Srijita Karmakar, Aditya Jonnalagadda, Craig K. Abbey

Purpose: Radiologists are tasked with visually scrutinizing large amounts of data produced by 3D volumetric imaging modalities. Small signals can go unnoticed during the 3d search because they are hard to detect in the visual periphery. Recent advances in machine learning and computer vision have led to effective computer-aided detection (CADe) support syste

Sungmin Pak, Francis A. Cucinotta

Astronauts participating in lunar landing missions will encounter exposure to albedo particles emitted from the lunar surface as well as primary high-energy particles in the spectra of galactic cosmic rays (GCRs) and solar particle events (SPEs). While existing studies have examined particle energy spectra and absorbed doses in limited radiation exposure sce

Trinath Sai Subhash Reddy Pittala, Uma Maheswara R Meleti, Manasa Thatipamula

In this project, we have explored machine learning approaches for predicting hearing loss thresholds on the brain's gray matter 3D images. We have solved the problem statement in two phases. In the first phase, we used a 3D CNN model to reduce high-dimensional input into latent space and decode it into an original image to represent the input in rich feature

Yan Zhang, Indrakshi Dey, Nicola Marchetti

Reconfigurable Intelligent Surfaces (RIS) are known as a promising technology to improve the performance of wireless communication networks, and have been extensively studied. Movable Antennas (MA) are a novel technology that fully exploits the antenna placement for enhancing the system performance. This article aims at evaluating the impact of transmit powe

Ellen L. Sirks, David Harvey, Richard Massey, Kyle A. Oman

Terrestrial particle accelerators collide charged particles, then watch the trajectory of outgoing debris - but they cannot manipulate dark matter. Fortunately, dark matter is the main component of galaxy clusters, which are continuously pulled together by gravity. We show that galaxy cluster mergers can be exploited as enormous, natural dark matter collider

George Boateng, Victor Kumbol

Recent AI advancements offer transformative potential for global education, yet their application often overlooks Africa's unique educational landscape. AfricAIED 2024 will address this gap, spotlighting efforts to develop AI in Education (AIED) systems tailored to Africa's needs. Building on the success of the inaugural workshop, AfricAIED 2024 will feature

Christof Ferreira Torres, Albin Mamuti, Ben Weintraub, Cristina Nita-Rotaru

The emergence of decentralized finance has transformed asset trading on the blockchain, making traditional financial instruments more accessible while also introducing a series of exploitative economic practices known as Maximal Extractable Value (MEV). Concurrently, decentralized finance has embraced rollup-based Layer-2 solutions to facilitate asset tradin

P. L. Knight, C. C. Gerry, R. J. Birrittella, P. M. Alsing

In this short perspective article we present our personal highlights on how the Jaynes-Cummings model has become a central model to describe spin-boson couplings underpinning much of modern quantum optics. To the current authors, the key contribution is a demonstration of a measurable effect that showed the discreteness of the quantized radiation field.

Rayan Mazouz, John Skovbekk, Frederik Baymler Mathiesen, Eric Frew

This paper introduces a method of identifying a maximal set of safe strategies from data for stochastic systems with unknown dynamics using barrier certificates. The first step is learning the dynamics of the system via Gaussian process (GP) regression and obtaining probabilistic errors for this estimate. Then, we develop an algorithm for constructing piecew

Shuai Lyu, Yao Sun, Linke Guo, Xiaoyong Yuan

Task-oriented semantic communications (TSC) enhance radio resource efficiency by transmitting task-relevant semantic information. However, current research often overlooks the inherent semantic distinctions among encoded features. Due to unavoidable channel variations from time and frequency-selective fading, semantically sensitive feature units could be mor

Goya van Boven, Yupei Du, Dong Nguyen

Gender-neutral pronouns are increasingly being introduced across Western languages. Recent evaluations have however demonstrated that English NLP systems are unable to correctly process gender-neutral pronouns, with the risk of erasing and misgendering non-binary individuals. This paper examines a Dutch coreference resolution system's performance on gender-n

Clara Dehman

This doctoral thesis investigates the long-term evolution of the strong magnetic fields within isolated neutron stars (NSs), the most potent magnetic objects in the universe. Their magnetic influence extends beyond their surface to encompass the magnetised plasma in their vicinity. The overarching magnetic configuration significantly impacts the observable c

R. J. Birrittella, P. M. Alsing, J. Schneeloch, C. C. Gerry

We revisit a method for mapping arbitrary single-mode pure states into superpositions of N00N states using an asymmetric non-linear Mach-Zehnder interferometer (ANLMZI). This method would allow for one to tailor-make superpositions of N00N states where each axis of the two-mode joint-photon number distribution is weighted by the statistics of any single-mode

Yuto Shida, Giulia Punzi, Yasuaki Kobayashi, Takeaki Uno

In this paper, we study for the first time the Diverse Longest Common Subsequences (LCSs) problem under Hamming distance. Given a set of a constant number of input strings, the problem asks to decide if there exists some subset $\mathcal X$ of $K$ longest common subsequences whose diversity is no less than a specified threshold $\Delta$, where we consider tw

Amarjeet Kumar, Hongxu Jiang, Muhammad Imran, Cyndi Valdes

Deep learning has become the de facto method for medical image segmentation, with 3D segmentation models excelling in capturing complex 3D structures and 2D models offering high computational efficiency. However, segmenting 2.5D images, which have high in-plane but low through-plane resolution, is a relatively unexplored challenge. While applying 2D models t

Nicholas W. Landry, William Thompson, Laurent Hébert-Dufresne, Jean-Gabriel Young

Network scientists often use complex dynamic processes to describe network contagions, but tools for fitting contagion models typically assume simple dynamics. Here, we address this gap by developing a nonparametric method to reconstruct a network and dynamics from a series of node states, using a model that breaks the dichotomy between simple pairwise and c

Fanhao Wang, Yuzhe Wang, Laiyi Feng, Changsheng Zhang

Despite the exciting progress in target-specific de novo protein binder design, peptide binder design remains challenging due to the flexibility of peptide structures and the scarcity of protein-peptide complex structure data. In this study, we curated a large synthetic dataset, referred to as PepPC-F, from the abundant protein-protein interface data and dev

Raph Levien, Arman Uguray

Vector graphics includes both filled and stroked paths as the main primitives. While there are many techniques for rendering filled paths on GPU, stroked paths have proved more elusive. This paper presents a technique for performing stroke expansion, namely the generation of the outline representing the stroke of the given input path. Stroke expansion is a g

Maxim Raginsky

We revisit the work of Mitter and Newton on an information-theoretic interpretation of Bayes' formula through the Gibbs variational principle. This formulation allowed them to pose nonlinear estimation for diffusion processes as a problem in stochastic optimal control, so that the posterior density of the signal given the observation path could be sampled by

Joseph Adamo, Hung-Jin Huang, Tim Eifler

We train neural networks to quickly generate redshift-space galaxy power spectrum covariances from a given parameter set (cosmology and galaxy bias). This covariance emulator utilizes a combination of traditional fully-connected network layers and transformer architecture to accurately predict covariance matrices for the high redshift, north galactic cap sam

Petros Lazaridis, Athanasia Thomoglou

The presented study aims to provide an efficient and reliable tool for rapid estimation of the shear capacity of a TRM-strengthened masonry wall. For this purpose, a data-driven methodology based on a machine learning system is proposed using a dataset constituted of experimental results selected from the bibliography. The outlier points were detected using

Valentina De Romeri, Yuber F. Perez-Gonzalez, Agnese Tolino

Primordial black holes (PBH), while still constituting a viable dark matter component, are expected to evaporate through Hawking radiation. Assuming the semi-classical approximation holds up to near the Planck scale, PBHs are expected to evaporate by the present time, emitting a significant flux of particles in their final moments, if produced in the early U

Ehsan Hoseinzade, Ke Wang

This study addresses the challenge of detecting semantic column types in relational tables, a key task in many real-world applications. While language models like BERT have improved prediction accuracy, their token input constraints limit the simultaneous processing of intra-table and inter-table information. We propose a novel approach using Graph Neural Ne

Tianyu Liu

State transition algorithm (STA) is a metaheuristic method for global optimization. Recently, a modified STA named parameter optimal state transition algorithm (POSTA) is proposed. In POSTA, the performance of expansion operator, rotation operator and axesion operator is optimized through a parameter selection mechanism. But due to the insufficient utilizati

ATLAS Collaboration

Inelastic beam-gas collisions at the Large Hadron Collider (LHC), within a few hundred metres of the ATLAS experiment, are known to give the dominant contribution to beam backgrounds. These are monitored by ATLAS with a dedicated Beam Conditions Monitor (BCM) and with the rate of fake jets in the calorimeters. These two methods are complementary since the BC

Yuma E. Ritterbusch, Johannes Fink, Christian Waldschmidt

Small, low-cost radar sensors offer a lighting independent sensing capability for indoor mobile robots that is useful for localization and mapping. Synthetic aperture radar (SAR) offers an attractive way to increase the angular resolution of small radar sensors for use on mobile robots to generate high-resolution maps of the indoor environment. This work qua

Djalil Chafaï, Ryan W. Matzke, Edward B. Saff, Minh Quan H. Vu

We consider Riesz energy problems with radial external fields. We study the question of whether or not the equilibrium is the uniform distribution on a sphere. We develop general necessary as well as general sufficient conditions on the external field that apply to powers of the Euclidean norm as well as certain Lennard--Jones type fields. Additionally, in t

Kaori Fuyuto, Jacky Kumar, Emanuele Mereghetti, Stefan Sandner

Sterile neutrinos with masses at the $\mathrm{keV}$ scale and mixing to the active neutrinos offer an elegant explanation of the observed dark matter (DM) density. However, the very same mixing inevitably leads to radiative photon emission and the non-observation of such peaked $X$-ray lines rules out this minimal sterile neutrino DM hypothesis. We show that

Justin Engelmann, Miguel O. Bernabeu

Artificial Intelligence in medicine is traditionally limited by the lack of massive training datasets. Foundation models, pre-trained models that can be adapted to downstream tasks with small datasets, could alleviate this problem. Researchers at Moorfields Eye Hospital (MEH) proposed RETFound-MEH, a retinal foundation model trained on 900,000 images, includ

S. P. Miao, N. C. Tsamis, R. P. Woodard

We present a new computation of the renormalized graviton self-energy induced by a loop of massless, minimally coupled scalars on de Sitter background. Our result takes account of the need to include a finite renormalization of the cosmological constant, which was not included in the first analysis. We also avoid preconceptions concerning structure functions

Kim HyeongHan, M. James Jee, Wonki Lee, John ZuHone

Although the Perseus cluster has often been regarded as an archetypical relaxed galaxy cluster, several lines of evidence including ancient, large-scale cold fronts, asymmetric plasma morphology, filamentary galaxy distribution, etc., provide a conflicting view of its dynamical state, suggesting that the cluster might have experienced a major merger. However

Julian De Vuyst, Stefan Eccles, Philipp A. Hoehn, Josh Kirklin

In quantum gravity, it has been argued that a proper accounting of the role played by an observer promotes the von Neumann algebra of observables in a given spacetime subregion from Type III to Type II. While this allows for a mathematically precise definition of its entropy, we show that this procedure depends on which observer is employed. We make this pre

Michael A. Tucker, Jason Hinkle, Charlotte R. Angus, Katie Auchettl

We present extensive observations of the Type II supernova (SN II) 2023ufx which is likely the most metal-poor SN II observed to-date. It exploded in the outskirts of a low-metallicity ($Z_{\rm host} \sim 0.1~Z_\odot$) dwarf ($M_g = -13.23\pm0.15$~mag; $r_e\sim 1$~kpc) galaxy. The explosion is luminous, peaking at $M_g\approx -18.5~$mag, and shows rapid evol

Anirban Das, Noah Kurinsky, Rebecca K. Leane

We recently pointed out that power measurements of single quasiparticle devices can be used to detect dark matter. These devices have the lowest known energy thresholds, far surpassing standard direct detection experiments, requiring energy deposition above only about an meV. We calculate dark matter induced quasiparticle densities in transmon qubits, and us

Vasco O. Duke-Walker, Jacob A. McFarland

Shock-driven multiphase mixing occurs in many physical systems such as explosive dispersal of chemical or biological agents, in the evolution of supernova remnants, and in supersonic and detonative combustion engines. This mixing process is driven by the Shock Driven Multiphase Instability (SDMI), a derivative of the canonical Richtmyer-Meshkov Instability (

J. Carbajo-Hijarrubia, L. Casamiquela, R. Carrera, L. Balaguer-Núñez

Context. Open clusters provide valuable information on stellar nucleosynthesis and the chemical evolution of the Galactic disc, as their age and distances can be measured more precisely with photometry than for field stars. Aims. Our aim is to study the chemical distribution of the Galactic disc using open clusters by analysing the existence of gradients wit

Konpal Shaukat Ali, Roberto Bomfin, Marwa Chafii

To reuse the scarce spectrum efficiently, a large full-duplex cellular network with integrated sensing and communication (ISAC) is studied. Monostatic detection at the base station (BS) is considered. At the BS, we receive two signals: the communication-mode uplink signal to be decoded and the radar-mode signal to be detected. After self-interference cancell

Jordi Folch Eguren, Sophie Klingel, Emmanuel Stamou, Mustafa Tabet

Light dark matter with flavor-violating couplings to fermions may be copiously produced in the laboratory as missing energy from decays of SM particles. Here we study the effective Lagrangian of a light dark vector with generic dipole or vector couplings. We calculate the resulting two-body decay rates of mesons, baryons and leptons as a function of the dark

Taehyun Kim, Dimitri A. Gadotti, Miguel Querejeta, Isabel Pérez

Bars drive gas inflow. As the gas flows inwards, shocks and shear occur along the bar dust lanes. Such shocks and shear can affect the star formation and change the gas properties. For four barred galaxies, we present H{\alpha} velocity gradient maps that highlight bar-driven shocks and shear using data from the PHANGS-MUSE and PHANGS-ALMA surveys which allo

I. Mendigutía, J. Lillo-Box, M. Vioque, J. Maldonado

(Abridged) The presence of short-period (< 10 days) planets around main sequence (MS) stars has been associated either with the dust-destruction region or with the magnetospheric gas-truncation radius in the protoplanetary disks that surround them during the pre-MS phase. However, previous analyses have only considered low-mass FGK stars, making it difficult

Christoph Hirche

Contraction coefficients give a quantitative strengthening of the data processing inequality. As such, they have many natural applications whenever closer analysis of information processing is required. However, it is often challenging to calculate these coefficients. As a remedy we discuss a quantum generalization of Doeblin coefficients. These give an effi

Andrea Gokus, Knud Jahnke, Paul M Woods, Vanessa A Moss

Travel to academic conferences -- where international flights are the norm -- is responsible for a sizeable fraction of the greenhouse gas (GHG) emissions associated with academic work. In order to provide a benchmark for comparison with other fields, as well as for future reduction strategies and assessments, we estimate the CO2-equivalent emissions for con

C. Bacchini, C. Nipoti, G. Iorio, F. Roman-Oliveira

Local gravitational instability (LGI) is considered crucial for regulating star formation and gas turbulence in galaxy discs, especially at high redshift. Instability criteria usually assume infinitesimally thin discs or rely on approximations to include the stabilising effect of the gas disc thickness. We test a new 3D instability criterion for rotating gas

Andrea Sante, Andreea S. Font, Sandra Ortega-Martorell, Ivan Olier

We present several machine learning (ML) models developed to efficiently separate stars formed in-situ in Milky Way-type galaxies from those that were formed externally and later accreted. These models, which include examples from artificial neural networks, decision trees and dimensionality reduction techniques, are trained on a sample of disc-like, Milky W

Simone Giacomelli, Raffaele Savelli, Gianluca Zoccarato

We introduce a new class of non-compact backgrounds of Type IIB string theory preserving eight supercharges by combining S-folds and non-perturbative 7-branes wrapping orbifolds, and study the four-dimensional superconformal field theories arising at low energy on $D3$-branes probing them. We draw a precise correspondence between this setup and the torus com

Jiawen Fan, Huanqing Chen, Camille Avestruz, Affan Khadir

Observations of the end stages of reionization indicate that at $z\approx 5-6$, the ionizing background is not uniform and the mean free path (MFP) changes drastically. As MFP is closely related to the distribution of Lyman Limit Systems and Damped Lyman-alpha Systems (LLSs and DLAs, or ionizing photon "sinks"), it is important to understand them. In this st

Giorgio Franceschelli, Mirco Musolesi

Large language models are revolutionizing several areas, including artificial creativity. However, the process of generation in machines profoundly diverges from that observed in humans. In particular, machine generation is characterized by a lack of intentionality and an underlying creative process. We propose a method called Creative Beam Search that uses

LHCb collaboration, R. Aaij, A. S. W. Abdelmotteleb, C. Abellan Beteta

The decays of the $B^{+}$ meson to the final state $D^{*-}D^{+}_{s}\pi^{+}$ are studied in proton-proton collision data collected with the LHCb detector at centre-of-mass energies of 7, 8, and 13 TeV, corresponding to a total integrated luminosity of 9 fb$^{-1}$. The ratio of branching fractions of the $B^{+}\to D^{*-}D^{+}_{s}\pi^{+}$ and $B^{0}\to D^{*-}D^

G. F. Paraschos, L. C. Debbrecht, J. A. Kramer, E. Traianou

The spatial scales of relativistic radio jets, probed by relativistic magneto-hydrodynamic jet launching simulations (RMHDs) and by most very-long-baseline interferometry (VLBI) observations differ by an order of magnitude. Bridging the gap between these RMHD simulations and VLBI observations requires selecting nearby active galactic nuclei (AGN), the parsec

Federico Sestito, Sara Vitali, Paula Jofre, Kim A. Venn

The most metal-poor stars provide valuable insights into the early chemical enrichment history of a system, carrying the chemical imprints of the first generations of supernovae. The most metal-poor region of the Sagittarius dwarf galaxy remains inadequately observed and characterised. To date, only $\sim4$ stars with [Fe/H]~$<-2.0$ have been chemically anal

Sami Dib, Jian Wen Zhou, Sébastien Comerón, Luis E. Garduño

Star formation estimates based on the counting of YSOs is commonly applied to nearby star-forming regions in the Galaxy. With this method, the SFRs are measured using the counts of YSOs in a particular protostellar Class, a typical protostellar mass, and the lifetime associated with this Class. However, the assumptions underlying the validity of the method s

Patrick Foldenauer, Jaime Hoefken Zink

In recent years, the gauge group $U(1)_{L_\mu-L_\tau}$ has received a lot of attention since it can, in principle, account for the observed excess in the anomalous muon magnetic moment $(g-2)_\mu$, as well as the Hubble tension. Due to unavoidable, loop-induced kinetic mixing with the SM photon and $Z$, the $U(1)_{L_\mu-L_\tau}$ gauge boson $A'$ can contribu

Li Fan, Bernhard Keller, Yu Qiu

Our aim in this paper is to prove two results related to the three constructions of cluster categories: as orbit categories, as singularity categories and as cosingularity categories. In the first part of the paper, we prove the universal property of pretriangulated orbit categories of dg categories first stated by the second-named author in 2005. We deduce

Hanbit Oh, Boran Zhou, Ya-Hui Zhang

Recent observations of an 80 K superconductor in La$_3$Ni$_2$O$_7$ under high pressure have attracted significant attention. Recent experiments indicate that La$_3$Ni$_2$O$_7$ may be in the charge transfer regime, challenging the previous models based purely on the Ni $d_{x^2-y^2}$ and $d_{z^2}$ orbitals. In this study, we propose a low energy model that inc

Sumanth Rao

Enterprises are constantly under attack from sophisticated adversaries. These adversaries use a variety of techniques to first gain access to the enterprise, then spread laterally inside its networks, establish persistence, and finally exfiltrate sensitive data, or hold it for ransom. While historically, enterprises have used different Incident Response syst

Penghao Zhu, Rui-Xing Zhang

Like electrons, Cooper pairs can carry a monopole charge if the pairing electrons come from two or more Fermi surfaces with different Chern numbers. In such an instance, a superconductor is necessarily nodal due to an inherent topological pairing obstruction. In this work, we show that a similar obstruction is also possible when there is only one Fermi surfa

Kristjan Müürsepp, Enrico Nardi, Clemente Smarra

We propose a mechanism in which the current acceleration of cosmic expansion is driven by continuous creation of energy density $\rho_b$ for a certain field $\varphi_b$. We accordingly modify Einstein equation, derive modified Friedmann equations and analyze the regimes in which cosmic acceleration occurs. The creation process requires $\rho_b\neq 0$ as init

Kareem El-Badry, Hans-Walter Rix, David W. Latham, Sahar Shahaf

We report discovery and spectroscopic follow-up of 21 astrometric binaries containing solar-type stars and dark companions with masses near 1.4 $M_{\odot}$. The simplest interpretation is that the companions are dormant neutron stars (NSs), though ultramassive white dwarfs (WDs) and tight WD+WD binaries cannot be fully excluded. We selected targets from Gaia

Paul Romatschke, Chun-Wei Su, Ryan Weller

We study the Abelian Higgs model with multiple scalar fields, but without mass terms. Solving the model non-perturbatively order-by-order in the number of scalar fields, we find that radiative corrections generate masses for the scalar and gauge boson, without spontaneous symmetry breaking. The mass scales are set by the $\Lambda$-parameter of the electrowea

Mason Ng, Paul S. Ray, Andrea Sanna, Tod E. Strohmayer

We present the discovery, with the Neutron Star Interior Composition Explorer (NICER), that SRGA J144459.2-604207 is a 447.9 Hz accreting millisecond X-ray pulsar (AMXP), which underwent a four-week long outburst starting on 2024 February 15. The AMXP resides in a 5.22 hr binary, orbiting a low-mass companion donor with $M_d>0.1M_\odot$. We report on the tem

Christopher Cappiello, Qinrui Liu, Gopolang Mohlabeng, Aaron C. Vincent

Cosmic ray (CR) upscattering of dark matter is considered as one of the most straightforward mechanisms to accelerate ambient dark matter, making it detectable at high threshold, large volume experiments. In this work, we revisit CR upscattered dark matter signals at the IceCube detector, focusing on lower energy data than was considered before. We consider

Jorick S. Vink, Paul Crowther, Alex Fullerton, Miriam Garcia

The Hubble Space Telescope has devoted 500 orbits to observing 250 massive stars with low metallicity in the ultraviolet (UV) range within the framework of the ULLYSES program. The X-Shooting ULLYSES (XShootU) project enhances the legacy value of this UV dataset by providing high-quality optical and near-infrared spectra, which are acquired using the wide-wa

Eric R. Coughlin, Mitchell C. Begelman

JWST observations demonstrate that supermassive black holes (SMBHs) exist by redshifts $z \gtrsim 10$, providing further evidence for "direct collapse" black hole (BH) formation, whereby massive ($\sim 10^{3-5} M_{\odot}$) SMBH seeds are generated within a few Myr as a byproduct of the rapid inflow of gas into the centers of protogalaxies. Here we analyze th

Alek Bedroya, Rashmish K. Mishra, Max Wiesner

We study universal features of the density of one-particle states $\rho(E)$ in weakly coupled theories of gravity at energies above the quantum gravity cutoff $\Lambda$, defined as the scale suppressing higher-derivative corrections to the Einstein--Hilbert action. Using thermodynamic properties of black holes, we show that in asymptotically flat spacetimes,

Ainesh Bakshi, Allen Liu, Ankur Moitra, Ewin Tang

We study the problem of Hamiltonian structure learning from real-time evolution: given the ability to apply $e^{-\mathrm{i} Ht}$ for an unknown local Hamiltonian $H = \sum_{a = 1}^m \lambda_a E_a$ on $n$ qubits, the goal is to recover $H$. This problem is already well-understood under the assumption that the interaction terms, $E_a$, are given, and only the

Sebastian Franco, Xingyang Yu

Generalized global symmetries, in particular non-invertible and categorical symmetries, have become a focal point in the recent study of quantum field theory (QFT). In this paper, we investigate aspects of symmetry topological field theories (SymTFTs) and anomalies of non-invertible symmetries for 2D QFTs from a string theory perspective. Our primary focus i

Ang Cao, Justin Johnson, Andrea Vedaldi, David Novotny

Contemporary 3D research, particularly in reconstruction and generation, heavily relies on 2D images for inputs or supervision. However, current designs for these 2D-3D mapping are memory-intensive, posing a significant bottleneck for existing methods and hindering new applications. In response, we propose a pair of highly scalable components for 3D neural f

Wenxun Dai, Ling-Hao Chen, Jingbo Wang, Jinpeng Liu

This work introduces MotionLCM, extending controllable motion generation to a real-time level. Existing methods for spatial-temporal control in text-conditioned motion generation suffer from significant runtime inefficiency. To address this issue, we first propose the motion latent consistency model (MotionLCM) for motion generation, building on the motion l

Paul Engstler, Andrea Vedaldi, Iro Laina, Christian Rupprecht

3D scene generation has quickly become a challenging new research direction, fueled by consistent improvements of 2D generative diffusion models. Most prior work in this area generates scenes by iteratively stitching newly generated frames with existing geometry. These works often depend on pre-trained monocular depth estimators to lift the generated images

Jia-Zheng Li, Xun-Jiang Luo, Fengcheng Wu, Meng Xiao

Utilizing Bott index vectors formulated through a series of polynomials of position operators under open boundary conditions, we establish a universal, rigorous, and complete correspondence between the Bott index vector and topological zero-energy corner states in systems with chiral symmetry. Our framework covers systems of arbitrary shapes, including topol

Ziming Liu, Yixuan Wang, Sachin Vaidya, Fabian Ruehle

Inspired by the Kolmogorov-Arnold representation theorem, we propose Kolmogorov-Arnold Networks (KANs) as promising alternatives to Multi-Layer Perceptrons (MLPs). While MLPs have fixed activation functions on nodes ("neurons"), KANs have learnable activation functions on edges ("weights"). KANs have no linear weights at all -- every weight parameter is repl

Rustam Mamedov

As the demand for digital information grows in fields like medicine, remote sensing, and archival, efficient image compression becomes crucial. This paper focuses on lossless image compression, vital for managing the increasing volume of image data without quality loss. Current research emphasizes techniques such as predictive coding, transform coding, and c

Tony Metger, Anand Natarajan, Tina Zhang

We construct a succinct classical argument system for QMA, the quantum analogue of NP, from generic and standard cryptographic assumptions. Previously, building on the prior work of Mahadev (FOCS '18), Bartusek et al. (CRYPTO '22) also constructed a succinct classical argument system for QMA. However, their construction relied on post-quantumly secure indist

Yasumasa Onoe, Sunayana Rane, Zachary Berger, Yonatan Bitton

Vision-language datasets are vital for both text-to-image (T2I) and image-to-text (I2T) research. However, current datasets lack descriptions with fine-grained detail that would allow for richer associations to be learned by models. To fill the gap, we introduce Descriptions of Connected and Contrasting Images (DOCCI), a dataset with long, human-annotated En

Yunhao Ge, Xiaohui Zeng, Jacob Samuel Huffman, Tsung-Yi Lin

Existing automatic captioning methods for visual content face challenges such as lack of detail, content hallucination, and poor instruction following. In this work, we propose VisualFactChecker (VFC), a flexible training-free pipeline that generates high-fidelity and detailed captions for both 2D images and 3D objects. VFC consists of three steps: 1) propos

Toler H. Webb, Daniel M. Sussman

A large number of powerful, high-quality, and open-source simulation packages exist to efficiently perform molecular dynamics simulations, and their prevalence has greatly accelerated discoveries across a wide range of scientific domains. These packages typically simulate particles in free (Euclidean) space, with options to specify a variety of boundary cond

Zhouxiang Zhao, Zhaohui Yang, Chongwen Huang, Li Wei

In this paper, the problem of spectral-efficient communication and computation resource allocation for distributed reconfigurable intelligent surfaces (RISs) assisted probabilistic semantic communication (PSC) in industrial Internet-of-Things (IIoT) is investigated. In the considered model, multiple RISs are deployed to serve multiple users, while PSC adopts

Purbesh Mitra, Sennur Ulukus

We consider an asynchronous decentralized learning system, which consists of a network of connected devices trying to learn a machine learning model without any centralized parameter server. The users in the network have their own local training data, which is used for learning across all the nodes in the network. The learning method consists of two processe

Zhipeng Yuan, Nasamu Musa, Katarzyna Dybal, Matthew Back

Every year, plant parasitic nematodes, one of the major groups of plant pathogens, cause a significant loss of crops worldwide. To mitigate crop yield losses caused by nematodes, an efficient nematode monitoring method is essential for plant and crop disease management. In other respects, efficient nematode detection contributes to medical research and drug

Yan Tao

Recently, Manolescu-Sarkar constructed a stable homotopy type for link Floer homology, which uses grid homology and accounts for all domains that do not pass through a specific square. In doing so, they produced an obstruction chain complex of the grid diagram with that square removed. We define the obstruction chain complex of the full grid, without the squ

B. J. P. Jones, E Marzec, J. Spitz

We discuss the size of an electron neutrino wave packet emerging from an electron capture decay using the formalism of open quantum systems. This quantitative result is based on methodology that we have previously used to predict the width of an electron antineutrino wave packet from a beta-decaying nucleus, adapted for the different initial states in electr

Kathleen Salazar-Serna, Lorena Cadavid, Carlos Franco

Deciphering travel behavior and mode choices is a critical aspect of effective urban transportation system management, particularly in developing countries where unique socio-economic and cultural conditions complicate decision-making. Agent-based simulations offer a valuable tool for modeling transportation systems, enabling a nuanced understanding and poli

Leon Garza, Lavanya Elluri, Anantaa Kotal, Aritran Piplai

Data protection and privacy is becoming increasingly crucial in the digital era. Numerous companies depend on third-party vendors and service providers to carry out critical functions within their operations, encompassing tasks such as data handling and storage. However, this reliance introduces potential vulnerabilities, as these vendors' security measures