July 2023 arXiv papers — page 54

Jaemarie Solyst, Judith Odili Uchidiuno, Erik Harpstead, Jonaya Kemper

Community-based afterschool programs are valuable spaces for researchers to codesign technologies with direct relevance to local communities. However, afterschool programs differ in resources available, culture, and student demographics in ways that may impact the efficacy of the codesign process and outcome. We ran a series of multi-week educational game co

Emily Newsom, Laure Zanna, Jonathan Gregory

The Ocean Heat Uptake Efficiency (OHUE) quantifies the ocean's ability to mitigate surface warming through deep heat sequestration. Despite its importance, the main controls on OHUE, as well as its nearly two-fold spread across contemporary climate models, remain unclear. We argue that OHUE is primarily controlled by the strength of mid-latitude ventilation

Dagne Wordofa, Mulugeta Bekele

This paper presents the investigation of convolutional neural network (CNN) prediction successfully recognizing the temperature of the non-equilibrium phases and phase transitions in two-dimensional (2D) Ising spins on square-lattice. The model uses image snapshots of ferromagnetic 2D spin configurations as an input shape to provide the average out put predi

Joshua Job

We present a function which connects the parameter of a previously published short sequence of selective number-dependent arbitrary phase (SNAP) and displacement gates acting on a qudit encoded into the Fock states of a superconducting cavity, $V_k(\alpha)=D(\alpha)R_\pi(k)D(-2\alpha)R_\pi(k)D(\alpha)$ to the angle of the Givens rotation $G(\theta)$ on level

Daniel Madrigal Diaz, Andre Manoel, Jialei Chen, Nalin Singal

We present Project Florida, a system architecture and software development kit (SDK) enabling deployment of large-scale Federated Learning (FL) solutions across a heterogeneous device ecosystem. Federated learning is an approach to machine learning based on a strong data sovereignty principle, i.e., that privacy and security of data is best enabled by storin

Shinji Watanabe

Quasicrystal (QC) has no periodicity but has a unique rotational symmetry forbidden in periodic crystals. Lack of microscopic theory of the crystalline electric field (CEF) in the QC and approximant crystal (AC) has prevented us from understanding the electric property, especially the magnetism. By developing the general formulation of the CEF in the rare-ea

Akash Velu, Skanda Vaidyanath, Dilip Arumugam

Oftentimes, environments for sequential decision-making problems can be quite sparse in the provision of evaluative feedback to guide reinforcement-learning agents. In the extreme case, long trajectories of behavior are merely punctuated with a single terminal feedback signal, leading to a significant temporal delay between the observation of a non-trivial r

A. Oliveros

In this study, we propose a reparameterization of a specific viable $f(R)$ gravity model to represent it as a perturbation of the $\Lambda$CDM model. The $f(R)$ gravity model under consideration includes two parameters, $b$ and $n$, which control how close the proposed model can be to $\Lambda$CDM, allowing for arbitrary proximity. Furthermore, it is shown t

Dennis O'Higgins

Despite the critical importance of Digital Transformation, up to 95% of initiatives fail to deliver expected business benefits. This paper explores the role of Business Architecture practices in enhancing digital transformation success. Using an adapted Balanced Scorecard approach and a Structural Equation Model (SEM), we analysed survey responses from 129 i

Robin Landry, John Moffat

We discuss the nonlocal nature of quantum mechanics and the link with relativistic quantum mechanics such as formulated by quantum field theory. We use here a nonlocal quantum field theory (NLQFT) which is finite, satisfies Poincar\'e invariance, unitarity and microscopic causality. This nonlocal quantum field theory associates infinite derivative entire fun

Yulin Gong, Rachel Bean, Patricio A. Gallardo, Eve M. Vavagiakis

We determine the efficacy of the kinematic Sunyaev-Zel'dovich signal extraction pipeline, using pairwise kSZ measurements, in recovering unbiased estimates of the signal and inference of the associated optical depth. We consider the impact of cluster co-alignments along the line of sight, the modeling of baryonic clustering, and the presence of diffuse gas,

Yinzi Xin, Jerry W. Xuan, Dimitri Mawet, Jason Wang

The Keck Planet Imager and Characterizer (KPIC) is an instrument at the Keck II telescope that enables high-resolution spectroscopy of directly imaged exoplanets and substellar companions. KPIC uses single-mode fibers to couple the adaptive optics system to Keck's near-infrared spectrometer (NIRSPEC). However, KPIC's sensitivity at small separations is limit

Avrim Blum, Princewill Okoroafor, Aadirupa Saha, Kevin Stangl

We consider the vulnerability of fairness-constrained learning to small amounts of malicious noise in the training data. Konstantinov and Lampert (2021) initiated the study of this question and presented negative results showing there exist data distributions where for several fairness constraints, any proper learner will exhibit high vulnerability when grou

William E. Doyle

This paper introduces significant improvements to the GravAD pipeline, a Python-based system for gravitational wave detection. These advancements include a reduction in waveform templates, implementation of simulated signals, and optimisation techniques. By integrating these advancements, GravAD exhibits increased performance, efficiency, and accuracy in pro

Xiaoyin Li, Feng Liu

Higher-order topological insulators (HOTIs) have attracted increasing interest as a unique class of topological quantum materials. One distinct property of HOTIs is the crystalline symmetry-imposed topological state at the lower-dimensional outer boundary, e.g. the zero-dimensional (0D) corner state of a 2D HOTI, used exclusively as a universal signature to

Xiaohan Zhang, Yifeng Zhu, Yan Ding, Yuqian Jiang

In existing task and motion planning (TAMP) research, it is a common assumption that experts manually specify the state space for task-level planning. A well-developed state space enables the desirable distribution of limited computational resources between task planning and motion planning. However, developing such task-level state spaces can be non-trivial

Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu

Deep neural networks based on linear RNNs interleaved with position-wise MLPs are gaining traction as competitive approaches for sequence modeling. Examples of such architectures include state-space models (SSMs) like S4, LRU, and Mamba: recently proposed models that achieve promising performance on text, genetics, and other data that require long-range reas

Declan Mages, Davide Farnocchia, Benjamin Donitz

Interstellar objects (ISOs) are small bodies that can travel through our solar system from other star systems. When present in our solar system, they represent an opportunity to study the properties and origins of these objects, as well as the potential for cross-pollination of material between star systems. With current propulsion technology, rendezvous wit

Lorenzo Bartolini, Sven Bjarke Gudnason

We utilize the top-down holographic QCD model, the Witten-Sakai-Sugimoto model, in a hybrid setting with the SLy4, soft chiral EFT and stiff chiral EFT equations of state to describe neutron stars with high precision. In particular, we employ a calibration that bootstraps the nuclear matter by fitting the Kaluza-Klein scale and the 't Hooft coupling such tha

Jacopo Borga, Cédric Boutillier, Valentin Féray, Pierre-Loïc Méliot

We obtain scaling and local limit results for large random Young tableaux of fixed shape $\lambda^0$ via the asymptotic analysis of a determinantal point process due to Gorin and Rahman (2019). More precisely, we prove: (1) an explicit description of the limiting surface of a uniform random Young tableau of shape $\lambda^0$, based on solving a complex-value

Matheus F. S. Alves, Júnior D. Toniato, Davi C. Rodrigues

Massive Brans-Dicke (BD) theory is among the simplest general relativity extensions. It is commonly found as the weak-field limit of other gravitational theories. Here we do a detailed post-Newtonian analysis of massive BD theories. We start by expanding the massive BD field equations following the Will-Nodtvedt Parameterized-Post-Newtonian (PPN) formalism,

Adam C. Schneider, Jeffrey A. Munn, Frederick J. Vrba, Justice Bruursema

We present positions, proper motions, and near-infrared photometry for 966 known objects with spectral types later than M observed as part of the the UKIRT Hemisphere Survey (UHS). We augment the photometry and astrometry from UHS with information from Gaia DR3, Pan-STARRS DR2, and CatWISE 2020 to produce a database of homogeneous photometry and astrometry f

Lala Shakti Swarup Ray, Bo Zhou, Sungho Suh, Paul Lukowicz

To help smart wearable researchers choose the optimal ground truth methods for motion capturing (MoCap) for all types of loose garments, we present a benchmark, DrapeMoCapBench (DMCB), specifically designed to evaluate the performance of optical marker-based and marker-less MoCap. High-cost marker-based MoCap systems are well-known as precise golden standard

Shagun Jhaver

Social media platforms like Facebook and Reddit host thousands of user-governed online communities. These platforms sanction communities that frequently violate platform policies; however, public perceptions of such sanctions remain unclear. In a pre-registered survey conducted in the US, I explore bystander perceptions of content moderation for communities

Jorge López, Charalampos Chatzinakis, Marc Cartigny, Claude Poletti

In recent years, computer networks and telecommunications in general have been shifting paradigms to adopt software-centric approaches. Software Defined Networking (SDN) is one of such paradigms that centralizes control and intelligent applications can be defined on top of this architecture. The latter enables the definition of the network behavior by means

Nelis Potgieter, Corli van Zyl, WD Schutte, Fred Lombard

The Population Stability Index (PSI) is a widely used measure in credit risk modeling and monitoring within the banking industry. Its purpose is to monitor for changes in the population underlying a model, such as a scorecard, to ensure that the current population closely resembles the one used during model development. If substantial differences between pop

R. Anthony-Petersen, A. Biekert, C. L. Chang, Y. Chang

The SPICE/HeRALD collaboration is performing R&D to enable studies of sub-GeV dark matter models using a variety of target materials. Here we report our recent progress on instrumenting a superfluid $^4$He target mass with a transition-edge sensor based calorimeter to detect both atomic signals (scintillation) and $^4$He quasiparticle (phonon and roton) exci

Xiangguo Liu, Ruochen Jiao, Yixuan Wang, Yimin Han

Recently significant progress has been made in vehicle prediction and planning algorithms for autonomous driving. However, it remains quite challenging for an autonomous vehicle to plan its trajectory in complex scenarios when it is difficult to accurately predict its surrounding vehicles' behaviors and trajectories. In this work, to maximize performance whi

Jindi Wu, Tianjie Hu, Qun Li

Quantum computing has shown considerable promise for compute-intensive tasks in recent years. For instance, classification tasks based on quantum neural networks (QNN) have garnered significant interest from researchers and have been evaluated in various scenarios. However, the majority of quantum classifiers are currently limited to binary classification ta

P. D. Ndione, S. T. Weber, D. O. Gericke, B. Rethfeld

We study the temperature-dependent optical properties of gold over a broad energy spectrum covering photon energies below and above the interband threshold. We apply a semi-analytical Drude-Lorentz model with temperature-dependent oscillator parameters. Our approximations are based on the distribution of electrons over the active bands with a density of stat

Matthew I. Jones, Matthew Chervenak, Nicholas A. Christakis

When confronted with a host of issues, groups often save time and energy by compiling many issues into a single bundle when making decisions. This reduces the time and cost of group decision-making, but it also leads to suboptimal outcomes as individuals lose the ability to express their preferences on each specific issue. We examine this trade-off by quanti

A. Kyriazis

In this paper we examine the possibility of dilute axion stars converting to photons in the weak, large-scale magnetic field of the Milky Way and show that they can resonate with the surrounding plasma and produce a sizable signal. We consider two possibilities for the plasma: free electrons and HII regions. In the former case, we argue that the frequency of

Virgile Dandoy, Joerg Jaeckel, Valentina Montoya

Dark matter direct (and indirect) detection experiments usually can only determine a specific combination of a power of the coupling and the dark matter density. This is also true for axion haloscopes which are sensitive to the product $g^{2}_{a\gamma\gamma}\rho_{\rm DM}$, the combination of axion-photon coupling squared and the dark matter density. In this

Qiang Ma, Liu Li, Vanessa Kyriakopoulou, Joseph Hajnal

Cortical surface reconstruction plays a fundamental role in modeling the rapid brain development during the perinatal period. In this work, we propose Conditional Temporal Attention Network (CoTAN), a fast end-to-end framework for diffeomorphic neonatal cortical surface reconstruction. CoTAN predicts multi-resolution stationary velocity fields (SVF) from neo

William Millsaps, Jonathan Schwartz, Zichao Wendy Di, Yi Jiang

Modern electron tomography has progressed to higher resolution at lower doses by leveraging compressed sensing methods that minimize total variation (TV). However, these sparsity-emphasized reconstruction algorithms introduce tunable parameters that greatly influence the reconstruction quality. Here, Pareto front analysis shows that high-quality tomograms ar

I. Ozan Yilmazlar, Mary E. Kurz

In the automotive industry, some vehicles, failed vehicles, cannot be produced according to the planned schedule due to some reasons such as material shortage, paint failure, etc. These vehicles are pulled out of the sequence, potentially resulting in an increased work overload. On the other hand, the reinsertion of failed vehicles is executed dynamically as

Reza Asrar Ghaderloo, Yidi Shen, Chanaka Singhabahu, Rakesh Resalayyan

Bus-clamping Pulse Width Modulation (PWM) is an effective method to reduce the switching loss in a three-phase voltage source inverter (VSI). In bus-clamping PWM scheme, the phase legs are switched using high frequency PWM signals for two-third of the line cycle, while for the remaining duration of cycle, the pole voltage is clamped to either positive or neg

Ting Bai, Alexander Johansson, Karl Henrik Johansson, Jonas Mårtensson

Truck platooning is a promising technology that enables trucks to travel in formations with small inter-vehicle distances for improved aerodynamics and fuel economy. The real-world transportation system includes a vast number of trucks owned by different fleet owners, for example, carriers. To fully exploit the benefits of platooning, efficient dispatching s

Nick Tehrany, Krijn Doekemeijer, Animesh Trivedi

With the ever-increasing amount of data generate in the world, estimated to reach over 200 Zettabytes by 2025, pressure on efficient data storage systems is intensifying. The shift from HDD to flash-based SSD provides one of the most fundamental shifts in storage technology, increasing performance capabilities significantly. However, flash storage comes with

Dmitriy Rivkin, Nikhil Kakodkar, Francois Hogan, Bobak H. Baghi

This work explores the capacity of large language models (LLMs) to address problems at the intersection of spatial planning and natural language interfaces for navigation. We focus on following complex instructions that are more akin to natural conversation than traditional explicit procedural directives typically seen in robotics. Unlike most prior work whe

Navid Ayoobi, Sadat Shahriar, Arjun Mukherjee

In this paper, we present a novel method for detecting fake and Large Language Model (LLM)-generated profiles in the LinkedIn Online Social Network immediately upon registration and before establishing connections. Early fake profile identification is crucial to maintaining the platform's integrity since it prevents imposters from acquiring the private and s

Cassidy K. Buhler, Hande Y. Benson

Given an allotment of land divided into parcels, government decision-makers, private developers, and conservation biologists can collaborate to select which parcels to protect, in order to accomplish sustainable ecological goals with various constraints. In this paper, we propose a mixed-integer optimization model that considers the presence of multiple spec

Quan Liu, Hanyu Zheng, Brandon T. Swartz, Ho hin Lee

Deep neural networks (DNNs) utilized recently are physically deployed with computational units (e.g., CPUs and GPUs). Such a design might lead to a heavy computational burden, significant latency, and intensive power consumption, which are critical limitations in applications such as the Internet of Things (IoT), edge computing, and the usage of drones. Rece

B. Alex Brown, Michio Honma, Ragnar Stroberg

Pairing energies for the addition of two neutrons on even-even nuclei with $ N=Z $ are studied. The $ Z $ dependence is attributed to the number and type of orbitals that are occupied in the valence shell-model space. Properties in the region from $ Z=60-100 $ depend on the location of the $ 0g_{9/2} $ orbital.

Nick Tehrany, Krijn Doekemeijer, Animesh Trivedi

Operational and performance characteristics of flash SSDs have long been associated with a set of Unwritten Contracts due to their hidden, complex internals and lack of control from the host software stack. These unwritten contracts govern how data should be stored, accessed, and garbage collected. The emergence of Zoned Namespace (ZNS) flash devices with th

Cesar Ceballos, Joseph Doolittle

The Heawood graph is a remarkable graph that played a fundamental role in the development of the theory of graph colorings on surfaces in the 19th and 20th centuries. Based on permutahedral tilings, we introduce a generalization of the classical Heawood graph indexed by a sequence of positive integers. We show that the resulting generalized Heawood graphs ar

George Winstone, Alexey Grinin, Mishkat Bhattacharya, Andrew A. Geraci

Optomechanics, the study of the mechanical interaction of light with matter, has proven to be a fruitful area of research that has yielded many notable achievements, including the direct detection of gravitational waves in kilometer-scale optical interferometers. Light has been used to cool and demonstrate quantum control over the mechanical degrees of freed

Bryan S. Graham, Andrin Pelican

This paper introduces a simulation algorithm for evaluating the log-likelihood function of a large supermodular binary-action game. Covered examples include (certain types of) peer effect, technology adoption, strategic network formation, and multi-market entry games. More generally, the algorithm facilitates simulated maximum likelihood (SML) estimation of

O. Barrera, I. Bartos

The heaviest black holes discovered through gravitational waves have masses that are difficult to explain with current standard stellar models. This discrepancy may be due to a series of hierarchical mergers, where the observed black holes are themselves the products of previous mergers. Here we present a method to estimate the masses and spins of previous g

Jonathan Gadea Harder, Timo Kötzing, Xiaoyue Li, Aishwarya Radhakrishnan

While most theoretical run time analyses of discrete randomized search heuristics focused on finite search spaces, we consider the search space $\mathbb{Z}^n$. This is a further generalization of the search space of multi-valued decision variables $\{0,\ldots,r-1\}^n$. We consider as fitness functions the distance to the (unique) non-zero optimum $a$ (based

Anubhab Haldar, Zhengjie Huang, Xuedan Ma, Pierre Darancet

We study the optical generation and control of coherent phonons in elemental bismuth (Bi) and antimony (Sb) using a classical equation of motion informed by first-principles calculations of the potential energy surface and the frequency-dependent macroscopic dielectric function along the zone-centered optical phonons coordinates. Using this approach, we demo

Shiyu Sun, Shu Wang, Xinda Wang, Yunlong Xing

Python has become the most popular programming language as it is friendly to work with for beginners. However, a recent study has found that most security issues in Python have not been indexed by CVE and may only be fixed by 'silent' security commits, which pose a threat to software security and hinder the security fixes to downstream software. It is critic

Fernando Haas

A canonical Hamiltonian is found for a reduced version of the Jackiw-Pi model for bilayer graphene. From the corresponding Lagrangian, the Noether point symmetries and conserved quantities are determined. The Noether symmetry group is the same as the fifth-dimensional group for the time-dependent harmonic oscillator. The realization of the algebra is achieve

J. R. Rizzo, C. Bordiu, C. Buemi, P. Leto

We investigated the molecular environment of AFGL 2298, an obscured Galactic Luminous blue variable (LBV) star which hosts a highly structured circumstellar environment with hints of multiple mass-loss events in the last few $10^4$ a. We present spectral line observations of AFGL 2298 at 1 and 3 mm performed with the IRAM 30m radio telescope. Furthermore, we

Govert Nijs, Bruno Scheihing-Hitschfeld, Xiaojun Yao

Suppression of open heavy flavors and quarkonia in heavy-ion collisions is among the most informative probes of the quark-gluon plasma. Interpreting the full wealth of data obtained from the collision events requires a precise understanding of the evolution of heavy quarks and quarkonia as they propagate through the nearly thermal and strongly coupled plasma

Yang Bai, Anthony Colas, Daisy Zhe Wang

Check-worthy claim detection aims at providing plausible misinformation to downstream fact-checking systems or human experts to check. This is a crucial step toward accelerating the fact-checking process. Many efforts have been put into how to identify check-worthy claims from a small scale of pre-collected claims, but how to efficiently detect check-worthy

M. J. Yzer, R. G. Visser, C. Dominik

We study the effect an atmosphere has on pebble orbits and spin build-up on a planet's surface during pebble accretion in the extreme case of a static atmosphere. We numerically integrate the equations of motion of pebbles in a planar, global frame with a planet, a central star and gas from a protoplanetary disc. An adiabatic atmosphere is then placed around

Bryce Morsky, Fuwei Zhuang, Zuojun Zhou

We study the roles of social and individual learning on outcomes of the Minority Game model of a financial market. Social learning occurs via agents adopting the strategies of their neighbours within a social network, while individual learning results in agents changing their strategies without input from other agents. In particular, we show how social learn

Christopher Gerling, Stefan Lessmann

Traditional banks face increasing competition from FinTechs in the rapidly evolving financial ecosystem. Raising operational efficiency is vital to address this challenge. Our study aims to improve the efficiency of document-intensive business processes in banking. To that end, we first review the landscape of business documents in the retail segment. Bankin

Recep Buğra Uludağ, Serhat Çağdaş, Yavuz Selim İşler, Neslihan Serap Şengör

In this paper, we presented a bio-realistic basal ganglia neural network and its integration into Intel's Loihi neuromorphic processor to perform simple Go/No-Go task. To incorporate more bio-realistic and diverse set of neuron dynamics, we used Izhikevich neuron model, implemented as microcode, instead of Leaky-Integrate and Fire (LIF) neuron model that has

Ganesh Pokharel, Brenden R. Ortiz, Linus Kautzsch, S. J. Gomez Alvarado

Here we study the stability of charge order in the kagome metal ScV6Sn6. Synchrotron x-ray diffraction measurements reveal high-temperature, short-range charge correlations at the wave vectors along q=(1/3,1/3,1/2) whose inter-layer correlation lengths diverge upon cooling. At the charge order transition, this divergence is interrupted and long-range order f

Damian P. San Roman Alerigi, David I. Ketcheson, Boon S. Ooi

We develop a finite volume method for Maxwell's equations in materials whose electromagnetic properties vary in space and time. We investigate both conservative and non-conservative numerical formulations. High-order methods accurately resolve fine structures that develop due to the varying material properties. Numerical examples demonstrate the effectivenes

José D. Huerta-Morales, Chenglong You, Omar S. Magaña-Loaiza, Shi-Hai Dong

Structured light beams, in particular those carrying orbital angular momentum (OAM), have gained a lot of attention due to their potential for enlarging the transmission capabilities of communication systems. However, the use of OAM-carrying light in communications faces two major problems, namely distortions introduced during propagation in disordered media

Hamid Mehdipour, Peter Kratzer

Janus materials have attracted much interest due to their intrinsic electric dipole moment and Rashba band splitting. We show that, by building bilayers of MoSeTe and WSeTe with different chalcogen atom sequences and different stacking patterns, one can modulate the net dipole moment strength and the Rashba effect, as well as the band alignment of the MoSeTe

Andrei A. Klishin, J. Nathan Kutz, Krithika Manohar

Large-dimensional empirical data in science and engineering frequently have a low-rank structure and can be represented as a combination of just a few eigenmodes. Because of this structure, we can use just a few spatially localized sensor measurements to reconstruct the full state of a complex system. The quality of this reconstruction, especially in the pre

Franklin Aldás, Alfredo Zenteno, Facundo Gómez, Daniel Hernandez-Lang

Merging of galaxy clusters are some of the most energetic events in the Universe, and they provide a unique environment to study galaxy evolution. We use a sample of 84 merging and relaxed SPT galaxy clusters candidates, observed with the Dark Energy Camera in the $0.11<z<0.88$ redshift range, to build colour-magnitude diagrams to characterize the impact of

Wilke van der Schee, Yen-Jie Lee, Govert Nijs, Yi Chen

We present an estimate of the yield of hard probes expected for collisions of the isobars $^{96}_{44}$Ru and $^{96}_{40}$Zr at collision energies reachable at RHIC and the LHC\@. These yields are proportional to the number of binary nucleon-nucleon interactions, which is characteristically different due to the presence of the large neutron skin in $^{96}_{40

Shenming Fu, Yuanyuan Zhang, Camille Avestruz, Ruben Coronel

We present observational evidence of the impact of triaxiality on radial profiles that extend to 40 Mpc from galaxy cluster centres in optical measurements. We perform a stacked profile analysis from a sample of thousands of nearly relaxed galaxy clusters from public data releases of the Dark Energy Survey (DES) and the Dark Energy Camera Legacy Survey (DECa

Alejandro H. Córsico, S. Reece Boston, Leandro G. Althaus, Mukremin Kilic

Ultra-massive white dwarf stars are currently being discovered at a considerable rate, thanks to surveys such as the {\it Gaia} space mission. These dense and compact stellar remnants likely play a major role in type Ia supernova explosions. It is possible to probe the interiors of ultra-massive white dwarfs through asteroseismology. In the case of the most

Alena Kalyakulina, Igor Yusipov, Alexey Moskalev, Claudio Franceschi

eXplainable Artificial Intelligence (XAI) is a rapidly progressing field of machine learning, aiming to unravel the predictions of complex models. XAI is especially required in sensitive applications, e.g. in health care, when diagnosis, recommendations and treatment choices might rely on the decisions made by artificial intelligence systems. AI approaches h

Zhiyuan Zhao, Xueying Ding, B. Aditya Prakash

Physics-Informed Neural Networks (PINNs) have emerged as a promising deep learning framework for approximating numerical solutions to partial differential equations (PDEs). However, conventional PINNs, relying on multilayer perceptrons (MLP), neglect the crucial temporal dependencies inherent in practical physics systems and thus fail to propagate the initia

Matthew Gebhardt, Daniel Anglés-Alcázar, Josh Borrow, Shy Genel

We quantify the cosmological spread of baryons relative to their initial neighboring dark matter distribution using thousands of state-of-the-art simulations from the Cosmology and Astrophysics with MachinE Learning Simulations (CAMELS) project. We show that dark matter particles spread relative to their initial neighboring distribution owing to chaotic grav

Victor Johnston, Anne Medling, Brent Groves, Lisa Kewley

Current methods of identifying the ionizing source of nebular emission in galaxies are well defined for the era of single fiber spectroscopy, but still struggle to differentiate the complex and overlapping ionization sources in some galaxies. With the advent of integral field spectroscopy, the limits of these previous classification schemes are more apparent

Lina M. Todenhagen, Martin S. Brandt

We study the contrast for electrical and optical readout of NV centers in diamond in dependence of the optical excitation wavelength using different excitation schemes. While the optically detected magnetic resonance (ODMR) works efficiently between 480 and 580 nm, electrically detected magnetic resonance (EDMR) shows a strong dependence on the excitation dy

Christian W. Bauer, Irian D'Andrea, Marat Freytsis, Dorota M. Grabowska

Due to rapidly improving quantum computing hardware, Hamiltonian simulations of relativistic lattice field theories have seen a resurgence of attention. This computational tool requires turning the formally infinite-dimensional Hilbert space of the full theory into a finite-dimensional one. For gauge theories, a widely-used basis for the Hilbert space relies

Yiqun Chen, Qiang Chen, Peize Sun, Shoufa Chen

We present a conceptually simple, efficient, and general framework for localization problems in DETR-like models. We add plugins to well-trained models instead of inefficiently designing new models and training them from scratch. The method, called RefineBox, refines the outputs of DETR-like detectors by lightweight refinement networks. RefineBox is easy to

Abigail Plummer, Caroline Adkins, Jean-François Louf, Andrej Košmrlj

Obstructions influence the growth and expansion of bodies in a wide range of settings -- but isolating and understanding their impact can be difficult in complex environments. Here, we study obstructed growth/expansion in a model system accessible to experiments, simulations, and theory: hydrogels swelling around fixed cylindrical obstacles with varying geom

Tomáš Roubíček

The thermodynamic model of visco-elastic deformable magnetic materials at finite strains is formulated in a fully Eulerian way in rates with the aim to describe thermoremanent paleomagnetism in crustal rocks. The Landau theory applied to a ferro-to-para-magnetic phase transition, the gradient theory for magnetization (leading to exchange energy) with general

Gissel P. Montaguth, Sergio Torres-Flores, Antonela Monachesi, Facundo A. Gómez

Compact groups of galaxies (CGs) show members with morphological disturbances, mainly products of galaxy-galaxy interactions, thus making them ideal systems to study galaxy evolution, in high-density environment. To understand how this environment affects the properties of galaxies, we select a sample of 340 CGs in the Stripe 82 region, for a total of 1083 g

Allan Tosta, Thais de Lima Silva, Giancarlo Camilo, Leandro Aolita

We present a hybrid quantum-classical framework for simulating generic matrix functions more amenable to early fault-tolerant quantum hardware than standard quantum singular-value transformations. The method is based on randomization over the Chebyshev approximation of the target function while keeping the matrix oracle quantum, and is assisted by a variant

Mehmet Kerim Yucel, Ramazan Gokberk Cinbis, Pinar Duygulu

Convolutional Neural Networks (CNN) are known to exhibit poor generalization performance under distribution shifts. Their generalization have been studied extensively, and one line of work approaches the problem from a frequency-centric perspective. These studies highlight the fact that humans and CNNs might focus on different frequency components of an imag

Projesh Nath Choudhury, Shivangi Yadav

Variation diminution (VD) is a fundamental property in total positivity theory, first studied in 1912 by Fekete-P\'olya for one-sided P\'olya frequency sequences, followed by Schoenberg, and by Motzkin who characterized sign regular (SR) matrices using VD and some rank hypotheses. A classical theorem by Gantmacher-Krein characterized the strictly sign regula

The GRAVITY Collaboration, R. Abuter, N. Aimar, P. Amaro Seoane

We present new astrometric and polarimetric observations of flares from Sgr A* obtained with GRAVITY, the near-infrared interferometer at ESO's Very Large Telescope Interferometer (VLTI), bringing the total sample of well-covered astrometric flares to four and polarimetric ones to six, where we have for two flares good coverage in both domains. All astrometr

Niccolò Baldelli, Hannes Karlsson, Benedikt Kloss, Matthew Fishman

The phenomena of superconductivity and charge density waves are observed in close vicinity in many strongly correlated materials. Increasing evidence from experiments and numerical simulations suggests both phenomena can also occur in an intertwined manner, where the superconducting order parameter is coupled to the electronic density. Employing density matr

Nicolás Abate, Mateo Koifman

We continue the study of the Tomita-Takesaki modular conjugation for a massless Dirac field in a generic multicomponent region in $1+1$ spacetime dimensions. In this paper we focus on the computations for a thermal state on a circle, namely on the euclidean torus. By analytic continuation from the modular flow we arrive at an explicit expression for the modu

L. Napolitano, L. Pentericci, A. Calabrò, P. Santini

The physical processes which make a galaxy a Lyman Alpha Emitter have been extensively studied for the past 25 years. However, the correlations between physical and morphological properties of galaxies and the strength of the Ly$\alpha$ emission line are still highly debated. Therefore, we investigate the correlations between the rest-frame Ly$\alpha$ equiva

Ewine F. van Dishoeck, S. Grant, B. Tabone, M. van Gelder

Early results from the JWST-MIRI guaranteed time programs on protostars (JOYS) and disks (MINDS) are presented. Thanks to the increased sensitivity, spectral and spatial resolution of the MIRI spectrometer, the chemical inventory of the planet-forming zones in disks can be investigated with unprecedented detail across stellar mass range and age. Here data ar

Wouter Buijsman, Yevgeny Bar Lev

Quantum many-body scars are atypical, highly nonthermal eigenstates embedded in a sea of thermal eigenstates that have been observed in, for example, kinetically constrained quantum many-body models. These special eigenstates are characterized by a bipartite entanglement entropy that scales as most logarithmically with the subsystem size. We use numerical op

M. M. Fausnaugh, P. J. Vallely, M. A. Tucker, C. S. Kochanek

We present 307 Type Ia supernova (SN) light curves from the first four years of the TESS mission. We use this sample to characterize the shapes of the early time light curves, measure the rise times from first light to peak, and search for companion star interactions. Using simulations, we show that light curves must have noise $<$10% of the peak to avoid bi

Oliver Zier, Volker Springel, Alexander C. Mayer

Especially in cold and high-density regions, the assumptions of ideal magnetohydrodynamics (MHD) can break down, making first order non-ideal terms such as Ohmic and ambipolar diffusion as well as the Hall effect important. In this study we present a new numerical scheme for the first two resistive terms, which we implement in the moving-mesh code AREPO usin

Nicolás Bernal, Marta Losada, Yosef Nir, Yogev Shpilman

The ATLAS Collaboration has recently reported a search for light-charged Higgs in $t\to H^+ b$ decay, with $H^+\to c\bar b$. An excess with a local significance of approximately $3\sigma$ is found at $m_{H^+}\approx130$ GeV, with a best-fit value of ${\rm BR}(t\to H^+b)\times {\rm BR}(H^+\to c\bar b)=(1.6\pm0.6)\times10^{-3}$. We study the implications of su

J. I. McDonald, B. Garbrecht, P. Millington

With axions now a primary candidate for dark matter, understanding their indirect astrophysical signatures is of paramount importance. Key to this is the production of photons from axions in magnetised astrophysical plasmas. While simple formulae for axion-photon mixing in 1D have been sketched several decades ago, there has recently been renewed interest in

Dion Noordhuis, Anirudh Prabhu, Christoph Weniger, Samuel J. Witte

Recent work has shown that axions can be efficiently produced via non-stationary pair plasma discharges in the polar cap region of pulsars. Here, we point out that for axion masses $10^{-9} \, {\rm eV} \lesssim m_a \lesssim 10^{-4} \, \rm eV$, a sizable fraction of the sourced axion population will be gravitationally confined to the neutron star. These axion

Yu-Ping Lin, Chunxiao Liu, Joel E. Moore

We present the mean-field phase diagram of electrons in a kagome flat band with repulsive interactions. In addition to flat-band ferromagnetism, the Hartree-Fock analysis yields cascades of unconventional magnetic orders driven by onsite repulsion as filling changes. These include a series of antiferromagnetic (AFM) spin-charge stripe orders, as well as an e

Syuhei Iguro, Teppei Kitahara

The measurements of the lepton flavor universality (LFU) in $\mathcal{B}({\bar{B}} \to D^{(\ast)} l \bar{\nu})$ indicate a significant deviation from the standard model prediction at a 3-4$\sigma$ level, revealing a violation of the LFU ($R_{D^{(\ast)}}$ anomaly). It is known that the $R_{D^{(\ast)}}$ anomaly can be easily accommodated by an $SU(2)_L$-single

Lukas W. Lindwasser

The explicit covariant actions and propagators are given for fields describing particles of all spins and masses, in any spacetime dimension. Massive particles are realized as "dimensionally reduced" massless particles. To obtain compact expressions for the propagators, it was useful to introduce an auxiliary vector coordinate $s^{\mu}$ and consider "hyperfi

Karan Chadha, Junye Chen, John Duchi, Vitaly Feldman

In this work, we study practical heuristics to improve the performance of prefix-tree based algorithms for differentially private heavy hitter detection. Our model assumes each user has multiple data points and the goal is to learn as many of the most frequent data points as possible across all users' data with aggregate and local differential privacy. We pr

Yosuke Shinya

Scale-wise evaluation of object detectors is important for real-world applications. However, existing metrics are either coarse or not sufficiently reliable. In this paper, we propose novel scale-wise metrics that strike a balance between fineness and reliability, using a filter bank consisting of triangular and trapezoidal band-pass filters. We conduct expe

Manon Blanc, Olivier Bournez

We prove that functions over the reals computable in polynomial time can be characterised using discrete ordinary differential equations (ODE), also known as finite differences. We also provide a characterisation of functions computable in polynomial space over the reals. In particular, this covers space complexity, while existing characterisations were only

Przemyslaw Grabowski

We prove a Galois-type correspondence between compositions of purely inseparable field extensions (including infinite ones) and subalgebras of differential operators. This correspondence can be utilized to establish a connection between separable field extensions and purely inseparable field extensions. Specifically, it serves as a progression towards gainin