July 2022 arXiv papers — page 11

Makariy A. Tanatar, Daniele Torsello, Kamal R. Joshi, Sunil Ghimire

Niobium is one of the most studied superconductors, both theoretically and experimentally. It is tremendously important for applications, and it has the highest superconducting transition temperature, $T_{c}=9.33$ K, of all pure metals. In addition to power applications in alloys, pure niobium is used for sensitive magneto-sensing, radio-frequency cavities,

Josiah Walker, Nakul Bajaj, Braden L. Crimmins, J. Alex Halderman

Pre-election logic and accuracy (L&A) testing is a process in which election officials validate the behavior of voting equipment by casting a known set of test ballots and confirming the expected results. Ideally, such testing can serve to detect certain forms of human error or fraud and help bolster voter confidence. We present the first detailed analysis o

Shikib Mehri, Yasemin Altun, Maxine Eskenazi

To facilitate zero-shot generalization in taskoriented dialog, this paper proposes Language Models as Data (LAD). LAD is a paradigm for creating diverse and accurate synthetic data which conveys the necessary structural constraints and can be used to train a downstream neural dialog model. LAD leverages GPT-3 to induce linguistic diversity. LAD achieves sign

Semih Barutcu, Aggelos K. Katsaggelos, Doğa Gürsoy

Ptychography is a well-studied phase imaging method that makes non-invasive imaging possible at a nanometer scale. It has developed into a mainstream technique with various applications across a range of areas such as material science or the defense industry. One major drawback of ptychography is the long data acquisition time due to the high overlap require

Jiabin Lin, Shana Moothedath

We consider the problem where M agents collaboratively interact with an instance of a stochastic K-armed contextual bandit, where K>>M. The goal of the agents is to simultaneously minimize the cumulative regret over all the agents over a time horizon T. We consider a setting where the exact context is observed after a delay and at the time of choosing the ac

Benedikt Prifling, Matthias Neumann, Simon Hein, Timo Danner

It is well known that the spatial distribution of the carbon-binder domain (CBD) offers a large potential to further optimize lithium-ion batteries. However, it is challenging to reconstruct the CBD from tomographic image data obtained by synchrotron tomography. In the present paper, we consider several approaches to segment 3D image data of two different ca

Joao Paulo de Brito Goncalves, Gustavo Alochio, Rodolfo da Silva Villaca, Roberta Lima Gomes

The fifth-generation (5G) wireless networks are expected to provide various services compared to the 4G and previous generations of networks. The Quality of Service requirements can be quite different in terms of latency, bandwidth, reliability, and availability. 5G technology allows the fragmentation of the network into small pieces, known as network slices

Samuel E. Otto, Alberto Padovan, Clarence W. Rowley

Data-driven reduced-order models often fail to make accurate forecasts of high-dimensional nonlinear dynamical systems that are sensitive along coordinates with low-variance because such coordinates are often truncated, e.g., by proper orthogonal decomposition, kernel principal component analysis, and autoencoders. Such systems are encountered frequently in

Xu Ouyang, Shahina Mohd Azam Ansari, Felix Xiaozhu Lin, Yangfeng Ji

As model finetuning is central to the modern NLP, we set to maximize its efficiency. Motivated by redundancy in training examples and the sheer sizes of pretrained models, we exploit a key opportunity: training only on important data. To this end, we set to filter training examples in a streaming fashion, in tandem with training the target model. Our key tec

Diego Córdoba, Luis Martínez-Zoroa

We consider solutions to the generalized Surface Quasi-geostrophic equation ($\gamma$-SQG) when the velocity is more singular than the active scalar function (i.e. $\gamma\in(0,1)$). In this paper we establish strong ill-posedness in $C^{k,\beta}$ ($k\geq 1$, $\beta\in(0,1]$ and $k+\beta>1+\gamma$) and we also construct solutions in $\mathbb{R}^2$ that initi

Derck Massa, Raman K. Prinja

UV wind line variability in OB stars appears to be universal. We review the evidence that the variability is due to large, dense, optically thick structures rooted in or near the photosphere. Using repeated bservations and a simple model we translate observed profile variations into optical depth variations and, consequently, variations in measured mass loss

Terrence Sejnowski

Large Language Models (LLMs) have been transformative. They are pre-trained foundational models that are self-supervised and can be adapted with fine tuning to a wide range of natural language tasks, each of which previously would have required a separate network model. This is one step closer to the extraordinary versatility of human language. GPT-3 and mor

Xing Nie, Bolin Ni, Jianlong Chang, Gaomeng Meng

In computer vision, fine-tuning is the de-facto approach to leverage pre-trained vision models to perform downstream tasks. However, deploying it in practice is quite challenging, due to adopting parameter inefficient global update and heavily relying on high-quality downstream data. Recently, prompt-based learning, which adds a task-relevant prompt to adapt

Sezen Lim, Tina Walber, Christoph Schaefer, Lena Riehl

Webcam eye tracking for the collection of gaze data in the context of user studies is convenient - it can be used in remote tests where participants do not need special hardware. The approach has strong limitations, especially regarding the motion-free nature of the test persons during data recording and the quality of the gaze data obtained. Our study with

Chinonso Nwankwo, Weizhong Dai

We propose a stable sixth-order compact finite difference scheme with a dynamic fifth-order staggered boundary scheme and 3(2) R-K Bogacki and Shampine adaptive time stepping for pricing American style options. To locate, fix and compute the free-boundary simultaneously with option and delta sensitivity, we introduce a Landau transformation. Furthermore, we

Corban Rivera, Chace Ashcraft, Alexander New, James Schmidt

Creating artificial intelligence (AI) systems capable of demonstrating lifelong learning is a fundamental challenge, and many approaches and metrics have been proposed to analyze algorithmic properties. However, for existing lifelong learning metrics, algorithmic contributions are confounded by task and scenario structure. To mitigate this issue, we introduc

Alexander P. Mangerel

Let $\chi$ be a primitive character modulo a prime $q$, and let $\delta > 0$. It has previously been observed that if $\chi$ has large order $d \geq d_0(\delta)$ then $\chi(n) \neq 1$ for some $n \leq q^{\delta}$, in analogy with Vinogradov's conjecture on quadratic non-residues. We give a new and simple proof of this fact. We show, furthermore, that if $d$

Minghan Chu, Xiaohua Wu, David E. Rival

It is well known that the Boussinesq turbulent viscosity hypothesis can yield inaccurate predictions when complex f low features are involved, e.g. laminar-turbulent transition. The focus of the study is to explore the capability of a physics-based uncertainty quantification (UQ) approach to quantify the model-form uncertainty in Reynolds-averaged Naiver-Sto

Sebastien Roch

Recent work on dissimilarity-based hierarchical clustering has led to the introduction of global objective functions for this classical problem. Several standard approaches, such as average linkage, as well as some new heuristics have been shown to provide approximation guarantees. Here we introduce a broad new class of objective functions which satisfy desi

Ryan Levy, Zoe Gonzalez Izquierdo, Zhihui Wang, Jeffrey Marshall

The Fermi-Hubbard model (FHM) on a two dimensional square lattice has long been an important testbed and target for simulating fermionic Hamiltonians on quantum hardware. We present an alternative for quantum simulation of FHMs based on an adiabatic protocol that could be an attractive target for next generations of quantum annealers. Our results rely on a r

Aveena Kottwani, Ayush Kumar

We explore techniques for eye gaze estimation using machine learning. Eye gaze estimation is a common problem for various behavior analysis and human-computer interfaces. The purpose of this work is to discuss various model types for eye gaze estimation and present the results from predicting gaze direction using eye landmarks in unconstrained settings. In u

Mario V. Wüthrich

The Gini index does not give a strictly consistent scoring rule in general. Therefore, maximizing the Gini index may lead to wrong decisions. The main issue is that the Gini index is a rank-based score that is not calibration-sensitive. We show that the Gini index allows for strictly consistent scoring if we restrict to the class of auto-calibrated regressio

Marko Toroš, Marion Cromb, Mauro Paternostro, Daniele Faccio

Many phenomena and fundamental predictions, ranging from Hawking radiation to the early evolution of the Universe rely on the interplay between quantum mechanics and gravity or more generally, quantum mechanics in curved spacetimes. However, our understanding is hindered by the lack of experiments that actually allow us to probe quantum mechanics in curved s

Taicheng Guo, Lu Yu, Basem Shihada, Xiangliang Zhang

The cold-start problem has been commonly recognized in recommendation systems and studied by following a general idea to leverage the abundant interaction records of warm users to infer the preference of cold users. However, the performance of these solutions is limited by the amount of records available from warm users to use. Thus, building a recommendatio

Stephen Power

Asymptotic equilibrium stresses are defined for countably infinite tensegrities and generalisations of the Roth-Whiteley characterisation of first-order rigidity are obtained. Generalisations of prestress stability and second order rigidity are given for countably infinite bar-joint frameworks and are shown to give sufficient conditions for continuous rigidi

Sourav Chakraborty, Arijit Ghosh, Soumi Nandi

We prove a colorful extension of a Helly-type theorem by Danzer and Gr\"{u}nbaum (Combinatorica, 1982) concerning two-piercing families of axis-parallel boxes in $\mathbb{R}^d$. We also show that our result is tight by constructing extremal families that achieve the bound. Related work includes a graph-theoretic proof of the original theorem by Pendavingh, P

Zhouyingcheng Liao, Jimei Yang, Jun Saito, Gerard Pons-Moll

We present the first method that automatically transfers poses between stylized 3D characters without skeletal rigging. In contrast to previous attempts to learn pose transformations on fixed or topology-equivalent skeleton templates, our method focuses on a novel scenario to handle skeleton-free characters with diverse shapes, topologies, and mesh connectiv

Anna Haensch, Dina Deitsch

Public art shapes our shared spaces. Public art should speak to community and context, and yet, recent work has demonstrated numerous instances of art in prominent institutions favoring outdated cultural norms and legacy communities. Motivated by this, we develop a novel recommender system to curate public art exhibits with built-in equity objectives and a l

Michael Rotman, Amit Dekel, Ran Ilan Ber, Lior Wolf

The evolution of dynamical systems is generically governed by nonlinear partial differential equations (PDEs), whose solution, in a simulation framework, requires vast amounts of computational resources. In this work, we present a novel method that combines a hyper-network solver with a Fourier Neural Operator architecture. Our method treats time and space s

Jagannath Mahapatra, Rajaraman Ganesh, Abhijit Sen

A 2D incompressible viscoresistive-MHD model [Mahapatra et. al., Phys. Plasmas 28, 072103 (2021)] is used to study the scaling of reconnection parameters in magnetic island coalescence problem under two interesting scenarios. Firstly, the effect of changing island half-width at a fixed system size is investigated. As the island half-width increases, the tota

Chaked R. J. Sayedoff, Ofer Strichman

Given two programs $p_1$ and $p_2$, typically two versions of the same program, the goal of regression verification is to mark pairs of functions from $p_1$ and $p_2$ that are equivalent, given a definition of equivalence. The most common definition is that of partial equivalence, namely that the two functions emit the same output if they are fed with the sa

Tapendu Rana, Sumit Kumar Rano

The aim of this article is to study the $L^{p}$-boundedness of pseudo-differential operators on a homogeneous tree $ \mathfrak{X} $. For $p\in (1,2)$, we establish a connection between the $L^{p}$-boundedness of the pseudo-differential operators on $ \mathfrak{X} $ and that on the group of integers $\mathbb{Z}$. We also prove an analogue of the Calderon-Vail

Ru Geng, Yixian Gao, Hongkun Zhang, Jian Zu

The rapid spread of COVID-19 disease has had a significant impact on the world. In this paper, we study COVID-19 data interpretation and visualization using open-data sources for 351 cities and towns in Massachusetts from December 6, 2020 to September 25, 2021. Because cities are embedded in rather complex transportation networks, we construct the spatio-tem

Makoto Katori

In the series of lectures, we will discuss probability laws of random points, curves, and surfaces. Starting from a brief review of the notion of martingales, one-dimensional Brownian motion (BM), and the $D$-dimensional Bessel processes, BES$_{D}$, $D \geq 1$, first we study Dyson's Brownian motion model with parameter $\beta >0$, DYS$_{\beta}$, which is re

David Belius, Marius A. Schmidt

We study the number of local maxima with given radial derivative of spherical mixed $p$-spin models and prove that the second moment matches the square of the first moment on exponential scale for arbitrary mixtures and any radial derivative. This is surprising, since for the number of local maxima with given radial derivative and given energy the correspond

Marcel Risch, Dulce M. Morales, Javier Villalobos, Denis Antipin

Chemical energy storage is an attractive solution to secure a sustainable energy supply. It requires an electrocatalyst to be implemented efficiently. In order to rationally improve the electrocatalyst materials and thereby the reaction efficiency, one must reveal the nature of the electrocatalyst under reaction conditions, i.e., its active state. For a bett

Luciano Zinni, Matías Bejas, Hiroyuki Yamase, Andrés Greco

The discovery of superconductivity in infinite-layer nickelates is presently an important topic in condensed-matter physics, and potential similarities to and differences from cuprates are under intense debate. We determine general features of the charge excitation spectrum in nickelates from two opposite viewpoints: (i) Nickelates are regarded as strongly c

Meng Liu, Tamal K. Dey, David F. Gleich

Complex prediction models such as deep learning are the output from fitting machine learning, neural networks, or AI models to a set of training data. These are now standard tools in science. A key challenge with the current generation of models is that they are highly parameterized, which makes describing and interpreting the prediction strategies difficult

Daniel Lobser, Jay Van Der Wall, Joshua Goldberg

Scalable coherent control hardware for quantum information platforms is rapidly growing in priority as their number of available qubits continues to increase. As these systems scale, more calibration steps are needed, leading to challenges with system instability as calibrated parameters drift. Moreover, the sheer amount of data required to run circuits with

Nicolas Tholozan, Konstantinos Tsouvalas

We exhibit the first examples of residually finite non-linear Gromov hyperbolic groups. Our examples are constructed as amalgamated products of torsion-free cocompact lattices in the rank 1 Lie group $\mathrm{Sp}(d,1)$, $d\geq 2$ along maximal cyclic subgroups.

Meghanath Macha Y, Sriram Ravindran, Deepak Pai, Anish Narang

We propose a fairness measure relaxing the equality conditions in the popular equal odds fairness regime for classification. We design an iterative, model-agnostic, grid-based heuristic that calibrates the outcomes per sensitive attribute value to conform to the measure. The heuristic is designed to handle high arity attribute values and performs a per attri

Siddharth Tiwary, Harsh Sharma, Himadri Shekhar Dhar

The transfer and storage of quantum information in a hybrid quantum system, consisting of an ensemble of atoms or spins interacting with a cavity, is adversely affected by the inhomogeneity of the spins, which negates the coherent exchange of excitations between the physical components. Using a full quantum treatment based on variational renormalization grou

M. A. Acero, B. Acharya, P. Adamson, L. Aliaga

Measuring observables to constrain models using maximum-likelihood estimation is fundamental to many physics experiments. Wilks' theorem provides a simple way to construct confidence intervals on model parameters, but it only applies under certain conditions. These conditions, such as nested hypotheses and unbounded parameters, are often violated in neutrino

Yuxiang Wang, You Zhang, Zhiyao Duan, Mark Bocko

In the growing field of virtual auditory display, personalized head-related transfer functions (HRTFs) play a vital role in establishing an accurate sound image for mixed and augmented reality applications. In this work, we propose an HRTF personalization method employing convolutional neural networks (CNN) to predict a subject HRTFs for all directions from

Marcel Guardia, Pau Martín, Jaime Paradela, Tere M. Seara

Consider the planar 3 Body Problem with masses $m_0,m_1,m_2>0$. In this paper we address two fundamental questions: the existence of oscillatory motions and of chaotic hyperbolic sets. In 1922, Chazy classified the possible final motions of the three bodies, that is the behaviors the bodies may have when time tends to infinity. One of the possible behaviors

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Based on a sample of $448.1\times10^6\ \psi(3686)$ events collected with the BESIII detector, a study of $\psi(3686)\to\Lambda\bar{\Lambda}\pi^0$ and $\psi(3686)\to\Lambda\bar{\Lambda}\eta$ is performed. Evidence of the isospin-violating decay $\psi(3686)\to\Lambda\bar{\Lambda}\pi^0$ is found for the first time with a statistical significance of $3.7\sigma$,

Magdalini Paschali, Qingyu Zhao, Ehsan Adeli, Kilian M. Pohl

A fundamental approach in neuroscience research is to test hypotheses based on neuropsychological and behavioral measures, i.e., whether certain factors (e.g., related to life events) are associated with an outcome (e.g., depression). In recent years, deep learning has become a potential alternative approach for conducting such analyses by predicting an outc

Michael Y. Hua, Sachin S. Desai, Amy C. Roma, Angela Di Fulvio

This is an abridged abstract; please see the full paper. This paper evaluates whether the nuclear nonproliferation regime applies to fusion power plants and finds that, legally, the regime does not apply. The paper then examines whether the nonproliferation regime should apply to fusion based on a technical evaluation. The paper concludes that fusion should

Tianqi Guo, Yin Wang, Luis Solorio, Jan P. Allebach

We share our recent findings in an attempt to train a universal segmentation network for various cell types and imaging modalities. Our method was built on the generalized U-Net architecture, which allows the evaluation of each component individually. We modified the traditional binary training targets to include three classes for direct instance segmentatio

Alan M. Knee, Isobel M. Romero-Shaw, Paul D. Lasky, Jess McIver

Orbital eccentricity is a key signature of dynamical binary black hole formation. The gravitational waves from a coalescing binary contain information about its orbital eccentricity, which may be measured if the binary retains sufficient eccentricity near merger. Dedicated waveforms are required to measure eccentricity. Several models have been put forward,

Diego Ayala, Daniel Durini, Jose Rangel-Magdaleno

Different space-filling curves (SFCs) are briefly reviewed in this paper, and a new one is proposed. A century has passed between the inception of this kind of curves, since then they have been found useful in computer science, particularly in data storage and indexing due to their clustering properties, being Hilbert curve the most well-known member of the

Tiago Gomes, Carlos Correia, Lisa Bardou, Olivier Beltramo-Martin

Large amounts of Adaptive-Optics (AO) control loop data and telemetry are currently inaccessible to end-users. Broadening access to those data has the potential to change the AO landscape on many fronts, addressing several use-cases such as derivation of the system's PSF, turbulence characterisation and optimisation of system control. We address one of the b

Kevin T. Grosvenor, Ruben Lier, Piotr Surówka

Proliferation of defects is a mechanism that allows for topological phase transitions. Such a phase transition is found in two dimensions for the XY-model, which lies in the Berezinskii-Kosterlitz-Thouless (BKT) universality class. The transition point can be found using renormalization group analysis. We apply renormalization group arguments to determine th

Natalia Zorii

The paper deals with minimum energy problems in the presence of external fields on a locally compact space $X$ with respect to a function kernel $\kappa$ satisfying the energy and consistency principles. For quite a general (not necessarily lower semicontinuous) external field $f$, we establish sufficient and/or necessary conditions for the existence of $\la

Lianghao Xia, Chao Huang, Chuxu Zhang

Graph Neural Networks (GNNs) have been shown as promising solutions for collaborative filtering (CF) with the modeling of user-item interaction graphs. The key idea of existing GNN-based recommender systems is to recursively perform the message passing along the user-item interaction edge for refining the encoded embeddings. Despite their effectiveness, howe

Junyu Liu, Connor T. Hann, Liang Jiang

In this paper, we propose the Quantum Data Center (QDC), an architecture combining Quantum Random Access Memory (QRAM) and quantum networks. We give a precise definition of QDC, and discuss its possible realizations and extensions. We discuss applications of QDC in quantum computation, quantum communication, and quantum sensing, with a primary focus on QDC f

Stuart Thiel, Larry Thiel, Gregory Butler

This paper presents ThielSort, a practical implementation of the Diverting Fast Radix (DFR) Algorithm. The theoretical improvements over classical radix sorts are outlined and implementation details are specified to demonstrate that the algorithm is competitive with the state of the art. The effectiveness of this implementation of the DFR algorithm is shown

Kajal Das

Twin-width is a recently introduced graph parameter. In this article, we compute twin-width of various finite graphs. In particular, we prove that the twin-widths of finite graphs with 4 and 5 vertices are less than equal to 1 and 2, respectively. We show that the constructions of dual graph and line graph do not preserve twin-width. Also, we give upper boun

Lin-Lin Su, Jun Ren, Z. D. Wang, Yan-Kui Bai

We study the properties of multipartite quantum correlation (MQC) in a one-dimensional spin-1/2 $XY$ chain, where the three-spin reduced states are focused on and the four introduced MQC measures are based on entanglement negativity and entanglement of formation. It is found that, even in the Ising case, the three-spin subsystems have the long-range MQCs and

Gabriele De Luca, Thomas J. Lampoltshammer, Johannes Scholz

A human is a thing that moves in space. Like all things that move in space, we can in principle use differential equations to describe their motion as a set of functions that maps time to position (and velocity, acceleration, and so on). With inanimate objects, we can reliably predict their trajectories by using differential equations that account for up to

Daniel B. Straus, Tomasz Klimczuk, Xianghan Xu, Robert J. Cava

Bulk CsEuBr$_3$ and CsEuCl$_3$ are experimentally shown to be magnetic semiconductors that order antiferromagnetically at Neel temperatures of 2.0 K and 1.0 K respectively. Given that nanoparticles and thin films of CsEuCl$_3$ have been reported to order ferromagnetically at a similar temperature, our observation of antiferromagnetic ordering in CsEuBr$_3$ a

Jisuke Kubo, Jeffrey Kuntz, Jonas Rezacek, Philipp Saake

We consider a generic model of quadratic gravity coupled to a single scalar and investigate the effects of gravitational degrees of freedom on inflationary parameters. We find that quantum corrections arising from the massive spin-2 ghost generate significant contributions to the effective inflationary potential and allow for a realization of the spontaneous

Thomas Seive, John Chisholm, Floriane Leclercq, Gregory Zeimann

Ionizing photons must have escaped from high-redshift galaxies, but the neutral high-redshift intergalactic medium makes it unlikely to directly detect these photons during the Epoch of Reionization. Indirect methods of studying ionizing photon escape fractions present a way to infer how the first galaxies may have reionized the universe. Here, we use HET/LR

Katrin Becker, Daniel Butter, Anindya Sengupta

We describe the linearized supergeometry of eleven dimensional supergravity with four off-shell local supersymmetries. We start with a background Minkowski 11D, N=1 superspace, and an additional ingredient of a global, constant, $G_2$-structure which facilitates the definition of a $4|4+7$ background superspace. A bottom-up construction of linear fluctuation

Prathamesh D. Tamhane, Brian R. McNamara, Helen R. Russell, Alastair C. Edge

Molecular gas flows are analyzed in 14 cluster galaxies (BCGs) centered in cooling hot atmospheres. The BCGs contain $10^{9}-10^{11}~\rm M_\odot$ of molecular gas, much of which is being moved by radio jets and lobes. The molecular flows and radio jet powers are compared to molecular outflows in 45 active galaxies within $z<0.2$. We seek to understand the re

O. Onishchenko, G. Guarnieri, P. Rosillo-Rodes, D. Pijn

Quantum thermodynamics is aimed at grasping thermodynamic laws as they apply to thermal machines operating in the deep quantum regime, a regime in which coherences and entanglement are expected to matter. Despite substantial progress, however, it has remained difficult to develop thermal machines in which such quantum effects are observed to be of pivotal im

John Soltis, Michelle Ntampaka, John Wu, John ZuHone

The eROSITA X-ray telescope, launched in 2019, is predicted to observe roughly 100,000 galaxy clusters. Follow-up observations of these clusters from Chandra, for example, will be needed to resolve outstanding questions about galaxy cluster physics. Deep Chandra cluster observations are expensive and follow-up of every eROSITA cluster is infeasible, therefor

D. Barba-González, C. Albertus, M. Ángeles Pérez-García

We use Molecular Dynamics simulations to study the formation and stability of single and multicomponent lattices in the outer crust of Neutron Stars. Including an improved treatment for Gaussian charge distributions of ions we obtain the expressions for the potential and forces arising from electron screened Coulomb interactions using the efficient Ewald sum

Jin Ming Koh, Tommy Tai, Ching Hua Lee

Chiral edge states are highly sought-after as paradigmatic topological states relevant to both quantum information processing and dissipationless electron transport. Using superconducting transmon-based quantum computers, we demonstrate chiral topological propagation that is induced by suitably designed interactions, instead of flux or spin-orbit coupling. A

Kasia Budzik, Davide Gaiotto, Justin Kulp, Jingxiang Wu

We study a class of universal Feynman integrals which appear in four-dimensional holomorphic theories. We recast the integrals as the Fourier transform of a certain polytope in the space of loop momenta (aka the ``Operatope''). We derive a set of quadratic recursion relations which appear to fully determine the final answer. Our strategy can be applied to a

Qifeng Huang, Lulu Fan

Here we present a statistical study on tidal features around massive early-type galaxies (ETGs). Utilizing the imaging data of the Hyper Suprime-Cam Subaru Strategic Program (HSC-SSP), we measure the flux fraction of tidal features ($f_{\rm tidal}$) in 2649 ETGs with stellar mass $M_*>10^{11}M_{\odot}$ and redshift $0.05<z<0.15$ using automated techniques. T

Shing Yan Li, Washington Taylor

We give a general description of gauge symmetry breaking using vertical and remainder fluxes in 4D F-theory models. The fluxes can break a geometric gauge group to a smaller group and induce chiral matter, even when the larger group admits no chiral matter representations. We focus specifically on applications to realizations of the Standard Model gauge grou

Nicholas Law, Alan Vasquez Soto, Hank Corbett, Nathan Galliher

The Argus Optical Array will be the first all-sky, arcsecond-resolution, 5-m class telescope. The 55 GPix Array, currently being prototyped, will consist of 900 telescopes with 61 MPix very-low-noise CMOS detectors enabling sub-second cadences. Argus will observe every part of the northern sky for 6-12 hours per night, achieving a simultaneously high-cadence

Wei-Xiang Feng

In the framework of gravothermal evolution of an ideal monatomic fluid, I examine the dynamical instability of the fluid sphere in ($N$+1) dimensions by exploiting Chandrasekhar's criterion to each quasistatic equilibrium along the sequence of the evolution. Once the instability is triggered, it would probably collapse into a black hole if no other interacti

Kaitlyn Shin, Kiyoshi W. Masui, Mohit Bhardwaj, Tomas Cassanelli

Fast radio bursts (FRBs) are brief, energetic, extragalactic flashes of radio emission whose progenitors are largely unknown. Although studying the FRB population is essential for understanding how these astrophysical phenomena occur, such studies have been difficult to conduct without large numbers of FRBs and characterizable observational biases. Using the

Yang Zou, Jongheon Jeong, Latha Pemula, Dongqing Zhang

Visual anomaly detection is commonly used in industrial quality inspection. In this paper, we present a new dataset as well as a new self-supervised learning method for ImageNet pre-training to improve anomaly detection and segmentation in 1-class and 2-class 5/10/high-shot training setups. We release the Visual Anomaly (VisA) Dataset consisting of 10,821 hi

Mohamed Hibat-Allah, Roger G. Melko, Juan Carrasquilla

Recurrent neural networks (RNNs) are a class of neural networks that have emerged from the paradigm of artificial intelligence and has enabled lots of interesting advances in the field of natural language processing. Interestingly, these architectures were shown to be powerful ansatze to approximate the ground state of quantum systems. Here, we build over th

Dominik Hahn, Maxime Dupont, Markus Schmitt, David J. Luitz

The quantum Jarzynski equality and the Crooks relation are fundamental laws connecting equilibrium processes with nonequilibrium fluctuations. They are promising tools to benchmark quantum devices and measure free energy differences. While they are well established theoretically and also experimental realizations for few-body systems already exist, their exp

Yibin Luo, Lulu Fan, Hu Zou, Lu Shen

\emph{Wide-field Infrared Survey Explorer} all-sky survey has discovered a new population of hot dust-obscured galaxies (Hot DOGs), which has been confirmed to be dusty quasars. Previous statistical studies have found significant overdensities of sub-millimeter and mid-IR selected galaxies around Hot DOGs, indicating they may reside in dense regions. Here we

Vincent Van Hemelryck

In this paper, minimal supersymmetric AdS$_3$ solutions on $G_2$-orientifolds of type IIA and IIB supergravity are studied. These are obtained by techniques of the bispinor formalism. A straightforward argument is derived against AdS$_3$ solutions in massless type IIA string theory on such $G_2$-backgrounds. Furthermore, it is shown that some of the AdS$_3$

Dawid Brzeminski, Zackaria Chacko, Abhish Dev, Ina Flood

We consider the general class of theories in which there is a new ultralight scalar field that mediates an equivalence principle violating, long-range force. In such a framework, the sun and the earth act as sources of the scalar field, leading to potentially observable location dependent effects on atomic and nuclear spectra. We determine the sensitivity of

Hamsa Padmanabhan, Abraham Loeb

Galaxy mergers at high redshifts trigger the activity of their central supermassive black holes, eventually also leading to their coalescence -- and a potential source of low-frequency gravitational waves detectable by the SKA Pulsar Timing Array (PTA). Two key parameters related to the fuelling of black holes are the Eddington ratio of quasar accretion $\et

Alexander C. Sobotka, Adrienne L. Erickcek, Tristan L. Smith

We test the assumption of entropy conservation between Big Bang nucleosynthesis and recombination by considering a massive particle that decays into a mixture of photons and other relativistic species. We employ Planck temperature and polarization anisotropies, COBE/FIRAS spectral distortion bounds, and the observed primordial deuterium abundance to constrai

Xander Faber, Jon Grantham, Everett W. Howe

The gonality of a smooth geometrically connected curve over a field $k$ is the smallest degree of a nonconstant $k$-morphism from the curve to the projective line. In general, the gonality of a curve of genus $g \ge 2$ is at most $2g - 2$. Over finite fields, a result of F.K. Schmidt from the 1930s can be used to prove that the gonality is at most $g+1$. Via

William D. Biggs, Jorge E. Santos

We construct the holographic duals to a large $N$, strongly coupled $\mathcal{N}=4$ super Yang-Mills conformal field theory defined on a four-dimensional de Sitter-Schwarzschild background. There are two distinct five-dimensional bulk solutions. One, named the black tunnel, is static and possesses two disconnected horizons. The other, the black hammock, cont

Marco Astorino

We show how to remove from the rotating C-metric spacetime, which describes accelerating Kerr black holes, both conical singularities. This can be done by embedding the metric into a swirling gravitational universe, through a proper Ehlers transformation. The spin-spin interaction between the external rotational background and the black hole provides the sou

Hank Corbett, Alan Vasquez Soto, Lawrence Machia, Nathan Galliher

The Argus Optical Array is a synoptic survey observatory, currently in development, that will have a total collecting area equivalent to a 5-meter monolithic telescope and an all-sky field of view, multiplexed from 900 commercial off-the-shelf telescopes. The Array will observe 7916 deg$^2$ every second during high-speed operations ($m_g\leq16.1$) and every

Ragadeepika Pucha, Naveen A. Reddy, Arjun Dey, Stéphanie Juneau

We investigate the effects of stellar populations and sizes on Ly$\alpha$ escape in 27 spectroscopically confirmed and 35 photometric Lyman-Alpha Emitters (LAEs) at z $\approx$ 2.65 in seven fields of the Bo\"otes region of the NOAO Deep Wide-Field Survey. We use deep $HST$/WFC3 imaging to supplement ground-based observations and infer key galaxy properties.

Devontae Baxter, Michael Cooper, Michael Balogh, Tim Carleton

We model satellite quenching at $z \sim 1$ by combining $14$ massive ($10^{13.8} < M_{\mathrm{halo}}/\mathrm{M}_{\odot} < 10^{15}$) clusters at $0.8 < z < 1.3$ from the GOGREEN and GCLASS surveys with accretion histories of $56$ redshift-matched analogs from the IllustrisTNG simulation. Our fiducial model, which is parameterized by the satellite quenching ti

Eric R. Coughlin, Chris Nixon

The tidal disruption of stars by supermassive black holes (SMBHs) probes relativistic gravity. In the coming decade, the number of observed tidal disruption events (TDEs) will grow by several orders of magnitude, allowing statistical inferences of the properties of the SMBH and stellar populations. Here we analyse the probability distribution functions of th

Yu-Ming Chen, Manibrata Sen, Walter Tangarife, Douglas Tuckler

Novel neutrino self-interaction can open up viable parameter space for the relic abundance of sterile-neutrino dark matter (S$\nu$DM). In this work, we constrain the relic target using core-collapse supernova which features the same fundamental process and a similar environment to the early universe era when S$\nu$DM is dominantly produced. We present a deta

Monica Gallegos-Garcia, Maya Fishbach, Vicky Kalogera, Christopher P L Berry

Gravitational-wave observations of binary black hole (BBH) systems point to black hole spin magnitudes being relatively low. These measurements appear in tension with high spin measurements for high-mass X-ray binaries (HMXBs). We use grids of MESA simulations combined with the rapid population-synthesis code COSMIC to examine the origin of these two binary

Xiaoming Zhao, Zhizhen Zhao, Alexander G. Schwing

While recovery of geometry from image and video data has received a lot of attention in computer vision, methods to capture the texture for a given geometry are less mature. Specifically, classical methods for texture generation often assume clean geometry and reasonably well-aligned image data. While very recent methods, e.g., adversarial texture optimizati

Sheng-Yu Wang, David Bau, Jun-Yan Zhu

Deep generative models make visual content creation more accessible to novice users by automating the synthesis of diverse, realistic content based on a collected dataset. However, the current machine learning approaches miss a key element of the creative process -- the ability to synthesize things that go far beyond the data distribution and everyday experi

Vitor Guizilini, Igor Vasiljevic, Jiading Fang, Rares Ambrus

Modern 3D computer vision leverages learning to boost geometric reasoning, mapping image data to classical structures such as cost volumes or epipolar constraints to improve matching. These architectures are specialized according to the particular problem, and thus require significant task-specific tuning, often leading to poor domain generalization performa

Benjamin Steltner, Thorben Menne, Maria Alessandra Papa, Heinz-Bernd Eggenstein

Searches for continuous gravitational waves target nearly monochromatic gravitational wave emission from e.g. non-axysmmetric fast-spinning neutron stars. Broad surveys often require to explicitly search for a very large number of different waveforms, easily exceeding $\sim10^{17}$ templates. In such cases, for practical reasons, only the top, say $\sim10^{1

Fernando Marchesano, Joan Quirant, Matteo Zatti

We consider massive type IIA orientifold compactifications of the form AdS$_4 \times X_6$, where $X_6$ admits a Calabi-Yau metric and is threaded by background fluxes. From a 4d viewpoint, fluxes generate a potential whose vacua have been classified, including one $\mathcal{N}=1$ and three perturbatively stable $\mathcal{N}=0$ branches. We reproduce this res

Yongming Rao, Wenliang Zhao, Yansong Tang, Jie Zhou

Recent progress in vision Transformers exhibits great success in various tasks driven by the new spatial modeling mechanism based on dot-product self-attention. In this paper, we show that the key ingredients behind the vision Transformers, namely input-adaptive, long-range and high-order spatial interactions, can also be efficiently implemented with a convo

Charles Burnette

A ring $R$ is called weakly periodic if every $x \in R$ can be written in the form $x = a + b,$ where $a$ is nilpotent and $b^m = b$ for some integer $m > 1.$ The aim of this note is to consider when a nonzero nilpotent element $r$ is the period of some power map $f(x) = x^n,$ in the sense that $f(x + r) = f(x)$ for all $x \in R,$ and how this relates to the

Milán Mosonyi, Gergely Bunth, Péter Vrana

We give systematic ways of defining monotone quantum relative entropies and (multi-variate) quantum R\'enyi divergences starting from a set of monotone quantum relative entropies. Despite its central importance in information theory, only two additive and monotone quantum extensions of the classical relative entropy have been known so far, the Umegaki and th