February 2021 arXiv papers — page 9

Die Duan, Jiansen He, Trevor A. Bowen, Lloyd D. Woodham

The anisotropy of solar wind turbulence is a critical issue in understanding the physics of energy transfer between scales and energy conversion between fields and particles in the heliosphere. Using the measurement of \emph{Parker Solar Probe} (\emph{PSP}), we present an observation of the anisotropy at kinetic scales in the slow, Alfvénic, solar wind in th

Alysson Gold, JP Paquette, Anna Stockklauser, Matthew J. Reagor

Assembling future large-scale quantum computers out of smaller, specialized modules promises to simplify a number of formidable science and engineering challenges. One of the primary challenges in developing a modular architecture is in engineering high fidelity, low-latency quantum interconnects between modules. Here we demonstrate a modular solid state arc

Zhiguang Zhao

In the present paper, we develop the algorithmic correspondence theory for hybrid logic with binder. We define the class of Sahlqvist inequalities, each inequality of which is shown to have a first-order frame correspondent effectively computable by an algorithm ALBA.

Shuze Liu, Weiran Shen, Haifeng Xu

A decision maker is choosing between an active action (e.g., purchase a house, invest certain stock) and a passive action. The payoff of the active action depends on the buyer's private type and also an unknown state of nature. An information seller can design experiments to reveal information about the realized state to the decision maker, and would lik

Harlin Lee, Boyue Li, Shelly DeForte, Mark Splaingard

Despite being crucial to health and quality of life, sleep -- especially pediatric sleep -- is not yet well understood. This is exacerbated by lack of access to sufficient pediatric sleep data with clinical annotation. In order to accelerate research on pediatric sleep and its connection to health, we create the Nationwide Children's Hospital (NCH) Sleep

Yariv Aizenbud, Ariel Jaffe, Meng Wang, Amber Hu

Modeling the distribution of high dimensional data by a latent tree graphical model is a prevalent approach in multiple scientific domains. A common task is to infer the underlying tree structure, given only observations of its terminal nodes. Many algorithms for tree recovery are computationally intensive, which limits their applicability to trees of modera

Joaquim Dias Garcia, Alexandre Street, Tito Homem-de-Mello, Francisco D. Muñoz

Forecasting and decision-making are generally modeled as two sequential steps with no feedback, following an open-loop approach. In this paper, we present application-driven learning, a new closed-loop framework in which the processes of forecasting and decision-making are merged and co-optimized through a bilevel optimization problem. We present our methodo

Jingbo Jiang, Xizi Chen, Chi-Ying Tsui

Recent literature has shown that convolutional neural networks (CNNs) with large kernels outperform vision transformers (ViTs) and CNNs with stacked small kernels in many computer vision tasks, such as object detection and image restoration. The Winograd transformation helps reduce the number of repetitive multiplications in convolution and is widely support

Youfa Li, Shengli Fan, Yanfen Huang

The traditional approaches to computerized tomography (CT) depend on the samples of Radon transform at multiple angles. In optics, the real time imaging requires the reconstruction of an object by the samples of Radon transform at a single angle (SA). Driven by this and motivated by the connection between Bin Han's construction of wavelet frames (e.g [13

Pierre Marchand, Vincent Guillet, Ugo Lebreuilly, Mordecai-Mark Mac Low

Dust grains play a major role in many astrophysical contexts. They affect the chemical, magnetic, dynamical, and optical properties of their environment, from galaxies down to the interstellar medium, star-forming regions, and protoplanetary disks. Their coagulation leads to shifts in their size distribution and ultimately to the formation of planets. Howeve

Sarthak Pati, Siddhesh P. Thakur, İbrahim Ethem Hamamcı, Ujjwal Baid

Deep Learning (DL) has the potential to optimize machine learning in both the scientific and clinical communities. However, greater expertise is required to develop DL algorithms, and the variability of implementations hinders their reproducibility, translation, and deployment. Here we present the community-driven Generally Nuanced Deep Learning Framework (G

Jiameng Fan, Wenchao Li

Deep reinforcement learning (DRL) agents are often sensitive to visual changes that were unseen in their training environments. To address this problem, we leverage the sequential nature of RL to learn robust representations that encode only task-relevant information from observations based on the unsupervised multi-view setting. Specifically, we introduce a

Joel A. Rosenfeld, Benjamin Russo, Xiuying Li

This manuscript gives a theoretical framework for a new Hilbert space of functions, the so called occupation kernel Hilbert space (OKHS), that operate on collections of signals rather than real or complex numbers. To support this new definition, an explicit class of OKHSs is given through the consideration of a reproducing kernel Hilbert space (RKHS). This s

Kan Jiang, Derong Kong, Wenxia Li

Let $m\in\mathbb N_{\ge 2}$, and let $\mathcal K=\{K_λ: λ\in(0, 1/m]\}$ be a class of Cantor sets, where $K_λ=\{\sum_{i=1}^\infty d_iλ^i: d_i\in\{0,1,\ldots, m-1\}, i\ge 1\}$. We investigate in this paper the likelyhood of a fixed point in the Cantor sets of $\mathcal K$. More precisely, for a fixed point $x\in(0,1)$ we consider the parameter set $Λ(x)=\{λ\i

Benjamín A. Itzá-Ortiz, Rubén A. Martínez-Avendaño, Hiroshi Nakazato

In this paper we show that the closure of the numerical range of an $n+1$-periodic tridiagonal operator is equal to the numerical range of a $2(n+1)\times 2(n+1)$ complex matrix.

Feng Xue, Junfeng Cao, Yu Zhou, Fei Sheng

Monocular depth prediction is an important task in scene understanding. It aims to predict the dense depth of a single RGB image. With the development of deep learning, the performance of this task has made great improvements. However, two issues remain unresolved: (1) The deep feature encodes the wrong farthest region in a scene, which leads to a distorted

Ranwa Al Mallah, Godwin Badu-Marfo, Bilal Farooq

Federated learning (FL) is a machine learning technique that aims at training an algorithm across decentralized entities holding their local data private. Wireless mobile networks allow users to communicate with other fixed or mobile users. The road traffic network represents an infrastructure-based configuration of a wireless mobile network where the Connec

Shubham Toshniwal, Sam Wiseman, Karen Livescu, Kevin Gimpel

Transformer language models have made tremendous strides in natural language understanding tasks. However, the complexity of natural language makes it challenging to ascertain how accurately these models are tracking the world state underlying the text. Motivated by this issue, we consider the task of language modeling for the game of chess. Unlike natural l

Li-Ping Yang, Zubin Jacob

Classical structured light with controlled polarization and orbital angular momentum (OAM) of electromagnetic waves has varied applications in optical trapping, bio-sensing, optical communications and quantum simulations. The classical electromagnetic theory of such structured light beams and pulses have advanced significantly over the last two decades. Howe

Chaobing Song, Jelena Diakonikolas

Cyclic block coordinate methods are a fundamental class of optimization methods widely used in practice and implemented as part of standard software packages for statistical learning. Nevertheless, their convergence is generally not well understood and so far their good practical performance has not been explained by existing convergence analyses. In this wo

Antonios Saravanos, Dongnanzi Zheng, Stavros Zervoudakis, Donatella Delfino

Locimetric authentication is a form of graphical authentication in which users validate their identity by selecting predetermined points on a predetermined image. Its primary advantage over the ubiquitous text-based approach stems from users' superior ability to remember visual information over textual information, coupled with the authentication process

Sanath Kumar Krishnamurthy, Vitor Hadad, Susan Athey

Computationally efficient contextual bandits are often based on estimating a predictive model of rewards given contexts and arms using past data. However, when the reward model is not well-specified, the bandit algorithm may incur unexpected regret, so recent work has focused on algorithms that are robust to misspecification. We propose a simple family of co

Pavel Etingof, Dmitri Nikshych, Victor Ostrik

In arXiv:1910.12059 Liu, Palcoux and Wu proved a remarkable necessary condition for a fusion ring to admit a unitary categorification, by constructing invariants of the fusion ring that have to be positive if it is unitarily categorifiable. The main goal of this note is to provide a somewhat more direct proof of this result. In the last subsection we discuss

P. De La Torre Luque, M. N. Mazziotta, F. Loparco, F. Gargano

Recent cosmic-ray measurements are challenging our models of propagation in the Galaxy. A good characterization of the secondary cosmic rays (B, Be, Li and sub-iron species) is crucial to constrain these models and exploit the precision of modern CR experiments. In this work, a Markov chain Monte Carlo analysis has been implemented to fit the experimental fl

Kevan Bell, Lyazzat Mukhangaliyeva, Layla Khalili, Parsin Haji Reza

An improved method of remote optical absorption spectroscopy and hyperspectral optical absorption imaging is described which takes advantage of the photoacoustic remote sensing detection architecture. A wide range of photoacoustic excitation wavelengths ranging from 210 nm to 1550 nm was provided by a nanosecond tunable source allowing access to various sali

Richard Allmendinger, Joshua Knowles

Multiobjective optimization problems with heterogeneous objectives are defined as those that possess significantly different types of objective function components (not just incommensurable in units or scale). For example, in a heterogeneous problem the objective function components may differ in formal computational complexity, practical evaluation effort (

Burcu Gürbüz

Delay differential equations are of great importance in science, engineering, medicine and biological models. These type of models include time delay phenomena which is helpful for characterising the real-world applications in machine learning, mechanics, economics, electrodynamics and so on. Besides, special classes of functional differential equations have

Xixun Lin, Jia Wu, Chuan Zhou, Shirui Pan

User cold-start recommendation is a long-standing challenge for recommender systems due to the fact that only a few interactions of cold-start users can be exploited. Recent studies seek to address this challenge from the perspective of meta learning, and most of them follow a manner of parameter initialization, where the model parameters can be learned by a

Rasoul Abazari

The purpose of this paper is to define statistically convergent sequences with respect to the metrics on generalized metric spaces (g-metric spaces) and investigate basic properties of this statistical form of convergence.

Chen Li, JinZhe Jiang, YaQian Zhao, RenGang Li

Hyperparameter optimization is a challenging problem in developing deep neural networks. Decision of transfer layers and trainable layers is a major task for design of the transfer convolutional neural networks (CNN). Conventional transfer CNN models are usually manually designed based on intuition. In this paper, a genetic algorithm is applied to select tra

Yaohui Wang, Guozheng Li, Zijian Wang, Yu Kang

Cloud-based services are surging into popularity in recent years. However, outages, i.e., severe incidents that always impact multiple services, can dramatically affect user experience and incur severe economic losses. Locating the root-cause service, i.e., the service that contains the root cause of the outage, is a crucial step to mitigate the impact of th

Simon Bilik, Lukas Kratochvila, Adam Ligocki, Ondrej Bostik

The Varroa destructor mite is one of the most dangerous Honey Bee (Apis mellifera) parasites worldwide and the bee colonies have to be regularly monitored in order to control its spread. Here we present an object detector based method for health state monitoring of bee colonies. This method has the potential for online measurement and processing. In our expe

Vasily Romanchak

In this paper, we prove that the Fechner and Stevens laws are equivalent (coincide up to isomorphism). Therefore, the problem does not exist.

Gorsev Argin, Burak Pak, Handan Turkoglu

The extensive use of smartphones in our everyday lives has created new modes of appropriation and behavior in public spaces. Recognition of these are essential for urban design and planning practices which help us to improve the relationship between humans, technologies, and urban environment. This study aims to research smartphone users in public space by o

Mark T Keane, Eoin M Kenny, Eoin Delaney, Barry Smyth

In recent years, there has been an explosion of AI research on counterfactual explanations as a solution to the problem of eXplainable AI (XAI). These explanations seem to offer technical, psychological and legal benefits over other explanation techniques. We survey 100 distinct counterfactual explanation methods reported in the literature. This survey addre

Daniel D. Brown, Huy Tuong Cao, Alexei Ciobanu, Peter Veitch

Differential wavefront sensing is an essential technique for optimising the performance of many precision interferometric experiments. Perhaps the most extensive application of this is for alignment sensing using radio-frequency beats measured with quadrant photodiodes. Here we present a new technique that uses optical demodulation to measure such optical be

Jun Hu, Yizhou Liang, Rui Ma

This paper presents the first family of conforming finite element divdiv complexes on tetrahedral grids in three dimensions. In these complexes, finite element spaces of $H(\text{divdiv},Ω;\mathbb{S})$ are from a current preprint [Chen and Huang, arXiv: 2007.12399, 2020] while finite element spaces of both $H(\text{symcurl},Ω;\mathbb{T})$ and $H^1(Ω;\mathbb{

Haikal Abdulah, Benjamin Huber, Sinan Lal, Hassan Abdallah

CXR-Net is a two-module Artificial Intelligence pipeline for the quick detection of SARS-CoV-2 from chest X-rays (CXRs). Module 1 was trained on a public dataset of 6395 CXRs with radiologist annotated lung contours to generate masks of the lungs that overlap the heart and large vasa. Module 2 is a hybrid convnet in which the first convolutional layer with l

Ce Wang, Moshiur Farazi, Nick Barnes

General purpose semantic segmentation relies on a backbone CNN network to extract discriminative features that help classify each image pixel into a 'seen' object class (ie., the object classes available during training) or a background class. Zero-shot semantic segmentation is a challenging task that requires a computer vision model to identify imag

Xinyi Huang, Naman Jain, Mahdi Abkar, Robert Kunz

Calibrating a Reynolds-averaged Navier-Stokes (RANS) model against data leads to an improvement. Determining {\it a priori} if such an improvement generalizes to flows outside the calibration data is an outstanding challenge. This work attempts to address this challenge via global epistemic Uncertainty Quantification (UQ). Unlike the available epistemic UQ m

Leandro Eichenberger, Michael Cochez, Benjamin Heitmann, Stefan Decker

Finding out the differences and commonalities between the knowledge of two parties is an important task. Such a comparison becomes necessary, when one party wants to determine how much it is worth to acquire the knowledge of the second party, or similarly when two parties try to determine, whether a collaboration could be beneficial. When these two parties c

Xiang Sun, Kenichi Soga, Alp Cinar, Zhenxiang Su

Geothermal heat, as renewable energy, shows great advantage with respect to its environmental impact due to its significantly lower CO2 emissions than conventional fossil fuel. Open and closed-loop geothermal heat pumps, which utilize shallow geothermal systems, are an efficient technology for cooling and heating buildings, especially in urban areas. Integra

D. Morachis Galindo, F. Rojas, Jesús A. Maytorena

The generalization of the geometric phase to the realm of mixed states is known as Uhlmann phase. Recently, applications of this concept to the field of topological insulators have been made and an experimental observation of a characteristic critical temperature at which the topological Uhlmann phase disappears has also been reported. Surprisingly, to our k

Zoë Bell, Jasmine Camero, Karina Cho, Trevor Hyde

Let $L_d$ be the Lattès map associated to the multiplication-by-$d$ endomorphism of an elliptic curve $E$ defined over a finite field $\mathbb{F}_q$. We determine the density $δ(L_d,q)$ of periodic points for $L_d$ in $\mathbb{P}^1(\mathbb{F}_q)$. We show that the periodic point densities $δ(L_d,q^n)$ converge as $n \rightarrow \infty$ along certain arithmet

Gabriel Goldberg

We prove the consistency of the theory ZFC + there is a strongly compact cardinal from the existence of a cardinal preserving embedding from the universe into an inner model. The proof almost shows that under SCH, every cardinal preserving embedding preserves the cofinality and continuum functions.

Isaac Johnson, Martin Gerlach, Diego Sáez-Trumper

A major challenge for many analyses of Wikipedia dynamics -- e.g., imbalances in content quality, geographic differences in what content is popular, what types of articles attract more editor discussion -- is grouping the very diverse range of Wikipedia articles into coherent, consistent topics. This problem has been addressed using various approaches based

Jakob Meldgaard Kjær, Lasse Kristensen, Mads Alberg Christensen

Access to quality travel time information for roads in a road network has become increasingly important with the rising demand for real-time travel time estimation for paths within road networks. In the context of the Danish road network (DRN) dataset used in this paper, the data coverage is sparse and skewed towards arterial roads, with a coverage of 23.88%

Vojtěch Dvořák

Consider the following game played by two players, called Waiter and Client, on the edges of $K_n$ (where $n$ is divisible by $3$). Initially, all the edges are unclaimed. In each round, Waiter picks two yet unclaimed edges. Client then chooses one of these two edges to be added to Waiter's graph and one to be added to Client's graph. Waiter wins if

Marco Di Francesco, Graziano Stivaletta

We consider the follow-the-leader particle approximation scheme for a $1d$ scalar conservation law with nonnegative $L^\infty_c$ initial datum and with a $C^1$ concave flux, which is known to provide convergence towards the entropy solution $ρ$ to the corresponding Cauchy problem. We provide two novel contributions to this theory. First, we prove that the on

Federico Belotti, Alessandro Casini, Leopoldo Catania, Stefano Grassi

We consider the derivation of data-dependent simultaneous bandwidths for double kernel heteroskedasticity and autocorrelation consistent (DK-HAC) estimators. In addition to the usual smoothing over lagged autocovariances for classical HAC estimators, the DK-HAC estimator also applies smoothing over the time direction. We obtain the optimal bandwidths that jo

Aizaz U. Chaudhry, Halim Yanikomeroglu

Laser inter-satellite links (LISLs) are envisioned between satellites in upcoming satellite constellations, such as Phase I of SpaceX's Starlink. Within a constellation, satellites can establish LISLs with other satellites in the same orbital plane or in different orbital planes. We present a classification of LISLs based on the location of satellites wi

Prathamesh Muzumdar, Ganga Prasad Basyal, Piyush Vyas

Salesperson's interpersonal skills have always played an important role in influencing various stages of customer's purchase decision. With the increase in retail outlets and merchandisers, retail operations have taken a pivotal role in influencing the salesperson's sales practices and customer's purchase decisions.This study tries to examine

A. Katsaris, P. A. Kalozoumis, F. K. Diakonos

The concept of the generalized continuity equation (GCE) was recently introduced in [J. Phys. A: Math. and Theor. {\bf 52}, 1552034 (2019)], and was derived in the context of $N$ independent Schrödinger systems. The GCE is induced by a symmetry transformation which mixes the states of these systems, even though the $N$-system Lagrangian does not. As the $N$-

Şaban Güvenç

In this paper, we consider Legendre trajectories of trans-$S$-manifolds. We obtain curvature characterizations of these curves and give a classification theorem. We also investigate Legendre curves whose Frenet frame fields are linearly dependent with certain combination of characteristic vector fields of the trans-$S$-manifold.

Na'im Kalantar, Bijay Kumar Agarwalla, Dvira Segal

Harmonic oscillator chains connecting two harmonic reservoirs at different constant temperatures cannot act as thermal diodes, irrespective of structural asymmetry. However, here we prove that perfectly harmonic junctions can rectify heat once the reservoirs (described by white Langevin noise) are placed under temperature gradients, which are asymmetric at t

G. P. Zhang, Y. H. Bai, Thomas F. George

Laser-induced ultrafast demagnetization has puzzled researchers around the world for over two decades. Intrinsic complexity in electronic, magnetic, and phononic subsystems is difficult to understand microscopically. So far it is not possible to explain demagnetization using a single mechanism, which suggests a crucial piece of information still missing. In

Eugenia Diaz-Gimenez, Ariel Zandivarez, Gary Mamon

We study the formation of over 6000 compact groups (CGs) of galaxies identified in mock redshift-space galaxy catalogues built from semi-analytical models of galaxy formation (SAMs) run on the Millennium Simulations. We select CGs of 4 members in our mock SDSS galaxy catalogues and, for each CG, we trace back in time the real-space positions of the most mass

Hunter Lang, Aravind Reddy, David Sontag, Aravindan Vijayaraghavan

Several works have shown that perturbation stable instances of the MAP inference problem in Potts models can be solved exactly using a natural linear programming (LP) relaxation. However, most of these works give few (or no) guarantees for the LP solutions on instances that do not satisfy the relatively strict perturbation stability definitions. In this work

Sebastian Burckhardt, Chris Gillum, David Justo, Konstantinos Kallas

Serverless is an increasingly popular choice for service architects because it can provide elasticity and load-based billing with minimal developer effort. A common and important use case is to compose serverless functions and cloud storage into reliable workflows. However, existing solutions for authoring workflows provide a rudimentary experience compared

Janice Chin, David Pearce

Automated specification-based testing has a long history with several notable tools having emerged. For example, QuickCheck for Haskell focuses on testing against user-provided properties. Others, such as JMLUnit, use specifications in the form of pre- and post-conditions to drive testing. An interesting (and under-explored) question is how effective this ap

Dominik Aumayr, Stefan Marr, Sophie Kaleba, Elisa Gonzalez Boix

With concurrency being integral to most software systems, developers combine high-level concurrency models in the same application to tackle each problem with appropriate abstractions. While languages and libraries offer a wide range of concurrency models, debugging support for applications that combine them has not yet gained much attention. Record & replay

Mayank Jain, Tarek AlSkaif, Soumyabrata Dev

Large-scale deployment of smart meters has made it possible to collect sufficient and high-resolution data of residential electric demand profiles. Clustering analysis of these profiles is important to further analyze and comment on electricity consumption patterns. Although many clustering techniques have been proposed in the literature over the years, it i

Matthias Gimperlein, Michael Schmiedeberg

The competition of depletion attractions and longer-ranged repulsions between colloidal particles in colloid-polymer mixtures leads to the formation of heterogeneous gel-like structures. For instance, gel networks, i.e., states where the colloids arrange in thin strands that span the whole system occur at low packing fractions for attractions that are strong

Hyojun A. Lee, Luiz G. A. Alves, Luís A. Nunes Amaral

Many systems of scientific interest can be conceptualized as multipartite networks. Examples include the spread of sexually transmitted infections, scientific collaborations, human friendships, product recommendation systems, and metabolic networks. In practice, these systems are often studied after projection onto a single class of nodes, losing crucial inf

Jamie Bamber, Oliver J. Tattersall, Katy Clough, Pedro G. Ferreira

The ringdown of a perturbed black hole contains fundamental information about space-time in the form of Quasi Normal Modes (QNM). Modifications to general relativity, or extended profiles of other fields surrounding the black hole, so called "black hole hair", can perturb the QNM frequencies. Previous works have examined the QNM frequencies of spheri

Peide Li, Rejaul Karim, Tapabrata Maiti

Tensor (multidimensional array) classification problem has become very popular in modern applications such as image recognition and high dimensional spatio-temporal data analysis. Support Tensor Machine (STM) classifier, which is extended from the support vector machine, takes CANDECOMP / Parafac (CP) form of tensor data as input and predicts the data labels

Kentaro Heya, Naoki Kanazawa

Implementation of high-fidelity swapping operations is of vital importance to execute quantum algorithms on a quantum processor with limited connectivity. We present an efficient pulse control technique, cross-cross resonance (CCR) gate, to implement iSWAP and SWAP operations with dispersively-coupled fixed-frequency transmon qubits. The key ingredient of th

George H. Choueiri, Jose M. Lopez, Atul Varshney, Sarath Sankar

Turbulence generally arises in shear flows if velocities and hence inertial forces are sufficiently large. In striking contrast, viscoelastic fluids can exhibit disordered motion even at vanishing inertia. Intermediate between these cases, a novel state of chaotic motion, `elasto-inertial turbulence' (EIT), has been observed in a narrow Reynolds number i

Carmen Romo-Luque

Liquid xenon offers several features, which make it suitable for applications in nuclear medicine, such as high scintillation yield and fast scintillation decay time. Moreover, being a continuous medium with a uniform response, liquid xenon allows one to avoid most of the geometrical distortions of conventional detectors based on scintillating crystals. In t

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh

State-of-the-art computer vision systems are trained to predict a fixed set of predetermined object categories. This restricted form of supervision limits their generality and usability since additional labeled data is needed to specify any other visual concept. Learning directly from raw text about images is a promising alternative which leverages a much br

Hailong Fu, Ke Huang, Kenji Watanabe, Takashi Taniguchi

In the Landau levels of a two-dimensional electron system or when flat bands are present, e.g. in twisted van der Waals bilayers, strong electron-electron interaction gives rise to quantum Hall ferromagnetism with spontaneously broken symmetries in the spin and isospin sectors. Quantum Hall ferromagnets support a rich variety of low-energy collective excitat

Adam Ingram, Sara Motta, Suzanne Aigrain, Aris Karastergiou

Binary supermassive black hole (SMBH) systems result from galaxy mergers, and will eventually coalesce due to gravitational wave (GW) emission if the binary separation can be reduced to $\lesssim 0.1$ pc by other mechanisms. Here, we explore a gravitational self-lensing binary SMBH model for the sharp (duration $\sim 1$ hr), quasi-regular X-ray flares -- dub

Andrew T. Pierce, Yonglong Xie, Seung Hwan Lee, Patrick R. Forrester

Symmetry-broken electronic phases support neutral collective excitations. For example, monolayer graphene in the quantum Hall regime hosts a nearly ideal ferromagnetic phase at filling factor $ν=1$ that spontaneously breaks spin rotation symmetry. This ferromagnet has been shown to support spin-wave excitations known as magnons which can be generated and det

M. E. Jarvis, C. M. Harrison, V. Mainieri, D. M. Alexander

We present the first results from the Quasar Feedback Survey, a sample of 42 z<0.2, [O III] luminous AGN (L[O III]>10^42.1 ergs/s) with moderate radio luminosities (i.e. L(1.4GHz)>10^23.4 W/Hz; median L(1.4GHz)=5.9x10^23 W/Hz). Using high spatial resolution (~0.3-1 arcsec), 1.5-6 GHz radio images from the Very Large Array, we find that 67 percent of the samp

J. Drew Hogg, Laura Blecha, Christopher S. Reynolds, Krista Lynne Smith

We present a spectroscopic and imaging study of an abnormal active galactic nucleus (AGN), 2MASX J00423991+3017515. This AGN is newly identified in the hard X-rays by the Swift BAT All-Sky survey and found in an edge-on disk galaxy interacting with a nearby companion. Here, we analyze the first optical spectra obtained for this system (taken in 2011 and 2016

Amit Jamadagni, Hendrik Weimer

We analyze the phase diagram of a topological insulator model including antiferromagnetic interactions in the form of an extended Su-Schrieffer Heeger model. To this end, we employ a recently introduced operational definition of topological order based on the ability of a system to perform topological error correction. We show that the necessary error correc

Julian May-Mann, Taylor L. Hughes

Higher order topological insulators (HOTIs) are a novel form of insulating quantum matter, which are characterized by having gapped boundaries that are separated by gapless corner or hinge states. Recently, it has been proposed that the essential features of a large class of HOTIs are captured by topological multipolar response theories. In this work, we sho

A. Scheie, M. Sanders, Yiming Qiu, T. R. Prisk

We report the low temperature magnetic properties of Nd$^{3+}$ pyrochlore $\rm Nd_2ScNbO_7$. Susceptibility and magnetization show an easy-axis moment, and heat capacity reveals a phase transition to long range order at $T_N=371(2)$ mK with a fully recovered $ΔS = R \ln(2)$, 53\% of it recovered for $T>T_N$. Elastic neutron scattering shows a long-range all-

Baohe Zhang, Raghu Rajan, Luis Pineda, Nathan Lambert

Model-based Reinforcement Learning (MBRL) is a promising framework for learning control in a data-efficient manner. MBRL algorithms can be fairly complex due to the separate dynamics modeling and the subsequent planning algorithm, and as a result, they often possess tens of hyperparameters and architectural choices. For this reason, MBRL typically requires s

Kirti Prakash, Benedict Diederich, Stefanie Reichelt, Rainer Heintzmann

Structured illumination microscopy (SIM) has emerged as an essential technique for 3D and live-cell super-resolution imaging. However, to date, there has not been a dedicated workshop or journal issue covering the various aspects of SIM, from bespoke hardware and software development and the use of commercial instruments to biological applications. This spec

Aneeq Zia, Kiran Bhattacharyya, Xi Liu, Ziheng Wang

Surgical data science is revolutionizing minimally invasive surgery by enabling context-aware applications. However, many challenges exist around surgical data (and health data, more generally) needed to develop context-aware models. This work - presented as part of the Endoscopic Vision (EndoVis) challenge at the Medical Image Computing and Computer Assiste

Ricardo Estrada, Kevin Kellinsky-Gonzalez

Recently Sasane defined a notion of evaluating a distribution at a point using delta sequences. In this paper, we explore the relationship between generalizations of his definition and the standard definition of distributional point values. This allows us to obtain a description of distributional point values via delta sequences and a characterization of whe

Thomas T. Kok, Rachel M. Brouwer, Rene M. Mandl, Hugo G. Schnack

Some data analysis applications comprise datasets, where explanatory variables are expensive or tedious to acquire, but auxiliary data are readily available and might help to construct an insightful training set. An example is neuroimaging research on mental disorders, specifically learning a diagnosis/prognosis model based on variables derived from expensiv

Luce Brotcorne, Sébastien Lepaul, Léonard von Niederhäusern

To guarantee the well-functioning of electricity distribution networks, it is crucial to constantly ensure the demand-supply balance. To do this, one can control the means of production, but also influence the demand: demand-side management becomes more and more popular as the demand keeps increasing and getting more chaotic. In this work, we propose a bilev

Zhaozhuo Xu, Aditya Desai, Menal Gupta, Anu Chandran

Traditional seismic processing workflows (SPW) are expensive, requiring over a year of human and computational effort. Deep learning (DL) based data-driven seismic workflows (DSPW) hold the potential to reduce these timelines to a few minutes. Raw seismic data (terabytes) and required subsurface prediction (gigabytes) are enormous. This large-scale, spatiall

Eanna E Flanagan

As a black hole evaporates, each outgoing Hawking quantum carries away some of the black holes asymptotic charges associated with the extended Bondi-Metzner-Sachs group. These include the Poincaré charges of energy, linear momentum, intrinsic angular momentum, and orbital angular momentum or center-of-mass charge, as well as extensions of these quantities as

Jean-Paul Blaizot, Jan M. Pawlowski, Urko Reinosa

We combine two non-perturbative approaches, one based on the two-particle-irreducible (2PI) action, the other on the functional renormalization group (fRG), in an effort to develop new non-perturbative approximations for the field theoretical description of strongly coupled systems. In particular, we exploit the exact 2PI relations between the two-point and

Noe Angelo Caruso, Alessandro Michelangeli

When a solution to an abstract inverse linear problem on Hilbert space is approximable by finite linear combinations of vectors from the cyclic subspace associated with the datum and with the linear operator of the problem, the solution is said to be a Krylov solution, i.e., it belongs to the Krylov subspace of the problem. Krylov solvability of the inverse

Haoxian Chen, Ziyi Huang, Henry Lam, Huajie Qian

We study the generation of prediction intervals in regression for uncertainty quantification. This task can be formalized as an empirical constrained optimization problem that minimizes the average interval width while maintaining the coverage accuracy across data. We strengthen the existing literature by studying two aspects of this empirical optimization.

Şaban Güvenç

In this paper, we study normal magnetic curves in $C$-manifolds. We prove that magnetic trajectories with respect to the contact magnetic fields are indeed $θ_{α}$-slant curves with certain curvature functions. Then, we give the parametrizations of normal magnetic curves in $\mathbb{R}^{2n+s}$ with its structures as a $C$-manifold.

Pablo Spiga

In this paper we propose a refinement of Sims conjecture concerning the cardinality of the point stabilizers in finite primitive groups and we make some progress towards this refinement. In this process, when dealing with primitive groups of diagonal type, we construct a finite primitive group $G$ on $Ω$ and two distinct points $α,β\in Ω$ with $G_{αβ}\unlhd

Bernhard Haslhofer, Rainer Stütz, Matteo Romiti, Ross King

There is currently an increasing demand for cryptoasset analysis tools among cryptoasset service providers, the financial industry in general, as well as across academic fields. At the moment, one can choose between commercial services or low-level open-source tools providing programmatic access. In this paper, we present the design and implementation of ano

Aria Beaupré, Anthony Dickson, David Milan, Christin Sum

In this paper we provide an abstract characterization of the inverse hulls of semigroups associated with Markov shifts. As an application of the characterization we give an example of Markov shifts that are not conjugate, but have isomorphic inverse hulls.

Rebecca Rothermel, Wladimir Panfilenko, Prateek Sharma, Anne Wald

Mathematical models describing the behavior of viscoelastic materials are often based on evolution equations that measure the change in stress depending on its material parameters such as stiffness, viscosity or relaxation time. In this article, we introduce a Maxwell-based rheological model, define the associated forward operator and the inverse problem in

Kiavash Satvat, Maliheh Shirvanian, Nitesh Saxena

In this paper, we introduce PASSAT, a practical system to boost the security assurance delivered by the current cloud architecture without requiring any changes or cooperation from the cloud service providers. PASSAT is an application transparent to the cloud servers that allows users to securely and efficiently store and access their files stored on public

Swaroopa Dola, Matthew B. Dwyer, Mary Lou Soffa

The reliability of software that has a Deep Neural Network (DNN) as a component is urgently important today given the increasing number of critical applications being deployed with DNNs. The need for reliability raises a need for rigorous testing of the safety and trustworthiness of these systems. In the last few years, there have been a number of research e

Benjamin F. Maier, Angelique Burdinski, Annika H. Rose, Frank Schlosser

Vaccination against COVID-19 with the recently approved mRNA vaccines BNT162b2 (BioNTech/Pfizer) and mRNA-1273 (Moderna) is currently underway in a large number of countries. However, high incidence rates and rapidly spreading SARS-CoV-2 variants are concerning. In combination with acute supply deficits in Europe in early 2021, the question arises of whether

Marcos Miralles López

These Monte Carlo studies describe the impact of higher order effects in both QCD and EW $t\bar{t}W$ production. Both next-to-leading inclusive and multileg setups are studied for $t\bar{t}W$ QCD production.

Andreia Sofia Teixeira, Francisco C. Santos, Alexandre P. Francisco, Fernando P. Santos

From social contracts to climate agreements, individuals engage in groups that must collectively reach decisions with varying levels of equality and fairness. These dilemmas also pervade Distributed Artificial Intelligence, in domains such as automated negotiation, conflict resolution or resource allocation. As evidenced by the well-known Ultimatum Game -- w

Muneer Alshowkan, Brian P. Williams, Philip G. Evans, Nageswara S. V. Rao

Practical quantum networking architectures are crucial for scaling the connection of quantum resources. Yet quantum network testbeds have thus far underutilized the full capabilities of modern lightwave communications, such as flexible-grid bandwidth allocation. In this work, we implement flex-grid entanglement distribution in a deployed network for the firs