March 2020 arXiv papers — page 64

Zhe Li, Tsz Nam Chan, Man Lung Yiu, Christian S. Jensen

Range aggregate queries find frequent application in data analytics. In some use cases, approximate results are preferred over accurate results if they can be computed rapidly and satisfy approximation guarantees. Inspired by a recent indexing approach, we provide means of representing a discrete point data set by continuous functions that can then serve as

Hao-Ran Yang, Hai-Jun Wu, Wei Gao, Carmelo Rosales-Guzmán

Ince-Gaussian (IG) mode, a recently discovered type of structured Gaussian beam, corresponds to eigenfunctions of the paraxial wave equation in elliptical coordinates. This propagation-invariant mode is of significance in various domains, and in particular, its nonlinear transformation; however, there have been few relevant studies to date. In this work, we

K. L. Zhang, Z. Song

The ground-state degeneracy of the quantum spin system is a characteristic of nontrivial topology, when it is gapped and robust against disordered perturbation. The corresponding quantum phase transition (QPT) is usually driven by a real parameter. We study a non-Hermitian Ising chain with two transverse fields, one real and another imaginary, based on the e

Quan Thoi Minh Nguyen

Post-quantum cryptography is inevitable. National Institute of Standards and Technology (NIST) starts standardizing quantum-resistant public-key cryptography (aka post-quantum cryptography). The reason is that investment in quantum computing is blooming which poses significant threats to our currently deployed cryptographic algorithms. As a security engineer

Andrew J. Taylor, Andrew Singletary, Yisong Yue, Aaron D. Ames

In this paper we seek to quantify the ability of learning to improve safety guarantees endowed by Control Barrier Functions (CBFs). In particular, we investigate how model uncertainty in the time derivative of a CBF can be reduced via learning, and how this leads to stronger statements on the safe behavior of a system. To this end, we build upon the idea of

Shuai Wang, Fan Lyu, Wei Feng, Song Wang

Referring expression comprehension (REC) aims to localize a text-related region in a given image by a referring expression in natural language. Existing methods focus on how to build convincing visual and language representations independently, which may significantly isolate visual and language information. In this paper, we argue that for REC the referring

Yang Xing, Chen Lv, Dongpu Cao, Efstathios Velenis

Mutual understanding between driver and vehicle is critically important to the design of intelligent vehicles and customized interaction interface. In this study, a unified driver behavior reasoning system toward multi-scale and multi-tasks behavior recognition is proposed. Specifically, a multi-scale driver behavior recognition system is designed to recogni

Zheng Deng, Chang-Jong Kang, Mark Croft, Wenmin Li

Given the consensus that pressure improves cation order in most of known materials, a discovery of pressure-induced disorder could require reconsideration of order-disorder transition in solid state physics/chemistry and geophysics. Double perovskites Y2CoIrO6 and Y2CoRuO6 synthesized at ambient pressure show B-site order, while the polymorphs synthesized at

Yu Tian, Kunbo Zhang, Leyuan Wang, Zhenan Sun

Face anti-spoofing is the key to preventing security breaches in biometric recognition applications. Existing software-based and hardware-based face liveness detection methods are effective in constrained environments or designated datasets only. Deep learning method using RGB and infrared images demands a large amount of training data for new attacks. In th

Garrett Compton, Ian A. Morrison

It is known that odd-dimensional de Sitter space acts as a transparent potential for free fields. Previous studies have explained this phenomena by relating de Sitter free field equations of motion to the time-independent Schrodinger equation with known transparent potentials. In this work we show that de Sitter's transparency is a consequence of an infinite

Alejandro Bravo-Doddoli

Carnot groups are subRiemannian manifolds. As such they admit geodesic flows, which are left-invariant Hamiltonian flows on their cotangent bundles. Some of these flows are integrable. Some are not. The space of k-jets for real-valued functions on the real line forms a Carnot group of dimension $k+2$. We show that its geodesic flow is integrable and that its

Brandon Buonacorsi, Benjamin Shaw, Jonathan Baugh

Shuttling of single electrons in gate-defined silicon quantum dots is numerically simulated. A minimal gate geometry without explicit tunnel barrier gates is introduced, and used to define a chain of accumulation mode quantum dots, each controlled by a single gate voltage. One-dimensional potentials are derived from a three-dimensional electrostatic model, a

Yoshikazu Giga, Jun Okamoto, Masaaki Uesaka

An explicit representation of the Gamma limit of a single-well Modica--Mortola functional is given for one-dimensional space under the graph convergence which is finer than conventional $L^1$-convergence or convergence in measure. As an application, an explicit representation of a singular limit of the Kobayashi-Warren-Carter energy, which is popular in mate

Yurika Yamada, Makoto Uemura, Ryosuke Itoh, Yasushi Fukazawa

We report on the variations of the physical parameters of the jet observed in the blazar Mrk 421, and discuss the origin of X-ray flares in the jet, based on the analysis of the several spectral energy distributions (SEDs). The SEDs are modeled using the one-zone synchrotron self-Compton (SSC) model and its parameters determined using a Markov chain Monte Ca

Jocemar Q. Chagas, Giuliano G. La Guardia, Ervin K. Lenzi

In this note, a numerical method based on finite differences to solve a class of nonlinear advection-diffusion fractional differential equation is proposed. The fractional operator considered here is the fractional Riemann-Liouville derivative or the fractional Riesz derivative of order $\alpha$. The consistency and unconditionally stability of the method ar

Julian Adamek, Cristian Barrera-Hinojosa, Marco Bruni, Baojiu Li

A number of codes for general-relativistic simulations of cosmological structure formation have been developed in recent years. Here we demonstrate that a sample of these codes produce consistent results beyond the Newtonian regime. We simulate solutions to Einstein's equations dominated by gravitomagnetism -- a vector-type gravitational field that doesn't e

Bin Li, Rong Wang, Jianjun Ma

We demonstrate the reliability and applicability of THz imaging for destructive and non-destructive water status monitoring of winter wheat leaves. Based on the measured THz transmission amplitude, we find that the water loss in the distal region is less than that in the basal region during the nature dehydration process. A high correlation is shown between

Rachel E. Keil, Alexander T. Miller, Mrinal Kumar, Anil V. Rao

A method is developed to numerically solve chance constrained optimal control problems. The chance constraints are reformulated as nonlinear constraints that retain the probability properties of the original constraint. The reformulation transforms the chance constrained optimal control problem into a deterministic optimal control problem that can be solved

Marius Hofert

It seems surprising that when applying widely used random number generators to generate one million random numbers on modern architectures, one obtains, on average, about 116 collisions. This article explains why, how to mathematically compute such a number, why they often cannot be obtained in a straightforward way, how to numerically compute them in a robu

Jinniu Hu, Ying Zhang, Hong Shen, Hiroshi Toki

The pion-mass-dependent nucleon-nucleon ($NN$) potentials in term of one-pion exchange and contact terms are obtained from the latest lattice QCD simulations of two-nucleon system, which employ the forms of leading order (LO) $NN$ potential from the chiral effective field theory and thus are named as the LO chiral potential in this work. We extract the coeff

Ricardo Peterson, Mohamadali Malakoutian, Xiaoqing Xu, Caitlin Chapin

Here we present an analysis of the mobility-limiting mechanisms of a two-dimensional hole gas on hydrogen-terminated diamond surfaces. The scattering rates of surface impurities, surface roughness, non-polar optical phonons, and acoustic phonons are included. Using a Schrodinger/Poisson solver, the heavy hole, light hole, and split-off bands are treated sepa

Paul Cohen, Tomasz Loboda

Redistribution systems iteratively redistribute mass between groups under the control of rules. PRAM is a framework for building redistribution systems. We discuss the relationships between redistribution systems, agent-based systems, compartmental models and Bayesian models. PRAM puts agent-based models on a sound probabilistic footing by reformulating them

Xin Huang, Stephen G. McGill, Jonathan A. DeCastro, Luke Fletcher

Predicting driver intentions is a difficult and crucial task for advanced driver assistance systems. Traditional confidence measures on predictions often ignore the way predicted trajectories affect downstream decisions for safe driving. In this paper, we propose a novel multi-task intent recognition neural network that predicts not only probabilistic driver

Hsien-Wei Chen

A new stochastic model for daily precipitation occurrence processes observed at multiple locations is developed. The modeling concept is to use the indicator function and the elliptical shape of multivariate Gaussian distribution to represent the joint probabilities of daily precipitation occurrences. By using this concept, the number of parameters needed fo

Mehran Seyedhosseini

In this paper we define a variant of Roe algebras for spaces with cylindrical ends and use this to study questions regarding existence and classification of metrics of positive scalar curvature on such manifolds which are collared on the cylindrical end. We discuss how our constructions are related to relative higher index theory as developed by Chang, Weinb

Andrew Lesniewski, Nicholas Lesniewski

We present a parsimonious stochastic model for valuation of options on the fraction of infected individuals during an epidemic. The underlying stochastic dynamical system is a stochastic differential version of the SIR model of mathematical epidemiology.

Daniele Bigoni, Yuming Chen, Nicolas Garcia Trillos, Youssef Marzouk

This paper suggests a framework for the learning of discretizations of expensive forward models in Bayesian inverse problems. The main idea is to incorporate the parameters governing the discretization as part of the unknown to be estimated within the Bayesian machinery. We numerically show that in a variety of inverse problems arising in mechanical engineer

Daniel Gordon, Kiana Ehsani, Dieter Fox, Ali Farhadi

Recent single image unsupervised representation learning techniques show remarkable success on a variety of tasks. The basic principle in these works is instance discrimination: learning to differentiate between two augmented versions of the same image and a large batch of unrelated images. Networks learn to ignore the augmentation noise and extract semantic

Leonid Datta

In artificial neural network, the activation function and the weight initialization method play important roles in training and performance of a neural network. The question arises is what properties of a function are important/necessary for being a well-performing activation function. Also, the most widely used weight initialization methods - Xavier and He

Farzan Erlik Nowruzi, Dhanvin Kolhatkar, Prince Kapoor, Fahed Al Hassanat

In this work, we propose the use of radar with advanced deep segmentation models to identify open space in parking scenarios. A publically available dataset of radar observations called SCORP was collected. Deep models are evaluated with various radar input representations. Our proposed approach achieves low memory usage and real-time processing speeds, and

Frank Mancolo

Eisen is an open source python package making the implementation of deep learning methods easy. It is specifically tailored to medical image analysis and computer vision tasks, but its flexibility allows extension to any application. Eisen is based on PyTorch and it follows the same architecture of other packages belonging to the PyTorch ecosystem. This simp

Adam Dziedzic, Vanlin Sathya, Muhammad Iqbal Rochman, Monisha Ghosh

The application of Machine Learning (ML) techniques to complex engineering problems has proved to be an attractive and efficient solution. ML has been successfully applied to several practical tasks like image recognition, automating industrial operations, etc. The promise of ML techniques in solving non-linear problems influenced this work which aims to app

Saeed Nosratabadi, Gergo Pinter, Amir Mosavi, Sandor Semperger

Sustainable business models also offer banks competitive advantages such as increasing brand reputation and cost reduction. However, no framework is presented to evaluate the sustainability of banking business models. To bridge this theoretical gap, the current study using A Delphi-Analytic Hierarchy Process method, firstly, developed a sustainable business

Elmo Benedetto, Ivana Bochicchio, Christian Corda, Fabiano Feleppa

It is well known, from Newtonian physics, that apparent forces appear when the motion of masses is described by using a non-inertial frame of reference. The generalized potential of such forces is rigorously analyzed focusing on their mathematical aspects.

Xi He, B Rajeswari Matam, Srikanth Bellary, Goutam Ghosh

Studies on the influence of a modern lifestyle in abetting Coronary Heart Diseases (CHD) have mostly focused on deterrent health factors, like smoking, alcohol intake, cheese consumption and average systolic blood pressure, largely disregarding the impact of a healthy lifestyle in mitigating CHD risk. In this study, 30+ years' World Health Organization (

Michael Groom, Ben Thornber

This paper investigates the influence of different broadband perturbations on the evolution of a Richtmyer--Meshkov turbulent mixing layer initiated by a Mach 1.84 shock traversing a perturbed interface separating gases with a density ratio of 3:1. Both the bandwidth of modes in the interface perturbation, as well as their relative amplitudes, are varied in

Lionel Haemmerlé, Lucio Mayer, Ralf S. Klessen, Takashi Hosokawa

We review the current status of knowledge concerning the early phases of star formation during cosmic dawn. This includes the first generations of stars forming in the lowest mass dark matter halos in which cooling and condensation of gas with primordial composition is possible at very high redshift ($z > 20$), namely metal-free Population III stars, and the

Samuel G. Corregidor, Álvaro Martínez-Pérez

Given a metric space $(X,d)$, a set $S\subseteq X$ is called a $k$-\emph{metric generator} for $X$ if any pair of different points of $X$ is distinguished by at least $k$ elements of $S$. A $k$-\emph{metric basis} is a $k$-metric generator of the minimum cardinality in $X$. We prove that ultrametric spaces do not have finite $k$-metric bases for $k>2$. We al

Mahdi Eskandari, Hamidreza Bakhshi

This paper considers the problem of estimating the sparse millimeter wave (mmWave) massive multiple-input multiple-output (MIMO) OFDM channel from 1-bit quantized measurements. Unlike previous quantized on-grid approaches to compressive sensing, we introduce an off-grid convex scheme which uses binary atomic norm minimization (BiANM) to estimate sparse chann

Carlos Junqueira-Junior, João Luiz F. Azevedo, Jairo Panetta, William R. Wolf

New regulations are imposing noise emissions limitations for the aviation industry which are pushing researchers and engineers to invest efforts in studying the aeroacoustics phenomena. Following this trend, an in-house computational fluid dynamics tool is build to reproduce high fidelity results of supersonic jet flows for aeroacoustic analogy applications.

Raj Dandekar, George Barbastathis

In a move described as unprecedented in public health history, starting 24 January 2020, China imposed quarantine and isolation restrictions in Wuhan, a city of more than 10 million people. This raised the question: is mass quarantine and isolation effective as a social tool in addition to its scientific use as a medical tool? In an effort to address this qu

Burchan Aydin, Subroto Singha

Objective of this study is to examine the impact of twelve specifications namely No. of Rotors, Max Flight Time(min.), Operating Range (m), Wingspan(mm), Weight(g), Payload Capacity(g), Max Speed(m/s), Max Flying Altitude(m), GPS Compatibility, Autonomous Flight, Collision Avoidance, Flight Battery (mAh) on the price of the drones. Using Stepwise Multiple Li

Yiping Wang, Gavin B. Osterhoudt, Yao Tian, Paige Lampen-Kelley

Significant efforts have focused on the magnetic excitations of relativistic Mott insulators, predicted to realize the Kitaev quantum spin liquid (QSL). This exactly solvable model involves a highly entangled state resulting from bond-dependent Ising interactions that produce excitations which are non-local in terms of spin flips. A key challenge in real mat

Qiu-He Peng, Jing-Jing Liu, Chi-Kang Chou

There are some particle physics theories that go beyond the so-called "standard cosmological model" to predict the existence of magnetic monopoles\,(MMs). The discovery of magnetic monopoles would be an incredible breakthrough in high-energy physics. The existence of MMs in the early Universe has been speculated and anticipated from Grand Unified The

A. P. Kazemi, S. M. Sheikholeslami, L. Volkmann

Let $k$ be a positive integer. A {\em Roman $k$-dominating function} on a graph $G$ is a labeling $f:V (G)\longrightarrow \{0, 1, 2\}$ such that every vertex with label 0 has at least $k$ neighbors with label 2. A set $\{f_1,f_2,\ldots,f_d\}$ of distinct Roman $k$-dominating functions on $G$ with the property that $\sum_{i=1}^df_i(v)\le 2k$ for each $v\in V(

Shiva Kumar, Jing Shao

Stochastic power fluctuation in a fiber optic system due to the interplay among dispersion, nonlinearity and partial coherence of the source is investigated. An analytical expression for the power fluctuation of a signal pulse due to its interference with an echo pulse generated due to the nonlinear interaction of signal pulses in a fiber optic system excite

Ali Anaissi, Basem Suleiman, Seid Miad Zandavi

Multi-way data analysis has become an essential tool for capturing underlying structures in higher-order datasets stored in tensor $\mathcal{X} \in \mathbb{R} ^{I_1 \times \dots \times I_N} $. $CANDECOMP/PARAFAC$ (CP) decomposition has been extensively studied and applied to approximate $\mathcal{X}$ by $N$ loading matrices $A^{(1)}, \dots, A^{(N)}$ where $N

Zhengyang Wu, Srivignesh Rajendran, Tarrence van As, Joelle Zimmermann

With the emergence of Virtual and Mixed Reality (XR) devices, eye tracking has received significant attention in the computer vision community. Eye gaze estimation is a crucial component in XR -- enabling energy efficient rendering, multi-focal displays, and effective interaction with content. In head-mounted XR devices, the eyes are imaged off-axis to avoid

Pierre-Alain Toupance, Bastien Chopard, Laurent Lef èvre

The definitions of delayed mutual information and multi-information are recalled. It is shown how the delayed mutual information may be used to reconstruct the interaction topology resulting from some unknown scale-free graph with its associated local dynamics. Delayed mutual information is also used to solve the community detection problem. A probabilistic

Ana I. Julio, Ricardo L. Soto

We say that a list $Λ=\{ λ_{1},\ldots ,λ_{n}\}$ of complex numbers is realizable, if it is the spectrum of a nonnegative matrix $A$ (the realizing matrix). We say that $Λ$ is universally realizable if it is realizable for each possible Jordan canonical form allowed by $ Λ.$ This work does not contain new results. As its title says, our goal is to show and em

Fabio Miletto Granozio

The sudden spread of Covid-19 outside China has pushed on March 11 the World Health Organization to acknowledge the ongoing outbreak as a pandemic. It is crucial in this phase to understand what should countries which presently lag behind in the spread of the infection learn from countries where the infection spread earlier. The choice of this work is to pre

Wen-Loong Ma, Noel Csomay-Shanklin, Aaron D. Ames

A robotic system can be viewed as a collection of lower-dimensional systems that are coupled via reaction forces (Lagrange multipliers) enforcing holonomic constraints. Inspired by this viewpoint, this paper presents a novel formulation for nonlinear control systems that are subject to coupling constraints via virtual "coupling" inputs that abstractl

Reaz Huq, Bogumil Kaminski, Atefeh Mashatan, Pawel Pralat

Consider the following broadcasting process run on a connected graph $G=(V,E)$. Suppose that $k \ge 2$ agents start on vertices selected from $V$ uniformly and independently at random. One of the agents has a message that she wants to communicate to the other agents. All agents perform independent random walks on $G$, with the message being passed when an ag

Kaan Akşit, Jan Kautz, David Luebke

We introduce a new gaze tracker for Head Mounted Displays (HMDs). We modify two off-the-shelf HMDs to be gaze-aware using Light Emitting Diodes (LEDs). Our key contribution is to exploit the sensing capability of LEDs to create low-power gaze tracker for virtual reality (VR) applications. This yields a simple approach using minimal hardware to achieve good a

Vincenzo Cirigliano, William Detmold, Amy Nicholson, Phiala Shanahan

Second order beta-decay processes with and without neutrinos in the final state are key probes of nuclear physics and of the nature of neutrinos. Neutrinoful double-beta decay is the rarest Standard Model process that has been observed and provides a unique test of the understanding of weak nuclear interactions. Observation of neutrinoless double-beta decay

Igor Tsukerman, A N M Shahriyar Hossain, Y. D. Chong

A general homogenization procedure for periodic electromagnetic structures, when applied to layered media with asymmetric lattice cells, yields an effective tensor with magnetoelectric coupling. Accurate results for transmission and reflection are obtained even in cases where classical effective medium theory breaks down. Magnetoelectric coupling accounts fo

Tanmoy Bhattacharya, Rajan Gupta, Boram Yoon

A review of recent lattice calculations of nucleon structure and matrix elements of operators in nucleons is presented. It primarily covers developments in the calculation of the matrix elements of the scalar, tensor, pseudo-scalar, axial-vector and vector operators in the ground state of neutrons and protons in the isospin symmetric limit. Some preliminary

Canlin Zhang, Xiuwen Liu, Daniel Bis

To improve the generalization of the representations for natural language processing tasks, words are commonly represented using vectors, where distances among the vectors are related to the similarity of the words. While word2vec, the state-of-the-art implementation of the skip-gram model, is widely used and improves the performance of many natural language

N. Lehraki, A. Attaf, M. S. Aida, N. Attaf

Zinc oxide thin films were deposited by ultrasonic spray pyrolysis technique using different Zinc precursors: Zinc acetate, Zinc nitrate and zinc chloride with different molarities. All deposited films were characterized by various techniques such as X-ray diffraction to determine the films structure, the scanning electron microscopy SEM for the morphology o

Aniket Anand Deshmukh, Abhimanu Kumar, Levi Boyles, Denis Charles

Contextual bandits are a common problem faced by machine learning practitioners in domains as diverse as hypothesis testing to product recommendations. There have been a lot of approaches in exploiting rich data representations for contextual bandit problems with varying degree of success. Self-supervised learning is a promising approach to find rich data re

Grayson Jorgenson

To each subvariety $X$ in projective $n$-space of codimension $m$ we associate an integer sequence of length $m + 1$ from $1$ to the degree of $X$ recording the maximal cardinalities of finite, reduced intersections of $X$ with linear subvarieties. We call this the sequence of secant indices of $X$. Similar numbers have been studied independently with the ai

Maarten De Boeck, Geertrui Van de Voorde

A Kakeya set $\mathcal{K}$ in an affine plane of order $q$ is the point set covered by a set $\mathcal{L}$ of $q+1$ pairwise non-parallel lines. Large Kakeya sets were studied by Dover and Mellinger; in [6] they showed that Kakeya sets with size at least $q^2-3q+9$ contain a large knot (a point of $\mathcal{K}$ lying on many lines of $\mathcal{L}$). In this

Tobias Klöffel, Gerald Mathias, Bernd Meyer

We present our recent code modernizations of the of the ab initio molecular dynamics program CPMD (www.cpmd.org) with a special focus on the ultra-soft pseudopotential (USPP) code path. Following the internal instrumentation of CPMD, all time critical routines have been revised to maximize the computational throughput and to minimize the communication overhe

Madan Ravi Ganesh, Jason J. Corso, Salimeh Yasaei Sekeh

Most approaches to deep neural network compression via pruning either evaluate a filter's importance using its weights or optimize an alternative objective function with sparsity constraints. While these methods offer a useful way to approximate contributions from similar filters, they often either ignore the dependency between layers or solve a more dif

Brian DeCost, Jason Hattrick-Simpers, Zachary Trautt, Aaron Kusne

Recently there has been an ever-increasing trend in the use of machine learning (ML) and artificial intelligence (AI) methods by the materials science, condensed matter physics, and chemistry communities. This perspective article identifies key scientific, technical, and social opportunities that the materials community must prioritize to consistently develo

Bas Peters, Eldad Haber

Tracking a horizon in seismic images or 3D volumes is an integral part of seismic interpretation. The last few decades saw progress in using neural networks for this task, starting from shallow networks for 1D traces, to deeper convolutional neural networks for large 2D images. Because geological structures are intrinsically 3D, we hope to see improved horiz

Marcin Sawicki, Liz Arcila-Osejo, Anneya Golob, Thibaud Moutard

We study the environments of a sample of 61 extremely rare z~1.6 Ultra-Massive Passively Evolving Galaxies (UMPEGs: stellar masses M_stars >10^11.5 M_sun) which -- based on clustering analysis presented in Cheema et al. (2020) -- appear to be associated with very massive (M_halo ~ 10^14.1 h^-1 M_sun) dark matter halos that are likely to be the progenitors of

Indrasis Chakraborty, Sai Pushpak Nandanoori, Soumya Kundu, Karanjit Kalsi

Effective utilization of flexible loads for grid services, while satisfying end-user preferences and constraints, requires an accurate estimation of the aggregated predictive flexibility offered by the electrical loads. Virtual battery (VB) models are often used to quantify the predictive flexibility in thermostatic loads (e.g. residential air-conditioners,

Erhan Bayraktar, H. Vincent Poor, Xin Zhang

We consider a prediction problem with two experts and a forecaster. We assume that one of the experts is honest and makes correct prediction with probability $μ$ at each round. The other one is malicious, who knows true outcomes at each round and makes predictions in order to maximize the loss of the forecaster. Assuming the forecaster adopts the classical m

Apurba Das

Higher derivations on an associative algebra generalizes higher order derivatives. We call a tuple consisting of an algebra and a higher derivation on it by an AssHDer pair. We define a cohomology for AssHDer pairs with coefficients in a representation. Next, we study central extensions, abelian extensions of AssHDer pairs and relate them to the second cohom

Carly Howett, John Spencer, Tom Nordheim

We use data from Cassini's Composite Infrared Spectrometer CIRS to map Mimas' surface temperatures and its thermophysical properties. This provides a dramatic improvement on the work in Howett et al. (2011), where the values were determined at only two regions on Mimas (one inside, and another outside of the anomalous region). We use all spatially-re

Ali Al-Aradi, Sebastian Jaimungal

We address the Merton problem of maximizing the expected utility of terminal wealth using techniques from variational analysis. Under a general continuous semimartingale market model with stochastic parameters, we obtain a characterization of the optimal portfolio for general utility functions in terms of a forward-backward stochastic differential equation (

Tyrel Stokes, Russell Steele, Ian Shrier

Recent theoretical work in causal inference has explored an important class of variables which, when conditioned on, may further amplify existing unmeasured confounding bias (bias amplification). Despite this theoretical work, existing simulations of bias amplification in clinical settings have suggested bias amplification may not be as important in many pra

Rishikesh Magar, Prakarsh Yadav, Amir Barati Farimani

The fast and untraceable virus mutations take lives of thousands of people before the immune system can produce the inhibitory antibody. Recent outbreak of novel coronavirus infected and killed thousands of people in the world. Rapid methods in finding peptides or antibody sequences that can inhibit the viral epitopes of COVID-19 will save the life of thousa

Anna Goldie, Azalia Mirhoseini

Placement Optimization is an important problem in systems and chip design, which consists of mapping the nodes of a graph onto a limited set of resources to optimize for an objective, subject to constraints. In this paper, we start by motivating reinforcement learning as a solution to the placement problem. We then give an overview of what deep reinforcement

Siyao Peng, Yang Liu, Yilun Zhu, Austin Blodgett

Adpositions are frequent markers of semantic relations, but they are highly ambiguous and vary significantly from language to language. Moreover, there is a dearth of annotated corpora for investigating the cross-linguistic variation of adposition semantics, or for building multilingual disambiguation systems. This paper presents a corpus in which all adposi

Qiong Liu, Byungjin An, Motohiko Nohmi, Masashi Obuchi

The emergence of a submerged vortex upstream of a pump can reduce pump intake efficiency and cause structural damage. In this study, we consider the use of active flow control with steady blowing to increase the pressure distribution within a single-phase pump-induced wall-normal vortex model, which is based on the Burgers vortex with a no-slip boundary cond

Renan Câmara Pereira, Pedro Costa

We explore the effect of including quantum fluctuations in the two flavor Nambu$-$Jona-Lasinio model at finite temperature. This is accomplished, in a symmetry preserving way, by including collective and noncollective modes in the one-meson-loop gap equation which originate from poles and branch cuts in the complex plane, respectively. The inclusion of a bos

Rui Sun, Xin Wang, Kong Zhang, Jun He

An optical tweezer composed of a strongly focused single-spatial-mode Gaussian beam of a red-detuned 1064-nm laser can confine a single-cesium (Cs) atom at the strongest point of the light intensity. We can use this for coherent manipulation of single-quantum bits and single-photon sources. The trapping lifetime of the atoms in the optical tweezers is very s

Girish M. Duvvuri, Seth Redfield, Dimitri Veras

The WD 1145+017 system shows irregular transit features that are consistent with the tidal disruption of differentiated asteroids with bulk densities $< 4$ g cm$^{-3}$ and bulk masses $\lesssim 10^{21}$ kg (Veras et al., 2017; arXiv:1610.06926). We use the open-source N-body code REBOUND (Rein and Liu, 2011; arXiv:1110.4876) to simulate this disruption with

Dmytro Kotovenko, Artsiom Sanakoyeu, Pingchuan Ma, Sabine Lang

Style transfer has recently received a lot of attention, since it allows to study fundamental challenges in image understanding and synthesis. Recent work has significantly improved the representation of color and texture and computational speed and image resolution. The explicit transformation of image content has, however, been mostly neglected: while arti

Nilin Abrahamsen

We generalize the `off-the-rack&#39; AGSP$\Rightarrow$entanglement bound implication of [Arad, Landau, and Vazirani &#39;12] from unique ground states to degenerate ground spaces. Our condition $RΔ\le1/2$ on a $(Δ,R)$-AGSP matches the non-degenerate case, whereas existing tools in the literature of spin chains would only be adequate to prove a less natural i

F. M. Vincentelli, Y. Cavecchi, P. Casella, S. Migliari

We report the detection of an infrared burst lagging a thermonuclear Type I X-ray burst from the accreting neutron star 4U 1728-34 (GX 354-0). Observations were performed simultaneously with XMM-Newton (0.7-12 keV), NuSTAR (3-79 keV) and HAWK-I@VLT (2.2$μ$m). We measure a lag of $4.75 \pm 0.5$ s between the peaks of the emission in the two bands. Due to the

Reinhard Alkofer, Astrid Eichhorn, Aaron Held, Carlos M. Nieto

We explore a simple parameterization of new physics that results in an ultraviolet complete gauge-quark sector of the Standard Model. Specifically, we add an antiscreening contribution to the beta functions of the gauge couplings and a flavor-independent, antiscreening contribution to the beta functions of the Yukawa couplings. These two free parameters give

Jingwei Huang, Justus Thies, Angela Dai, Abhijit Kundu

Realistic color texture generation is an important step in RGB-D surface reconstruction, but remains challenging in practice due to inaccuracies in reconstructed geometry, misaligned camera poses, and view-dependent imaging artifacts. In this work, we present a novel approach for color texture generation using a conditional adversarial loss obtained from wea

Huanian Zhang, Taotao Fang, Dennis Zaritsky, Peter Behroozi

We continue our empirical study of the emission line flux originating in the cool ($T\sim10^4$ K) gas that populates the halos of galaxies and their environments. Specifically, we present results obtained for a sample of galaxy pairs with a range of projected separations, {\bf $10 < {S_p/\rm kpc} < 200$}, and mass ratios $<$ 1:5, intersected by 5,443 SDSS li

Austin Hinkel, Susan Gardner, Brian Yanny

We study a set of solar neighborhood ($d < 3$ kpc) stars from Gaia Data Release 2 to determine azimuthal star count differences, i.e., left and right of the line from the Galactic center through the sun - and compare these differences north and south. In this companion paper to Gardner et al. (2020), we delineate our procedures to remove false asymmetries fr

Tomas Neuman, Matt Eichenfield, Matthew Trusheim, Lisa Hackett

We introduce a method for high-fidelity quantum state transduction between a superconducting microwave qubit and the ground state spin system of a solid-state artificial atom, mediated via an acoustic bus connected by piezoelectric transducers. Applied to present-day experimental parameters for superconducting circuit qubits and diamond silicon vacancy cente

Sheng-Chieh Lin, Jheng-Hong Yang, Rodrigo Nogueira, Ming-Feng Tsai

We applied the T5 sequence-to-sequence model to tackle the AI2 WinoGrande Challenge by decomposing each example into two input text strings, each containing a hypothesis, and using the probabilities assigned to the &#34;entailment&#34; token as a score of the hypothesis. Our first (and only) submission to the official leaderboard yielded 0.7673 AUC on March

Maxim S. Kovalev, Lev V. Utkin, Ernest M. Kasimov

A new method called SurvLIME for explaining machine learning survival models is proposed. It can be viewed as an extension or modification of the well-known method LIME. The main idea behind the proposed method is to apply the Cox proportional hazards model to approximate the survival model at the local area around a test example. The Cox model is used becau

Junye Wen, Mujahid Khan, Meiru Che, Yan Yan

Symbolic execution is a powerful systematic software analysis technique, but suffers from the high cost of constraint solving, which is the key supporting technology that affects the effectiveness of symbolic execution. Techniques like Green and GreenTrie reuse constraint solutions to speed up constraint solving for symbolic execution; however, these reuse t

R. de C. Lima, José A. C. Nogales, S. H. Pereira

In this work we study and compare the features of gravitational entropy near the throat of transversable wormholes formed by exotic matter and wormholes in galactic halos. We have verified that gravitational entropy and entropy density of these wormholes in regions near their throats are indistinguishable for objects of same throat, despite the fact they are

Islam Elnabarawy, Wei Jiang, Donald C. Wunsch

Collaborative filtering recommendation systems provide recommendations to users based on their own past preferences, as well as those of other users who share similar interests. The use of recommendation systems has grown widely in recent years, helping people choose which movies to watch, books to read, and items to buy. However, users are often concerned a

Krzysztof Mnich, Agnieszka Kitlas Golińska, Aneta Polewko-Klim, Witold R. Rudnicki

Super learner algorithm can be applied to combine results of multiple base learners to improve quality of predictions. The default method for verification of super learner results is by nested cross validation. It has been proposed by Tsamardinos et al., that nested cross validation can be replaced by resampling for tuning hyper-parameters of the learning al

Gabriel Fernandes, Miguel Moreno, Assaf Rinot

We introduce a generalization of stationary set reflection which we call &#34;filter reflection&#34;, and show it is compatible with the axiom of constructibility as well as with strong forcing axioms. We prove the independence of filter reflection from ZFC, and present applications of filter reflection to the study of canonical equivalence relations of the

Seyed Hadi Mirfarshbafan, Christoph Studer

We propose equalization-based data detection algorithms for all-digital millimeter-wave (mmWave) massive multiuser multiple-input multiple-out (MU-MIMO) systems that exploit sparsity in the beamspace domain to reduce complexity. We provide a condition on the number of users, basestation antennas, and channel sparsity for which beamspace equalization can be l

Huynh Van Luong, Boris Joukovsky, Nikos Deligiannis

Deep unfolding methods---for example, the learned iterative shrinkage thresholding algorithm (LISTA)---design deep neural networks as learned variations of optimization methods. These networks have been shown to achieve faster convergence and higher accuracy than the original optimization methods. In this line of research, this paper develops a novel deep re

Karim Makki, Amine Bohi, Augustin C. Ogier, Marc-Emmanuel Bellemare

In this paper, we propose a method for characterizing 3D shapes from point clouds and we show a direct application on a study of organ temporal deformations. As an example, we characterize the behavior of a bladder during a forced respiratory motion with a reduced number of 3D surface points: first, a set of equidistant points representing the vertices of qu

Marc Habermann, Weipeng Xu, Michael Zollhoefer, Gerard Pons-Moll

Human performance capture is a highly important computer vision problem with many applications in movie production and virtual/augmented reality. Many previous performance capture approaches either required expensive multi-view setups or did not recover dense space-time coherent geometry with frame-to-frame correspondences. We propose a novel deep learning a

Kyle R. Bryenton1, Andrew R. Cameron, Keegan L. A. Kirk, Nasser Saad

The analysis of many physical phenomena can be reduced to the study of solutions of differential equations with polynomial coefficients. In the present work, we establish the necessary and sufficient conditions for the existence of polynomial solutions to the linear differential equation \begin{equation*} \sum_{k=0}^{n} α_{k} \, r^{k} \, y&#39;&#39;(r) + \su