February 2020 arXiv papers — page 3

D. V. Gal'tsov, M. Khlopunov

In odd space-time dimensions, the retarded solution of the massless wave equation has support not only on the light cone, but also inside it. At the same time, a free massless field should propagate at the speed of light. The apparent contradiction of these two features is resolved by the fact that the emitted part of the field in the wave zone depends on th

Jens Braband, Hendrik Schäbe

In this paper we discuss how systems with Artificial Intelligence (AI) can undergo safety assessment. This is relevant, if AI is used in safety related applications. Taking a deeper look into AI models, we show, that many models of artificial intelligence, in particular machine learning, are statistical models. Safety assessment would then have t o concentra

Pengcheng Zhang, Jianan Yu, Shunhui Ji

Testing is an important technique to improve the quality of Ethereum smart contract programs. However, current work on testing smart contract only focus on static problems of smart contract programs. A data flow oriented test case generation approach for dynamic testing of smart contract programs is still missing. To address this problem, this paper proposes

Akshay Ajagekar, Fengqi You

The purpose of this paper is to explore the applications of quantum computing to energy systems optimization problems and discuss some of the challenges faced by quantum computers with techniques to overcome them. The basic concepts underlying quantum computation and their distinctive characteristics in comparison to their classical counterparts are also dis

Jeng Yi Lee, Lujun Huang, Lei Xu, Andrey E. Miroshnichenko

We propose a universal strategy to realize a broadband control on arbitrary scatterers, through multiple coherent beams. By engineering the phases and amplitudes of incident beams, one can suppress the dominant scattering partial waves, making the obstacle lose its intrinsic responses in a broadband spectrum. The associated coherent beams generate a finite a

Xuhui Peng, Jianhua Huang, Rangrang Zhang

In this paper, we establish the existence, uniqueness and attraction properties of an invariant measure for the real Ginzburg-Landau equation in the presence of a degenerate stochastic forcing acting only in four directions. The main challenge is to establish time asymptotic smoothing properties of the Markovian dynamics corresponding to this system. To achi

Akihiro Yabe, Takanori Maehara

Data-driven decision-making is performed by solving a parameterized optimization problem, and the optimal decision is given by an optimal solution for unknown true parameters. We often need a solution that satisfies true constraints even though these are unknown. Robust optimization is employed to obtain such a solution, where the uncertainty of the paramete

Nan Chen

In this paper, the author study the throttling process of the Rotating Bardeen-AdS black hole in a systematic way. In the exended phase space, the mass of black holes should be viewed as entheply. We derive the Joule-Thomson coefficient $μ$ explicitly, and with numerical method, we depict the inversion curves and isenthalpic curves with different parameter $

M. A. Teeti

In this study, we consider the physical layer security in the downlink of a Massive MIMO system employing one-bit quantization at the base station (BS). We assume an active eavesdropper that attempts to spoiling the channel estimation acquisition at the BS for a legitimate user, whereas overhearing on downlink transmission. We consider the two most widesprea

Abanoub M. Girgis, Jihong Park, Chen-Feng Liu, Mehdi Bennis

While Remote control over wireless connections is a key enabler for scalable control systems consisting of multiple actuator-sensor pairs, i.e., control systems, it entails two technical challenges. Due to the lack of wireless resources, only a limited number of control systems can be served, making the state observations outdated. Further, even after schedu

David Kay, Vanessa Styles

We propose an efficient solver for saddle point problems arising from finite element approximations of nonlocal multi-phase Allen--Cahn variational inequalities. The solver is seen to behave mesh independently and to have only a very mild dependence on the number of phase field variables. In addition we prove convergence, in three GMRES iterations, of the ap

Pawel Krajewski, Piotr Kachlicki, Anna Piasecka, Maria Surma

In barley plants, water shortage causes many changes on the morphological, physiological and biochemical levels resulting in the reduction of grain yield. In the present study the results of various experiments on the response of the same barley recombinant inbred lines to water shortage, including phenotypic, proteomic and metabolomic traits were integrated

Davi Obata

In this paper we prove that for sufficiently large parameters the standard map has a unique measure of maximal entropy (m.m.e.). Moreover, we prove: the m.m.e. is Bernoulli, and the periodic points with Lyapunov exponents bounded away from zero equidistribute with respect to the m.m.e. We prove some estimates regarding the Hausdorff dimension of the m.m.e. a

Raza Rahi, Sumant Pushp, Arif Khan, Smriti Kumar Sinha

Morphological analyzers are the essential milestones for many linguistic applications like; machine translation, word sense disambiguation, spells checkers, and search engines etc. Therefore, development of an effective morphological analyzer has a greater impact on the computational recognition of a language. In this paper, we present a finite state transdu

Martin Bordemann, Jaigyoung Choe, Jens Hoppe

The determinantal variety $Σ_{pq}$ is defined to be the set of all $p\times q$ real matrices with $p\geq q$ whose ranks are strictly smaller than $q$. It is proved that $Σ_{pq}$ is a minimal cone in $\mathbb R^{pq}$ and all its strata are regular minimal submanifolds.

A. Cardesin-Moinelo, G. Piccioni, A. Migliorini, D. Grassi

One of the striking features about Venus atmosphere is its temporal variability and dynamics, with a chaotic polar vortex, large-scale atmospheric waves, sheared features, and variable winds that depend on local time and possibly orographic features. The aim of this research is to combine data accumulated over several years and obtain a global mean state of

Tim von Oehsen, Alexander Fabisch, Shivesh Kumar, Frank Kirchner

Several publications are concerned with learning inverse kinematics, however, their evaluation is often limited and none of the proposed methods is of practical relevance for rigid-body kinematics with a known forward model. We argue that for rigid-body kinematics one of the first proposed machine learning (ML) solutions to inverse kinematics -- distal teach

Yingshi Chen

We present a general architecture of deep differentiable forest and its sparse attention mechanism. The differentiable forest has the advantages of both trees and neural networks. Its structure is a simple binary tree, easy to use and understand. It has full differentiability and all variables are learnable parameters. We would train it by the gradient-based

Ralf Drautz

The atomic cluster expansion (Drautz, Phys. Rev. B 99, 014104 (2019)) is extended in two ways, the modelling of vectorial and tensorial atomic properties and the inclusion of atomic degrees of freedom in addition to the positions of the atoms. In particular, atomic species, magnetic moments and charges are attached to the atomic positions and an atomic clust

Yuki Ishihara, Kazuhiro Yokoyama

In this paper, we propose a new method for localization of polynomial ideal, which we call "Local Primary Algorithm". For an ideal $I$ and a prime ideal $P$, our method computes a $P$-primary component of $I$ after checking if $P$ is associated with $I$ by using "double ideal quotient" $(I:(I:P))$ and its variants which give us a lot of infor

Xuan Su, Wee Sun Lee, Zhen Zhang

We propose a new sampling-based approach for approximate inference in filtering problems. Instead of approximating conditional distributions with a finite set of states, as done in particle filters, our approach approximates the distribution with a weighted sum of functions from a set of continuous functions. Central to the approach is the use of sampling to

Hailong Li, Haiwen Liu, Hua Jiang, X. C. Xie

We investigate the 3D quantum Hall effect in Weyl semimetals and elucidate a global picture of the edge states. The edge states hosting 3D quantum Hall effect are combinations of Fermi arcs and chiral bulk Landau levels parallel to the magnetic field. The Hall conductance, $σ_{xz}^H$, shows quantized plateaus at Weyl nodes while tuning the magnetic field. Ho

Sebastiano Boscarino, Seung-Yeon Cho, Giovanni Russo, Seok-Bae Yun

In this paper, we propose a new semi-Lagrangian scheme for the polyatomic ellipsoidal BGK model. In order to avoid time step restrictions coming from convection term and small Knudsen number, we combine a semi-Lagrangian approach for the convection term with an implicit treatment for the relaxation term. We show how to explicitly solve the implicit step, thu

Wenqi Shao, Shitao Tang, Xingang Pan, Ping Tan

Convolutional Neural Networks (CNNs) are typically constructed by stacking multiple building blocks, each of which contains a normalization layer such as batch normalization (BN) and a rectified linear function such as ReLU. However, this work shows that the combination of normalization and rectified linear function leads to inhibited channels, which have sm

Xing Fan, Hao Luo, Chi Zhang, Wei Jiang

Due to its potential wide applications in video surveillance and other computer vision tasks like tracking, person re-identification (ReID) has become popular and been widely investigated. However, conventional person re-identification can only handle RGB color images, which will fail at dark conditions. Thus RGB-infrared ReID (also known as Infrared-Visible

Hanyu Li, Yuanyang Zhu

We present randomized algorithms based on block Krylov space method for estimating the trace and log-determinant of Hermitian positive semi-definite matrices. Using the properties of Chebyshev polynomial and Gaussian random matrix, we provide the error analysis of the proposed estimators and obtain the expectation and concentration error bounds. These bounds

Lyderic Bocquet

This is a turning point for nanofluidics. Recent progress allows envisioning both fundamental discoveries for the transport of fluids at the ultimate scales, and disruptive technologies for the water-energy nexus.

Yang Xu, Jing Wang, Maohai Huang, Jianyan Wei

With its large field of view, GWAC can record hundreds of meteors every day. These meteors are valuable treasures for some meteor research groups. It is therefore very important to accurately find all of these meteors. To address the challenge of precisely distinguishing meteors from other elongated objects in a GWAC-like sky survey system, we design and imp

Chih-Chieh Hung, Chun-Yen Shen

In the work of S. Petermichl, S. Treil and A. Volberg it was explicitly constructed that the Riesz transforms in any dimension $n \geq 2$ can be obtained as an average of dyadic Haar shifts provided that an integral is nonzero. It was shown in the paper that when $n=2$, the integral is indeed nonzero (negative) but for $n \geq 3$ the nonzero property remains

Pankaj K. Agarwal, Hsien-Chih Chang, Subhash Suri, Allen Xiao

We investigate dynamic versions of geometric set cover and hitting set where points and ranges may be inserted or deleted, and we want to efficiently maintain an (approximately) optimal solution for the current problem instance. While their static versions have been extensively studied in the past, surprisingly little is known about dynamic geometric set cov

Chaehan So

When people buy products online, they primarily base their decisions on the recommendations of others given in online reviews. The current work analyzed these online reviews by sentiment analysis and used the extracted sentiments as features to predict the product ratings by several machine learning algorithms. These predictions were disentangled by various

Salman Sajad Wani, Dylan Sutherland, Behnam Pourhassan, Mir Faizal

Using T-duality, we will argue that a zero point length exists in the low energy effective field theory of string theory on compactified extra dimensions. Furthermore, if we neglect the oscillator modes, this zero point length would modify low quantum mechanical systems. As this zero length is fixed geometrically, it is important to analyze how it modifies p

Xiaopeng Mo, Jie Xu

This paper studies a federated edge learning system, in which an edge server coordinates a set of edge devices to train a shared machine learning model based on their locally distributed data samples. During the distributed training, we exploit the joint communication and computation design for improving the system energy efficiency, in which both the commun

Longlong Jing, Toufiq Parag, Zhe Wu, Yingli Tian

We propose a semi-supervised learning approach for video classification, VideoSSL, using convolutional neural networks (CNN). Like other computer vision tasks, existing supervised video classification methods demand a large amount of labeled data to attain good performance. However, annotation of a large dataset is expensive and time consuming. To minimize t

Jose A. Magpantay

I show how the Lindblad Plus equation will follow from the Feynman-Vernon theory. The Plus refers to the inclusion of non-Markov processes in the Lindblad equation resulting in an integro-differential general master equation. The equivalence of this general master equation and not the Lindblad equation alone to the Feynman-Vernon theory should be expected be

Ruqi Zhang, A. Feder Cooper, Christopher De Sa

Stochastic gradient Hamiltonian Monte Carlo (SGHMC) is an efficient method for sampling from continuous distributions. It is a faster alternative to HMC: instead of using the whole dataset at each iteration, SGHMC uses only a subsample. This improves performance, but introduces bias that can cause SGHMC to converge to the wrong distribution. One can prevent

Elsayed A. H. Elamir

After rejecting the null hypothesis in the analysis of variance, the next step is to make the pairwise comparisons to find out differences in means. The purpose of this paper is threefold. The foremost aim is to suggest expression for calculating decision limit that enables us to collect the test and pairwise comparisons in one step. This expression is propo

Dejun Liu, Lin Chen, Feng Liu

Compact and low-loss photonic crystal waveguides are critical in integrated terahertz (THz) applications. Compared with pure metal or dielectric photonic crystal waveguides, hybrid (metal-dielectric) integrated waveguides provide a simple way to further improve the field confinement and the propagation loss. In this work, we investigate a hybrid waveguide co

Yong Wang

In this paper, we obtain Chen's inequalities for submanifolds in $(κ,μ)$-contact space form with two kinds of generalized semi-symmetric non-metric connections.

Yu-chen Sung, Sagar V. Patil, Michael G. Safonov

For a non-linear MIMO feedback system, the robustness against uncertain time-variations in the feedback loop is investigated in an input-output framework. A general sufficient condition in terms of a bound on average rates of time-variation for the system to be stable is derived. The condition gives a tolerable limit on infrequent large variations or slow ti

Jiahao Xu, Alan M. Ferrenberg, David P. Landau

We apply extensive Monte Carlo simulations to study the probability distribution $P(m)$ of the order parameter $m$ for the simple cubic Ising model with periodic boundary condition at the transition point. Sampling is performed with the Wolff cluster flipping algorithm, and histogram reweighting together with finite-size scaling analyses are then used to ext

Gabriel S. Denicol, Jorge Noronha

We investigate whether hydrodynamic attractors are present in simulations of the quark-gluon plasma formed in heavy-ion collisions. We argue that Lagrangian schemes to solve the relativistic viscous fluid equations can be particularly useful to characterize the properties of attractors in heavy ion collisions. Preliminary results are shown in Israel-Stewart

Wonhee Ko, Marek Kolmer, Jiaqiang Yan, Anh D. Pham

The interplay between magnetism and non-trivial topology in magnetic topological insulators (MTI) is expected to give rise to a variety of exotic topological quantum phenomena, such as the quantum anomalous Hall (QAH) effect and the topological axion states. A key to assessing these novel properties is to tune the Fermi level in the exchange gap of the Dirac

Fuwei Li, Lifeng Lai, Shuguang Cui

In this paper, we investigate how to manipulate the coefficients obtained via linear regression by adding carefully designed poisoning data points to the dataset or modify the original data points. Given the energy budget, we first provide the closed-form solution of the optimal poisoning data point when our target is modifying one designated regression coef

Daliang Xu, Dongwei Chen, Chun Yang, KangSun

Use-After-Free vulnerabilities, allowing the attacker to access unintended memory via dangling pointers, are more threatening. However, most detection schemes can only detect dangling pointers and invalid them, but not provide a tolerance mechanism to repair the errors at runtime. Also, these techniques obtain and manage the metadata inefficiently with compl

E. V. Stock, R. da Silva

In this work we propose a two-dimensional extension of a previously defined one-dimensional version of a model of counterflowing particles, which considers an adapted Fermi-Dirac distribution to describe the transition probabilities. In this modified and extended version of the model, we consider that only particles of different species interact and they hop

Kristopher Pierson, Alex Povitsky

The vorticity confinement (VC) method was used with total variation diminishing (TVD) schemes to reduce possible over-confinement and applied to tip vortices shed by edges of wings in order to predict induced drag using far-field integration. The optimal VC parameter was determined first by application to 2-D vortices and then to tip vortices shed by a 3-D w

Xiang Zhang, Qingqing Yang, Jinru Ding, Ziyue Wang

Knowledge Graphs (KGs) are graph-structured knowledge bases storing factual information about real-world entities. Understanding the uniqueness of each entity is crucial to the analyzing, sharing, and reusing of KGs. Traditional profiling technologies encompass a vast array of methods to find distinctive features in various applications, which can help to di

George S. Barron, Bryan T. Gard, Orien J. Altman, Nicholas J. Mayhall

One of the most promising applications of noisy intermediate-scale quantum computers is the simulation of molecular Hamiltonians using the variational quantum eigensolver. We show that encoding symmetries of the simulated Hamiltonian in the VQE ansatz reduces both classical and quantum resources compared to other, widely available ansatze. Through simulation

Cara D. Brooks, Alberto A. Condori, Nicholas Seguin

Given two $d\times d$ matrices, say $A$ and $B$, when do $p(A)$ and $p(B)$ have the same ``size'' for every polynomial $p$? In this article, we provide definitive results in the cases $d=2$ and $d=3$ when the notion of size used is the spectral norm.

Wang-Sheng Liu, Sai Hung Cheung

Reliability-based design optimization (RBDO) provides a rational and sound framework for finding the optimal design while taking uncertainties into ac-count. The main issue in implementing RBDO methods, particularly stochastic simu-lation based ones, is the computational burden arising from the evaluation of reliability constraints. In this contribution, we

Yijin Liu, Fandong Meng, Yufeng Chen, Jinan Xu

The Sentence-State LSTM (S-LSTM) is a powerful and high efficient graph recurrent network, which views words as nodes and performs layer-wise recurrent steps between them simultaneously. Despite its successes on text representations, the S-LSTM still suffers from two drawbacks. Firstly, given a sentence, certain words are usually more ambiguous than others,

Yinjie Lei, Yan Liu, Pingping Zhang, Lingqiao Liu

Most existing crowd counting methods require object location-level annotation, i.e., placing a dot at the center of an object. While being simpler than the bounding-box or pixel-level annotation, obtaining this annotation is still labor-intensive and time-consuming especially for images with highly crowded scenes. On the other hand, weaker annotations that o

Chengshuai Shi, Wei Xiong, Cong Shen, Jing Yang

The decentralized stochastic multi-player multi-armed bandit (MP-MAB) problem, where the collision information is not available to the players, is studied in this paper. Building on the seminal work of Boursier and Perchet (2019), we propose error correction synchronization involving communication (EC-SIC), whose regret is shown to approach that of the centr

Yang Xu, Liping Xin, Jing Wang, Xuhui Han

The ground-based wide-angle camera array (GWAC) generates millions of single frame alerts per night. After the complicated and elaborate filters by multiple methods, a couple of dozens of candidates are still needed to be confirmed by follow-up observations in real-time. In order to free scientists from the complex and high-intensity follow-up tasks, we deve

Chengyuan Li, Yue Wang, Baitian Tang, Antonino P. Milone

Recent studies have revealed that the onset age for the presence of multiple stellar populations (MPs) in star clusters seems to correspond to the disappearance of the extended main-sequence turnoff (eMSTO) in young clusters, a pattern associated with stellar rotations. A speculative suggestion is that MPs might be caused by the magnetic brake, a stellar evo

Prashant Vijay Gaikwad, Anjali Kshirsagar

A new class of tetragonally symmetric 2D octagonal family of monolayers (o-MLs) has emerged recently and demands understanding at the fundamental level. o-MLs of metal nitride and carbide family (BN, AlN, GaN, GeC, SiC) along with C and BP are computationally designed and their stability and electronic structure are investigated. These binary o-MLs show mixe

Mojtaba Haghighatlari, Jie Li, Farnaz Heidar-Zadeh, Yuchen Liu

Recently supervised machine learning has been ascending in providing new predictive approaches for chemical, biological and materials sciences applications. In this Perspective we focus on the interplay of machine learning algorithm with the chemically motivated descriptors and the size and type of data sets needed for molecular property prediction. Using Nu

Heron Caldas

We investigate the superfluid-to-normal zero temperature quantum phase transitions of asymmetric two-component Fermi gases as a function of the chemical potential imbalance $h$. The calculations are performed for homogeneous and trapped imbalanced systems. We concentrate at unitarity, characterized by a divergent interaction parameter $k_F a$, where most of

Keiichi Akama

We incorporate confining effects into statistical formulation of quantum chromodynamics (QCD). It implies that quark-gluon clusters existed in the early universe, triggering the information accumulation in nature. The confinement-driven clustering would explain the reason why the quark-gluon plasma in the heavy-ion ollision experiments looks like liquid unli

Tao Ji, Liqian Chen, Xiaoguang Mao, Xin Yi

Merging other branches into the current working branch is common in collaborative software development. However, developers still heavily rely on the textual merge tools to handle the complicated merge tasks. The latent semantic merge conflicts may fail to be detected and degrade the software quality. Regression testing is able to prevent regression faults a

John Demme

This whitepaper proposes a unified framework for hardware design tools to ease the development and inter-operability of said tools. By creating a large ecosystem of hardware development tools across vendors, academia, and the open source community, we hope to significantly increase much need productivity in hardware design.

Vo Tien Phong, E. J. Mele

The electronic bands of twisted bilayer graphene (TBLG) with a large-period moiré superlattice fracture to form narrow Bloch minibands that are spectrally isolated by forbidden energy gaps from remote dispersive bands. When these gaps are sufficiently large, one can study a band-projected Hamiltonian that correctly represents the dynamics within the miniband

Lan Di, Yudi Gu, Guoqi Qian, George Xianzhi Yuan

This paper focuses on studying and understanding of stochastic dynamics in population composition when the population is subject to rumor spreading. We undertake the study by first developing an individual Susceptible-Exposed-Infectious-Removed (iSEIR) model, an extension of the SEIR model, for summarizing rumor-spreading behaviors of interacting groups in t

Luting Yang, Bingqian Lu, Shaolei Ren

Running deep neural network (DNN) inference on mobile devices, i.e., mobile inference, has become a growing trend, making inference less dependent on network connections and keeping private data locally. The prior studies on optimizing DNNs for mobile inference typically focus on the metric of average inference latency, thus implicitly assuming that mobile i

Yue Zhao, Craig O. Heinke, Vlad Tudor, Arash Bahramian

Using a 16.2 hr radio observation by the Australia Telescope Compact Array (ATCA) and archival Chandra data, we found $>5σ$ radio counterparts to 4 known and 3 new X-ray sources within the half-light radius ($r_\mathrm{h}$) of the Galactic globular cluster NGC 6397. The previously suggested millisecond pulsar (MSP) candidate, U18, is a steep-spectrum ($S_ν\p

Kelly Boothby, Paul Bunyk, Jack Raymond, Aidan Roy

This paper presents an overview of the topology of D-Wave's next-generation quantum processors. It provides examples of minor embeddings and discusses performance of embedding algorithms for the new topology compared to the existing Chimera topology. It also presents some initial performance results for simple, standard Ising model classes of problems.

Mike Lampton

The Doomsday Argument (DA) has sparked a variety of opinions. Here I address a key question posed by F. Simpson (2016) that confronts the views of DA proponents and those who, like me, oppose the DA. I agree that typical locations within a complete spatial distribution are calculable using ordinary frequentist probability. But I argue that the temporal proba

Matan Leibovich, George Papanicolaou, Chrysoula Tsogka

We consider imaging of fast moving small objects in space, such as low earth orbit satellites. The imaging system consists of ground based, asynchronous sources of radiation and several passive receivers above the dense atmosphere. We use the cross correlation of the received signals to reduce distortions from ambient medium fluctuations. Imaging with correl

James Wallbridge

We introduce a new deep learning architecture for predicting price movements from limit order books. This architecture uses a causal convolutional network for feature extraction in combination with masked self-attention to update features based on relevant contextual information. This architecture is shown to significantly outperform existing architectures s

Duc P. Truong, Erik Skau, Vladimir I. Valtchinov, Boian S. Alexandrov

Currently, high-dimensional data is ubiquitous in data science, which necessitates the development of techniques to decompose and interpret such multidimensional (aka tensor) datasets. Finding a low dimensional representation of the data, that is, its inherent structure, is one of the approaches that can serve to understand the dynamics of low dimensional la

Zhe Zeng, Paolo Morettin, Fanqi Yan, Antonio Vergari

Weighted model integration (WMI) is a very appealing framework for probabilistic inference: it allows to express the complex dependencies of real-world problems where variables are both continuous and discrete, via the language of Satisfiability Modulo Theories (SMT), as well as to compute probabilistic queries with complex logical and arithmetic constraints

Don Jean Baptiste Anoman, François Arnault, Simone Naldi

We describe a protocol for generating random numbers based on the existence of quantum violations of a free Clauser-Horne-Shimony-Holt inequality, namely CHSH-3. Our method uses semidefinite programming relaxations to compute such violations. In a standard setting the CHSH-3 inequality involves two separated qutrits and compatible measurement, that is, commu

Michael P. Evans, Simon H. Tindemans

This paper presents a framework for deriving the storage capacity that an electricity system requires in order to satisfy a chosen risk appetite. The framework takes as inputs user-defined event categories, parameterised by peak power-not-served, acceptable number of events per year and permitted probability of exceeding these constraints, and returns as an

Yi-Cheng Chen, Ping-En Lu, Cheng-Shang Chang, Tzu-Hsuan Liu

In this paper, we conduct mathematical and numerical analyses to address the following crucial questions for COVID-19: (Q1) Is it possible to contain COVID-19? (Q2) When will be the peak and the end of the epidemic? (Q3) How do the asymptomatic infections affect the spread of disease? (Q4) What is the ratio of the population that needs to be infected to achi

Zhuolin Yang, Zhikuan Zhao, Boxin Wang, Jiawei Zhang

Intensive algorithmic efforts have been made to enable the rapid improvements of certificated robustness for complex ML models recently. However, current robustness certification methods are only able to certify under a limited perturbation radius. Given that existing pure data-driven statistical approaches have reached a bottleneck, in this paper, we propos

Aliasghar Tarkhan, Noah Simon

In many biomedical applications, outcome is measured as a ``time-to-event'' (eg. disease progression or death). To assess the connection between features of a patient and this outcome, it is common to assume a proportional hazards model, and fit a proportional hazards regression (or Cox regression). To fit this model, a log-concave objective function

F. Ulrich-Pur, T. Bergauer, A. Burker, S. Hatamikia

Ion beam therapy has become a frequently applied form of cancer therapy over the last years. The advantage of ion beam therapy over conventional radiotherapy using photons is the strongly localized dose deposition, leading to a reduction of dose applied to surrounding healthy tissue. Currently, treatment planning for proton therapy is based on X-ray computed

Maarten Golterman, Ethan T. Neil, Yigal Shamir

We extend dilaton chiral perturbation theory (dChPT) to include the taste splittings in the Nambu--Goldstone sector observed in lattice simulations of near-conformal theories with staggered fermions. We then apply dChPT to a recent simulation by the LSD collaboration of the SU(3) gauge theory with 8 fermions in the fundamental representation, which is believ

G. Grissonnanche, S. Thériault, A. Gourgout, M. -E. Boulanger

The nature of the pseudogap phase of cuprates remains a major puzzle. One of its new signatures is a large negative thermal Hall conductivity $κ_{\rm xy}$, which appears for dopings $p$ below the pseudogap critical doping $p^*$, but whose origin is as yet unknown. Because this large $κ_{\rm xy}$ is observed even in the undoped Mott insulator La$_2$CuO$_4$, i

Mohammed Alser, Jeremy Rotman, Kodi Taraszka, Huwenbo Shi

Massively parallel sequencing techniques have revolutionized biological and medical sciences by providing unprecedented insight into the genomes of humans, animals, and microbes. Modern sequencing platforms generate enormous amounts of genomic data in the form of nucleotide sequences or reads. Aligning reads onto reference genomes enables the identification

Daniel Giles, Lucianne Walkowicz

In the present era of large scale surveys, big data presents new challenges to the discovery process for anomalous data. Such data can be indicative of systematic errors, extreme (or rare) forms of known phenomena, or most interestingly, truly novel phenomena which exhibit as-of-yet unobserved behaviors. In this work we present an outlier scoring methodology

John Kastner, Hanan Samet, Hong Wei

With the rapid continuing spread of COVID-19, it is clearly important to be able to track the progress of the virus over time in order to be better prepared to anticipate its emergence and spread in new regions as well as declines in its presence in regions thereby leading to or justifying "reopening" decisions. There are many applications and web si

Wissam Antoun, Fady Baly, Hazem Hajj

The Arabic language is a morphologically rich language with relatively few resources and a less explored syntax compared to English. Given these limitations, Arabic Natural Language Processing (NLP) tasks like Sentiment Analysis (SA), Named Entity Recognition (NER), and Question Answering (QA), have proven to be very challenging to tackle. Recently, with the

Vivian Dornelas, Eduardo H. Colombo, Cristóbal López, Emilio Hernández-García

We study the effect that disturbances in the ecological landscape exert on the spatial distribution of a population that evolves according to the nonlocal FKPP equation. Using both numerical and analytical techniques, we explore the three types of stationary profiles that can develop near abrupt spatial variations in the environmental conditions vital for po

Xiangyu Zhao, Xudong Zheng, Xiwang Yang, Xiaobing Liu

Online recommendation and advertising are two major income channels for online recommendation platforms (e.g. e-commerce and news feed site). However, most platforms optimize recommending and advertising strategies by different teams separately via different techniques, which may lead to suboptimal overall performances. To this end, in this paper, we propose

Giosuè Muratore

Let $X$ be a smooth complex projective variety. Using a construction devised to Gathmann, we present a recursive formula for some of the Gromov-Witten invariants of $X$. We prove that, when $X$ is homogeneous, this formula gives the number of osculating rational curves at a general point of a general hypersurface of $X$. This generalizes the classical well k

J. C. Xavier, M. A. Rajabpour

We calculate the entanglement and the universal boundary entropy (BE) in the critical quantum spin chains, such as the transverse field Ising chain and the XXZ chain, with arbitrary direction of the boundary magnetic field (ADBMF). We determine the boundary universality class that an ADBMF induces. In particular, we show that the induced boundary conformal f

M. Ablikim, M. N. Achasov, P. Adlarson, S. Ahmed

Crucial inputs for a variety of $CP$-violation studies can be determined through the analysis of pairs of quantum-entangled neutral $D$ mesons, which are produced in the decay of the $ψ(3770)$ resonance. The relative strong-phase parameters between $D^0$ and $\bar{D}^0$ in the decays $D^0\rightarrow K^0_{S,L}π^+π^-$ are studied using 2.93~${\rm fb}^{-1}$ of

Magda Peligrad

In this paper we study the additive functionals of Markov chains via conditioning with respect to both past and future of the chain. We shall point out new sufficient projective conditions, which assure that the variance of partial sums of n consecutive random variables of a stationary Markov chain is linear in n. The paper also addresses the central limit t

Immanuel Ben Porat

We investigate variants of a Three Circles type Theorem in the context of \mathcal{Q}-valued functions. We prove some convexity inequalities related to the L^{2} growth function in the \mathcal{Q}-valued settings. Optimality of these inequalities and comparsion to the case of real valued harmonic functions is also discussed.

Logan Francis, Nienke van der Marel

Transition disks with large inner dust cavities are thought to host massive companions. However, the disk structure inside the companion orbit and how material flows toward an actively accreting star remain unclear. We present a high resolution continuum study of inner disks in the cavities of 38 transition disks. Measurements of the dust mass from archival

Joel L. Pfeffer, Sebastian Trujillo-Gomez, J. M. Diederik Kruijssen, Robert A. Crain

The ages and metallicities of globular clusters (GCs) are known to be powerful tracers of the properties of their progenitor galaxies, enabling their use in determining the merger histories of galaxies. However, while useful in separating GCs into individual accretion events, the orbits of GC groups themselves have received less attention as probes of their

Kambiz Azarian, Yash Bhalgat, Jinwon Lee, Tijmen Blankevoort

This paper presents a novel differentiable method for unstructured weight pruning of deep neural networks. Our learned-threshold pruning (LTP) method learns per-layer thresholds via gradient descent, unlike conventional methods where they are set as input. Making thresholds trainable also makes LTP computationally efficient, hence scalable to deeper networks

Lee Lindblom, Benjamin J. Owen

We describe directed searches for continuous gravitational waves from twelve well localized non-pulsing candidate neutron stars in young supernova remnants using data from Advanced LIGO's second observing run. We assumed that each neutron star is isolated and searched a band of frequencies from 15 to 150\,Hz, consistent with frequencies expected from kno

Lauren Bandklayder, Julia E. Bergner, Rhiannon Griffiths, Brenda Johnson

In this paper we present background results in enriched category theory and enriched model category theory necessary for developing model categories of enriched functors suitable for doing functor calculus.

Marijan Palmisano, Martin Steinberger, Martin Horn

An optimal control law for networked control systems with a discrete-time linear time-invariant (LTI) system as plant and networks between sensor and controller as well as between controller and actuator is proposed. This controller is designed by solving an optimization problem that is a generalization of the optimization problem used to obtain the Linear Q

Dandan Ji, Eric Brown

We present observations of oscillations in the shape of the temperature profile of the large-scale circulation (LSC) of turbulent Rayleigh-B{é}nard convection. Temperature measurements are broken down into Fourier moments as a function of $θ-θ_0$, where $θ$ is the azimuthal angle in a horizontal plane at mid-height, and $θ_0$ is the LSC orientation. The osci

Zachary C Williams, Dylan E McNamara

Empirical diagnosis of stability has received considerable attention, mostly focused on variance metrics for early warning signals of abrupt system change. Despite this, the theoretical foundation and application has been limited to relatively simple system changes such as bifurcating fixed points where variability is extrinsic to the steady state. There is

Mario Bukal, Boris Muha

In this paper we review and systematize the mathematical theory on justification of sixth-order thin-film equations as reduced models for various fluid-structure interaction systems in which fluids are lubricating underneath elastic structures. Justification is based on careful examination of energy estimates, weak convergence results of solutions of the ori