October 2020 arXiv papers — page 15

K Nobleson, Amna Ali, Sarmistha Banik

In this paper, we examine neutron star structure in perturbative $f(R)$ gravity models with realistic equation of state. We obtain mass-radius relations in two gravity models of the form $f_{1}(R)=R+ \alpha R(e^{-R/R_0}-1)$ and $f_{2}(R)=R+\alpha R^2$. For this purpose, we consider NS with several nucleonic as well as strange EoSs generated in the framework

Smisha M A, P G Romeo

Gamma-semigroup is introduced as a generalization of semigroups by M. K Sen and Saha. In this paper we describe amalgam of two Gamma-semigroups and discuss the embeddability of this amalgam. Further we obtained a necessary condition for the embeddability of completely alpha-regular Gamma-semigroup amalgam.

Ting Wang, Xike Xie, Xin Cao, Torben Bach Pedersen

The proliferation of advanced mobile terminals opened up a new crowdsourcing avenue, spatial crowdsourcing, to utilize the crowd potential to perform real-world tasks. In this work, we study a new type of spatial crowdsourcing, called time-continuous spatial crowdsourcing (TCSC in short). It supports broad applications for long-term continuous spatial data a

Marcin Wątorek, Stanisław Drożdż, Jarosław Kwapień, Ludovico Minati

The review introduces the history of cryptocurrencies, offering a description of the blockchain technology behind them. Differences between cryptocurrencies and the exchanges on which they are traded have been shown. The central part surveys the analysis of cryptocurrency price changes on various platforms. The statistical properties of the fluctuations in t

Tomohiro Furukawa, Sanefumi Moriyama, Tomoki Nakanishi

It is a well-known result by Hanany and Witten that, when two five-branes move across each other, D3-branes stretching between them are generated. Later the same brane configurations played a crucial role in understanding the worldvolume theory of multiple M2-branes. Recently the partition function of multiple M2-branes was transformed to the Fredholm determ

Reetika Joshi, Brigitte Schmieder, Akiko Tei, Guillaume Aulanier

The Interface Region Imaging Spectrograph(IRIS) with its high spatial and temporal resolution brings exceptional plasma diagnostics of solar chromospheric and coronal activity during magnetic reconnection. The aim of this work is to study the fine structure and dynamics of the plasma at a jet base forming a mini flare between two emerging magnetic fluxes (EM

S. Crossley, R. W. Whatmore, N. D. Mathur, X. Moya

Electrically driven adiabatic changes of temperature are identified in the archetypal electrocaloric material PbSc0.5Ta0.5O3 by comparing isothermal changes of electrical polarization due to slow variation of electric field, and adiabatic changes of electrical polarization due to fast variation of electric field. By obtaining isothermal (adiabatic) electrica

Gary P. T. Choi, Yechen Liu, Lok Ming Lui

With the advancement in 3D scanning technology, there has been a surge of interest in the use of point clouds in science and engineering. To facilitate the computations and analyses of point clouds, prior works have considered parameterizing them onto some simple planar domains with a fixed boundary shape such as a unit circle or a rectangle. However, the ge

Xuejie Liu, Hongxia Huang, Jialun Ping, Dianyong Chen

We conduct a dynamical calculation of pentaquark systems with quark contents $sssu\bar{u}$ in the framework of two quark models: the chiral quark model(ChQM) and quark delocalization color screening model(QDCSM). The effective potentials between baryon and meson clusters are given, and the possible bound states are also investigated. Besides, the study of th

Vitalii Yunko, Małgorzata Białous, Leszek Sirko

We investigated the spectra of resonances of four-vertex microwave networks simulating both quantum graphs with preserved and with partially violated time-reversal invariance before and after an edge switch operation. We show experimentally that under the edge switch operation the spectra of the microwave networks with preserved time reversal symmetry are le

Noriyuki Hashimoto, Noboru Osawa, Kosuke Yamazaki, Shinsuke Ibi

Orthogonal time frequency and space (OTFS) modulation is a promising technology that satisfies high Doppler requirements for future mobile systems. OTFS modulation encodes information symbols and pilot symbols into the two-dimensional (2D) delay-Doppler (DD) domain. The received symbols suffer from inter-Doppler interference (IDI) in the fading channels with

Anna Bertiger, Dorian Ehrlich, Elizabeth Milićević, Kaisa Taipale

The quantum cohomology ring of the Grassmannian is determined by the quantum Pieri rule for multiplying by Schubert classes indexed by row or column-shaped partitions. We provide a direct equivariant generalization of Postnikov's quantum Pieri rule for the Grassmannian in terms of cylindric shapes, complementing related work of Gorbounov and Korff in quantum

Yizun He, Lingjing Ji, Yuzhuo Wang, Liyang Qiu

The absorption of traveling photons resonant with electric dipole transitions of an atomic gas naturally leads to electric dipole spin wave excitations. For a number of applications, it would be highly desirable to shape and coherently control the spatial waveform of the spin waves before spontaneous emission can occur. This paper details a recently develope

Shaolin Ji, Rundong Xu

This paper examines the stochastic maximum principle (SMP) for a forward-backward stochastic control system where the backward state equation is characterized by the backward stochastic differential equation (BSDE) with quadratic growth and the forward state at the terminal time is constrained in a convex set with probability one. With the help of the theory

Fraser Hall, Leandros Maglaras, Theodoros Aivaliotis, Loukas Xagoraris

Development and growth of Internet of Things (IoT) technology has exponentially increased over the course of the last 10 years since its inception, and as a result has directly influenced the popularity and size of smart homes. In this article we present the main technologies and applications that constitute a smart home, we identify the main security and pr

Alexander Shevtsov Alexander Shevtsov, Maria Oikonomidou, Despoina Antonakaki, Polyvios Pratikakis

A very large number of people use Online Social Networks daily. Such platforms thus become attractive targets for agents that seek to gain access to the attention of large audiences, and influence perceptions or opinions. Botnets, collections of automated accounts controlled by a single agent, are a common mechanism for exerting maximum influence. Botnets ma

Ziyang Tang, Yihao Feng, Na Zhang, Jian Peng

Off-policy evaluation provides an essential tool for evaluating the effects of different policies or treatments using only observed data. When applied to high-stakes scenarios such as medical diagnosis or financial decision-making, it is crucial to provide provably correct upper and lower bounds of the expected reward, not just a classical single point estim

Fariborz Salehi, Babak Hassibi

Despite the enormous success of machine learning models in various applications, most of these models lack resilience to (even small) perturbations in their input data. Hence, new methods to robustify machine learning models seem very essential. To this end, in this paper we consider the problem of binary classification with adversarial perturbations. Invest

Hanle Zheng, Yujie Wu, Lei Deng, Yifan Hu

Spiking neural networks (SNNs) are promising in a bio-plausible coding for spatio-temporal information and event-driven signal processing, which is very suited for energy-efficient implementation in neuromorphic hardware. However, the unique working mode of SNNs makes them more difficult to train than traditional networks. Currently, there are two main route

Zhi Wang, Chicheng Zhang, Manish Kumar Singh, Laurel D. Riek

In many real-world applications, multiple agents seek to learn how to perform highly related yet slightly different tasks in an online bandit learning protocol. We formulate this problem as the $\epsilon$-multi-player multi-armed bandit problem, in which a set of players concurrently interact with a set of arms, and for each arm, the reward distributions for

Ke Chen, Beici Liang, Xiaoshuan Ma, Minwei Gu

Personalized recommendation on new track releases has always been a challenging problem in the music industry. To combat this problem, we first explore user listening history and demographics to construct a user embedding representing the user's music preference. With the user embedding and audio data from user's liked and disliked tracks, an audio embedding

Alok Kumbhare, Reza Azimi, Ioannis Manousakis, Anand Bonde

Datacenter designers rely on conservative estimates of IT equipment power draw to provision resources. This leaves resources underutilized and requires more datacenters to be built. Prior work has used power capping to shave the rare power peaks and add more servers to the datacenter, thereby oversubscribing its resources and lowering capital costs. This wor

Jean Richert, Tarek Khalil

The consistent definition of the thermodynamic functions of small open quantum systems in contact with an environment in equilibrium with a heat bath has been the subject of many debates in the quantum community. In the present work we reproduce and comment parts of a recent approach of this subject by Rivas [15]. This approach overcomes the controversial di

Genadi Levin

Let P be a non-linear polynomial, K_P the filled Julia set of P, f a renormalization of P and K_f the filled Julia set of f. We show, loosely speaking, that there is a finite-to-one function \lambda from the set of P-external rays having limit points in K_f onto the set of f-external rays to K_f such that R and \lambda(R) share the same limit set. In particu

Debaldev Jana, Saikat Batabyal, M. Lakshmanan

In the present work, we explore the influence of habitat complexity on the activities of prey and predator of a spatio-temporal system by incorporating self diffusion. First we modify the Rosenzweig-MacArthur predator-prey model by incorporating the effects of habitat complexity on the carrying capacity and fear effect of prey and predator functional respons

Shan-Shan Ding, Kai Leong Chong, Jun-Qiang Shi, Guang-Yu Ding

When a fluid system is subject to strong rotation, centrifugal fluid motion is expected, i.e., denser (lighter) fluid moves outward (inward) from (toward) the axis of rotation. Here we demonstrate, both experimentally and numerically, the existence of an unexpected outward motion of warm and lighter vortices in rotating turbulent convection. This anomalous v

Geoffrey M. Vasil, Keith Julien, Nicholas A. Featherstone

This paper considers the dominant dynamical, thermal and rotational balances within the solar convection zone. The reasoning is such that: Coriolis forces balance pressure gradients. Background vortex stretching, baroclinic torques and nonlinear advection balance jointly. Turbulent fluxes convey what part of the solar luminosity that radiative diffusion cann

Jifan Zhang, Lalit Jain, Kevin Jamieson

This work proposes a procedure for designing algorithms for specific adaptive data collection tasks like active learning and pure-exploration multi-armed bandits. Unlike the design of traditional adaptive algorithms that rely on concentration of measure and careful analysis to justify the correctness and sample complexity of the procedure, our adaptive algor

Tanuka Chattopadhyay, Sreerup Mondal, Suman Paul, Subhadip Maji

The present work explores the origin of the formation of star clusters in our Galaxy and in Small Magellanic Cloud (SMC) through simulated H-R diagrams and compare those with observed star clusters. The simulation study produces synthetic H-R diagrams by Markov Chain Monte Carlo (MCMC) technique using star formation history (SFH), luminosity function (LF), a

Veysel Çelik

In this study, the structural, electronic and optical properties of Pb doped rutile SnO$_2$ were investigated using the range separated hybrid exchange-correlation functional method. In the calculations, LDA functional was used instead of PBE functional. The electronic structure of SnO$_2$ obtained by this method is quite compatible with the experimental dat

Fariborz Salehi, Ehsan Abbasi, Babak Hassibi

Logistic models are commonly used for binary classification tasks. The success of such models has often been attributed to their connection to maximum-likelihood estimators. It has been shown that gradient descent algorithm, when applied on the logistic loss, converges to the max-margin classifier (a.k.a. hard-margin SVM). The performance of the max-margin c

Byungju Kim, Jaeyoung Lee, Kyungsu Kim, Sungjin Kim

Although well-trained deep neural networks have shown remarkable performance on numerous tasks, they rapidly forget what they have learned as soon as they begin to learn with additional data with the previous data stop being provided. In this paper, we introduce a novel algorithm, Incremental Class Learning with Attribute Sharing (ICLAS), for incremental cla

Rory Bunker, Keisuke Fujii, Hiroyuki Hanada, Ichiro Takeuchi

Given a set of sequences comprised of time-ordered events, sequential pattern mining is useful to identify frequent subsequences from different sequences or within the same sequence. However, in sport, these techniques cannot determine the importance of particular patterns of play to good or bad outcomes, which is often of greater interest to coaches and per

Wei Chen, Bowen Zhang, Shi Jin, Bo Ai

Sparse signal recovery problems from noisy linear measurements appear in many areas of wireless communications. In recent years, deep learning (DL) based approaches have attracted interests of researchers to solve the sparse linear inverse problem by unfolding iterative algorithms as neural networks. Typically, research concerning DL assume a fixed number of

Rory Bunker, Kirsten Spencer

Performance indicators that contributed to success at the group stage and play-off stages of the 2019 Rugby World Cup were analysed using publicly available data obtained from the official tournament website using both a non-parametric statistical technique, Wilcoxon's signed rank test, and a decision rules technique from machine learning called RIPPER. Our

Anshul Guha

An $n$-crossing projection of a link $L$ is a projection of $L$ onto a plane such that $n$ points on $L$ are superimposed on top of each other at every crossing. We prove that for all $k \in \mathbb{N}$ and all links $L$, the inequality $$c_{2k+1}(L) \geq \frac{2g(L) + r(L)-1}{k^2}$$ holds, where $c_{2k+1}(L)$, $g(L)$, and $r(L)$ are the $(2k+1)$-crossing nu

S. Ideta, S. Johnston, T. Yoshida, K. Tanaka

Hybridization of Bogoliubov quasiparticles (BQPs) between the CuO$_2$ layers in the triple-layer cuprate high-temperature superconductor Bi$_2$Sr$_2$Ca$_2$Cu$_3$O$_{10+\delta}$ is studied by angle-resolved photoemission spectroscopy (ARPES). In the superconducting state, an anti-crossing gap opens between the outer- and inner-BQP bands, which we attribute pr

Zhuoxi Liu, Zheng Wang, Bo Yang, Kimihiko Nakano

In this article, the authors present a novel method to learn the personalized tactic of discretionary lane-change initiation for fully autonomous vehicles through human-computer interactions. Instead of learning from human-driving demonstrations, a reinforcement learning technique is employed to learn how to initiate lane changes from traffic context, the ac

Liangkai Zhou, Yuncong Hong, Shuai Wang, Ruihua Han

Edge intelligence is an emerging network architecture that integrates sensing, communication, computing components, and supports various machine learning applications, where a fundamental communication question is: how to allocate the limited wireless resources (such as time, energy) to the simultaneous model training of heterogeneous learning tasks? Existin

J. D. García-Aguilar, Juan Carlos Gómez-Izquierdo

We construct a multiscalar and non-renormalizable model where the $\mathbf{S}_{3}$ flavor symmetry drives mainly the Yukawa couplings. In the quark sector, the Nearest Neighbor Interaction (NNI) textures are behind the CKM mixing matrix so that this is fitted in good agreement with the last available results. In the lepton sector, an almost diagonal charged

Alexander Frenkel, Petr Horava, Stephen Randall

We present a family of topological quantum gravity theories associated with the geometric theory of the Ricci flow on Riemannian manifolds. First we use BRST quantization to construct a "primitive" topological Lifshitz-type theory for only the spatial metric, with spatial diffeomorphism invariance and no gauge symmetry, associated with Hamilton's Ricci flow:

Chi Chang, Kimberly Kelly, M. Lee Van Horn, Richard T. Houang

The current research has two aims. First, to demonstrate the utility conditional nonparametric multilevel latent class analysis (NP-MLCA) for multi-site program evaluation using an empirical dataset. Second, to investigate how classification accuracy and parameter estimation of a conditional NP-MLCA are affected by six study factors: the quality of latent cl

Manuele Filaci, Pierre Martinetti

After a brief review on the applications of twisted spectral triples to physics, we adapt to the twisted case the notion of real part of a spectral triple. In particular, when one twists a usual spectral triple by its grading, we show that - depending on the $KO$ dimension - the real part is either twisted as well, or is the intersection of the initial algeb

Sung-Feng Huang, Shun-Po Chuang, Da-Rong Liu, Yi-Chen Chen

Speech separation has been well developed, with the very successful permutation invariant training (PIT) approach, although the frequent label assignment switching happening during PIT training remains to be a problem when better convergence speed and achievable performance are desired. In this paper, we propose to perform self-supervised pre-training to sta

Abhijit Biswas, Benjamin Seibold

This paper addresses the question whether there are numerical schemes for constant-coefficient advection problems that can yield convergent solutions for an infinite time horizon. The motivation is that such methods may serve as building blocks for long-time accurate solutions in more complex advection-dominated problems. After establishing a new notion of c

Delong Zhu, Tong Zhou, Jiahui Lin, Yuqi Fang

Online state-time trajectory planning in highly dynamic environments remains an unsolved problem due to the unpredictable motions of moving obstacles and the curse of dimensionality from the state-time space. Existing state-time planners are typically implemented based on randomized sampling approaches or path searching on discretized state graph. The smooth

Tianxin Wei, Fuli Feng, Jiawei Chen, Ziwei Wu

The general aim of the recommender system is to provide personalized suggestions to users, which is opposed to suggesting popular items. However, the normal training paradigm, i.e., fitting a recommender model to recover the user behavior data with pointwise or pairwise loss, makes the model biased towards popular items. This results in the terrible Matthew

Yu Xu, Hongtao Rong, Qingyan Wang, Dingsong Wu

Single-layer FeSe films grown on the SrTiO3 substrate (FeSe/STO) have attracted much attention because of their possible record-high superconducting critical temperature Tc and distinct electronic structures in iron-based superconductors. However, it has been under debate on how high its Tc can really reach due to the inconsistency of the results obtained fr

D. Sahoo, G. B. Mohanty, K. Trabelsi, I. Adachi

We search for lepton-number- and baryon-number-violating decays $\tau^{-}\to\overline{p}e^{+}e^{-}$, $pe^{-}e^{-}$, $\overline{p}e^{+}\mu^{-}$, $\overline{p}e^{-}\mu^{+}$, $\overline{p}\mu^{+}\mu^{-}$, and $p\mu^{-}\mu^{-}$ using 921 fb$^{-1}$ of data, equivalent to $(841\pm12)\times 10^6$ $\tau^{+}\tau^{-}$ events, recorded with the Belle detector at the KE

Shaolei Wang, Zhongyuan Wang, Wanxiang Che, Ting Liu

Most existing approaches to disfluency detection heavily rely on human-annotated corpora, which is expensive to obtain in practice. There have been several proposals to alleviate this issue with, for instance, self-supervised learning techniques, but they still require human-annotated corpora. In this work, we explore the unsupervised learning paradigm which

Rodion N. Déev

A theorem of O. Haupt, rediscovered by M. Kapovich and celebrated by his proof invoking Ratner theory, describes the set of de Rham cohomology classes on a topological orientable surface, which can be realized by an abelian differential in some respective complex structure, in purely topological terms. We make an attempt to describe similarly pairs and tripl

Alexandru Doicu, Lei Zhao, Adrian Doicu

A stochastic optimization algorithm for analyzing planar central and balanced configurations in the $n$-body problem is presented. We find a comprehensive list of equal mass central configurations satisfying the Morse equality up to $n=12$. We show some exemplary balanced configurations in the case $n=5$, as well as some balanced configurations without any a

G. R. Boroun, B. Rezaei

We describe the determination of the DIS structure functions $F_{2}$ and $F_{L}$ by using the singlet Dokshitzer-Gribov-Lipatov-Altarelli-Parisi (DGLAP) and Altarelli-Martinelli equations at small values of $x$. The determination of the longitudinal structure function is presented as a parameterization of $F_{2}(x,Q^{2})$ and its derivative. Analytical expre

Fukang Tian, Haiyu Wu, Bo Xu

Facing the rapid growth in the issuance of financial tickets (or bills, invoices etc.), traditional manual invoice reimbursement and financial accounting system are imposing an increasing burden on financial accountants and consuming excessive manpower. To solve this problem, we proposes an iterative self-learning Framework of Financial Ticket intelligent Re

Jerin Mohan N D, Titus K Mathew

A dissipative model of the Universe based on the causal relativistic truncated Israel-Stewart theory is analysed in the context of recent accelerated expansion of the Universe. The bulk viscosity and relaxation time are taken as $\xi=\alpha\rho^s$ and $\tau=\frac{\alpha}{\epsilon\gamma(2-\gamma)}\rho^{s-1}$ respectively. For $s=1/2,$ we found an analytical s

Zongze Li, Shuai Wang, Miaowen Wen, Yik-Chung Wu

Reconfigurable intelligent surface (RIS) has the potential to significantly enhance the network secure transmission performance by reconfiguring the wireless propagation environment. However, due to the passive nature of eavesdroppers and the cascaded channel brought by the RIS, the eavesdroppers' channel state information is imperfectly obtained at the base

Manu Jayadharan, Eldar Khattatov, Ivan Yotov

We develop non-overlapping domain decomposition methods for the Biot system of poroelasticity in a mixed form. The solid deformation is modeled with a mixed three-field formulation with weak stress symmetry. The fluid flow is modeled with a mixed Darcy formulation. We introduce displacement and pressure Lagrange multipliers on the subdomain interfaces to imp

Peng Xiao, Zhongzhou Luo, Yuqing Deng, Gengyuan Wang

Meibography is a non-contact imaging technique used by ophthalmologists to assist in the evaluation and diagnosis of meibomian gland dysfunction (MGD). While artificial qualitative analysis of meibography images could lead to low repeatability and efficiency and multi-parametric analysis is demanding to offer more comprehensive information in discovering sub

Yves Ismaël Ngounou Bakam, Denys Pommeret

In this paper we study nonparametric estimators of copulas and copula densities. We first focus our study on a density copula estimator based on a polynomial orthogonal projection of the joint density. A new copula estimator is then deduced. Its asymptotic properties are studied: we provide a large functional class for which this construction is optimal in t

Shengwen Xie, Juan Ren

In this paper, we present a hybrid position/force controller for operating joint robots. The hybrid controller has two goals -- motion tracking and force regulating. As long as these two goals are not mutually exclusive, they can be decoupled in some way. In this work, we make use of the smooth and invertible mapping from joint space to task space to decoupl

M. F. Fernandes, M. A. Solís-Prosser, L. Neves

The quantum analogue of ptychography, a powerful coherent diffractive imaging technique, is a simple method for reconstructing $d$-dimensional pure states. It relies on measuring partially overlapping parts of the input state in a single orthonormal basis and feeding the outcomes to an iterative phase-retrieval algorithm for postprocessing. We provide a proo

D. Unger, A. Abeln, C. Enss, A. Fleischmann

Axion helioscopes like the planned International Axion Observatory (IAXO) search for evidence of axions and axion-like particles (ALPs) from the Sun. A strong magnetic field is used to convert ALPs into photons via the generic ALP-photon coupling. To observe the resulting photons, X-ray detectors with low background and high efficiency are necessary. In addi

Renato Miyagusuku, Koichi Ozaki

Wireless signal strength based localization can enable robust localization for robots using inexpensive sensors. For this, a location-to-signal-strength map has to be learned for each access point in the environment. Due to the ubiquity of Wireless networks in most environments, this can result in tens or hundreds of maps. To reduce the dimensionality of thi

Mohammad Ali

Education sector is adopting new technologies for both teaching and learning pedagogy. Augmented Reality (AR) is a new technology that can be used in the educational pedagogy to enhance the engagement with students. Students interact with AR-based educational material for more visualization and explanation. Therefore, the use of AR in education is becoming m

Adnan Ghazy AlAmoush

Making use of the Hadamard product(or convolution), we find some estimates on the Taylor-Maclaurin coefficients $|a_{2}|$ and $|a_{3}|$ for functions belong to bi univalent functions of the Bazilevi$\check{c}$ type of order $\gamma$. Several (known or new) consequences of the results are also pointed out.

Conner Ballew, Gregory Roberts, Philip Camayd-Muñoz, Maximilien F Debbas

Metasurfaces advanced the field of optics by reducing the thickness of optical components and merging multiple functionalities into a single layer device. However, this generally comes with a reduction in performance, especially for multifunctional and broadband applications. Three-dimensional metastructures can provide the necessary degrees of freedom for a

Ziyuan Zhao, Kartik Chopra, Zeng Zeng, Xiaoli Li

Diabetes is one of the most common disease in individuals. \textit{Diabetic retinopathy} (DR) is a complication of diabetes, which could lead to blindness. Automatic DR grading based on retinal images provides a great diagnostic and prognostic value for treatment planning. However, the subtle differences among severity levels make it difficult to capture imp

Yueming Lyu, Yuan Yuan, Ivor W. Tsang

Quasi-Monte Carlo (QMC) is an essential tool for integral approximation, Bayesian inference, and sampling for simulation in science, etc. In the QMC area, the rank-1 lattice is important due to its simple operation, and nice properties for point set construction. However, the construction of the generating vector of the rank-1 lattice is usually time-consumi

Jasper S. Wijnands, Haifeng Zhao, Kerry A. Nice, Jason Thompson

The World Health Organization has listed the design of safer intersections as a key intervention to reduce global road trauma. This article presents the first study to systematically analyze the design of all intersections in a large country, based on aerial imagery and deep learning. Approximately 900,000 satellite images were downloaded for all intersectio

C. L. Saiz, J. A. Delgado, J. van Tol, T. Tartaglia

Broadening the knowledge and understanding on the magnetic correlations in van der Waals layered magnets is critical in realizing their potential next-generation applications. In this study, we employ high frequency (240 GHz) electron spin resonance (ESR) spectroscopy on plate-like CrBr$_{3}$ to gain insight into the magnetic interactions as a function of te

N. I. Maxted, A. J. Ruiter, K. Belczynski, I. R. Seitenzahl

Energy released when the core of a high-mass star collapses into a black hole often powers an explosion that creates a supernova remnant. Black holes have limited windows of observability, and consequently are rarely identified in association with supernova remnants. Analysing multi-messenger data, we show that MAXI J1535-571 is the black hole produced in th

Hongchao Li

For a long period of time, we have been seeking how Berry curvature influnces the transport properties in materials breaking time-reversal symmetry. In time-reversal symmetric material, there will be no thermoelectric current induced by Berry curvature in linear regime. However, the nonlinear Hall current can be shown in non-magnetic and non-centrosymmetric

Arunashish Datta, Mayukh Nath, David Yang, Shreyas Sen

Human Body Communication (HBC) has come up as a promising alternative to traditional radio frequency (RF) Wireless Body Area Network (WBAN) technologies. This is essentially due to HBC providing a broadband communication channel with enhanced signal security in the physical layer due to lower radiation from the human body as compared to its RF counterparts.

Feilong Zhang

In this brief, a model-free adaptive predictive control (MFAPC) is proposed. It outperforms the current model-free adaptive control (MFAC) for not only solving the time delay problem in multiple-input multiple-output (MIMO) systems but also relaxing the current rigorous assumptions for sake of a wider applicable range. The most attractive merit of the propos

Bruno Nachtergaele, Robert Sims, Amanda Young

We study the stability with respect to a broad class of perturbations of gapped ground state phases of quantum spin systems defined by frustration-free Hamiltonians. The core result of this work is a proof using the Bravyi-Hastings-Michalakis (BHM) strategy that under a condition of Local Topological Quantum Order, the bulk gap is stable under perturbations

Haoyuan Zhang, Yonghong Hou, Pichao Wang, Zihui Guo

This paper presents a study of automatic design of neural network architectures for skeleton-based action recognition. Specifically, we encode a skeleton-based action instance into a tensor and carefully define a set of operations to build two types of network cells: normal cells and reduction cells. The recently developed DARTS (Differentiable Architecture

Constantinos Chamzas, Zachary Kingston, Carlos Quintero-Peña, Anshumali Shrivastava

Earlier work has shown that reusing experience from prior motion planning problems can improve the efficiency of similar, future motion planning queries. However, for robots with many degrees-of-freedom, these methods exhibit poor generalization across different environments and often require large datasets that are impractical to gather. We present SPARK an

Kiyoshi Kotani, Akihiko Akao, Hayato Chiba

Interactions of inhibitory neurons produce gamma oscillations (30--80 Hz) in the local field potential, which is known to be involved in functions such as cognition and attention. In this study, the modified theta model is considered to investigate the theoretical relationship between the microscopic structure of inhibitory neurons and their gamma oscillatio

Étienne Tétreault

Considering Schur positivity of differences of plethysms of homogeneous symmetric functions, we introduce a new relation on integer partitions. This relation is conjectured to be a partial order, with its restriction to one part partitions equivalent to the classical Foulkes conjecture. We establish some of the properties of this relation via the constructio

Xiaowu Dai, Michael I. Jordan

We study the problem of decision-making in the setting of a scarcity of shared resources when the preferences of agents are unknown a priori and must be learned from data. Taking the two-sided matching market as a running example, we focus on the decentralized setting, where agents do not share their learned preferences with a central authority. Our approach

Ana Anusic, Christopher Mouron

We give an upper bound for the topological entropy of maps on inverse limit spaces in terms of their set-valued components. In a special case of a diagonal map on the inverse limit space $\underleftarrow{\lim}(I,f)$, where every diagonal component is the same map $g\colon I\to I$ which strongly commutes with $f$ (i.e. $f^{-1}\circ g=g\circ f^{-1}$), we show

Luigi Ferraro, Federico Galetto, Francesca Gandini, Hang Huang

We describe a significant update to the existing InvariantRing package for Macaulay2. In addition to expanding and improving the methods of the existing package for actions of finite groups, the updated package adds functionality for computing invariants of diagonal actions of tori and finite abelian groups as well as invariants of arbitrary linearly reducti

Xicheng Zhang

Consider the following McKean-Vlasov SDE: $$ d X_t=\sqrt{2}d W_t+\int_{{\mathbb R}^d}K(t,X_t-y)\mu_{X_t}(dy)d t,\ \ X_0=x, $$ where $\mu_{X_t}$ stands for the distribution of $X_t$ and $K(t,x): {\mathbb R}_+\times{\mathbb R}^d\to{\mathbb R}^d$ is a time-dependent divergence free vector field. Under the assumption $K\in L^q_t(\widetilde L_x^p)$ with $\frac dp

Abdulrahman Alaql, Swarup Bhunia

Hardware IP protection has been one of the most critical areas of research in the past years. Recently, attacks on hardware IPs (such as reverse engineering or cloning) have evolved as attackers have developed sophisticated techniques. Therefore, hardware obfuscation has been introduced as a powerful tool to protect IPs against piracy attacks. However, many

Jan Schneider

We give a geometrically motivated measure of skewness, define a mean value triangle number, and dispersion (in that order) of a fuzzy number without reference or seeking analogy to the namesake but parallel concepts in probability theory. These measures come about by way of a new representation of fuzzy numbers as parameterized curves respectively their asso

Ana Anusic, Christopher Mouron

Maps $f,g\colon I\to I$ are called strongly commuting if $f\circ g^{-1}=g^{-1}\circ f$. We show that strongly commuting, piecewise monotone maps $f,g$ can be decomposed into a finite number of invariant intervals (or period 2 intervals) on which $f,g$ are either both open maps, or at least one of them is monotone. As a consequence, we show that strongly comm

Thao Nguyen, Maithra Raghu, Simon Kornblith

A key factor in the success of deep neural networks is the ability to scale models to improve performance by varying the architecture depth and width. This simple property of neural network design has resulted in highly effective architectures for a variety of tasks. Nevertheless, there is limited understanding of effects of depth and width on the learned re

Weinan Wang, Xi Zhang

In many industry settings, online controlled experimentation (A/B test) has been broadly adopted as the gold standard to measure product or feature impacts. Most research has primarily focused on user engagement type metrics, specifically measuring treatment effects at mean (average treatment effects, ATE), and only a few have been focusing on performance me

Ben Kane, Sudhir Pujahari

In this paper, we study moments of Hurwitz class numbers associated to imaginary quadratic orders restricted into fixed arithmetic progressions. In particular, we fix $t$ in an arithmetic progression $t\equiv m\pmod{M}$ and consider the ratio of the $2k$-th moment to the zeroeth moment for $H(4n-t^2)$ as one varies $n$. The special case $n=p^r$ yields as a c

Yoshimichi Ueda

We propose an abstract framework of a kind of representation theory for $C^*$-flows, i.e., $C^*$-algebras equipped with one-parameter automorphism groups, as a proper generalization of Olshanski's formalism of unitary representation theory for infinite-dimensional groups such as the infinite-dimensional unitary group $\mathrm{U}(\infty)$. The present framewo

Ali Boyali, Lyu Zheming, Vijay John, Rathour Swarn

In this study, we detail the procedures for designing gain scheduling controllers by Linear Quadratic $H_\infty$ robust optimization methods in Linear Matrix Inequalities (LMI) framework. The controllers are aimed at steering control of the autonomous vehicles. We first construct the Linear Parameter Varying (LPV) vehicle models and synthesize the robust con

Chen Ying, Li Shi

The data acquisition console is an important component of the EAST data acquisition system which provides unified data acquisition and long-term data storage for diagnostics. The data acquisition console is used to manage the data acquisition configuration information and control the data acquisition workflow. The data acquisition console has been developed

Zhaofang Bai, Shuanping Du

As an important quantum resource, quantum coherence play key role in quantum information processing. It is often concerned with manipulation of families of quantum states rather than individual states in isolation. Given two pairs of coherent states $(\rho_1,\rho_2)$ and $(\sigma_1,\sigma_2)$, we are aimed to study how can we determine if there exists a stri

Kuo Chen, Jingang Yi, Dezhen Song

Ranging from cart-pole systems and autonomous bicycles to bipedal robots, control of these underactuated balance robots aims to achieve both external (actuated) subsystem trajectory tracking and internal (unactuated) subsystem balancing tasks with limited actuation authority. This paper proposes a learning model-based control framework for underactuated bala

Adela Kawka, Stéphane Vennes, Nicole F. Allard, T. Leininger

We present an analysis of photometric, spectroscopic and spectropolarimetric data of the nearby, cool, magnetic DZ white dwarf PM J08186-3110. High dispersion spectra show the presence of Zeeman splitted spectral lines due to the presence of a surface average magnetic field of 92 kG. The strong magnesium and calcium lines show extended wings shaped by intera

A. Amon, K. Bechtol, A. J. Connolly, S. W. Digel

The commissioning team for the Vera C. Rubin observatory is planning a set of engineering and science verification observations with the Legacy Survey of Space and Time (LSST) commissioning camera and then the Rubin Observatory LSST Camera. The time frame for these observations is not yet fixed, and the commissioning team will have flexibility in selecting f

Wendong Gan, Haitao Chen, Yin Yan, Jianwei Li

This paper presents the IQIYI voice conversion system (T24) for Voice Conversion 2020. In the competition, each target speaker has 70 sentences. We have built an end-to-end voice conversion system based on PPG. First, the ASR acoustic model calculates the BN feature, which represents the content-related information in the speech. Then the Mel feature is calc

Alister D Costa, Stefan Denkovski, Michal Malyska, Sae Young Moon

Multiple Sclerosis (MS) is a chronic, inflammatory and degenerative neurological disease, which is monitored by a specialist using the Expanded Disability Status Scale (EDSS) and recorded in unstructured text in the form of a neurology consult note. An EDSS measurement contains an overall "EDSS" score and several functional subscores. Typically, expert knowl

Nick Lawrence, Mingren Shen, Ruiqi Yin, Cloris Feng

The use of accurate scanning transmission electron microscopy (STEM) image simulation methods require large computation times that can make their use infeasible for the simulation of many images. Other simulation methods based on linear imaging models, such as the convolution method, are much faster but are too inaccurate to be used in application. In this p

Drew Linsley, Junkyung Kim, Alekh Ashok, Thomas Serre

We introduce a deep recurrent neural network architecture that approximates visual cortical circuits. We show that this architecture, which we refer to as the gamma-net, learns to solve contour detection tasks with better sample efficiency than state-of-the-art feedforward networks, while also exhibiting a classic perceptual illusion, known as the orientatio