April 2020 arXiv papers — page 37

Selcuk Haciomeroglu

A long in-plane beam polarization can be a desired feature for spin measurement experiments in storage rings. The spin precession of the particles within a beam can be controlled by means of the frozen spin method and beam bunching via RF cavities, eventually yielding a polarization lifetime of 10--100 seconds. Previous studies have shown that it can be furt

Pierre Fortin, Ambroise Fleury, François Lemaire, Michael Monagan

Two essential problems in Computer Algebra, namely polynomial factorization and polynomial greatest common divisor computation, can be efficiently solved thanks to multiple polynomial evaluations in two variables using modular arithmetic. In this article, we focus on the efficient computation of such polynomial evaluations on one single CPU core. We first sh

D. X. Li, H. W. Xiao, C. Yang, X. Q. Shao

The multipartite Greenberger-Horne-Zeilinger (GHZ) states are indispensable elements for various quantum information processing tasks. Here we put forward two deterministic proposals to dissipatively prepare tripartite GHZ states in a neutral atom system. The first scheme can be considered as an extension of a recent work [T. M. Wintermantel, Y. Wang, G. Loc

Manuel Norman

In [1] we introduced the concept of structured space, which is a topological space that locally resembles some algebraic structures. In [2] we proceeded the study of these spaces, developing two cohomology theories. The aim of this paper is to define categories of structured spaces, (pre)sheaves with values in such categories, and generalised notions of vect

Gabriele Carcassi, Christine A. Aidala

In this work we show the equivalence between Hamiltonian mechanics and conservation of information entropy. We will show that distributions with coordinate independent values for information entropy require that the manifold on which the distribution is defined is charted by conjugate pairs (i.e. it is a symplectic manifold). We will also show that further r

Anastasios Bountis, J. J. P. Veerman, Franco Vivaldi

We consider the integrable (zero perturbation) two--dimensional standard map, in light of current developments on ergodic sums of irrational rotations, and recent numerical evidence that it might possess non-trivial q-Gaussian statistics. Using both classical and recent results, we show that the phase average of the sum of centered positions of an orbit, for

Ryan L. Mann, Tyler Helmuth

We establish a polynomial-time approximation algorithm for partition functions of quantum spin models at high temperature. Our algorithm is based on the quantum cluster expansion of Neto\v{c}n\'y and Redig and the cluster expansion approach to designing algorithms due to Helmuth, Perkins, and Regts. Similar results have previously been obtained by related me

Francesco Giacosa

The ground-state (lightest) hybrid nonet with exotic quantum numbers $J^{PC}=1^{-+}$ and the nonet of their chiral partners with $J^{PC}=1^{+-}$ build a homochiral multiplet involving left- and right-handed currents, which under chiral transformation change just as (axial-)vector mesons. Masses and interactions of hybrids can be obtained in the context of th

Kai Fukami, Koji Fukagata, Kunihiko Taira

We present a new turbulent data reconstruction method with supervised machine learning techniques inspired by super resolution and inbetweening, which can recover high-resolution turbulent flows from grossly coarse flow data in space and time. For the present machine learning based data reconstruction, we use the downsampled skip-connection/multi-scale model

Damian Barabonkov, Samantha D'Alonzo, Joseph Pierre, Daniel Kondor

Following the growth of dock-based bike sharing systems as an eco-friendly solution for transportation in urban areas, Dockless systems are revolutionizing the market for the increased flexibility they offer to users. Bike redistribution is a common approach to improve service, and there exists extensive research considering static and dynamic rebalancing st

Yoshiharu Kawamura

We reconsider a generation of up-type quark mass hierarchy in the standard model and clarify how a mechanism works to realize the hierarchy without severe fine tuning.

Dening Lu, Xuequan Lu, Yangxing Sun, Jun Wang

Point cloud filtering, the main bottleneck of which is removing noise (outliers) while preserving geometric features, is a fundamental problem in 3D field. The two-step schemes involving normal estimation and position update have been shown to produce promising results. Nevertheless, the current normal estimation methods including optimization ones and deep

Taku Ishida, Eiichi Wakai, Shunsuke Makimura, Andrew M. Casella

A high-intensity proton beam exposure with 181 MeV energy has been conducted at Brookhaven Linac Isotope Producer facility on various material specimens for accelerator targetry applications, including titanium alloys as a beam window material. The radiation damage level of the analyzed capsule was 0.25 dpa at beam center region with an irradiation temperatu

Mathis Schmieder, Taro Eichler, Sven Wittig, Michael Peter

Fifth generation (5G) mobile networks are expected to play an increasing role in industrial communication with private mobile communication networks deployed on company premises. For planning, standardization and product development, it is crucial to to thoroughly understand the radio channel characteristics of such environments. Frequencies around 3.7 GHz w

George Lazarides, Qaisar Shafi

We investigate a non-supersymmetric $SO(10)\times U(1)_{\rm PQ}$ axion model in which the spontaneous breaking of $U(1)_{\rm PQ}$ occurs after inflation, and the axion domain wall problem is resolved by employing the Lazarides-Shafi mechanism. This requires the introduction of two fermion 10-plets, such that the surviving discrete symmetry from the explicit

Apurba Biswas, V . V. Prasad, O. Raz, R. Rajesh

Mpemba effect refers to the counterintuitive result that, when quenched to a low temperature, a system at higher temperature may equilibrate faster than one at intermediate temperatures. This effect has recently been demonstrated in driven granular gases, both for smooth as well as rough hard-sphere systems based on a perturbative analysis. In this paper, we

Will Gilbert, Andre Saraiva, Wee Han Lim, Chih Hwan Yang

The advanced nanoscale integration available in silicon complementary metal-oxide-semiconductor (CMOS) technology provides a key motivation for its use in spin-based quantum computing applications. Initial demonstrations of quantum dot formation and spin blockade in CMOS foundry-compatible devices are encouraging, but results are yet to match the control of

Salvatore Capozziello, Vesna Borka Jovanović, Duško Borka, Predrag Jovanović

We show that fundamental plane of elliptical galaxies can be used to obtain observational constraints on metric theories of gravity. Being it connected to global properties of ellipticals, it can fix parameters of modified gravity. Specifically, we use fundamental plane to constrain modified theories of gravity with Yukawa-like corrections which commonly eme

Vrishab Krishna

Abundancy index refers to the ratio of the sum of the divisors of a number to the number itself. It is a concept of great importance in defining friendly and perfect numbers. Here, we describe a suitable generalization of abundancy index to the ring of Gaussian integers ($\mathbb{Z}[i]$). We first show that this generalization possesses many of the useful pr

Jan Vykopal, Valdemar Švábenský, Ee-Chien Chang

The concept of Capture the Flag (CTF) games for practicing cybersecurity skills is widespread in informal educational settings and leisure-time competitions. However, it is not much used in university courses. This paper summarizes our experience from using jeopardy CTF games as homework assignments in an introductory undergraduate course. Our analysis of da

Ruiyang Song, Kuang Xu

We propose and analyze a temporal concatenation heuristic for solving large-scale finite-horizon Markov decision processes (MDP), which divides the MDP into smaller sub-problems along the time horizon and generates an overall solution by simply concatenating the optimal solutions from these sub-problems. As a "black box" architecture, temporal concatenation

Jonas Deré, Marcos Origlia

Every simply connected and connected solvable Lie group $G$ admits a simply transitive action on a nilpotent Lie group $H$ via affine transformations. Although the existence is guaranteed, not much is known about which Lie groups $G$ can act simply transitive on which Lie groups $H$. So far the focus was mainly on the case where $G$ is also nilpotent, leadin

Johannes Lederer, Michael Vogt

Much of the theory for the lasso in the linear model $Y = X \beta^* + \varepsilon$ hinges on the quantity $2 \| X^\top \varepsilon \|_{\infty} / n$, which we call the lasso's effective noise. Among other things, the effective noise plays an important role in finite-sample bounds for the lasso, the calibration of the lasso's tuning parameter, and inference on

Yu-Kai Huang, Yueh-Cheng Liu, Tsung-Han Wu, Hung-Ting Su

The performance of image based stereo estimation suffers from lighting variations, repetitive patterns and homogeneous appearance. Moreover, to achieve good performance, stereo supervision requires sufficient densely-labeled data, which are hard to obtain. In this work, we leverage small amount of data with very sparse but accurate disparity cues from LiDAR

Gihun Lee, Sangmin Bae, Jaehoon Oh, Se-Young Yun

With the success of deep learning in various fields and the advent of numerous Internet of Things (IoT) devices, it is essential to lighten models suitable for low-power devices. In keeping with this trend, MicroNet Challenge, which is the challenge to build efficient models from the view of both storage and computation, was hosted at NeurIPS 2019. To develo

R. Ito, S. Takada, A. Ludwig, A. D. Wieck

We develop a coherent beam splitter for single electrons driven through two tunnel-coupled quantum wires by surface acoustic waves (SAWs). The output current through each wire oscillates with gate voltages to tune the tunnel-coupling and potential difference between the wires. This oscillation is assigned to coherent electron tunneling motion that can be use

Jannik Dreier, Jean-Guillaume Dumas, Pascal Lafourcade, Léo Robert

In 1968, Liu described the problem of securing documents in a shared secret project. In an example, at least six out of eleven participating scientists need to be present to open the lock securing the secret documents. Shamir proposed a mathematical solution to this physical problem in 1979, by designing an efficient $k$-out-of-$n$ secret sharing scheme base

Dhiman Bhowmick, Pinaki Sengupta

We propose that Weyl triplons are expected to appear in the low energy magnetic excitations in the canonical Shastry-Sutherland compound, \ce{SrCu2(BO3)2}, a quasi-2D quantum magnet. Our results show that when a minimal, realistic inter-layer coupling is added to the well-established microscopic model describing the excitation spectrum of the individual laye

Karachentsev I. D., Kaisin S. S

We used the $H\alpha$ images from a large sample of nearby late-type dwarf galaxies to investigate properties of their emission structure. The sample consists of three hundred galaxies of the irregular (Irr), Magellanic irregular (Im), blue compact dwarf (BCD), and transition (Tr) types situated within a distance of 11 Mpc. In each galaxy, we indicated: the

Fabrizio Roccaforte, Giuseppe Greco, Patrick Fiorenza

This paper aims to give a short overview on some relevant processing issues existing in SiC and GaN power devices technology. The main focus is put on the importance of the channel mobility in transistors, which is one of the keys to reduce RON and power dissipation. Specifically, in the case of the 4H-SiC planar MOSFETs the most common solutions and recent

S. A. Nikolaev, I. V. Solovyev

We show how low-energy electronic models derived from the first-principles electronic structure calculations can help to rationalize the magnetic properties of two lacunar spinel compounds GaM4S8 with light (M=V) and heavy (M=Mo) transition-metal elements, which are responsible for different spin-orbit interaction strength. In the model, each magnetic lattic

M. Hiraishi, K. M. Kojima, H. Okabe, S. Takeshita

The magnetism of the second antiferromagnetic phase (AF2) arising in the iron-based LaFeAsO$_{1-x}$H$_{x}$ superconductor for $x\gtrsim0.4$ was investigated by muon spin rotation measurements under hydrostatic pressure up to 2.6 GPa. The N\'eel temperature ($T_{\rm N}$) obtained for a sample with $x=0.51$ exhibits considerably greater sensitivity to pressure

Yiben Yang, Chaitanya Malaviya, Jared Fernandez, Swabha Swayamdipta

Recent advances in commonsense reasoning depend on large-scale human-annotated training data to achieve peak performance. However, manual curation of training examples is expensive and has been shown to introduce annotation artifacts that neural models can readily exploit and overfit on. We investigate G-DAUG^C, a novel generative data augmentation method th

Seyed-Iman Mirzadeh, Mehrdad Farajtabar, Hassan Ghasemzadeh

In recent years, neural networks have demonstrated an outstanding ability to achieve complex learning tasks across various domains. However, they suffer from the "catastrophic forgetting" problem when they face a sequence of learning tasks, where they forget the old ones as they learn new tasks. This problem is also highly related to the "stability-plasticit

Bo Li, Shuo-yiin Chang, Tara N. Sainath, Ruoming Pang

End-to-end (E2E) models fold the acoustic, pronunciation and language models of a conventional speech recognition model into one neural network with a much smaller number of parameters than a conventional ASR system, thus making it suitable for on-device applications. For example, recurrent neural network transducer (RNN-T) as a streaming E2E model has shown

Hung The Nguyen, Tung Duy Nguyen, Vu Phi Tran, Matthew Garratt

The control and guidance of multi-robots (swarm) is a non-trivial problem due to the complexity inherent in the coupled interaction among the group. Whether the swarm is cooperative or non-cooperative, lessons can be learnt from sheepdogs herding sheep. Biomimicry of shepherding offers computational methods for swarm control with the potential to generalize

Honghui Liu, Haiyang Wang, Askar B. Abdikamalov, Dimitry Ayzenberg

X-ray reflection spectroscopy is potentially a powerful tool to probe the spacetime geometry around astrophysical black holes and test general relativity in the strong field regime. However, precision tests of general relativity are only possible if we employ the correct astrophysical model and we can limit the systematic uncertainties. It is thus crucial to

Karl H. Hofmann, Linus Kramer

We study universal enveloping Hopf algebras of Lie algebras in the category of weakly complete vector spaces over the real and complex field.

Christopher Choy, Wei Dong, Vladlen Koltun

We present Deep Global Registration, a differentiable framework for pairwise registration of real-world 3D scans. Deep global registration is based on three modules: a 6-dimensional convolutional network for correspondence confidence prediction, a differentiable Weighted Procrustes algorithm for closed-form pose estimation, and a robust gradient-based SE(3)

Brendan K. Beare, Alexis Akira Toda

The first confirmed case of Coronavirus Disease 2019 (COVID-19) in the US was reported on January 21, 2020. By the end of March, 2020, there were more than 180000 confirmed cases in the US, distributed across more than 2000 counties. We find that the right tail of this distribution exhibits a power law, with Pareto exponent close to one. We investigate wheth

Lidan Wang, Guoli Zhou

In this article, we study the stability of solutions to 3D stochastic primitive equations driven by fractional noise. Since the fractional Brownian motion is essentially different from Brownian motion, lots of stochastic analysis tools are not available to study the exponential stability for the stochastic systems. Therefore, apart from the standard method f

Fuad Noman, Gamal Alkawsi, Dallatu Abbas, Ammar Alkahtani

Wind energy has gained a huge interest in the recent years in various countries due to the high demand of energy and the shortage of traditional electricity sources. This is because it is cost effective and environmentally friendly source that could contribute significantly to the reduction of the ever-increasing carbon emissions. Wind energy is one of the f

Kingman Cheung, Yi-Lun Chung, Hiroyuki Ishida, Chih-Ting Lu

The model of heavy neutral leptons (HNLs) is one of the well-motivated models beyond the standard model (BSM) from both theoretical and phenomenological point of views. It is an indispensable ingredient to explain the puzzle of tiny neutrino masses and the origin of the matter-antimatter asymmetry in our Universe, based on the models in which the simplest Ty

Yingying Shi, Yongchao Zeng, Jean Engo, Botang Han

Energy efficiency technologies (EETs) are crucial for saving energy and reducing carbon dioxide emissions. However, the diffusion of EETs in small and medium-sized enterprises is rather slow. Literature shows the interactions between innovation adopters and potential adopters have significant impacts on innovation diffusion. Enterprises lack the motivation t

n3He Collaboration, M. T. Gericke, S. Baeßler, L. Barrón-Palos

We report the first precision measurement of the parity-violating asymmetry in the direction of proton emission with respect to the neutron spin, in the reaction $^{3}\mathrm{He}(\mathrm{n},\mathrm{p})^{3}\mathrm{H}$, using the capture of polarized cold neutrons in an unpolarized active $^3\rm{He}$ target. The asymmetry is a result of the weak interaction be

Zhe Wang, Tao Du, N. M. Anoop Krishnan, Morten M. Smedskjaer

Vapor deposition can yield glasses that are more stable than those obtained by the traditional melt-quenching route. However, it remains unclear whether vapor-deposited glasses are "allowable" or "forbidden," that is, if they are equivalent to glasses formed by cooling extremely slowly a liquid or if they differ in nature from melt-quenched glasses. Here, ba

Subrato Bharati, Prajoy Podder, Niketa Gandhi, Ajith Abraham

Multiple input multiple output (MIMO) system transmission is a popular diversity technique to improve the reliability of a communication system where transmitter, communication channel and receiver are the important elements. Data transmission reliability can be ensured when the bit error rate is very low. Normally, multiple antenna elements are used at both

Stuart Rogers

An algorithm for recommending a suite of boxes for shipping a retailer's online customer orders is presented.

Carlos Fernández-Loría, Foster Provost, Jesse Anderton, Benjamin Carterette

This study presents a systematic comparison of methods for individual treatment assignment, a general problem that arises in many applications and has received significant attention from economists, computer scientists, and social scientists. We group the various methods proposed in the literature into three general classes of algorithms (or metalearners): l

Yeon-Koo Che, Kyungmin Kim, Weijie Zhong

We study statistical discrimination of individuals based on payoff-irrelevant social identities in markets that utilize ratings and recommendations for social learning. Even though rating/recommendation algorithms can be designed to be fair and unbiased, ratings-based social learning can still lead to discriminatory outcomes. Our model demonstrates how users

Joyce Jiyoung Whang, Inderjit S. Dhillon

The goal of co-clustering is to simultaneously identify a clustering of rows as well as columns of a two dimensional data matrix. A number of co-clustering techniques have been proposed including information-theoretic co-clustering and the minimum sum-squared residue co-clustering method. However, most existing co-clustering algorithms are designed to find p

Susen Yang, Yong Liu, Yonghui Xu, Chunyan Miao

Graph neural networks (GNN) have recently been applied to exploit knowledge graph (KG) for recommendation. Existing GNN-based methods explicitly model the dependency between an entity and its local graph context in KG (i.e., the set of its first-order neighbors), but may not be effective in capturing its non-local graph context (i.e., the set of most related

Saman Zare, Sheila Edalatpour

Analytical expressions for calculating the energy density and spatial correlation function of thermal emission by a homogeneous, isothermal sphere of arbitrary size and material are presented. The spectral distribution and the power law governing the distance-dependent energy density are investigated in the near-field and far-field regimes for silicon carbid

Haotian Weng, Artem Lenskiy

Algorithmic trading has proliferated the area of quantitative finance for already over a decade. The decisions are made without human intervention using the data provided by brokerage firms and exchanges. There is an emerging intermediate layer of financial players that are placed in between a broker and algorithmic traders. The role of these players is to a

Johannes Hendriks, Nicholas O'Dell, Adrian Wills, Anton Tremsin

Energy resolved neutron transmission techniques can provide high-resolution images of strain within polycrystalline samples allowing the study of residual strain and stress in engineered components. Strain is estimated from such data by analysing features known as Bragg-edges for which several methods exist. It is important for these methods to provide both

Hui Zhao, Mei-Ming Zhang, Naihuan Jing, Zhi-Xi Wang

We study separability criteria in multipartite quantum systems of arbitrary dimensions by using the Bloch representation of density matrices. We first derive the norms of the correlation tensors and obtain the necessary conditions for separability under partition of tripartite and four-partite quantum states. Moreover, based on the norms of the correlation t

Kaiwen Chen, Baofang Song

We investigated the linear stability of pipe flow with anisotropic slip length at the wall by considering streamwise and azimuthal slip separately as the limiting cases. Our numerical analysis shows that streamwise slip renders the flow less stable but does not cause instability. The exponential decay rate of the least stable mode appears to be $\propto Re^{

E. Harikumar, Leela Ganesh Chandra Lakkaraju, Vishnu Rajagopal

In this paper, we show that the causally connected $4$-dimensional line element of the $\kappa$-deformed Minkowski space-time induces an upper cut-off on the proper acceleration and derive this maximal acceleration, valid up to first order in the deformation parameter. We find a contribution to maximal acceleration which is independent of $\hbar$ and thus si

Marcus E. Lower, Ryan M. Shannon, Simon Johnston, Matthew Bailes

The soft-gamma repeater Swift J1818.0$-$1607 is only the fifth magnetar found to exhibit pulsed radio emission. Using the Ultra-Wideband Low receiver system of the Parkes radio telescope, we conducted a 3 h observation of Swift J1818.0$-$1607. Folding the data at a rotation period of $P = 1.363$ s, we obtained wideband polarization profiles and flux density

Seiji Takeda, Toshiyuki Hama, Hsiang-Han Hsu, Victoria A. Piunova

The discovery of new materials has been the essential force which brings a discontinuous improvement to industrial products' performance. However, the extra-vast combinatorial design space of material structures exceeds human experts' capability to explore all, thereby hampering material development. In this paper, we present a material industry-oriented web

Gilda González, Jorgelina López

This work presents the study of the variability of foF2 and hmF2 at a low latitude station in South America (Tucum\'an, 26.9{\deg}S, 294.6{\deg}E; magnetic latitude 15.5{\deg}S, Argentina). Ground based ionosonde measurements obtained during different seasonal and solar activity conditions (a year of low solar activity, 2009 and one of high solar activity, 2

Gabriella Böhm

We study integrals of Hopf monoids in duoidal endohom categories of naturally Frobenius map monoidales in monoidal bicategories. We prove two Maschke type theorems, relating the separability of the underlying monoid and comonoid, respectively, to the existence of normalized integrals. It covers the examples provided by Hopf monoids in braided monoidal catego

D. T. Hoai, P. Tuan-Anh, P. T. Nhung, P. Darriulat

We study the morpho-kinematics of the circumbinary envelope of Mira Ceti between $\sim$100 and $\sim$350 au from the stars using ALMA observations of the SiO ($\nu$=0, $J$=5-4) and CO ($\nu$=0, $J$=3-2) emissions with the aim of presenting an accurate and reliable picture of what cannot be ignored when modelling the dynamics at stake. A critical study of the

Jose Daniel Lara, Jonathan T. Lee, Duncan Callaway, Bri-Mathias Hodge

Computer simulations that demonstrate the valueof novel approaches are crucial to developing more flexibleand robust power systems operations with high penetrations ofrenewable energy at multiple geographic and temporal scales.However, optimization-based simulations that depend on forecastdata often face challenges in evaluating performance, reproducingresul

Saul Ancari, Igor Miranda

In this article, we study hypersurfaces $\Sigma\subset \mathbb{R}^{n+1}$ with constant weighted mean curvature. Recently, Wei-Peng proved a rigidity theorem for CWMC hypersurfaces that generalizes Le-Sesum classification theorem for self-shrinker. More specifically, they showed that a complete CWMC hypersurface with polynomial volume growth, bounded norm of

Shota Imaki, Zebin Qiu

We scrutinize the novel chiral transport phenomenon driven by spacetime torsion, namely the chiral torsional effect (CTE). We calculate the torsion-induced chiral currents with finite temperature, density and curvature in the most general torsional gravity theory. The conclusion complements the previous study on the CTE by including curvature and substantiat

Bozhi Wu, Sen Chen, Cuiyun Gao, Lingling Fan

Machine learning (ML) based approach is considered as one of the most promising techniques for Android malware detection and has achieved high accuracy by leveraging commonly-used features. In practice, most of the ML classifications only provide a binary label to mobile users and app security analysts. However, stakeholders are more interested in the reason

Konstantin Pieper, Armenak Petrosyan

Convex $\ell_1$ regularization using an infinite dictionary of neurons has been suggested for constructing neural networks with desired approximation guarantees, but can be affected by an arbitrary amount of over-parametrization. This can lead to a loss of sparsity and result in networks with too many active neurons for the given data, in particular if the n

Loc Truong, Chace Jones, Brian Hutchinson, Andrew August

Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning attacks manipulate training data to induce unreliability of an ML model, whereas backdoor data poisoning attacks maintain system performance unless the ML model is presented with

Min Dai, Ting Gao, Yubin Lu, Yayun Zheng

In recent years, the discovery of complex dynamic systems in various fields through data-driven methods has attracted widespread attention. This method has played the role of data and has become an advantageous tool for us to study complex phenomena. In this work, we propose a framework for detecting the dynamic behavior, such as the maximum likelihood trans

Zezhou Cheng, Saadia Gabriel, Pankaj Bhambhani, Daniel Sheldon

The US weather radar archive holds detailed information about biological phenomena in the atmosphere over the last 20 years. Communally roosting birds congregate in large numbers at nighttime roosting locations, and their morning exodus from the roost is often visible as a distinctive pattern in radar images. This paper describes a machine learning system to

Aymen Hamrouni, Hakim Ghazzai, Turki Alelyani, Yehia Massoud

The wide spread of mobile devices has enabled a new paradigm of innovation called Mobile Crowdsourcing (MCS) where the concept is to allow entities, e.g., individuals or local authorities, to hire workers to help from the crowd of connected people, to execute a task or service. Some complex tasks require the collaboration of multiple workers to ensure its su

Xingbo Liu, Xiushan Nie, Qi Dai, Yupan Huang

Due to the compelling efficiency in retrieval and storage, similarity-preserving hashing has been widely applied to approximate nearest neighbor search in large-scale image retrieval. However, existing methods have poor performance in retrieval using an extremely short-length hash code due to weak ability of classification and poor distribution of hash bit.

Yeuk Hay Joshua Lam, Yuan Liu, Romyar Sharifi, Preston Wake

Given a profinite group G of finite p-cohomological dimension and a pro-p quotient H of G by a closed normal subgroup N, we study the filtration on the Iwasawa cohomology of N by powers of the augmentation ideal in the group algebra of H. We show that the graded pieces are related to the cohomology of G via analogues of Bockstein maps for the powers of the a

Caio A. G. Prado, Wen-Jing Xing, Shanshan Cao, Guang-You Qin

It is widely acknowledged that heavy flavor probes are sensitive to the properties of the quark-gluon plasma and are often considered an important tool for the plasma tomography studies. Forward rapidity observables can provide further insight on the dynamics of the medium due to the interplay between the medium size and the differences in the production spe

Zhaofeng Ding, Zihao Zhu, Jian Zhang, Cheng Tan

We report results of muon spin relaxation and rotation ($\mu$SR) experiments on the spin-liquid candidate~YbMgGaO$_{4}$. No static magnetism $\gtrsim 0.003\mu_B$ per Yb ion, ordered or disordered, is observed down to 22~mK, a factor of two lower in temperature than previous measurements. Persistent (temperature-independent) spin dynamics are observed up to 0

Jiawei Du, Hanshu Yan, Vincent Y. F. Tan, Joey Tianyi Zhou

It has been shown that the majority of existing adversarial defense methods achieve robustness at the cost of sacrificing prediction accuracy. The undesirable severe drop in accuracy adversely affects the reliability of machine learning algorithms and prohibits their deployment in realistic applications. This paper aims to address this dilemma by proposing a

Matthew A. Petroff, Graeme E. Addison, Charles L. Bennett, Janet L. Weiland

In order to extract cosmological information from observations of the millimeter and submillimeter sky, foreground components must first be removed to produce an estimate of the cosmic microwave background (CMB). We developed a machine-learning approach for doing so for full-sky temperature maps of the millimeter and submillimeter sky. We constructed a Bayes

Dane Taylor

Multiplex networks are a common modeling framework for interconnected systems and multimodal data, yet we still lack fundamental insights for how multiplexity affects stochastic processes. We introduce a novel ``Markov chains of Markov chains'' model called multiplex Markov chains (MMCs) such that with probably $(1-\omega)\in [0,1]$ random walkers remain in

Tao Wang, Junsong Wang, Chang Xu, Chao Xue

Model quantization is a widely used technique to compress and accelerate deep neural network (DNN) inference, especially when deploying to edge or IoT devices with limited computation capacity and power consumption budget. The uniform bit width quantization across all the layers is usually sub-optimal and the exploration of hybrid quantization for different

Thomás Jung Spier

Inspired by Viennot's observation that matching polynomials are numerators of branched continued fractions we present a proof of the Heilmann-Lieb Theorem.

David Amaro Alcalá, Dylan Spivak, Hubert de Guise

We show that sums of carefully chosen coincidence rates in a multiphoton interferometry experiment can be simplified by replacing the original unitary scattering matrix with a coset matrix containing $0$s. The number and placement of these $0$s reduces the complexity of each term in the sum without affecting the original sum of rates. In particular, the eval

Frédéric Simard, Josée Desharnais, François Laviolette

Cops and Robbers games have been studied for the last few decades in computer science and mathematics. As in general pursuit evasion games, pursuers (cops) seek to capture evaders (robbers); however, players move in turn and are constrained to move on a discrete structure, usually a graph, and know the exact location of their opponent. In 2017, Bonato and Ma

Victoria L. Lemieux, Darra Hofman, Hoda Hamouda, Danielle Batista

This paper reports on the development and evaluation of a prototype blockchain solution for private and secure individual omics health data management and sharing. This solution is one output of a multidisciplinary project investigating the social, data and technical issues surrounding application of blockchain technology in the context of personalized healt

Frederik Broucke, Gregory Debruyne, Jasson Vindas

We construct a Beurling generalized number system satisfying the Riemann hypothesis and whose integer counting function displays extremal oscillation in the following sense. The prime counting function of this number system satisfies $\pi(x)= \operatorname*{Li} (x)+ O(\sqrt{x})$, while its integer counting function satisfies the oscillation estimate $N(x) =

Jiahua Dong, Yang Cong, Gan Sun, Bineng Zhong

Unsupervised domain adaptation has attracted growing research attention on semantic segmentation. However, 1) most existing models cannot be directly applied into lesions transfer of medical images, due to the diverse appearances of same lesion among different datasets; 2) equal attention has been paid into all semantic representations instead of neglecting

Dario Rodrigues, Kevin Andersson, Mariano Cababie, Andre Donadon

Skipper-CCD can achieve deep sub-electron readout noise making possible the absolute determination of the exact number of ionized electrons in a large range, from 0 to above 1900 electrons. In this work we present a novel technique that exploits this unique capability to allow self-calibration and the ultimate determination of silicon properties. We performe

Burkhard Hoppenstedt, Manfred Reichert, Ghada El-Khawaga, Klaus Kammerer

In the context of Industry 4.0, the knowledge extraction from sensor information plays an important role. Often, information gathered from sensor values reveals meaningful insights for production levels, such as anomalies or machine states. In our use case, we identify production phases through the inspection of sensor values with the help of convolutional n

Nikolay Malkin, Anthony Ortiz, Caleb Robinson, Nebojsa Jojic

We show that simple patch-based models, such as epitomes, can have superior performance to the current state of the art in semantic segmentation and label super-resolution, which uses deep convolutional neural networks. We derive a new training algorithm for epitomes which allows, for the first time, learning from very large data sets and derive a label supe

Thanh Vinh Vo, Pengfei Wei, Wicher Bergsma, Tze-Yun Leong

This work extends causal inference with stochastic confounders. We propose a new approach to variational estimation for causal inference based on a representer theorem with a random input space. We estimate causal effects involving latent confounders that may be interdependent and time-varying from sequential, repeated measurements in an observational study.

Ibrahim Tamim, Manar Jammal, Hassan Hawilo, Abdallah Shami

The shift towards a completely virtualized networking environment is triggered by the emergence of software defined networking and network function virtualization (NFV). Network service providers have unlocked immense capabilities by these technologies, which have enabled them to dynamically adapt to user needs by deploying their network services in real-tim

Kirsten Eisentraeger, Sean Hallgren, Chris Leonardi, Travis Morrison

Computing endomorphism rings of supersingular elliptic curves is an important problem in computational number theory, and it is also closely connected to the security of some of the recently proposed isogeny-based cryptosystems. In this paper we give a new algorithm for computing the endomorphism ring of a supersingular elliptic curve $E$ that runs, under ce

Arshdeep Sekhon, Zhe Wang, Yanjun Qi

Learning the differential statistical dependency network between two contexts is essential for many real-life applications, mostly in the high dimensional low sample regime. In this paper, we propose a novel differential network estimator that allows integrating various sources of knowledge beyond data samples. The proposed estimator is scalable to a large n

Filiberto Fele, Kostas Margellos

We consider a multi-agent noncooperative game with agents' objective functions being affected by uncertainty. Following a data driven paradigm, we represent uncertainty by means of scenarios and seek a robust Nash equilibrium solution. We treat the Nash equilibrium computation problem within the realm of probably approximately correct (PAC) learning. Bui

Gregor Wiedemann, Seid Muhie Yimam, Chris Biemann

Fine-tuning of pre-trained transformer networks such as BERT yield state-of-the-art results for text classification tasks. Typically, fine-tuning is performed on task-specific training datasets in a supervised manner. One can also fine-tune in unsupervised manner beforehand by further pre-training the masked language modeling (MLM) task. Hereby, in-domain da

Calvin Alexandre Fracassi Farias, Renato Pakter, Yan Levin

We investigate the stability of a uniform elliptical vortex in a two-dimensional incompressible Euler fluid. It's demonstrated that for small eccentricities, the vortex relaxes to a core-halo structure that undergoes rigid rotation with the central core remaining elliptical. For large eccentricities, the vortex splits into two quasi-circular vortices that re

Sourav Chatterjee, Persi Diaconis

We show that the convergence of finite state space Markov chains to stationarity can often be considerably speeded up by alternating every step of the chain with a deterministic move. Under fairly general conditions, we show that not only do such schemes exist, they are numerous.

Babak Naderi, Sebastian Möller

The rank correlation coefficients and the ranked-based statistical tests (as a subset of non-parametric techniques) might be misleading when they are applied to subjectively collected opinion scores. Those techniques assume that the data is measured at least at an ordinal level and define a sequence of scores to represent a tied rank when they have precisely

Kumar J. B. Ghosh, Sabre Kais, Dudley R. Herschbach

We present a simple interpolation formula using dimensional limits $D=1$ and $D=\infty$ to obtain the $D=3$ ground-state energies of atoms and molecules. For atoms, these limits are linked by first-order perturbation terms of electron-electron interactions. This unorthodox approach is illustrated by ground-states for two, three, and four electron atoms, with

Ninghao Liu, Mengnan Du, Ruocheng Guo, Huan Liu

Despite the recent advances in a wide spectrum of applications, machine learning models, especially deep neural networks, have been shown to be vulnerable to adversarial attacks. Attackers add carefully-crafted perturbations to input, where the perturbations are almost imperceptible to humans, but can cause models to make wrong predictions. Techniques to pro