March 2020 arXiv papers — page 119

Serhan Gül, Dimitri Podborski, Jangwoo Son, Gurdeep Singh Bhullar

Volumetric video is an emerging technology for immersive representation of 3D spaces that captures objects from all directions using multiple cameras and creates a dynamic 3D model of the scene. However, processing volumetric content requires high amounts of processing power and is still a very demanding task for today's mobile devices. To mitigate this,

Jeffrey Galkowski, Jacob Shapiro

In this note, we prove weighted resolvent estimates for the semiclassical Schrödinger operator $-h^2 Δ+ V(x) : L^2(\mathbb{R}^n) \to L^2(\mathbb{R}^n)$, $n \neq 2$. The potential $V$ is real-valued, and assumed to either decay at infinity or to obey a radial $α$-Hölder continuity condition, $0\leq α\leq 1$, with sufficient decay of the local radial $C^α$ nor

Eleni Bakali, Aggeliki Chalki, Aris Pagourtzis

An important objective of research in counting complexity is to understand which counting problems are approximable. In this quest, the complexity class TotP, a hard subclass of #P, is of key importance, as it contains self-reducible counting problems with easy decision version, thus eligible to be approximable. Indeed, most problems known so far to admit an

Minyong Guo, Peng-Cheng Li

Recently, a novel $4D$ Einstein-Gauss-Bonnet (EGB) gravity was formulated and a spherically symmetric black hole solution in this theory was derived by D. Glavan and C. Lin \cite{Glavan:2019inb}. In this paper, we study the geodesic motions in the background of the spherically symmetric black hole, by focusing on the innermost stable circular orbits (ISCO) f

Fang Qin, Shuai Li, Z. Z. Du, C. M. Wang

The charge-density-wave (CDW) mechanism of the 3D quantum Hall effect has been observed recently in ZrTe$_5$ [Tang et al., Nature 569, 537 (2019)]. Different from previous cases, the CDW forms on a one-dimensional (1D) band of Landau levels, which strongly depends on the magnetic field. However, its theory is still lacking. We develop a theory for the CDW me

Xiang Zhang, Gerrit E. W. Bauer, Tao Yu

We propose a method to control surface phonon transport by weak magnetic fields based on the pumping of surface acoustic waves (SAWs) by magnetostriction. We predict that the magnetization dynamics of a nanowire on top of a dielectric films injects SAWs with opposite angular momenta into opposite directions. Two parallel nanowires form a phononic cavity that

Václav Rozhoň

We present a simple analysis of k-means|| (Bahmani et al., PVLDB 2012) -- a distributed variant of the k-means++ algorithm (Arthur and Vassilvitskii, SODA 2007). Moreover, the bound on the number of rounds is improved from $O(\log n)$ to $O(\log n / \log\log n)$, which we show to be tight.

Juebin Lao, Chengfeng Cai, Zhao-Huan Yu, Yu-Pan Zeng

We explore the Dirac fermionic and complex scalar dark matter in the framework of a hidden $\mathrm{U}(1)_\mathrm{X}$ gauge theory with kinetic mixing between the $\mathrm{U}(1)_\mathrm{X}$ and $\mathrm{U}(1)_\mathrm{Y}$ gauge fields. The $\mathrm{U}(1)_\mathrm{X}$ gauge symmetry is spontaneously broken due to a hidden Higgs field. The kinetic mixing provide

Steven Y. K. Wong, Jennifer Chan, Lamiae Azizi, Richard Y. D. Xu

We consider the problem of neural network training in a time-varying context. Machine learning algorithms have excelled in problems that do not change over time. However, problems encountered in financial markets are often time-varying. We propose the online early stopping algorithm and show that a neural network trained using this algorithm can track a func

Steffen Franke, Ralf Methling, Dirk Uhrlandt, Sergey Gortschakow

A switching-off process very similar to those in real high-voltage self-blast circuit-breakers is emulated in a model chamber to study the arc properties by optical emission spectroscopy. The arc is operated in a chamber filled with SF$_6$ between a pin-tulip contact system enclosed by a PTFE nozzle. Transparent windows in the chamber wall and a slit in the

Xiaocheng Li, Chunlin Sun, Yinyu Ye

In this paper, we develop a simple and fast online algorithm for solving a class of binary integer linear programs (LPs) arisen in general resource allocation problem. The algorithm requires only one single pass through the input data and is free of doing any matrix inversion. It can be viewed as both an approximate algorithm for solving binary integer LPs a

Sang June Lee, Jun Seok Oh

Let $C_n$ be a cyclic group of order $n$. A sequence $S$ of length $\ell$ over $C_n$ is a sequence $S = a_1\boldsymbol\cdot a_2\boldsymbol\cdot \ldots\boldsymbol\cdot a_{\ell}$ of $\ell$ elements in $C_n$, where a repetition of elements is allowed and their order is disregarded. We say that $S$ is a zero-sum sequence if $\Sigma_{i=1}^{\ell} a_i = 0$ and that

Roberto Costantini, Luciano Colazzo, Laura Batini, Matus Stredansky

The self-assembly of Leucoquinizarin molecule on Au(111) surface is shown to be characterized by the molecules mostly in their keto-enolic tautomeric form, with evidences of their temporary switching to other tautomeric forms. This reveals a metastable chemistry of the assembled molecules, to be considered for their possible employment in the formation of mo

Eunji Chong, Yongxin Wang, Nataniel Ruiz, James M. Rehg

We address the problem of detecting attention targets in video. Our goal is to identify where each person in each frame of a video is looking, and correctly handle the case where the gaze target is out-of-frame. Our novel architecture models the dynamic interaction between the scene and head features and infers time-varying attention targets. We introduce a

Satoshi X. Nakamura, Takatsugu Ishikawa, Toru Sato

We discuss the possibility of extracting the neutron-neutron scattering length $a_{nn}$ and effective range $r_{nn}$ from cross section data ($d^2σ/dM_{nn}/dΩ_π$), as a function of the $nn$ invariant mass $M_{nn}$, for $π^+$ photoproduction on the deuteron ($γd\to π^+nn$). The analysis is based on a $γd\to π^+nn$ reaction model in which realistic elementary

Jonathan Love

Given a pair of elliptic curves $E_1,E_2$ over a field $k$, we have a natural map $\text{CH}^1(E_1)_0\otimes\text{CH}^1(E_2)_0\to\text{CH}^2(E_1\times E_2)$, and a conjecture due to Beilinson predicts that the image of this map is finite when $k$ is a number field. We construct a $2$-parameter family of elliptic curves that can be used to produce examples of

Juan Maya, Leonardo Rey Vega

We consider a distributed detection problem where measurements at each sensor follow a general parametric distribution. The network does not have a central processing unit or fusion center (FC). Thus, each node takes some measurements, does some processing, exchanges messages with its neighbors and finally makes a decision (typically the same for all nodes)

P. Drozdowski, C. Rathgeb, A. Dantcheva, N. Damer

Systems incorporating biometric technologies have become ubiquitous in personal, commercial, and governmental identity management applications. Both cooperative (e.g. access control) and non-cooperative (e.g. surveillance and forensics) systems have benefited from biometrics. Such systems rely on the uniqueness of certain biological or behavioural characteri

Heling Deng

Primordial bubbles that possibly nucleate through quantum tunneling during inflation in a multidimensional potential might have left some relic detectable at the present time. These bubbles turn into black holes during the radiation era, which may account for the LIGO black holes, supermassive black holes, and may play an important role in dark matter. Typic

Saehyung Lee, Hyungyu Lee, Sungroh Yoon

Adversarial examples cause neural networks to produce incorrect outputs with high confidence. Although adversarial training is one of the most effective forms of defense against adversarial examples, unfortunately, a large gap exists between test accuracy and training accuracy in adversarial training. In this paper, we identify Adversarial Feature Overfittin

Wei-ting Chiu, Roxanne M. Tutchton, Giacomo Resta, Tsung-Han Lee

Studying the local moment and 5$f$-electron occupations sheds insight into the electronic behavior in actinide materials. X-ray absorption spectroscopy (XAS) has been a powerful tool to reveal the valence electronic structure when assisted with theoretical calculations. However, the analysis currently taken in the community on the branching ratio of the XAS

Stefan Kratsch, Tomáš Masařík, Irene Muzi, Marcin Pilipczuk

Given two disjoint sets $W_1$ and $W_2$ of points in the plane, the Optimal Discretization problem asks for the minimum size of a family of horizontal and vertical lines that separate $W_1$ from $W_2$, that is, in every region into which the lines partition the plane there are either only points of $W_1$, or only points of $W_2$, or the region is empty. Equi

Min Gao, Junwei Zhang, Junliang Yu, Jundong Li

Recommender systems (RSs) now play a very important role in the online lives of people as they serve as personalized filters for users to find relevant items from an array of options. Owing to their effectiveness, RSs have been widely employed in consumer-oriented e-commerce platforms. However, despite their empirical successes, these systems still suffer fr

Fabio Muratore, Christian Eilers, Michael Gienger, Jan Peters

When learning policies for robot control, the required real-world data is typically prohibitively expensive to acquire, so learning in simulation is a popular strategy. Unfortunately, such polices are often not transferable to the real world due to a mismatch between the simulation and reality, called 'reality gap'. Domain randomization methods tackl

Frank Nielsen, Richard Nock

It is well-known that the Bhattacharyya, Hellinger, Kullback-Leibler, $α$-divergences, and Jeffreys' divergences between densities belonging to a same exponential family have generic closed-form formulas relying on the strictly convex and real-analytic cumulant function characterizing the exponential family. In this work, we report (dis)similarity formul

Péter Burcsi, Gabriele Fici, Zsuzsanna Lipták, Rajeev Raman

A prefix normal word is a binary word with the property that no substring has more $1$s than the prefix of the same length. By proving that the set of prefix normal words is a bubble language, we can exhaustively list all prefix normal words of length $n$ as a combinatorial Gray code, where successive strings differ by at most two swaps or bit flips. This Gr

Yong Bai, Yuanfang Guo, Jinjie Wei, Lin Lu

With the development of deep neural networks, digital fake paintings can be generated by various style transfer algorithms.To detect the fake generated paintings, we analyze the fake generated and real paintings in Fourier frequency domain and observe statistical differences and artifacts. Based on our observations, we propose Fake Generated Painting Detecti

Zhaofeng Kang, Jiang Zhu

Classical scale invariance (CSI) may shed light on the weak scale origin, but the realistic CSI extension to the standard model requires a bosonic trigger. We propose a scalar Dark Matter(DM) field $X$ as the trigger, establishing a strong connection between the successful radiative breaking of CSI and DM phenomenologies. The latter forces the breaking scale

Chihiro Noguchi, Tatsuro Kawamoto

Communities commonly overlap in real-world networks. This is a motivation to develop overlapping community detection methods, because methods for non-overlapping communities may not perform well. However, deterioration mechanism of the detection methods used for non-overlapping communities have rarely been investigated theoretically. Here, we analyze an accu

Boris Latosh

Review of the most basic issues appearing in the most conservative approaches to quantum theory of gravity is given. The most part of the review is devoted to issues of perturbative quantization based on functional integral technique. Discussion of canonical quantization program in context of quantum gravity is given. Discussion of effective field theory met

Erica Brondolin

The CMS detector will undergo significant improvements to face the 10-fold increase in integrated luminosity of LHC, the so-called High-Luminosity LHC, scheduled to start in 2027. This will include a completely new calorimeter in the CMS endcap regions, which should be able to withstand fluences of up to 10 16 n$_{eq}$ /cm$^2$ . The new High Granularity Calo

Yao-Yuan Yang, Cyrus Rashtchian, Hongyang Zhang, Ruslan Salakhutdinov

Current methods for training robust networks lead to a drop in test accuracy, which has led prior works to posit that a robustness-accuracy tradeoff may be inevitable in deep learning. We take a closer look at this phenomenon and first show that real image datasets are actually separated. With this property in mind, we then prove that robustness and accuracy

Cuong Nguyen, Thanh-Toan Do, Gustavo Carneiro

We introduce a new and rigorously-formulated PAC-Bayes meta-learning algorithm that solves few-shot learning. Our proposed method extends the PAC-Bayes framework from a single task setting to the meta-learning multiple task setting to upper-bound the error evaluated on any, even unseen, tasks and samples. We also propose a generative-based approach to estima

Dalong Zhang, Xin Huang, Ziqi Liu, Zhiyang Hu

Machine learning over graphs have been emerging as powerful learning tools for graph data. However, it is challenging for industrial communities to leverage the techniques, such as graph neural networks (GNNs), and solve real-world problems at scale because of inherent data dependency in the graphs. As such, we cannot simply train a GNN with classic learning

B. Ananthanarayan, Abhijit B. Das, Ratan Sarkar

The ASPIRE program, which is based on the Landau singularities and the method of power geometry to unveil the regions required for the evaluation of a given Feynman diagram asymptotically in a given limit, also allows for the evaluation of scaling coming from the top facets. In this work, we relate the scaling having equal components of the top facets of the

Edric Matwiejew, Jingbo Wang

QSW_MPI is a python package developed for time-series simulation of continuous-time quantum stochastic walks. This model allows for the study of Markovian open quantum systems in the Lindblad formalism, including a generalisation of the continuous-time random walk and continuous-time quantum walk. Consisting of a python interface accessing parallelised Fortr

Chaochao Chen, Jun Zhou, Bingzhe Wu, Wenjin Fang

Point-of-Interest (POI) recommendation has been extensively studied and successfully applied in industry recently. However, most existing approaches build centralized models on the basis of collecting users' data. Both private data and models are held by the recommender, which causes serious privacy concerns. In this paper, we propose a novel Privacy pre

Man Xie, Xin-Nian Wang, Han-Zhong Zhang

Under the assumption that a quark-gluon plasma droplet is produced and its evolution can be described by hydrodynamics in p + A collisions, $γ$-triggered hadron spectra are studied within a next-to-leading-order perturbative QCD parton model with the medium-modified parton fragmentation functions. The initial conditions and space-time evolution of the small

Cen Chen, Chen Liang, Jianbin Lin, Li Wang

The insurance industry has been creating innovative products around the emerging online shopping activities. Such e-commerce insurance is designed to protect buyers from potential risks such as impulse purchases and counterfeits. Fraudulent claims towards online insurance typically involve multiple parties such as buyers, sellers, and express companies, and

Mohit Lamba, Kranthi Kumar, Kaushik Mitra

Light Field (LF) offers unique advantages such as post-capture refocusing and depth estimation, but low-light conditions limit these capabilities. To restore low-light LFs we should harness the geometric cues present in different LF views, which is not possible using single-frame low-light enhancement techniques. We, therefore, propose a deep neural network

Yiming Sun, Bing Cao, Pengfei Zhu, Qinghua Hu

Drone-based vehicle detection aims at finding the vehicle locations and categories in an aerial image. It empowers smart city traffic management and disaster rescue. Researchers have made mount of efforts in this area and achieved considerable progress. Nevertheless, it is still a challenge when the objects are hard to distinguish, especially in low light co

Su-Chan Park

We introduce and numerically study the branching annihilating random walks with long-range attraction (BAWL). The long-range attraction makes hopping biased in such a manner that particle's hopping along the direction to the nearest particle has larger transition rate than hopping against the direction. Still, unlike the Lévy flight, a particle only hops

Sungjin Im, Mahshid Montazer Qaem, Benjamin Moseley, Xiaorui Sun

This paper considers $k$-means clustering in the presence of noise. It is known that $k$-means clustering is highly sensitive to noise, and thus noise should be removed to obtain a quality solution. A popular formulation of this problem is called $k$-means clustering with outliers. The goal of $k$-means clustering with outliers is to discard up to a specifie

Michael D. Himes, Joseph Harrington, Adam D. Cobb, Atilim Gunes Baydin

Atmospheric retrieval determines the properties of an atmosphere based on its measured spectrum. The low signal-to-noise ratio of exoplanet observations require a Bayesian approach to determine posterior probability distributions of each model parameter, given observed spectra. This inference is computationally expensive, as it requires many executions of a

Chuankun Zhang, Stephen B. Schoun, Christoph M. Heyl, Gil Porat

We demonstrate a femtosecond enhancement cavity with a crossed-beam geometry for efficient generation and extraction of extreme-ultraviolet (XUV) frequency combs at a 154 MHz repetition rate. We achieve a record-high out-coupled power of 600 μW, directly usable for spectroscopy, at a wavelength of 97 nm. This corresponds to a >60% out-coupling efficiency. Th

Gurpreet Singh, Soumyajit Gupta, Matt Lease, Clint N. Dawson

Partial Differential Equations are infinite dimensional encoded representations of physical processes. However, imbibing multiple observation data towards a coupled representation presents significant challenges. We present a fully convolutional architecture that captures the invariant structure of the domain to reconstruct the observable system. The propose

Chengxi Li, Stanley H. Chan, Yi-Ting Chen

A significant amount of people die in road accidents due to driver errors. To reduce fatalities, developing intelligent driving systems assisting drivers to identify potential risks is in an urgent need. Risky situations are generally defined based on collision prediction in the existing works. However, collision is only a source of potential risks, and a mo

Yuni Iwamasa, Kenjiro Takazawa

For two matroids $M_1$ and $M_2$ with the same ground set $V$ and two cost functions $w_1$ and $w_2$ on $2^V$, we consider the problem of finding bases $X_1$ of $M_1$ and $X_2$ of $M_2$ minimizing $w_1(X_1)+w_2(X_2)$ subject to a certain cardinality constraint on their intersection $X_1 \cap X_2$. For this problem, Lendl, Peis, and Timmermans (2019) discusse

Chen-Yu Wang, Shi-Jun Liang, Shuang Wang, Pengfei Wang

Early processing of visual information takes place in the human retina. Mimicking neurobiological structures and functionalities of the retina provide a promising pathway to achieving vision sensor with highly efficient image processing. Here, we demonstrate a prototype vision sensor that operates via the gate-tunable positive and negative photoresponses of

Dongqi Wu, Dileep Kalathil, Miroslav Begovic, Le Xie

This paper introduces the concept of Deep Reinforcement Learning based architecture for protective relay design in power distribution systems with many distributed energy resources (DERs). The performance of widely-used overcurrent protection scheme is hindered by the presence of distributed generation, power electronic interfaced devices and fault impedance

I. M. Ross

We show that a direct shooting method is mathematically equivalent to an indirect method in the sense of certain first-order conditions. Specific mathematical formulas pertaining to the equivalence of a direct shooting method with an indirect method are derived. We also show that a theoretical equivalence does not necessarily translate to practical equivalen

Kouhei Nakaji

In this paper, we introduce an efficient algorithm for the quantum amplitude estimation task which works in noisy intermediate-scale quantum(NISQ) devices. The quantum amplitude estimation is an important problem which has various applications in fields such as quantum chemistry, machine learning, and finance. Because the well-known algorithm for the quantum

Nicholas Triantafillou

Let $K$ be a number field with ring of integers $\mathcal O_{K}$. We prove that if $3$ does not divide $ [K:\mathbb Q]$ and $3$ splits completely in $K$, then the unit equation has no solutions in $K$. In other words, there are no $x, y \in \mathcal O_{K}^{\times}$ with $x + y = 1$. Our elementary $p$-adic proof is inspired by the Skolem-Chabauty-Coleman met

Ren Liao, Fangyu Xiong, Xuzong Chen

We propose a spinless Bose-Hubbard model in an one-dimensional (1D) double-chain tilted lattice at unit filling per cell. A subspace of this model can be faithfully mapped to the 1D transverse Ising model through superexchange interaction with second-order perturbation theory. At a valid parameter region, numerical results show good agreement of these two mo

Satoshi Nakamura

The notion of coupled Kähler-Einstein metrics was introduced recently by Hultgren-WittNyström. In this paper we discuss deformation of a coupled Kähler-Einstein metrics on a Fano manifold. In particular we obtain a necessary and sufficient condition for a coupled Kähler-Einstein metric to be deformed to another coupled Kähler-Einstein metric for a Fano manif

Lindsay Sonderhouse, Christian Sanner, Ross B. Hutson, Akihisa Goban

Many-body quantum systems can exhibit a striking degree of symmetry unparalleled by their classical counterparts. While in real materials SU($N$) symmetry is an idealization, this symmetry is pristinely realized in fully controllable ultracold alkaline-earth atomic gases. Here, we study an SU($N$)-symmetric Fermi liquid of $^{87}$Sr atoms, where $N$ can be t

Fang Yang, Yayun Zheng, Jinqiao Duan, Ling Fu

In light of the rapid recent retreat of Arctic sea ice, the extreme weather events triggering the variability in Arctic ice cover has drawn increasing attention. A non-Gaussian $α$-stable Lévy process is thought to be an appropriate model to describe such extreme event. The maximal likely trajectory, based on the nonlocal Fokker-Planck equation, is applied t

Yat Tin Chow, Youjun Deng, Youzi He, Hongyu Liu

We present the discovery of a novel and intriguing global geometric structure of the (interior) transmission eigenfunctions associated with the Helmholtz system. It is shown in generic scenarios that there always exists a sequence of transmission eigenfunctions with the corresponding eigenvalues going to infinity such that those eigenfunctions are localized

Karthik Menon, Rajat Mittal

A method to predict the aeroelastic pitch response of an airfoil to gusts is presented. The prediction is based on energy maps generated by high-fidelity fluid dynamic simulations of the airfoil with prescribed pitch oscillations. The energy maps quantify the exchange of energy between the pitching airfoil and the flow, and serve as manifolds over which the

Liam Madden, Stephen Becker, Emiliano Dall'Anese

This paper investigates online algorithms for smooth time-varying optimization problems, focusing first on methods with constant step-size, momentum, and extrapolation-length. Assuming strong convexity, precise results for the tracking iterate error (the limit supremum of the norm of the difference between the optimal solution and the iterates) for online gr

Dongyi Wei, Shiwu Yang

In this paper, we study the asymptotic decay properties for defocusing semilinear wave equations in $\mathbb{R}^{1+2}$ with pure power nonlinearity. By applying new vector fields to null hyperplane, we derive improved time decay of the potential energy, with a consequence that the solution scatters both in the critical Sobolev space and energy space for all

Jiefeng Liu

We study (quasi-)twilled pre-Lie algebras and the associated $L_\infty$-algebras and differential graded Lie algebras. Then we show that certain twisting transformations on (quasi-)twilled pre-Lie algbras can be characterized by the solutions of Maurer-Cartan equations of the associated differential graded Lie algebras ($L_\infty$-algebras). Furthermore, we

Alexandre Défossez, Léon Bottou, Francis Bach, Nicolas Usunier

We provide a simple proof of convergence covering both the Adam and Adagrad adaptive optimization algorithms when applied to smooth (possibly non-convex) objective functions with bounded gradients. We show that in expectation, the squared norm of the objective gradient averaged over the trajectory has an upper-bound which is explicit in the constants of the

ALICE Collaboration

This paper presents the measurements of $π^{\pm}$, $\rm{K}^{\pm}$, $\rm{p}$ and $\bar{\rm{p}}$ transverse momentum ($p_{\rm{T}}$) spectra as a function of charged-particle multiplicity density in proton-proton (pp) collisions at $\sqrt{s}$ = 13 TeV with the ALICE detector at the LHC. Such study allows us to isolate the center-of-mass energy dependence of lig

Sinan G. Aksoy, Mark Kempton, Stephen J. Young

The cyclic edge-connectivity of a graph $G$ is the least $k$ such that there exists a set of $k$ edges whose removal disconnects $G$ into components where every component contains a cycle. We show that for graphs of minimum degree at least 3 and girth $g$ at least 4, the cyclic edge-connectivity is bounded above by $(Δ-2)g$ where $Δ$ is the maximum degree. W

Wei Wang, Bing Wang, Peijun Zhao, Changhao Chen

In this paper, we present a novel end-to-end learning-based LiDAR relocalization framework, termed PointLoc, which infers 6-DoF poses directly using only a single point cloud as input, without requiring a pre-built map. Compared to RGB image-based relocalization, LiDAR frames can provide rich and robust geometric information about a scene. However, LiDAR poi

Claude Gravel, Daniel Panario, Bastien Rigault

We develop a new algorithm to compute determinants of all possible Hankel matrices made up from a given finite length sequence over a finite field. Our algorithm fits within the dynamic programming paradigm by exploiting new recursive relations on the determinants of Hankel matrices together with new observations concerning the distribution of zero determina

Feng Jin, Arindam Sengupta, Siyang Cao

In this paper we propose mmFall - a novel fall detection system, which comprises of (i) the emerging millimeter-wave (mmWave) radar sensor to collect the human body's point cloud along with the body centroid, and (ii) a variational recurrent autoencoder (VRAE) to compute the anomaly level of the body motion based on the acquired point cloud. A fall is cl

Elaine C. F. S. Fortes, Oswaldo D. Miranda, Floyd W. Stecker, Carlos A. Wuensche

In this paper, we explore the potential astrophysical signatures of dark matter (DM) annihilations in ultra-compact dwarf galaxies (UCDs) considering two of the richest known galaxy clusters within 100 million light-years, nominally, Virgo and Fornax. Fornax UCD3 is the most luminous known UCD and M59 UCD3 is the most massive known UCD. With the detection of

A. A. Araújo Filho, R. V. Maluf

In this work, we study the thermodynamic properties of a photon gas in a heat bath within the context of higher-derivative electrodynamics. Specifically, we analyze Podolsky's theory and its extension involving the Lorentz symmetry violation recently proposed in the literature. First, we use the concept of the number of available states of the system in

Jiang Chang, Zhen Yuan, Xiang-Xiang Xue, Iulia T. Simion

A large number of new members ($\sim$150) of the Cetus Stream (CS) were identified from their clustering features in dynamical space using 6D kinematic data by combining LAMOST DR5 and Gaia DR2 surveys. They map a diffuse structure that extends over at least 100 degrees in the northern and southern Galactic hemispheres, at heliocentric distances between 20 t

Qiuping A. Wang

This paper provides a derivation of Zipf-Pareto laws directly from the principle of least effort. A probabilistic functional of efficiency is introduced as the consequence of an extension of the nonadditivity of the efficiency of thermodynamic engine to a large number of living agents assimilated to engines, all randomly distributed over their output. Applic

Cheongho Han, Doeon Kim, Andrzej Udalski, Andrew Gould

We analyze KMT-2019-BLG-1339, a microlensing event with an obvious but incompletely resolved brief anomaly feature around the peak of the light curve. Although the origin of the anomaly is identified to be a companion to the lens with a low mass ratio $q$, the interpretation is subject to two different degeneracy types. The first type is the ambiguity in $ρ$

Lars Larsson, William Tärneberg, Cristian Klein, Erik Elmroth

By intrinsic necessity, Kubernetes is a complex platform. Its complexity makes conducting performance analysis in that environment fraught with difficulties and emergent behavior. Applications leveraging more "moving parts" such as the Istio service mesh makes the platform strictly more complex, not less. In this paper we study how underlying platfor

Clemens JS Schaefer, Patrick Faley, Emre O Neftci, Siddharth Joshi

The energy efficiency of neuromorphic hardware is greatly affected by the energy of storing, accessing, and updating synaptic parameters. Various methods of memory organisation targeting energy-efficient digital accelerators have been investigated in the past, however, they do not completely encapsulate the energy costs at a system level. To address this sho

Mengxiao Hu, Jinlong Li, Maolin Hu, Tao Hu

In conditional Generative Adversarial Networks (cGANs), when two different initial noises are concatenated with the same conditional information, the distance between their outputs is relatively smaller, which makes minor modes likely to collapse into large modes. To prevent this happen, we proposed a hierarchical mode exploring method to alleviate mode coll

Ines Rieger, Jaspar Pahl, Dominik Seuss

Balancing methods for single-label data cannot be applied to multi-label problems as they would also resample the samples with high occurrences. We propose to reformulate this problem as an optimization problem in order to balance multi-label data. We apply this balancing algorithm to training datasets for detecting isolated facial movements, so-called Actio

Joshua J. Levy, Rebecca M. Lebeaux, Anne G. Hoen, Brock C. Christensen

Importance: Following a century of increase, life expectancy in the United States has stagnated and begun to decline in recent decades. Using satellite images and street view images prior work has demonstrated associations of the built environment with income, education, access to care and health factors such as obesity. However, assessment of learned image

Rateb Jabbar, Mohammed Shinoy, Mohamed Kharbeche, Khalifa Al-Khalifa

Qatar expects more than a million visitors during the 2022 World Cup, which will pose significant challenges. The high number of people will likely cause a rise in road traffic congestion, vehicle crashes, injuries and deaths. To tackle this problem, Naturalistic Driver Behavior can be utilised which will collect and analyze data to estimate the current Qata

Felix M. Lev

In standard quantum theory, symmetry is defined in the spirit of Klein's Erlangen Program: the background space has a symmetry group, and the basic operators should commute according to the Lie algebra of that group. We argue that the definition should be the opposite: background space has a direct physical meaning only on classical level while on quantu

Timothy Matthew Fawcett, Stephanie Irausquin, Mikhail Simin, Homayoun Valafar

Current protein forcefields like the ones seen in CHARMM or Xplor-NIH have many terms that include bonded and non-bonded terms. Yet the forcefields do not take into account the use of hydrogen bonds which are important for secondary structure creation and stabilization of proteins. SCOPE is an open-source program that generates proteins from rotamer space. I

Kamalaker Dadi, Gaël Varoquaux, Antonia Machlouzarides-Shalit, Krzysztof J. Gorgolewski

Population imaging markedly increased the size of functional-imaging datasets, shedding new light on the neural basis of inter-individual differences. Analyzing these large data entails new scalability challenges, computational and statistical. For this reason, brain images are typically summarized in a few signals, for instance reducing voxel-level measures

Anjaneya Teja Sarma Kalvakolanu

Plant disease detection is a huge problem and often require professional help to detect the disease. This research focuses on creating a deep learning model that detects the type of disease that affected the plant from the images of the leaves of the plants. The deep learning is done with the help of Convolutional Neural Network by performing transfer learni

Makoto Nakamura

A semilinear ordinary differential equation is derived from a semilinear Schrödinger equation in the homogeneous and isotropic spacetime by the Ehrenfest theorem. The Cauchy problem for the equation is considered. Exact solutions and nonexistence of global weak solutions of the equation are also considered in the de Sitter spacetime. The effects of spatial e

Siyi Liu, Ziang Leng, Derry Wijaya

Mirroring is the behavior in which one person subconsciously imitates the gesture, speech pattern, or attitude of another. In conversations, mirroring often signals the speakers enjoyment and engagement in their communication. In chatbots, methods have been proposed to add personas to the chatbots and to train them to speak or to shift their dialogue style t

João P. Galdino, P. H. Figueirêdo, Ramón E. R. González, Juan Lombana

In this work, a generalization of the study of the human gait was made from already existent models in the literature, like models of Keller and Kockshenev. In this hybrid model, a strategy of metabolic energy minimization is combined in a race process, with a non-linear description of the movement of the mass center's libration, trying to reproduce the

Peng Zhang, Jianbin Fang, Canqun Yang, Chun Huang

This article presents an automatic approach to quickly derive a good solution for hardware resource partition and task granularity for task-based parallel applications on heterogeneous many-core architectures. Our approach employs a performance model to estimate the resulting performance of the target application under a given resource partition and task gra

Xiangyu Zhang, Ramin Bashizade, Yicheng Wang, Cheng Lyu

Statistical machine learning often uses probabilistic algorithms, such as Markov Chain Monte Carlo (MCMC), to solve a wide range of problems. Probabilistic computations, often considered too slow on conventional processors, can be accelerated with specialized hardware by exploiting parallelism and optimizing the design using various approximation techniques.

Gurcan Comert, Mizanur Rahman, Mhafuzul Islam, Mashrur Chowdhury

Connected vehicle (CV) systems are cognizant of potential cyber attacks because of increasing connectivity between its different components such as vehicles, roadside infrastructure, and traffic management centers. However, it is a challenge to detect security threats in real-time and develop appropriate or effective countermeasures for a CV system because o

Jiaosheng Li, Yuhui Li, Ju Li, Qinnan Zhang

A novel framework of optical image hiding based on deep learning (DL) is proposed in this paper, and hidden information can be reconstructed from an interferogram by using an end to end network with high-quality. By using the prior data between the hidden image and the object image, a generative adversarial network was trained so that it can learn the hiding

V. Sorianello, G. Contestabile, M. Romagnoli

Graphene is a 2D material with appealing electronic and optoelectronic properties. It is a zero-bandgap material with valence and conduction bands meeting in a single point (Dirac point) in the momentum space. Its conductivity can be changed by shifting the Fermi level energy via an external electric field. This important property determines broadband and tu

Hangyu Mao, Zhibo Gong, Zhen Xiao

In cooperative multi-agent reinforcement learning (MARL), how to design a suitable reward signal to accelerate learning and stabilize convergence is a critical problem. The global reward signal assigns the same global reward to all agents without distinguishing their contributions, while the local reward signal provides different local rewards to each agent

Felix Last, Max Haeberlein, Ulf Schlichtmann

Typical semiconductor chips include thousands of mostly small memories. As memories contribute an estimated 25% to 40% to the overall power, performance, and area (PPA) of a chip, memories must be designed carefully to meet the system's requirements. Memory arrays are highly uniform and can be described by approximately 10 parameters depending mostly on

Mahdi Ebrahimi

Suppose $Γ$ is a finite simple graph. If $D$ is a dominating set of $Γ$ such that each $x\in D$ is contained in the set of vertices of an odd cycle of $Γ$, then we say that $D$ is an odd dominating set for $Γ$. For a finite group $G$, let $Δ(G)$ denote the character graph built on the set of degrees of the irreducible complex characters of $G$. In this paper

Mazyar Ghani Varzaneh, Sebastian Riedel

Building on results obtained in [GVRS], we prove Local Stable and Unstable Manifold Theorems for nonlinear, singular stochastic delay differential equations. The main tools are rough paths theory and a semi-invertible Multiplicative Ergodic Theorem for cocycles acting on measurable fields of Banach spaces obtained in [GVR].

Youngsub Yoon

In 2016, Erik Verlinde proposed a new theory of gravity called "emergent gravity" by using mathematical formulas used in the theory of elasticity. In 2017, De-Chang Dai and Dejan Stojkovic claimed to point out inconsistencies in Verlinde's emergent gravity. We point out that their claim was based on misunderstanding of the dictionary between emer

Shounak Ghosh, A. D. Kanfon, Amit Das, M. J. S. Houndjo

We propose a stellar model under the $f(\mathbb{T},\mathcal{T})$ gravity following Mazur-Mottola's conjecture [Mazur (2001), Mazur (2004)] known as gravastar which is generally believed as a viable alternative to black hole. The gravastar consists of three regions, viz., (I) Interior region, (II) Intermediate shell region, and (III) Exterior region. The

Muhammad K. A. Hamdan, Diane T. Rover, Matthew J. Darr, John Just

Mass flow estimation is of great importance to several industries, and it can be quite challenging to obtain accurate estimates due to limitation in expense or general infeasibility. In the context of agricultural applications, yield monitoring is a key component to precision agriculture and mass flow is the critical factor to measure. Measuring mass flow al

Anh Minh Pham

We give a Pfaffian formula to compute the partition function of the Ising model on any graph $G$ embedded in a closed, possibly non-orientable surface. This formula, which is suitable for computational purposes, is based on the relation between the Ising model on $G$ and the dimer model on its terminal graph $G^T$. By combining the ideas of Loebl-Masbaum \ci

So-Myoung Park, Simon P. Goodwin, Sungsoo S. Kim

We show that dynamical evolution in a strong (Galactic Centre-like) tidal field can create clusters that would appear to have very top-heavy IMFs. The tidal disruption of single star forming events can leave several bound `clusters' spread along 20 pc of the orbit within 1-2 Myr. These surviving (sub)clusters tend to contain an over-abundance of massive