November 2018 arXiv papers — page 102

Didier Bresch, Mathieu Colin, Khawla Msheik, Pascal Noble

In this note, we propose in the full generality a link between the BD entropy introduced by D. Bresch andB. Desjardins for the viscous shallow-water equations and the Bernis-Friedman (called BF) dissipative entropyintroduced to study the lubrications equations. Dierent dissipative entropies are obtained playing with the dragterms on the viscous shallow water

Norbert Bodendorfer, Fabian Haneder

We discuss how SU$(1,1)$ coherent states from the discrete series allow for a natural coarse graining operation. The physical application are quantum theories based on a set of three extensive observables whose Poisson algebra is isomorphic to su$(1,1)$. In particular, we show that a Perelomov coherent state with representation label $N j_0$ and spinor label

Xi Chen, Jie Tang, Yizhou Sun

Network dynamics has always been a meaningful topic deserving exploration in the realm of academy. previous network models contain two parts: (1) generating structure as per user property; (2) changing property as per network structure. Properties in these models, however, cannot be interpreted to concept in prevalent social theories or empirical truth. Also

Takuma Imamura

Suenaga and Hasuo introduced a nonstandard programming language ${\bf While}^{\bf dt}$ which models hybrid systems. We demonstrate why ${\bf While}^{\bf dt}$ is not suitable for modeling actual computations.

B. Rezaei, G. R. Boroun

An analytical solution of the QCD evolution equations for the singlet and gluon distribution is presented. We decouple DGLAP evolution equations into the initial conditions by using a Laplace transform method at $N^{n}LO$ analysis. The relationship between the nonlinear behavior and color dipole model is considered based on an effective exponent behavior at

Naoyuki Koike

In this paper, we investigate a regularized mean curvature flow starting from an invariant hypersurface in a Hilbert space equipped with an isometric and almost free action of a Hilbert Lie group whose orbits are minimal regularizable submanifolds. We prove that, if the initial invariant hypersurface satisfies a certain kind of horizontally convexity conditi

Arpita Mal, Kallol Paul, T. S. S. R. K. Rao, Debmalya Sain

We study approximate Birkhoff-James orthogonality of bounded linear operators defined between normed linear spaces $\mathbb{X}$ and $\mathbb{Y}.$ As an application of the results obtained, we characterize smoothness of a bounded linear operator $T$ under the condition that $\mathbb{K}(\mathbb{X},\mathbb{Y}),$ the space of compact linear operators is an $M-$i

Jiali Li, Tiankai Chen, Kaizhuo Lim, Lingtong Chen

The understanding of inorganic reactions, especially those far from the equilibrium state, is relatively limited due to their inherent complexity. Poor understandings on the underlying synthetic chemistry have constrained the design of efficient synthesis routes towards desired final products, especially those inorganic materials at atomic precision. In this

Yoonchang Sung, Deeksha Dixit, Pratap Tokekar

In this paper, we study the problem of exploring an unknown Region Of Interest (ROI) with a team of aerial robots. The size and shape of the ROI are unknown to the robots. The objective is to find a tour for each robot such that each point in the ROI must be visible from the field-of-view of some robot along its tour. In conventional exploration using ground

Bang-Yen Chen, Siraj Uddin, Azeb Alghanemi, Awatif AL-Jedani

In this paper, we prove that there are no proper $CRS$ bi-warped product submanifolds other than contact CR-biwarped products in Sasakian manifolds. On the other hand, we prove that if $M$ is a $CRS$ bi-warped product of the form $M=N_T \times_{f_1}N^{n_{1}}_\perp\times_{f_2} N^{n_{2}}_θ$ in a cosymplectic manifold $\widetilde M$, then its second fundamental

Tomislav Plesa

Biochemical reactions involving three or more reactants, called higher-molecular reactions, play an important role in theoretical systems and synthetic biology. In particular, such reactions underpin a variety of important bio-dynamical phenomena, such as multi-stability/multi-modality, oscillations, bifurcations, and noise-induced effects. However, only rea

Xin Wang, Jiawei Wu, Da Zhang, Yu Su

Although promising results have been achieved in video captioning, existing models are limited to the fixed inventory of activities in the training corpus, and do not generalize to open vocabulary scenarios. Here we introduce a novel task, zero-shot video captioning, that aims at describing out-of-domain videos of unseen activities. Videos of different activ

Yohsuke Murase, Hiroyasu Matsushima, Itsuki Noda, Tomio Kamada

We present a software framework called CARAVAN, which was developed for comprehensive simulations on massive parallel computers. The framework runs user-developed simulators with various input parameters in parallel without requiring the knowledge of parallel programming. The framework is useful for exploring high-dimensional parameter spaces, for which samp

Peiyang Song, Fengkui Gong, Qiang Li, Guo Li

Faster-than-Nyquist (FTN) is a promising paradigm to improve bandwidth utilization at the expense of additional intersymbol interference (ISI). In this paper, we apply state-of-the-art deep learning (DL) technology into receiver design for FTN signaling and propose two DL-based new architectures. Firstly, we propose an FTN signal detection based on DL and co

Yikuan Li, Liang Yao, Chengsheng Mao, Anand Srivastava

Acute kidney injury (AKI) in critically ill patients is associated with significant morbidity and mortality. Development of novel methods to identify patients with AKI earlier will allow for testing of novel strategies to prevent or reduce the complications of AKI. We developed data-driven prediction models to estimate the risk of new AKI onset. We generated

Kursat Rasim Mestav, Jaime Luengo-Rozas, Lang Tong

The problem of state estimation for unobservable distribution systems is considered. A deep learning approach to Bayesian state estimation is proposed for real-time applications. The proposed technique consists of distribution learning of stochastic power injection, a Monte Carlo technique for the training of a deep neural network for state estimation, and a

Natalie P. Schieber, Michael R. Shirts

In this study, we incorporate configuration mapping between simulation ensembles into the successive interpolation of multistate reweighting (SIMR) method in order to increase phase space overlap between neighboring simulation ensembles. This significantly increases computational efficiency over the original SIMR method in many situations. We use this approa

Hannah R. Schwartz

We show that the number of double points of smoothly immersed 2-spheres representing certain homology classes of an oriented, smooth, closed, simply-connected 4-manifold X must increase with the complexity of corresponding h-cobordisms from X to X. As an application, we give results restricting the minimal number of double points of immersed spheres in manif

B. ODea, T. W. Boonstra, M. E. Larsen, T. Nguyen

Due to its popularity and availability, social media data may present a new way to identify individuals who are experiencing mental illness. By analysing blog content, this study aimed to investigate the associations between linguistic features and symptoms of depression, generalised anxiety, and suicidal ideation. This study utilised a longitudinal study de

Osman Tursun, Simon Denman, Sabesan Sivapalan, Sridha Sridharan

The demand for large-scale trademark retrieval (TR) systems has significantly increased to combat the rise in international trademark infringement. Unfortunately, the ranking accuracy of current approaches using either hand-crafted or pre-trained deep convolution neural network (DCNN) features is inadequate for large-scale deployments. We show in this paper

Bogdan Danila, Tiberiu Harko, Francisco S. N. Lobo, Man Kwong Mak

We consider vacuum static spherically symmetric solutions in the hybrid metric-Palatini gravity theory, which is a combination of the metric and Palatini $f(R)$ formalisms unifying local constraints at the Solar System level and the late-time cosmic acceleration. We adopt the scalar-tensor representation of the hybrid metric-Palatini theory, in which the sca

Adam Logan

For two varieties of dimension $5$ constructed as double covers of ${\mathbb P}^5$ branched along the union of $12$ hyperplanes, we prove that the number of points over ${\mathbb F}_p$ can be expressed in terms of Artin symbols and the $p$th Fourier coefficients of modular forms. Many analogous results are known in dimension $\le 3$, but very few in higher d

Jianeng Zhou, Zhongxiang Wang, Liang Chen, Paul J. Wiita

Since 2016 October, the active galaxy PKS 2247-131 has undergone a gamma-ray outburst, which we studied using data obtained with the Fermi Gamma-ray Space Telescope. The emission arises from a relativistic jet in PKS 2247-131, as an optical spectrum only shows a few weak absorption lines, typical of the BL Lacertae sub-class of the blazar class of active gal

Yves Le Jan

The purpose of the present note is to review and improve the convergence of the renormalized winding fields.

Hyungjun Lim, Younggwan Kim, Youngmoon Jung, Myunghun Jung

Previous researches on acoustic word embeddings used in query-by-example spoken term detection have shown remarkable performance improvements when using a triplet network. However, the triplet network is trained using only a limited information about acoustic similarity between words. In this paper, we propose a novel architecture, phonetically associated tr

Nelson Yalta, Shinji Watanabe, Takaaki Hori, Kazuhiro Nakadai

Casual conversations involving multiple speakers and noises from surrounding devices are common in everyday environments, which degrades the performances of automatic speech recognition systems. These challenging characteristics of environments are the target of the CHiME-5 challenge. By employing a convolutional neural network (CNN)-based multichannel end-t

Mingxia Huo, Ying Li

The error model of a quantum computer is essential for optimizing quantum algorithms to minimize the impact of errors using quantum error correction or error mitigation. Noise with temporal correlations, e.g. low-frequency noise and context-dependent noise, is common in quantum computation devices and sometimes even significant. However, conventional tomogra

Philip Greengard

Generalized prolate spheroidal functions (GPSFs) arise naturally in the study of bandlimited functions as the eigenfunctions of a certain truncated Fourier transform. In one dimension, the theory of GPSFs (typically referred to as prolate spheroidal wave functions) has a long history and is fairly complete. Furthermore, more recent work has led to the develo

Zhi-Gang Wang

In this article, we introduce a P-wave between the diquark and antidiquark explicitly to construct the vector tetraquark currents, and study the vector tetraquark states with the QCD sum rules systematically, and obtain the lowest vector tetraquark masses up to now. The present predictions support assigning the $Y(4220/4260)$, $Y(4320/4360)$, $Y(4390)$ and $

Zeev Dvir, Alexander Golovnev, Omri Weinstein

We show that static data structure lower bounds in the group (linear) model imply semi-explicit lower bounds on matrix rigidity. In particular, we prove that an explicit lower bound of $t \geq ω(\log^2 n)$ on the cell-probe complexity of linear data structures in the group model, even against arbitrarily small linear space $(s= (1+\varepsilon)n)$, would alre

N. Sirica, R. I. Tobey, L. X. Zhao, G. F. Chen

We investigate polarization-dependent ultrafast photocurrents in the Weyl semimetal TaAs using terahertz (THz) emission spectroscopy. Our results reveal that highly directional, transient photocurrents are generated along the non-centrosymmetric c-axis regardless of incident light polarization, while helicity-dependent photocurrents are excited within the ab

Sam Kumar, Michael P Andersen, Hyung-Sin Kim, David E. Culler

Low-power and lossy networks (LLNs) enable diverse applications integrating many resource-constrained embedded devices, often requiring interconnectivity with existing TCP/IP networks as part of the Internet of Things. But TCP has received little attention in LLNs due to concerns about its overhead and performance, leading to LLN-specific protocols that requ

Ruizong Li, Tianyou Gao, Dongfang Zhang, Shi-Guo Peng

We experimentally and theoretically observe the expansion behaviors of a spherical Bose-Einstein condensate. A rubidium condensate is produced in an isotropic optical dipole trap with an asphericity of 0.037. We measure the variation of the condensate size during the expansion process. The free expansion of the condensate is isotropic, which is different fro

Gopal P. Sarma, Adam Safron, Nick J. Hay

We describe a biologically-inspired research agenda with parallel tracks aimed at AI and AI safety. The bottom-up component consists of building a sequence of biophysically realistic simulations of simple organisms such as the nematode $Caenorhabditis$ $elegans$, the fruit fly $Drosophila$ $melanogaster$, and the zebrafish $Danio$ $rerio$ to serve as platfor

Nicolas Gontier, Koustuv Sinha, Peter Henderson, Iulian Serban

Current conversational systems can follow simple commands and answer basic questions, but they have difficulty maintaining coherent and open-ended conversations about specific topics. Competitions like the Conversational Intelligence (ConvAI) challenge are being organized to push the research development towards that goal. This article presents in detail the

Sebastian E. Reyes-Lillo, Karin M. Rabe, Jeffrey B. Neaton

We use first principles density functional theory calculations to investigate the effect of biaxial strain in the low-temperature structural and ferroelectric properties of [111]-oriented SrTiO$_3$. We find that [111] biaxial strain, achievable by coherent epitaxial growth along the [111] direction, induces structural distortions in SrTiO$_3$ that are not pr

Steven Duplij

This article continues the study of concrete algebra-like structures in our polyadic approach, where the arities of all operations are initially taken as arbitrary, but the relations between them, the arity shapes, are to be found from some natural conditions ("arity freedom principle"). In this way, generalized associative algebras, coassociative coalgebras

Tao Li, Adam Miranowicz, Keyu Xia, Franco Nori

We propose a resource-efficient error-rejecting entangled-state analyzer for polarization-encoded multiphoton systems. Our analyzer is based on two single-photon quantum-nondemolition detectors, where each of them is implemented with a four-level emitter (e.g., a quantum dot) coupled to a one-dimensional system (such as a micropillar cavity or a photonic nan

Richard Garner

Jacobs' hypernormalisation is a construction on finitely supported discrete probability distributions, obtained by generalising certain patterns occurring in quantitative information theory. In this paper, we generalise Jacobs' notion in turn, by describing a notion of hypernormalisation in the abstract setting of a symmetric monoidal category endowed with a

Lucas C. F. Ferreira, Monisse Postigo

In this work we consider the Keller-Segel system coupled with Navier-Stokes equations in $\mathbb{R}^{N}$ for $N\geq2$. We prove the global well-posedness with small initial data in Besov-Morrey spaces. Our initial data class extends previous ones found in the literature such as that obtained by Kozono-Miura-Sugiyama (J. Funct. Anal. 2016). It allows to cons

P. Jameson Graber, Alpár R. Mészáros, Francisco J. Silva, Daniela Tonon

In this paper, using variational approaches, we investigate the first order planning problem arising in the theory of mean field games. We show the existence and uniqueness of weak solutions of the problem in the case of a large class of Hamiltonians with arbitrary superlinear order of growth at infinity and local coupling functions. We require the initial a

Charles Roques-Carmes, Yichen Shen, Cristian Zanoci, Mihika Prabhu

The inability of conventional electronic architectures to efficiently solve large combinatorial problems motivates the development of novel computational hardware. There has been much effort recently toward developing novel, application-specific hardware, across many different fields of engineering, such as integrated circuits, memristors, and photonics. How

Marc Jourdan, Sebastien Blandin, Laura Wynter, Pralhad Deshpande

The Bitcoin transaction graph is a public data structure organized as transactions between addresses, each associated with a logical entity. In this work, we introduce a complete probabilistic model of the Bitcoin Blockchain. We first formulate a set of conditional dependencies induced by the Bitcoin protocol at the block level and derive a corresponding ful

Dmitriy Volinskiy, Lana Cuthbertson, Omid Ardakanian

Economies and societal structures in general are complex stochastic systems which may not lend themselves well to algebraic analysis. An addition of subjective value criteria to the mechanics of interacting agents will further complicate analysis. The purpose of this short study is to demonstrate capabilities of agent-based computational economics to be a pl

Arkady Molev-Shteiman, Xiao-Feng Qi

Reduction of comparison cycles leads to power savings of a successive-approximation-register (SAR) analog-to-digital converters (ADC). We establish that the lowest average number of comparison cycles of a SAR ADC approaches the entropy of the ADC output, and proposed a simple adaptive algorithm that approaches this lower bound. Today's SAR ADC uses binar

Dharmendra Kumar Mishra, Aicha Sekhari, Sébastien Henry, Dharmendra Mishra

The rapid technological enhancement and innovations in current days have changed people's thought. The use of Information Technology tools in people's daily life has changed their life style completely. The advent of various innovative smart products in the market has tremendous impact on people's lifestyle. They want to know their heart beat whi

Gouranga C Nayak

The present lattice QCD method can not study the hadron formation from the quarks and gluons. This is because it operates the unphysical QCD Hamiltonian of all the quarks plus antiquarks plus gluons inside the hadron on the physical energy eigenstate of the hadron to obtain the physical energy eigenvalue of the hadron which is not correct because of the non-

Sophea Chhun, Néjib Moalla, Yacine Ouzrout

Natural language is understandable by human and not machine. None technical persons can only use natural language to specify their business requirements. However, the current version of Business process management and notation (BPMN) tools do not allow business analysts to implement their business processes without having technical skills. BPMN tool is a too

Yan Mary He

We obtain asymptotic counting results with error terms for complex orthospectrum for Schottky groups and orbit counting function for quadratic polynomials. Moreover, we prove equidistribution of holonomy associated to these dynamical systems. Our results are obtained by considering generalized $L$-functions coming from the Basmajian-type identities introduce

Patricio Gaete, José A. Helayël-Neto, L. P. R. Ospedal

We examine physical aspects for the electric version of a recently proposed logarithmic electrodynamics, for which the electric field of a point-like charge is finite at the origin. It is shown that this electrodynamics displays the vacuum birefringence phenomenon in the presence of external magnetic field. Afterwards we compute the lowest-order modification

Mircea Merca

In this paper we give a convolution identity for the complete and elementary symmetric functions. This result can be used to proving and discovering some combinatorial identities involving $r$-Stirling numbers, $r$-Whitney numbers and $q$-binomial coefficients. As a corollary we derive a generalization of the quantum Vandermonde's convolution identity.

H. T. Kung, Bradley McDanel, Sai Qian Zhang

This paper describes a novel approach of packing sparse convolutional neural networks for their efficient systolic array implementations. By combining subsets of columns in the original filter matrix associated with a convolutional layer, we increase the utilization efficiency of the systolic array substantially (e.g., ~4x) due to the increased density of no

Jay Lofstead, Joshua Baker, Andrew Younge

Trusting simulation output is crucial for Sandia's mission objectives. We rely on these simulations to perform our high-consequence mission tasks given national treaty obligations. Other science and modeling applications, while they may have high-consequence results, still require the strongest levels of trust to enable using the result as the foundation

Yao Liu, Giovanni Dipierro, Enrico Ragusa, Giuseppe Lodato

Gap-like structures in protoplanetary disks are likely related to planet formation processes. In this paper, we present and analyze high resolution (0.17*0.11 arcsec) 1.3 mm ALMA continuum observations of the protoplanetary disk around the Herbig Ae star MWC 480. Our observations for the first time show a gap centered at ~74au with a width of ~23au, surround

L. M. Pismen

Morphogenetic patterns are highly sophisticated dissipative structures. Are they governed by the same general mechanisms as chemical and hydrodynamic patterns? Turing's symmetry breaking and Wolpert's signalling provide alternative mechanisms. The current evidence points out that the latter is more relevant but reality is still far more complicated.

D. Rosa González, H. Muriel, Y. D. Mayya, I. Aretxaga

We present new spectroscopic data of the BL Lac RGB 2243+203, and its surroundings, obtained with the OSIRIS Multi Object Spectrograph (MOS) mounted in the Gran Telescopio Canarias (GTC). The spectra of neither the BL Lac nor its host galaxy show any spectral feature, thus hindering direct determination of its redshift. The spectroscopic redshift distributio

Truyen Nguyen

We study global regularity for solutions of quasilinear elliptic equations of the form $÷\A(x,u,\nabla u) = ÷\F $ in rough domains $Ω$ in $\R^n$ with nonhomogeneous Dirichlet boundary condition. The vector field $\A$ is assumed to be continuous in $u$, and its growth in $\nabla u$ is like that of the $p$-Laplace operator. We establish global gradient estimat

William Detmold, Gurtej Kanwar, Michael L. Wagman

Correlation functions in one-dimensional complex scalar field theory provide a toy model for phase fluctuations, sign problems, and signal-to-noise problems in lattice field theory. Phase unwrapping techniques from signal processing are applied to lattice field theory in order to map compact random phases to noncompact random variables that can be numericall

Ilias Diakonikolas, Daniel M. Kane

The degree-$d$ Chow parameters of a Boolean function $f: \{-1,1\}^n \to \mathbb{R}$ are its degree at most $d$ Fourier coefficients. It is well-known that degree-$d$ Chow parameters uniquely characterize degree-$d$ polynomial threshold functions (PTFs) within the space of all bounded functions. In this paper, we prove a robust version of this theorem: For $f

Michael Albrow

I discuss the possibility that dark energy is a scalar field whose quanta are extremely light and very weakly interacting superluminal particles, i.e. tachyons, with purely imaginary mass $m = iΓ$ with $Γ$ real.

Roberto Leonarduzzi, Patrice Abry, Herwig Wendt, Stéphane Jaffard

Multifractal analysis has become a powerful signal processing tool that characterizes signals or images via the fluctuations of their pointwise regularity, quantified theoretically by the so-called multifractal spectrum. The practical estimation of the multifractal spectrum fundamentally relies on exploiting the scale dependence of statistical properties of

Jenő Szirmai

In \cite{Sz17-2} we considered hyperball packings in $3$-dimensional hyperbolic space. We developed a decomposition algorithm that for each saturated hyperball packing provides a decomposition of $\HYP$ into truncated tetrahedra. In order to get a density upper bound for hyperball packings, it is sufficient to determine the density upper bound of hyperball p

Thi-Phong Nguyen

We discuss the use of differential sampling method to image local perturbations in anisotropic periodic layers, extending earlier works on the isotropic case. We study in particular the new interior transmission problem that is associated with the inverse problem when only a single Floquet-Bloch mode is used. We prove Fredholm properties of this problem unde

Jonathan Bartlett

First year calculus is often taught in a way that is very burdensome to the student. Students have to memorize a diversity of processes for essentially performing the same task. However, many calculus processes can be simplified and streamlined so that fewer concepts can provide more flexibility and capability for first-year students.

Aleksandr Cariow, Galina Cariowa

This paper presents a structural design of the hardware-efficient module for implementation of convolution neural network (CNN) basic operation with reduced implementation complexity. For this purpose we utilize some modification of the Winograd minimal filtering method as well as computation vectorization principles. This module calculate inner products of

Jiayang Liu, Weiming Zhang, Nenghai Yu

Deep Neural Networks (DNNs) have recently led to significant improvements in many fields. However, DNNs are vulnerable to adversarial examples which are samples with imperceptible perturbations while dramatically misleading the DNNs. Adversarial attacks can be used to evaluate the robustness of deep learning models before they are deployed. Unfortunately, mo

Chao Deng, Xuemei Hu, Xiaoxu Li, Jinli Suo

Single-pixel imaging (SPI) is an emerging technique which has attracts wide attention in various research fields. However, restricted by the low reconstruction quality and large amount of measurements, the practical application is still in its infancy. Inspired by the fact that natural scenes exhibit unique degenerate structures in the low dimensional subspa

Koray Düztaş

In this work we investigate validity of the weak form of the cosmic censorship conjecture in the interaction of Kerr-Sen black holes with neutral test fields. Previous studies of the Klein-Gordon equation on Kerr-Sen background imply that superradiance occurs for scalar fields. We show that scalar fields can overspin a nearly extremal black hole into a naked

Martin Karafiát, Murali Karthick Baskar, Shinji Watanabe, Takaaki Hori

This paper investigates the applications of various multilingual approaches developed in conventional hidden Markov model (HMM) systems to sequence-to-sequence (seq2seq) automatic speech recognition (ASR). On a set composed of Babel data, we first show the effectiveness of multi-lingual training with stacked bottle-neck (SBN) features. Then we explore variou

L. Chang, Yacine Ouzrout, Antoine Nongaillard, Abdelaziz Bouras

As one of Bayesian analysis tools, Hidden Markov Model (HMM) has been used to in extensive applications. Most HMMs are solved by Baum-Welch algorithm (BWHMM) to predict the model parameters, which is difficult to find global optimal solutions. This paper proposes an optimized Hidden Markov Model with Particle Swarm Optimization (PSO) algorithm and so is call

Giovanna Cottin

Many models of new physics beyond the Standard Model are able to describe massive, long-lived particles with macroscopic decays, which can be reconstructed as displaced vertices inside the inner trackers of the LHC experiments. In addition, the lack of evidence of any new physics at the LHC motivates to perform more unconventional searches, such as looking f

Vyacheslav M. Abramov

This paper studies a discrete model of a large dam where the difference between lower and upper levels, $L$, is assumed to be large. Passage across the levels leads to damage, and the damage costs of crossing the lower or upper level are proportional to the large parameter $L$. Input stream of water is described by compound Poisson process, and the water cos

Christopher Ryba

We answer a question of Zeilberger and Zeilberger about certain partition statistics.

Marcus Carlsson

We provide theory for the computation of convex envelopes of non-convex functionals including an l2-term, and use these to suggest a method for regularizing a more general set of problems. The applications are particularly aimed at compressed sensing and low rank recovery problems but the theory relies on results which potentially could be useful also for ot

Wenbo Guo, Sui Huang, Yunzhe Tao, Xinyu Xing

Understanding and interpreting how machine learning (ML) models make decisions have been a big challenge. While recent research has proposed various technical approaches to provide some clues as to how an ML model makes individual predictions, they cannot provide users with an ability to inspect a model as a complete entity. In this work, we propose a novel

Brett Van Der Goetz, Leon Otis, Eric Neuscamman

We introduce a basis of counting functions that, by cleanly tessellating three dimensional space, allows real space number counting Jastrow factors to be straightforwardly applied to general molecular situations. By exerting direct control over electron populations in local regions of space and encoding pairwise correlations between these populations, these

Elizabeth Salesky, Susanne Burger, Jan Niehues, Alex Waibel

When translating from speech, special consideration for conversational speech phenomena such as disfluencies is necessary. Most machine translation training data consists of well-formed written texts, causing issues when translating spontaneous speech. Previous work has introduced an intermediate step between speech recognition (ASR) and machine translation

Peter J Forrester, Shi-Hao Li

A $θ$-deformation of the Laguerre weighted Cauchy two-matrix model, and the Bures ensemble, is introduced. Such a deformation is familiar from the Muttalib-Borodin ensemble. The $θ$-deformed Cauchy-Laguerre two-matrix model is a two-component determinantal point process. It is shown that the correlation kernel, and its hard edge scaled limit, can be written

Andrea Carosso, Anna Hasenfratz, Ethan T. Neil

Gradient flow has proved useful in the definition and measurement of renormalized quantities on the lattice. Recently, the fact that it suppresses high-modes of the field has been used to construct new, continuous RG transformations both analytically and on the lattice, distinct from the usual blocking techniques in spin models and gauge theories. In this wo

Gabriel Ryan, Abigail Mosca, Remco Chang, Eugene Wu

When inspecting information visualizations under time critical settings, such as emergency response or monitoring the heart rate in a surgery room, the user only has a small amount of time to view the visualization "at a glance". In these settings, it is important to provide a quantitative measure of the visualization to understand whether or not the

Jianwen Li, Kristin Y. Rozier, Geguang Pu, Yueling Zhang

We present here a SAT-based framework for LTLf (Linear Temporal Logic on Finite Traces) satisfiability checking. We use propositional SAT-solving techniques to construct a transition system for the input LTLf formula; satisfiability checking is then reduced to a path-search problem over this transition system. Furthermore, we introduce CDLSC (Conflict-Driven

David Bryant, Michael Charleston

The Minimal Ancestral Deviation (MAD) method is a recently introduced procedure for estimating the root of a phylogenetic tree, based only on the shape and branch lengths of the tree. The method is loosely derived from the midpoint rooting method, but, unlike its predecessor, makes use of all pairs of OTUs when positioning the root. In this note we establish

Matthew R. Kirchner

We introduce a method to perform automatic thresholding of SIFT descriptors that improves matching performance by at least 15.9% on the Oxford image matching benchmark. The method uses a contrario methodology to determine a unique bin magnitude threshold. This is done by building a generative uniform background model for descriptors and determining when bin

Auralee Edelen, Christopher Mayes, Daniel Bowring, Daniel Ratner

Machine learning (ML) is a subfield of artificial intelligence. The term applies broadly to a collection of computational algorithms and techniques that train systems from raw data rather than a priori models. ML techniques are now technologically mature enough to be applied to particle accelerators, and we expect that ML will become an increasingly valuable

P. G. Matveeva, D. N. Aristov, D. Meidan, D. B. Gutman

Dirac materials have unique transport properties, partly due to the presence of surface states. A new type of Dirac materials, protected by non-symmorphic symmetries was recently proposed by Young and Kane [1]. By breaking of time reversal or inversion symmetry one can split the Dirac cones into Weyl nodes. The later are characterized by local Chern numbers,

Rebecca Centeno

The weak field approximation (WFA) is a conceptually simple and computationally light method for inferring the magnetic field strength and its orientation in the Sun's atmosphere. In this work we study the validity and limitations of this tool when applied to full Stokes Ca II 8542 A profiles to extract information about the chromospheric magnetic field.

Taolue Chen, Matthew Hague, Anthony W. Lin, Philipp Rümmer

The design and implementation of decision procedures for checking path feasibility in string-manipulating programs is an important problem, whose applications include symbolic execution and automated detection of cross-site scripting (XSS) vulnerabilities. A (symbolic) path is a finite sequence of assignments and assertions (i.e. without loops), and checking

Amir-Hossein Karimi, Alexander Wong, Ali Ghodsi

Supervised dimensionality reduction strategies have been of great interest. However, current supervised dimensionality reduction approaches are difficult to scale for situations characterized by large datasets given the high computational complexities associated with such methods. While stochastic approximation strategies have been explored for unsupervised

Rodger I. Thompson

This paper uses the beta function formalism to extend the analysis of quintessence cosmological parameters to the logarithmic and exponential dark energy potentials. The previous paper (Thompson 2018) demonstrated the formalism using power and inverse power potentials. The essentially identical evolution of the Hubble parameter for all of the quintessence ca

I. Pagotto, E. M. Corsini, M. Sarzi, B. Pagani

We present new measurements for the nuclear stellar velocity dispersion $σ_{\ast}$ within sub-arcsecond apertures for 28 nearby galaxies. Our data consist of Space Telescope Imaging Spectrograph (STIS) long-slit spectra obtained with the G750M grating centred on the H$α$ spectral range. We fit the spectra using a library of single stellar population models a

Kshitij Tiwari, Xuesu Xiao, Nak Young Chong

Mobile robots are increasingly being used to assist with active pursuit and law enforcement. One major limitation for such missions is the resource (battery) allocated to the robot. Factors like nature and agility of evader, terrain over which pursuit is being carried out, plausible traversal velocity and the amount of necessary data to be collected all infl

Lin Chen, Lei Xu, Shouhuai Xu, Zhimin Gao

Bribery in election (or computational social choice in general) is an important problem that has received a considerable amount of attention. In the classic bribery problem, the briber (or attacker) bribes some voters in attempting to make the briber's designated candidate win an election. In this paper, we introduce a novel variant of the bribery proble

Ali Taimori, Farokh Marvasti

Compressive sensing is a new technology for modern computational imaging systems. In comparison to widespread conventional image sensing, the compressive imaging paradigm requires specific forensic analysis techniques and tools. In this regards, one of basic scenarios in image forensics is to distinguish traditionally sensed images from sophisticated compres

Dragana Bozovic, Aleksander Kelenc, Iztok Peterin, Ismael G. Yero

Let $G=(V,E)$ be a graph. A set of vertices $A$ is an incidence generator for $G$ if for any two distinct edges $e,f\in E(G)$ there exists a vertex from $A$ which is an endpoint of either $e$ or $f$. The smallest cardinality of an incidence generator for $G$ is called the incidence dimension and is denoted by $dim_I(G)$. A set of vertices $P$ is a 2-packing

Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz

This paper addresses the mapping problem. Using a conjugate prior form, we derive the exact theoretical batch multi-object posterior density of the map given a set of measurements. The landmarks in the map are modeled as extended objects, and the measurements are described as a Poisson process, conditioned on the map. We use a Poisson process prior on the ma

K. Gretchen Greene

In this paper, we confront the problem of deep learning's big labeled data requirements, offer a rule based strategy for extreme augmentation of small data sets and apply that strategy with the image to image translation model by Isola et al. (2016) to automate cel style cartoon coloring with very limited training data. While our experimental results usi

Charles Collot, Anne-Sophie de Suzzoni

We consider a Hartree equation for a random variable, which describes the temporal evolution of infinitely many Fermions. On the Euclidean space, this equation possesses equilibria which are not localised. We show their stability through a scattering result, with respect to localised perturbations in the defocusing case in high dimensions $d\geq 4$. This pro

Alireza Abdoli, Amy C. Murillo, Chin-Chia M. Yeh, Alec C. Gerry

Poultry farms are an important contributor to the human food chain. Worldwide, humankind keeps an enormous number of domesticated birds (e.g. chickens) for their eggs and their meat, providing rich sources of low-fat protein. However, around the world, there have been growing concerns about the quality of life for the livestock in poultry farms; and increasi

Yoshitaka Saiki, James A. Yorke

We investigate numerically complex dynamical systems where a fixed point is surrounded by a disk or ball of quasiperiodic orbits, where there is a change of variables (or conjugacy) that converts the system into a linear map. We compute this "linearization" (or conjugacy) from knowledge of a single quasiperiodic trajectory. In our computations of rot

Z. Felfli, A. Z. Msezane

Here we investigate ground and metastable negative ion formation in low-energy electron collisions with the actinide atoms Th, Pa, U, Np and Pu through the elastic total cross sections (TCSs) calculations. For these atoms, the presence of two or more open d- and f- subshell electrons presents a formidable computational task for conventional theoretical metho