July 2019 arXiv papers — page 38

Sita Sundar, Zhandos A. Moldabekov

We present the results of an investigation of the wakefield around a stationary charged grain in an external magnetic field with non-zero transverse component with respect to the ion flow direction. The impact of the orientation of magnetic field on the wake behavior in streaming complex plasmas is assessed. In contrast to previously reported significant sup

Olivier Pfister

This topical review introduces the theoretical and experimental advances in continuous-variable (CV) --- i.e., qumode-based in lieu of qubit-based --- large-scale, fault-tolerant quantum computing and quantum simulation. An introduction to the physics and mathematics of multipartite entangled CV cluster states is given, and their connection to experimental c

Ning Wang, Wengang Zhou, Yibing Song, Chao Ma

Correlation filters (CF) have received considerable attention in visual tracking because of their computational efficiency. Leveraging deep features via off-the-shelf CNN models (e.g., VGG), CF trackers achieve state-of-the-art performance while consuming a large number of computing resources. This limits deep CF trackers to be deployed to many mobile platfo

Xiaoping Zhai, Zhi-Min Chen

The Cauchy problem of the compressible Oldroyd-B model without damping mechanism in R^n$ with $n\ge2$ is considered. The lack of dissipation in density and stress tensor in the model is compensated by exploiting an intrinsic structure and introducing new quantities between density, velocity and stress tensor. Therefore, global solutions to the system with sm

Da Chen, Laurent D. Cohen

In this chapter, we give an overview of part of our previous work based on the minimal path framework and the Eikonal partial differential equation (PDE). We show that by designing adequate Riemannian and Randers geodesic metrics the minimal paths can be utilized to search for solutions to almost all of the active contour problems and to the Euler-Mumford el

Miguel Picallo, Florian Dörfler

Many optimization problems incorporate uncertainty affecting their parameters and thus their objective functions and constraints. As an example, in chance-constrained optimization the constraints need to be satisfied with a certain probability. To solve these problems, scenario optimization is a well established methodology that ensures feasibility of the so

Nesma M. Rezk, Madhura Purnaprajna, Tomas Nordström, Zain Ul-Abdin

Recurrent Neural Networks (RNNs) are a class of machine learning algorithms used for applications with time-series and sequential data. Recently, there has been a strong interest in executing RNNs on embedded devices. However, difficulties have arisen because RNN requires high computational capability and a large memory space. In this paper, we review existi

Anna V. Kimmel

The analysis of the structure, chemical stability, electronic and ferroelectric properties of the interfaces between Pt(001) and PbZrTiO$_3$(001) (PZT) have been performed with $ab$ $initio$ methods. We show that the chemical environment plays a critical role in determining the interfacial reconstruction and charge redistribution at the metal/oxide interface

Angelos Charalambidis, Christos Nomikos, Panos Rondogiannis

A classical result in descriptive complexity theory states that Datalog expresses exactly the class of polynomially computable queries on ordered databases. In this paper we extend this result to the case of higher-order Datalog. In particular, we demonstrate that on ordered databases, for all $k\geq2$, $k$-order Datalog captures $(k-1)$-EXPTIME. This result

Cao H. Nam

An anomaly observed recently in the $^8$Be nuclear transition by the Atomki collaboration hints at a weakly-coupled, light new gauge boson with a mass of about $17$ MeV. In this paper, we propose that this new gauge boson comes from a short-distance structure of the spacetime, rather than from an extension of the Standard Model through adding an extra $\math

Peng Zhang, Jian-Jun Bian, Chong Yang, Jin-Yu Zhang

The continuous miniaturization of modern electromechanical systems calls for a comprehensive understanding of the mechanical properties of metallic materials specific to micrometer and sub-micrometer scales. At these scales, the nature of dislocation-mediated plasticity changes radically: sub-micrometer metallic samples exhibit high yield strengths, however

Luis A. Anchordoqui, Carlos Garcia Canal, Sergio J. Sciutto, Jorge F. Soriano

Recently, the ALICE Collaboration reported an enhancement of the yield ratio of strange and multi-strange hadrons to charged pions as a function of multiplicity at mid-rapidity in proton-proton, proton-lead, lead-lead, and xenon-xenon scattering. ALICE observations provide a strong indication that a quark-gluon plasma is partly formed in high multiplicity ev

Dalu Guo, Chang Xu, Dacheng Tao

This paper revisits the bilinear attention networks in the visual question answering task from a graph perspective. The classical bilinear attention networks build a bilinear attention map to extract the joint representation of words in the question and objects in the image but lack fully exploring the relationship between words for complex reasoning. In con

Matteo Negri

We consider second order phase field functionals, in the continuum setting, and their discretization with isogeometric tensor product B-splines. We prove that these functionals, continuum and discrete, $\Gamma$-converge to a brittle fracture energy, defined in the space $GSBD^2$. In particular, in the isogeometric setting, since the projection operator is no

Jérôme Laurent, Daniel Royer, Claire Prada

Elastic waves guided along bars of rectangular cross section exhibit complex dispersion. This paper studies in-plane modes propagating at low frequencies in thin isotropic rectangular waveguides through experiments and numerical simulations. These modes result from the coupling at the edge between the first order shear horizontal mode $SH_0$ of phase velocit

Rafał Latała, Piotr Nayar

We derive new comparison inequalities between weak and strong moments of norms of random vectors with optimal (up to an universal factor) constants. We discuss applications to the concentration of log-concave random vectors and bounds on $p$-summing norms of finite rank operators.

Xiurui Geng, Lei Wang

Principal skewness analysis (PSA) has been introduced for feature extraction in hyperspectral imagery. As a third-order generalization of principal component analysis (PCA), its solution of searching for the locally maximum skewness direction is transformed into the problem of calculating the eigenpairs (the eigenvalues and the corresponding eigenvectors) of

Christian Reinhardt, Alice Chau, Joachim Stadel, Ravit Helled

Despite many similarities, there are significant observed differences between Uranus and Neptune: while Uranus is tilted and has a regular set of satellites, suggesting their accretion from a disk, Neptune's moons are irregular and are captured objects. In addition, Neptune seems to have an internal heat source, while Uranus is in equilibrium with solar insu

Arash Jafarizadeh, M. A. Rajabpour

We study general entanglement properties of the excited states of the one dimensional translational invariant free fermions and coupled harmonic oscillators. In particular, using the integrals of motion, we prove that these Hamiltonians independent of the gap (mass) has infinite excited states that can be described by conformal field theories with integer or

Soham Shanbhag, Ravi Banavar

This report proposes a discrete time observer for the continuous time rigid body kinematics on the rotation group $\mathbb{S}\mathbb{O}(3)$. The work draws on two research schools - one by Chang based on feedback integrators for systems evolving on manifolds,and the other by Mahony, who proposed an observer for attitude dynamics. The discrete time observer i

Bruno Duchesne

We study representations $G\to H$ where $G$ is either a simple Lie group with real rank at least 2 or an infinite dimensional orthogonal group of some quadratic form of finite index at least 2 and $H$ is such an orthogonal group as well. The real, complex and quaternionic cases are considered. Contrarily to the rank one case, we show that there is no exotic

Hisashi Kotegawa, Eiichi Matsuoka, Toshiaki Uga, Masaki Takemura

We report resistivity measurements under pressure for Kondo-lattice ferromagnet CeRh$_6$Ge$_4$, and present that a quantum ferromagnetic (FM) phase transition is easily achieved. In most clean metallic ferromagnets, a quantum critical point (QCP) at zero field is avoided by changing the FM transition to a discontinuous transition or to an antiferromagnetic t

I-Lin Ho

Diffractive optical elements (DOEs) are widely applied as compact solutions for desired light manipulations via wavefront shaping. Recent advanced chip applications further require their feature sizes to move down to the subwavelength, which inevitably brings forth vectorial effects of optical fields and makes the typical scalar-based theory invalid. However

Jonas Kölzer, Daniel Rosenbach, Christian Weyrich, Tobias W. Schmitt

Universal conductance fluctuations and the weak antilocalization effect are defect structure specific fingerprints in the magnetoconductance that are caused by electron interference. Experimental evidence is presented that the conductance fluctuations in the present topological insulator (Bi$_{0.57}$Sb$_{0.43}$)$_2$Te$_3$ nanoribbons which are selectively gr

Laura P. Schaposnik

These notes have been prepared as reading material for the mini-course given by the author at the "2019 Graduate Summer School" at Park City Mathematics Institute - Institute for Advanced Study. We begin by introducing Higgs bundles and their main properties (Lecture 1), and then we discuss the Hitchin fibration and its different uses (Lecture 2). The second

Liang Pan, Chee-Meng Chew, Gim Hee Lee

Motivated by the success of encoding multi-scale contextual information for image analysis, we propose our PointAtrousGraph (PAG) - a deep permutation-invariant hierarchical encoder-decoder for efficiently exploiting multi-scale edge features in point clouds. Our PAG is constructed by several novel modules, such as Point Atrous Convolution (PAC), Edge-preser

Vytautas Gruslys, Shoham Letzter, Natasha Morrison

A well-known conjecture of Frankl and F\"{u}redi from 1989 states that an initial segment of colex of has the largest Lagrangian of any $r$-uniform hypergraph with $m$ hyperedges. We show that this is true when $r=3$. We also give a new proof of a related conjecture of Nikiforov and a counterexample to an old conjecture of Ahlswede and Katona.

Dario A. Bini, Beatrice Meini, Jie Meng

Quadratic matrix equations of the kind $A_1X^2+A_0X+A_{-1}=X$ are encountered in the analysis of Quasi--Birth-Death stochastic processes where the solution of interest is the minimal nonnegative solution $G$. In many queueing models, described by random walks in the quarter plane, the coefficients $A_1,A_0,A_{-1}$ are infinite tridiagonal matrices with an al

Jun Li, Zu-Cheng Chen, Qing-Guo Huang

Primordial gravitational waves generated during inflation lead to the B-mode polarization in the cosmic microwave background and a stochastic gravitational wave background in the Universe. We will explore the current constraint on the tilt of primordial gravitational-wave spectrum, and forecast how the future observations can improve the current constraint.

Iryna Egorova, Mateusz Piorkowski, Gerald Teschl

This paper discusses some general aspects and techniques associated with the long-time asymptotics of steplike solutions of the Korteweg--de Vries (KdV) equation via vector Riemann--Hilbert problems. We also elaborate on an ill-posedness of the matrix Riemann--Hilbert problem for the KdV case in the class of matrices with square integrable singularities. Fur

V. Somà, P. Navrátil, F. Raimondi, C. Barbieri

A novel parameterisation of a Hamiltonian based on chiral effective field theory is introduced. Specifically, three-nucleon operators at next-to-next-to-leading order are combined with an existing (and successful) two-body interaction containing terms up to next-to-next-to-next-to-leading order. The resulting potential is labelled $N\!N\!$+$3N\text{(lnl)}$.

Ángel Cuevas, José González Cabañas, Aritz Arrate, Rubén Cuevas

The recent European General Data Protection Regulation (GDPR) and other data protection regulations restrict the processing of some categories of personal data (health, political orientation, sexual preferences, religious beliefs, ethnic origin, etc.) due to the privacy risks associated to such information. The GDPR refers to these categories as sensitive pe

Giovanni Pizzi, Valerio Vitale, Ryotaro Arita, Stefan Blügel

Wannier90 is an open-source computer program for calculating maximally-localised Wannier functions (MLWFs) from a set of Bloch states. It is interfaced to many widely used electronic-structure codes thanks to its independence from the basis sets representing these Bloch states. In the past few years the development of Wannier90 has transitioned to a communit

Diego H. O. Machado, Antonio Crespo-Poveda, Alexander S. Kuznetsov, Klaus Biermann

Coherent super-high-frequency (SHF) vibrations provide an excellent tool for the modulation and control of excitations in semiconductors. Here, we investigate the piezoelectric generation and propagation of longitudinal bulk acoustic waves (LBAWs) with frequencies up to 20 GHz in GaAs crystals using bulk acoustic wave resonators (BAWRs) based on piezoelectri

Chenyang Lu, Gijs Dubbelman

We propose a novel single-step training strategy that allows convolutional encoder-decoder networks that use skip connections, to complete partially observed data by means of hallucination. This strategy is demonstrated for the task of completing 2-D road layouts as well as 3-D vehicle shapes. As input, it takes data from a partially observed domain, for whi

Jean Lasserre

We show that the global minimum (resp. maximum) of a continuous function on a compact set can be approximated from above (resp. from below) by computing the smallest (rest. largest) eigenvalue of a hierarchy of (r x r) tri-diagonal univariate moment matrices of increasing size. Equivalently it reduces to computing the smallest (resp. largest) root of a certa

Jürgen Meyer-ter-Vehn, Rafael Ramis

The rate of photon absorption in warm dense matter (WDM) induced by free-free electron-ion collisions is derived from Sommerfeld's cross-section for non-relativistic bremsstrahlung emission, making use of detailed balance relations. Warm dense matter is treated as a metal-like state in the approximation of a uniform degenerate electron gas and a uniform ion

Takahiro Aoi

Let $(X,L_{X})$ be an $n$-dimensional polarized manifold. Let $D$ be a smooth hypersurface defined by a holomorphic section of $L_{X}$. In this paper, we study the existence of a complete scalar-flat K\"{a}hler metric on $X \setminus D$ on the assumption that $D$ has a constant positive scalar curvature K\"{a}hler metric.

Ryo Kikkawa, Munehiro Nishida, Yutaka Kadoya

We investigate bound states in the continuum (BICs) in a planar dielectric waveguide structure consisting of a gold grating on a dielectric layer with a back layer of metal. In this structure, Friedrich-Wintgen (FW) BICs caused by the destructive interference between the radiations from two waveguide modes appear near the anti-crossing point of the dispersio

H. Jabraoui, S. Ouaskit, J. Richard, J. -L Garden

A glass is a non-equilibrium thermodynamic state whose physical properties depend on time. Glass formation from the melt, as well as the inverse process of liquid structural recovery from the glass are non-equilibrium processes. A positive amount of entropy is produced during such irreversible processes. In this paper, we address the issue of the determinati

Jun-Jie Wei, Zhengxiang Li, He Gao, Xue-Feng Wu

Extragalactic dispersion measures (DMs) obtained from observations of fast radio bursts (FRBs) are an excellent tool for probing intergalactic medium (IGM) and for conducting cosmography. However, the DM contribution from the IGM (${\rm DM_{IGM}}$) depends on the fraction of baryon mass in the IGM, $f_{\rm IGM}$, which is not properly constrained. As $f_{\rm

Mohammad Mohammadi Amiri, Deniz Gunduz

We study federated machine learning at the wireless network edge, where limited power wireless devices, each with its own dataset, build a joint model with the help of a remote parameter server (PS). We consider a bandwidth-limited fading multiple access channel (MAC) from the wireless devices to the PS, and propose various techniques to implement distribute

Wolfgang Bock, Jose Luis da Silva, Ludwig Streit

In this paper we introduce and study three classes of fractional periodic processes. An application to ring polymers is investigated. We obtain a closed analytic expressions for the form factors, the Debye functions and their asymptotic decay. The relation between the end-to-halftime and radius of gyration is computed for these classes of periodic processes.

Alexander V. Grayver, Jerome Noir

This study reports an approach and presents its open-source implementation for quantitative analysis of experimental flows using streak images and Convolutional Neural Networks (CNN). The latter are applied to retrieve a length and an angle from streaks, which can be used to deduce kinetic energy and directionality (up to 180$^{\circ}$ ambiguity) of an image

Rosa Camps, Xavier Mora, Laia Saumell

We study a method for proportional representation that was proposed at the turn from the nineteenth to the twentieth century by Gustav Enestr\"om and Edvard Phragm\'en. Like Phragm\'en's better-known iterative minimax method, it is assumed that the voters express themselves by means of approval voting. In contrast to the iterative minimax method, however, he

Nishchal R. Dwivedi, Sudhir R. Jain

We establish a connection between macroscopic "heating or cooling" of a finite many-body quantum system and the non-adiabatic Landau-Zener-Stückelberg transitions between its quantum states. We have considered the well-known Nilsson model for describing the single-particle states of nuclei and subject the system to a random walk in the deformation sp

Yohann de Castro, Sébastien Gadat, Clément Marteau, Cathy Maugis

This paper investigates the statistical estimation of a discrete mixing measure $\mu$0 involved in a kernel mixture model. Using some recent advances in l1-regularization over the space of measures, we introduce a "data fitting and regularization" convex program for estimating $\mu$0 in a grid-less manner from a sample of mixture law, this method is referred

Long Zhu

The multinucleon transfer process is one promising approach for producing neutron-rich heavy nuclei. The favorable projectile-target combinations play a key role in experiments. As one important approach to investigate the multinucleon transfer process, one new version of the dinuclear system (DNS) model is developed. The improved version of the DNS model is

Hyeonwoo Yu

We present NOLBO, a variational observation model estimation for 3D multi-object from 2D single shot. Previous probabilistic instance-level understandings mainly consider the single-object image, not single shot with multi-object; relations between objects and the entire scene are out of their focus. The objectness of each observation also hardly join their

Erik Daniel, Elias Rohrer, Florian Tschorsch

Zcash is a privacy-preserving cryptocurrency that provides anonymous monetary transactions. While Zcash's anonymity is part of a rigorous scientific discussion, information on the underlying peer-to-peer network are missing. In this paper, we provide the first long-term measurement study of the Zcash network to capture key metrics such as the network siz

Olivier Guéant, Iuliia Manziuk, Jiang Pu

When firms want to buy back their own shares, they have a choice between several alternatives. If they often carry out open market repurchase, they also increasingly rely on banks through complex buyback contracts involving option components, e.g. accelerated share repurchase contracts, VWAP-minus profit-sharing contracts, etc. The entanglement between the e

Mathieu Dutour Sikirić, David Madore, Philippe Moustrou, Frank Vallentin

In this paper we define the chromatic number of a lattice: It is the least number of colors one needs to color the interiors of the cells of the Voronoi tessellation of a lattice so that no two cells sharing a facet are of the same color. We compute the chromatic number of the root lattices, their duals, and of the Leech lattice, we consider the chromatic nu

Junghee Cho, Junseok Kwon, Byung-Woo Hong

We present an adaptive regularization algorithm that can be effectively applied to the optimization problem in deep learning framework. Our regularization algorithm aims to take into account the fitness of data to the current state of model in the determination of regularity to achieve better generalization. The degree of regularization at each element in th

Kei Irie

For any nonempty, compact and fiberwise convex set $K$ in $T^*\mathbb{R}^n$, we prove an isomorphism between symplectic homology of $K$ and a certain relative homology of loop spaces of $\mathbb{R}^n$. We also prove a formula which computes symplectic homology capacity (which is a symplectic capacity defined from symplectic homology) of $K$ using homology of

Miguel Navascues, Sukhbinder Singh, Antonio Acin

As quantum technologies develop, we acquire control of an ever-growing number of quantum systems. Unfortunately, current tools to detect relevant quantum properties of quantum states, such as entanglement and Bell nonlocality, suffer from severe scalability issues and can only be computed for systems of a very modest size, of around $6$ sites. In order to ad

Yuki Hirano, Michael Wemyss

Let $f\colon X\to\mathrm{Spec}\, R$ be a 3-fold flopping contraction, where $X$ has at worst Gorenstein terminal singularities and $R$ is complete local. We describe the space of Bridgeland stability conditions on the null subcategory $\mathscr{C}$ of the bounded derived category of $X$, which consists of those complexes that derive pushforward to zero, and

Duško Jojić, Gaiane Panina, Rade Živaljević

We prove several versions of N. Alon's "necklace-splitting theorem", subject to additional constraints, as illustrated by the following results. (1) The "almost equicardinal necklace-splitting theorem" claims that, without increasing the number of cuts, one guarantees the existence of a fair splitting such that each thief is allocated (approximately) one and

Linqing Feng, Jun Ho Song, Jiwon Kim, Soomin Jeong

Quantitative analysis of cell nuclei in microscopic images is an essential yet challenging source of biological and pathological information. The major challenge is accurate detection and segmentation of densely packed nuclei in images acquired under a variety of conditions. Mask R-CNN-based methods have achieved state-of-the-art nucleus segmentation. Howeve

Takashi Furuya

In this paper, we consider the inverse scattering problem to reconstruct the defect in an open periodic waveguide from near field data. Our first aim is to mention that there is a mistake in the factorization method of Lechleiter 2008. By this we can not apply it to solve this inverse problem. Our second aim is to give ways to understand the defect from insi

Ümit Ertem, Özgün Sütemen, Özgür Açık, Aytolun Çatalkaya

M-theory backgrounds in the form of unwarped compactifications with or without fluxes are considered. We construct the bilinear forms of supergravity Killing spinors for different choices of spinor inner products on these backgrounds. The equations satisfied by the bilinear forms and their decompositions into product manifolds are obtained for different inne

Genrich Belitskii, Alberto F. Boix, Dmitry Kerner

Artin approximation and other related approximation results are used in various areas. The traditional formulation of such results is restricted to filtrations by powers of ideals, $\{I^j\}$, and to Noetherian rings. In this paper we extend several approximation results both to rather general filtrations and to $C^r$-rings, for $2\le r\le\infty$. As an auxil

Jonas Miguet, Marina Pasquet, Florence Rouyer, Yuan Fang

Surface bubbles have attracted much interest in the past decades. In this article, we propose to explore the lifetime and thinning dynamics of centimetric surface bubbles. We study the impact of the bubbles size as well as that of the atmospheric humidity through a careful control and systematic variation of the relative humidity in the measuring chamber. We

Hana Čenčariková, Jozef Strečka, Andrej Gendiar

The combination of an exact and Corner Transfer Matrix Renormalization Group (CTMRG) methods is used to study an influence of external electric and magnetic fields on existence of intriguing reentrant magnetic transitions in a coupled spin-electron model on a decorated square lattice. The two-dimensional (2D) decorated square lattice with localized nodal spi

Genrich Belitskii, Dmitry Kerner

The classical lemma of Borel reads: any power series with real coefficients is the Taylor series of a smooth function. Algebraically this means the surjectivity of the completion map at a point, $C^\infty(\Bbb{R}^n) \twoheadrightarrow \Bbb{R}[[\underline{x}]]$. Similarly, Whitney extension theorem implies the surjectivity of the completion at closed subsets

Anisa M H Chorwadwala

In this paper, we deal with an obstacle placement problem inside a disk, that can be formulated as an energy minimization problem with respect to the rotations of the obstacle about its center, with respect to the translations of the obstacle within a planar disk and also with respect to the expansion or contraction of the obstacle inside the disk. We also i

R. Sijs, S. Kooij, D. Bonn

Spraying is a widely used method to produce a liquid sheet that break up into droplets of a certain size distribution. When spraying simple liquids, it is known which experimental parameters determine the droplet size distribution. For many applications however, surfactants are added, producing a hitherto unknown effect on the droplet size distribution. Usin

Tsendsuren Munkhdalai, Alessandro Sordoni, Tong Wang, Adam Trischler

We augment recurrent neural networks with an external memory mechanism that builds upon recent progress in metalearning. We conceptualize this memory as a rapidly adaptable function that we parameterize as a deep neural network. Reading from the neural memory function amounts to pushing an input (the key vector) through the function to produce an output (the

Devra Garfinkle Johnson

This paper is part of the program to classify Kazhdan-Lusztig cells for Weyl groups of type $D_n$. We prove analogous results to those of section 4 of Kazhdan-Lusztig's original paper, this time related to a parabolic subgroup of type $D_4$. We also show how this is used in the definition of the generalized $τ$-invariant.

Claudio Heinrich, Kristoffer H. Hellton, Alex Lenkoski, Thordis L. Thorarinsdottir

Seasonal weather forecasts are crucial for long-term planning in many practical situations and skillful forecasts may have substantial economic and humanitarian implications. Current seasonal forecasting models require statistical postprocessing of the output to correct systematic biases and unrealistic uncertainty assessments. We propose a multivariate post

Victor Brasch, Ewelina Obrzud, Steve Lecomte, Tobias Herr

The capability to store light for extended periods of time enables optical cavities to act as narrow-band optical filters, whose linewidth corresponds to the cavity's inverse energy storage time. Here, we report on nonlinear filtering of an optical pulse train based on temporal dissipative Kerr solitons in microresonators. Our experimental results in com

Yunheung Song, Jongseok Lim, Jaewook Ahn

Extremely fast qubit controls can greatly reduce the calculation time in quantum computation, and potentially resolve the finite-time decoherence issues in many physical systems. Here, we propose and experimentally demonstrate pico-second time-scale controls of atomic clock state qubits, using Berry-phase gates implemented with a pair of chirped laser pulses

Akio Kawauchi

It is shown that any handle-irreducible summand of every stable-ribbon surface-link is a unique ribbon surface-link up to equivalences, so that every stable-ribbon surface-link is a ribbon surface-link. This is a generalization of a previously observed result for a stably trivial surface-link. Two observations are given. One observation is that a connected s

Susanne Pfalzner

Stars form predominantly in groups which display a broad spectrum of masses, sizes, and other properties. Despite this diversity there exist an underlying structure that can constrain cluster formation theories. We show how combining observations with simulations allows to disclose this underlying structure. One example is the mass-radius relation for young

A. S. Everhardt, T. Denneulin, A. Gruenebohm, Y-T. Shao

Proximity to phase transitions (PTs) is frequently responsible for the largest dielectric susceptibilities in ferroelectrics. The impracticality of using temperature as a control parameter to reach those large responses has motivated the design of solid solutions with phase boundaries between different polar phases at temperatures (typically room temperature

Sangyun Oh, Hye-Jin S. Kim, Jongeun Lee, Junmo Kim

We introduce Repetition-Reduction network (RRNet) for resource-constrained depth estimation, offering significantly improved efficiency in terms of computation, memory and energy consumption. The proposed method is based on repetition-reduction (RR) blocks. The RR blocks consist of the set of repeated convolutions and the residual connection layer that take

Samuel Yu, Heon Lee, John Kim

Currently, the visually impaired rely on either a sighted human, guide dog, or white cane to safely navigate. However, the training of guide dogs is extremely expensive, and canes cannot provide essential information regarding the color of traffic lights and direction of crosswalks. In this paper, we propose a deep learning based solution that provides infor

Alex Garivaltis

This note provides a neat and enjoyable expansion and application of the magnificent Ordentlich-Cover theory of "universal portfolios." I generalize Cover's benchmark of the best constant-rebalanced portfolio (or 1-linear trading strategy) in hindsight by considering the best bilinear trading strategy determined in hindsight for the realized sequence of asse

Mengjiao Yang, Been Kim

Interpretability is an important area of research for safe deployment of machine learning systems. One particular type of interpretability method attributes model decisions to input features. Despite active development, quantitative evaluation of feature attribution methods remains difficult due to the lack of ground truth: we do not know which input feature

Hayate Iso, Yui Uehara, Tatsuya Ishigaki, Hiroshi Noji

We propose a data-to-text generation model with two modules, one for tracking and the other for text generation. Our tracking module selects and keeps track of salient information and memorizes which record has been mentioned. Our generation module generates a summary conditioned on the state of tracking module. Our model is considered to simulate the human-

Yeonjong Shin, George Em Karniadakis

In this paper, we study the trainability of rectified linear unit (ReLU) networks. A ReLU neuron is said to be dead if it only outputs a constant for any input. Two death states of neurons are introduced; tentative and permanent death. A network is then said to be trainable if the number of permanently dead neurons is sufficiently small for a learning task.

Qinbin Li, Zeyi Wen, Zhaomin Wu, Sixu Hu

Federated learning has been a hot research topic in enabling the collaborative training of machine learning models among different organizations under the privacy restrictions. As researchers try to support more machine learning models with different privacy-preserving approaches, there is a requirement in developing systems and infrastructures to ease the d

Lan Hu, Wanting Xu, Kun Huang, Laurent Kneip

In an effort to increase the capabilities of SLAM systems and produce object-level representations, the community increasingly investigates the imposition of higher-level priors into the estimation process. One such example is given by employing object detectors to load and register full CAD models. Our work extends this idea to environments with unknown obj

Katsuki Aoki, Shinji Mukohyama

We consider generic derivative corrections to the Einstein gravity and find new classes of theories without ghost around the Minkowski background by means of an extension of the spacetime geometry. We assume the Riemann-Cartan geometry, i.e. a geometry with a non-vanishing torsion, and consider all possible terms in the Lagrangian up to scaling dimension fou

Pawel Grzegrzolka, Jeremy Siegert

In this paper, we generalize Dranishnikov's asymptotic inductive dimension to the setting of coarse proximity spaces. We show that in this more general context, the asymptotic inductive dimension of a coarse proximity space is bigger or equal to the inductive dimension of its boundary, and consequently may be strictly bigger than the covering dimension of th

Tomoya Machide

It is known a method for converting a system of Boolean polynomial equations to a single Boolean polynomial equation with less variables. In this paper, we show a formula for systems of Boolean polynomial equations which is based on the method. The formula has a structure of binary tree, and conforms to De Morgan's duality. Using the formula, we prove a comp

Vishakha Patil, Ganesh Ghalme, Vineet Nair, Y. Narahari

We study an interesting variant of the stochastic multi-armed bandit problem, called the Fair-SMAB problem, where each arm is required to be pulled for at least a given fraction of the total available rounds. We investigate the interplay between learning and fairness in terms of a pre-specified vector denoting the fractions of guaranteed pulls. We define a f

Xue-Min Jiang, Chengfeng Cai, Zhao-Huan Yu, Yu-Pan Zeng

We study a dark matter model with one singlet complex scalar and two Higgs doublets. The scalar potential respects a softly broken global symmetry, which makes the imaginary part of the singlet become a pseudo-Nambu-Goldstone boson acting as a dark matter candidate. The pseudo-Nambu-Goldstone nature of the boson leads to the vanishing of its tree-level scatt

Frederick Tung, Greg Mori

Knowledge distillation is a widely applicable technique for training a student neural network under the guidance of a trained teacher network. For example, in neural network compression, a high-capacity teacher is distilled to train a compact student; in privileged learning, a teacher trained with privileged data is distilled to train a student without acces

Joel Gibson

The product monomial crystal was defined by Kamnitzer, Tingley, Webster, Weekes, and Yacobi for any semisimple simply-laced Lie algebra $\mathfrak{g}$, and depends on a collection of parameters $\mathbf{R}$. We show that a family of truncations of this crystal are Demazure crystals, and give a Demazure-type formula for the character of each truncation, and t

Zhongxu Zhai, Andrew Benson, Yun Wang, Gustavo Yepes

We perform a simulation with Galacticus, a semi-analytical galaxy formation model, to predict the number counts of H$α$ and [OIII] emitting galaxies. With a state-of-the-art N-body simulation, UNIT, we first calibrate Galacticus with the current observation of H$α$ luminosity function. The resulting model coupled with a dust attenuation model, can reproduce

Lucas Tabelini Torres, Thiago M. Paixão, Rodrigo F. Berriel, Alberto F. De Souza

Deep learning has been successfully applied to several problems related to autonomous driving. Often, these solutions rely on large networks that require databases of real image samples of the problem (i.e., real world) for proper training. The acquisition of such real-world data sets is not always possible in the autonomous driving context, and sometimes th

Yujun Zhang, Minjae Kim, Jernej Mravlje, Changhee Sohn

Perovskite rhodates are characterized by intermediate strengths of both electronic correlation as well as spin-orbit coupling (SOC) and usually behave as moderately correlated metals. A recent publication (Phys. Rev. B 95, 245121(2017)) on epitaxial SrRhO$_3$ thin films unexpectedly reported a bad-metallic behavior and suggested the occurrence of antiferroma

Yun Soo Myung, De-Cheng Zou

We investigate the black holes in the new massive conformal gravity which is not invariant under conformal transformations because of the presence of the Einstein-Hilbert term. First, we show that the small Schwarzschild black hole is unstable against the $s$-mode of linearized Ricci tensor by solving the Lichnerowicz-Ricci tensor equation. This instability

Morgan Williamson, Maxim Tsoi, Pin-Wei Huang, Ganping Ju

Magnetotransport properties of granular oxide-segregated CoPtCr films were studied on both macroscopic and microscopic length scales by performing bulk and point-contact magnetoresistance measurements, respectively. Such a perpendicular magnetic medium is used in state-of-the-art hard disc drives and if combined with magnetoresistive phenomena (for read/writ

Su Kong Chong, Kyu Bum Han, Taylor D. Sparks, Vikram V. Deshpande

The paired top and bottom Dirac surface states, each associated with a half-integer quantum Hall (QH) effect, and a resultant integer QH conductance ({\nu}e2/h), are hallmarks of a three-dimensional (3D) topological insulator (TI). In a dual-gated system, chemical potentials of the paired surface states are controlled through separate gates. In this work, we

Chaoran Huang, Thomas Ferreira de Lima, Aashu Jha, Siamak Abbaslou

We experimentally demonstrate an all-optical programmable thresholder on a silicon photonic circuit. By exploiting the nonlinearities in a resonator-enhanced Mach-Zehnder interferometer (MZI), the proposed optical thresholder can discriminate two optical signals with very similar amplitudes. We experimentally achieve a signal contrast enhancement of 40, whic

Patrik V. Nabelek

In this paper we show that all algebro-geometric finite gap solutions to the Korteweg--de Vries equation can be realized as a limit of N-soliton solutions as N diverges to infinity (see remark 1 for the precise meaning of this statement). This is done using the the primitive solution framework initiated by [5,28,31]. One implication of this result is that th

Xiangyu He, Ke Cheng, Qiang Chen, Qinghao Hu

Long-range dependencies modeling, widely used in capturing spatiotemporal correlation, has shown to be effective in CNN dominated computer vision tasks. Yet neither stacks of convolutional operations to enlarge receptive fields nor recent nonlocal modules is computationally efficient. In this paper, we present a generic family of lightweight global descripto

Wei Shen, Yilu Guo, Yan Wang, Kai Zhao

Age estimation from facial images is typically cast as a label distribution learning or regression problem, since aging is a gradual progress. Its main challenge is the facial feature space w.r.t. ages is inhomogeneous, due to the large variation in facial appearance across different persons of the same age and the non-stationary property of aging. In this p

Brian Sutton, Rafatul Faria, Lakshmi A. Ghantasala, Risi Jaiswal

In this paper we present a concrete design for a probabilistic (p-) computer based on a network of p-bits, robust classical entities fluctuating between -1 and +1, with probabilities that are controlled through an input constructed from the outputs of other p-bits. The architecture of this probabilistic computer is similar to a stochastic neural network with