November 2018 arXiv papers — page 48

Guillermo Arreaga-Garcia

We present high-resolution hydrodynamical simulations aimed at following the gravitational collapse of a gas core, in which a turbulent spectrum of velocity is implemented only initially. We determine the maximal value of the ratio of kinetic energy to gravitational energy, denoted here by $\left(\frac{E_{\rm kin} }{E_{\rm grav}}\right)_{\rm max}$, so that t

Matthew Junge, Hanbaek Lyu

Ballistic annihilation is an interacting system in which particles placed throughout the real line move at preassigned velocities and annihilate upon colliding. The longstanding conjecture that in the symmetric three-velocity setting there exists a phase transition for the survival of middle-velocity particles was recently resolved by Haslegrave, Sidoraviciu

A. A. Kotov, D. A. Glazov, A. V. Malyshev, A. V. Vladimirova

Ground-state energies of the one- and two-electron uranium dimers are calculated for internuclear distances in the range D=40--1000 fm and compared with the previous calculations. The generalization of the dual-kinetic-balance approach for axially symmetric systems is employed to solve the two-center Dirac equation without the partial-wave expansion for the

Shuyao Wu, Shuangcheng Li

Monetization of the non-use and nonmarket values of ecosystem services is important especially in the areas of environmental cost-benefit analysis, management and environmental impact assessment. However, the reliability of valuation estimations has been criticized due to the biases that associated with methods like the popular contingent valuation method (C

Amir Shakouri

This paper deals with the impulsive formation control of spacecraft in the presence of constraints on the position vector and time. Determining a set of path constraints can increase the safety and reliability in an impulsive relative motion of spacecraft. Specially, the feasibility problem of the position norm constraints is considered in this paper. Under

Md Mofijul Islam, Amar Debnath, Tahsin Al Sayeed, Jyotirmay Nag Setu

Deep Learning algorithms are often used as black box type learning and they are too complex to understand. The widespread usability of Deep Learning algorithms to solve various machine learning problems demands deep and transparent understanding of the internal representation as well as decision making. Moreover, the learning models, trained on sequential da

Katelyn Plaisier Leisman, Gino Biondini, Gregor Kovacic

Boundary value problems for the nonlinear Schrodinger equation on the half line in laboratory coordinates are considered. A class of boundary conditions that lead to linearizable problems is identified by introducing appropriate extensions to initial-value problems on the infinite line, either explicitly or by constructing a suitable Backlund transformation.

Mohammad Ali Javidian, Linyuan Lu, Marco Valtorta, Zhiyu Wang

We propose a directed acyclic hypergraph framework for a probabilistic graphical model that we call Bayesian hypergraphs. The space of directed acyclic hypergraphs is much larger than the space of chain graphs. Hence Bayesian hypergraphs can model much finer factorizations than Bayesian networks or LWF chain graphs and provide simpler and more computationall

Milagros Izquierdo, Sebastián Reyes-Carocca

Belolipetsky and Jones classified those compact Riemann surfaces of genus $g$ admitting a large group of automorphisms of order $\lambda (g-1)$, for each $\lambda >6,$ under the assumption that $g-1$ is a prime number. In this article we study the remaining large cases; namely, we classify Riemann surfaces admitting $5(g-1)$ and $6(g-1)$ automorphisms, with

Johanna M. Vos, Beth A. Biller, Mariangela Bonavita, Simon Eriksson

We report the results of a $J$-band survey for photometric variability in a sample of young, low-gravity objects using the New Technology Telescope (NTT) and the United Kingdom InfraRed Telescope (UKIRT). Surface gravity is a key parameter in the atmospheric properties of brown dwarfs and this is the first large survey that aims to test the gravity dependenc

Jordy Davelaar, Thomas Bronzwaer, Daniel Kok, Ziri Younsi

We present a full 360 degree (i.e., 4$\pi$ steradian) general-relativistic ray-tracing and radiative transfer calculations of accreting supermassive black holes. We perform state-of-the-art three-dimensional general relativistic magnetohydrodynamical simulations using the BHAC code, subsequently post-processing this data with the radiative transfer code RAPT

Hugo Tschirhart, Ernest Teng Siang Ong, Pinaki Sengupta, Thomas L. Schmidt

We investigate an antiferromagnetic spin-$1$ Heisenberg chain in the presence of Dyzaloshinskii-Moriya interactions (DMI) and an external magnetic field. We study the resulting spin chain using a combination of numerical and analytical techniques. Using DMRG simulations to determine the spectral gap and the entanglement spectrum, we map out the phase diagram

Stephen Bonner, John Brennan, Ibad Kureshi, Georgios Theodoropoulos

Graphs are a commonly used construct for representing relationships between elements in complex high dimensional datasets. Many real-world phenomenon are dynamic in nature, meaning that any graph used to represent them is inherently temporal. However, many of the machine learning models designed to capture knowledge about the structure of these graphs ignore

Nektarios Aslanidis, Aurelio F. Bariviera, Oscar Martinez-Ibañez

This letter explores the behavior of conditional correlations among main cryptocurrencies, stock and bond indices, and gold, using a generalized DCC class model. From a portfolio management point of view, asset correlation is a key metric in order to construct efficient portfolios. We find that: (i) correlations among cryptocurrencies are positive, albeit va

L. Herrera, A. Di Prisco, J. Ospino

The recently proposed definition of complexity for static and spherically symmetric self--gravitating systems [1], is extended to the fully dynamic situation. In this latter case we have to consider not only the complexity factor of the structure of the fluid distribution, but also the condition of minimal complexity of the pattern of evolution. As we shall

Giuseppe Mazzuoccolo, Jean Paul Zerafa

In 1994, it was conjectured by Fan and Raspaud that every simple bridgeless cubic graph has three perfect matchings whose intersection is empty. In this paper we answer a question recently proposed by Mkrtchyan and Vardanyan, by giving an equivalent formulation of the Fan-Raspaud Conjecture. We also study a possibly weaker conjecture originally proposed by t

Zhiyu Yao, Yunbo Wang, Mingsheng Long, Jianmin Wang

In classic video action recognition, labels may not contain enough information about the diverse video appearance and dynamics, thus, existing models that are trained under the standard supervised learning paradigm may extract less generalizable features. We evaluate these models under a cross-dataset experiment setting, as the above label bias problem in vi

Mehmet Saygin Seyfioglu, Baris Erol, Sevgi Zubeyde Gurbuz, Moeness G. Amin

Recently, deep neural networks (DNNs) have been the subject of intense research for the classification of radio frequency (RF) signals, such as synthetic aperture radar (SAR) imagery or micro-Doppler signatures. However, a fundamental challenge is the typically small amount of data available due to the high costs and resources required for measurements. Smal

Kostantinos Papadamou, Savvas Zannettou, Bogdan Chifor, Sorin Teican

Current authentication methods on the Web have serious weaknesses. First, services heavily rely on the traditional password paradigm, which diminishes the end-users' security and usability. Second, the lack of attribute-based authentication does not allow anonymity-preserving access to services. Third, users have multiple online accounts that often reflect d

Ross Anderson, Joey Huchette, Christian Tjandraatmadja, Juan Pablo Vielma

We present an ideal mixed-integer programming (MIP) formulation for a rectified linear unit (ReLU) appearing in a trained neural network. Our formulation requires a single binary variable and no additional continuous variables beyond the input and output variables of the ReLU. We contrast it with an ideal "extended" formulation with a linear number of additi

Marcus Carlsson

We consider "spectral" matrix-functions for Hermitian matrices, where the novelty is that the function applied to the spectrum is allowed to be a vector-field rather than a scalar function (a.k.a isotropic matrix functions). We prove first order approximation formulas, generalizing the classical Daleskii-Krein theorem, as well as Lipschitz estimates.

Li Wenliang, Danica J. Sutherland, Heiko Strathmann, Arthur Gretton

The kernel exponential family is a rich class of distributions, which can be fit efficiently and with statistical guarantees by score matching. Being required to choose a priori a simple kernel such as the Gaussian, however, limits its practical applicability. We provide a scheme for learning a kernel parameterized by a deep network, which can find complex l

Konstantinos Dareiotis, Benjamin Gess

We prove the existence and uniqueness of entropy solutions for nonlinear diffusion equations with nonlinear conservative gradient noise. As particular applications our results include stochastic porous media equations, as well as the one-dimensional stochastic mean curvature flow in graph form.

Mirsad Cosovic

We present a detailed study on application of factor graphs and the belief propagation (BP) algorithm to the power system state estimation (SE) problem. We start from the BP solution for the linear DC model, for which we provide a detailed convergence analysis. Using BP-based DC model we propose a fast real-time state estimator for the power system SE. The p

Max Klimm, Philipp Warode

We show that computing an equilibrium in atomic splittable congestion games with player-specific affine cost functions $l_{e,i}(x) = a_{e,i} x + b_{e,i}$ is $\mathsf{PPAD}$-complete. To prove that the problem is contained in $\mathsf{PPAD}$, we develop a homotopy method that traces an equilibrium for varying flow demands of the players. A key technique for t

Jörn Bleck-Neuhaus

Starting from the observation that the simplest form of forced mechanical oscillation serves as a standard model for analyzing a broad variety of resonance processes in many fields of physics and engineering, the remarkably slow development leading to this insight is reviewed. Forced oscillations and mechanical resonance were already described by Galileo ear

Esteban Reyes, Cristopher Gómez, Esteban Norambuena, Javier Ruiz-del-Solar

The main goal of the paper is to provide Pepper with a near real-time object recognition system based on deep neural networks. The proposed system is based on YOLO (You Only Look Once), a deep neural network that is able to detect and recognize objects robustly and at a high speed. In addition, considering that YOLO cannot be run in the Pepper's internal com

Yating Liu, Gilles Pagès

We study the convergence rate of the optimal quantization for a probability measure sequence $(\mu_{n})_{n\in\mathbb{N}^{*}}$ on $\mathbb{R}^{d}$ converging in the Wasserstein distance in two aspects: the first one is the convergence rate of optimal quantizer $x^{(n)}\in(\mathbb{R}^{d})^{K}$ of $\mu_{n}$ at level $K$; the other one is the convergence rate of

Milan Batista

In this paper, we revised a post-buckling of an elastic circular plate subject to uniform pressure on its edge. The governing von Karman equations are solved by power series method and numerical colocation method. An alternative method for calculation of coefficients of the series solution is described. It is shown that the power series solution is useful on

Andrea Bondesan, Laurent Boudin, Marc Briant, Bérénice Grec

We consider the Boltzmann operator for mixtures with cutoff Maxwellian, hard potentials, or hard spheres collision kernels. In a perturbative regime around the global Maxwellian equilibrium, the linearized Boltzmann multi-species operator $\mathbf{L}$ is known to possess an explicit spectral gap $\lambda_{\mathbf{L}}$, in the global equilibrium weighted $L^2

J Ovalle, R Casadio, R da Rocha, A Sotomayor

We investigate how a spherically symmetric scalar field can modify the Schwarzschild vacuum solution when there is no exchange of energy-momentum between the scalar field and the central source of the Schwarzschild metric. This system is described by means of the gravitational decoupling by Minimal Geometric Deformation (MGD-decoupling), which allows us to s

Chandrachur Chakraborty, Parthasarathi Majumdar

The exact precession frequency of a freely-precessing test gyroscope is derived for a $2+1$ dimensional rotating acoustic black hole analogue spacetime, without making the somewhat unrealistic assumption that the gyroscope is static. We show that, as a consequence, the gyroscope crosses the acoustic ergosphere of the black hole with a finite precession frequ

Billy Edwards, Malena Rice, Tiziano Zingales, Marcell Tessenyi

The Twinkle space telescope has been designed for the characterisation of exoplanets and Solar System objects. Operating in a low Earth, Sun-synchronous orbit, Twinkle is equipped with a 45 cm telescope and visible (0.4 - 1um) and infrared (1.3 - 4.5um) spectrometers which can be operated simultaneously. Twinkle is a general observatory which will provide on

Florian Schanzenbacher, Nadir Farhi, Fabien Leurent, Gérard Gabriel

This paper is an extended abstract on a traffic model for the train dynamics on a metro line with a junction. The dynamic model includes control laws on the dwell and on the run time, taking into account the passenger travel demand. Our model extends two existing traffic models: 1. a model that describes the train dynamics on a metro line with a junction but

René Oswald, Michael Hansen, Eugen Wiens, Alexander Yu. Nevsky

Properties of persistent spectral holes (SHs) relevant for frequency metrology have been investigated in the system $Eu^{3+}:Y_{2}SiO_{5}$ (0.5%) at crystallographic site 1 and a temperature of $1.2$ Kelvin. Hole linewidths as small as $0.6~kHz$ have been reliably achieved. The theoretically predicted $T^4$-dependence of the frequency shift with temperature

Chaorong Li, Huang Wei, Huafu Chen

In this paper, we proposed an effective face feature extraction method by Learning Gabor Log-Euclidean Gaussian with Whitening Principal Component Analysis (WPCA), called LGLG-WPCA. The proposed method learns face features from the embedded multivariate Gaussian in Gabor wavelet domain; it has the robust performance to adverse conditions such as varying pose

Yaliang Gui, Mario Miscuglio, Zhizhen Ma, Mohammad T. Tahersima

The class of transparent conductive oxides includes the material indium tin oxide (ITO) and has become a widely used material of modern every-day life such as in touch screens of smart phones and watches, but also used as an optically transparent low electrically-resistive contract in the photovoltaics industry. More recently ITO has shown epsilon-near-zero

Jaksa Vucicevic, Jure Kokalj, Rok Zitko, Nils Wentzell

Recent experiments on cold atoms in optical lattices allow for a quantitative comparison of the measurements to the conductivity calculations in the square lattice Hubbard model. However, the available calculations do not give consistent results and the question of the exact solution for the conductivity in the Hubbard model remained open. In this letter we

Pravendra Singh, Manikandan R, Neeraj Matiyali, Vinay P. Namboodiri

We propose a framework for compressing state-of-the-art Single Shot MultiBox Detector (SSD). The framework addresses compression in the following stages: Sparsity Induction, Filter Selection, and Filter Pruning. In the Sparsity Induction stage, the object detector model is sparsified via an improved global threshold. In Filter Selection & Pruning stage, we s

Mihály András Pocsai, Imre Ferenc Barna, Károly Tőkési

The photoionisation of rubidium in strong infra-red laser fields based on ab initio calculations was investigated. The bound and the continuum states are described with Slater orbitals and Coulomb wave packets, respectively. The bound state spectra were calculated with the variational method and we found it reproduced the experimental data within a few perce

Hai-Liang Wu, Zhi-Wei Sun

The well-known Lagrange's four-square theorem states that any integer $n\in\mathbb{N}=\{0,1,2,...\}$ can be written as the sum of four squares. Recently, Z.-W. Sun investigated the representations of $n$ as $x^2+y^2+z^2+w^2$ with certain linear restrictions involving the integer variables $x,y,z,w$. In this paper, via the theory of quadratic forms, we furthe

Elizabeth Meckes, Kathryn Stewart

We consider the empirical eigenvalue distribution of an $m\times m$ principle submatrix of an $n\times n$ random unitary matrix distributed according to Haar measure. Earlier work of Petz and R\'effy identified the limiting spectral measure if $\frac{m}{n}\to\alpha$, as $n\to\infty$; under suitable scaling, the family $\{\mu_\alpha\}_{\alpha\in(0,1)}$ of lim

Jian Li, Diego F. Torres, Francesco Coti Zelati, Alessandro Papitto

Based on a theoretical selection of pulsars as candidates for detection at X-ray energies, we present an analysis of archival X-ray observations done with Chandra and XMM-Newton of PSR J1747-2958 (the pulsar in the "Mouse" nebula), PSR J2021+3651 (the pulsar in the "Dragonfly" nebula), and PSR J1826-1256. X-ray pulsations from PSR J1747-2958 and PSR J1826-12

Bart Jacobs, Aleks Kissinger, Fabio Zanasi

Extracting causal relationships from observed correlations is a growing area in probabilistic reasoning, originating with the seminal work of Pearl and others from the early 1990s. This paper develops a new, categorically oriented view based on a clear distinction between syntax (string diagrams) and semantics (stochastic matrices), connected via interpretat

Tom Ryder, Andrew Golighty, A. Stephen McGough, Dennis Prangle

State-space models (SSMs) provide a flexible framework for modelling time-series data. Consequently, SSMs are ubiquitously applied in areas such as engineering, econometrics and epidemiology. In this paper we provide a fast approach for approximate Bayesian inference in SSMs using the tools of deep learning and variational inference.

Gabriela Jeronimo, Mercedes Pérez Millán, Pablo Solernó

Under mass-action kinetics, biochemical reaction networks give rise to polynomial autonomous dynamical systems whose parameters are often difficult to estimate. We deal in this paper with the problem of identifying the kinetic parameters of a class of biochemical networks which are abundant, such as multisite phosphorylation systems and phosphorylation casca

Stijn Cambie

Fix $d \ge 3$. We show the existence of a constant $c>0$ such that any graph of diameter at most $d$ has average distance at most $d-c \frac{d^{3/2}}{\sqrt n}$, where $n$ is the number of vertices. Moreover, we exhibit graphs certifying sharpness of this bound up to the choice of $c$. This constitutes an asymptotic solution to a longstanding open problem of

A. Antognini, Y. Bao, I. Belosevic, A. Eggenberger

A novel device to compress the phase space of a muon beam by a factor of $10^{10}$ with a $10^{-3}$ efficiency is under development. A surface muon beam is stopped in a helium gas target consisting of several compression stages, wherein strong electric and magnetic fields are applied. The spatial extent of the stopped muon swarm is decreased by means of thes

Benjamin Danglot, Oscar Luis Vera-Pérez, Benoit Baudry, Martin Monperrus

In the literature, there is a rather clear segregation between manually written tests by developers and automatically generated ones. In this paper, we explore a third solution: to automatically improve existing test cases written by developers. We present the concept, design, and implementation of a system called \dspot, that takes developer-written test ca

Karthik Adimurthi, Sun-Sig Byun, Wontae Kim

In this paper, we study the existence of distributional solutions solving \cref{main-3} on a bounded domain $\Omega$ satisfying a uniform capacity density condition where the nonlinear structure $\mathcal{A}(x,t,\nabla u)$ is modelled after the standard parabolic $p$-Laplace operator. In this regard, we need to prove a priori estimates for the gradient of th

Amy Winebarger, Mark Weber, Christian Bethge, Cooper Downs

Slitless spectrometers can provide simultaneous imaging and spectral data over an extended field of view, thereby allowing rapid data acquisition for extended sources. In some instances, when the object is greatly extended or the spectral dispersion is too small, there may be locations in the focal plane where contributions from emission lines at different w

Marc Bosch, Gordon A. Christie, Christopher M. Gifford

Semantic segmentation is a powerful method to facilitate visual scene understanding. Each pixel is assigned a label according to a pre-defined list of object classes and semantic entities. This becomes very useful as a means to summarize large scale overhead imagery. In this paper we present our work on semantic segmentation with applications to overhead ima

Valeriano Aiello

In [Jo14] and [Jo18] Vaughan Jones introduced a construction which yields oriented knots and links from elements of the oriented Thompson group $\vec{F}$. In this paper we prove, by analogy with Alexander's classical theorem establishing that every knot or link can be represented as a closed braid, that given an oriented knot/link $\vec{L}$, there exists an

Pravendra Singh, Vinay Sameer Raja Kadi, Nikhil Verma, Vinay P. Namboodiri

Convolutional neural networks (CNN) have achieved impressive performance on the wide variety of tasks (classification, detection, etc.) across multiple domains at the cost of high computational and memory requirements. Thus, leveraging CNNs for real-time applications necessitates model compression approaches that not only reduce the total number of parameter

Nils Asmussen, Antoine Gérardin, Andreas Nyffeler, Harvey B. Meyer

Hadronic light-by-light scattering in the anomalous magnetic moment of the muon $a_\mu$ is one of two hadronic effects limiting the precision of the Standard Model prediction for this precision observable, and hence the new-physics discovery potential of direct experimental determinations of $a_\mu$. In this contribution, we report on recent progress in the

Di-Chang Chen, Ji-Lin Zhou, Ji-Wei Xie, Ming Yang

Planetary systems can survive the stellar evolution, as evidenced by the atmospheric metal pollution and dusty disks of single white dwarfs. Recent observations show that 1 to 4 percent of single white dwarfs are accompanied by dusty disks, while the occurrence rate of metal pollution is about 25 to 50 percent . The dusty disks and metal pollution have been

Yonah Biers-Ariel

We find finite-state recurrences to enumerate the words on the alphabet $[n]^r$ which avoid the patterns 123 and $1k(k-1)\dots2$, and, separately, the words which avoid the patterns 1234 and $1k(k-1)\dots2$.

Michel Pain, Olivier Zindy

In this paper, we prove absence of temperature chaos for the two-dimensional discrete Gaussian free field using the convergence of the full extremal process, which has been obtained recently by Biskup and Louidor. This means that the overlap of two points chosen under Gibbs measures at different temperatures has a nontrivial distribution. Whereas this distri

Florian Staub

We have reached a new era of particle physics in which the properties of the Higgs boson, in particular its mass, turned into precision observables. Therefore, it is necessary to have accurate predictions of these properties in models for new physics. I give an overview of available tools for supersymmetric and non-supersymmetric models which are publically

Daniel Kincses

Different regions on the QCD phase diagram can be investigated by varying the collision energy and the centrality in heavy-ion collisions. In our latest measurements at the PHENIX experiment at RHIC, we utilize L\'evy-type sources to describe the measured HBT correlation functions. In this paper we report the current status of the analysis of the centrality

Bastien Fernandez

We study the chaos of travelling waves (TW) in unidirectional chains of bistable maps. Previous numerical results suggested that this property is selective, {\sl viz.}\ given the parameters, there is at most a single (non-trivial) velocity for which the corresponding set of wave profiles has positive topological entropy. However, mathematical proofs have rem

Andrei N. Soklakov

Disagreement is an essential element of science and life in general. The language of probabilities and statistics is often used to describe disagreements quantitatively. In practice, however, we want much more than that. We want disagreements to be resolved. This leaves us with a substantial knowledge gap which is often perceived as a lack of practical intui

LHCb collaboration, R. Aaij, C. Abellán Beteta, B. Adeva

A search for $CP$ violation in the Cabibbo-suppressed $D^0 \rightarrow K^+ K^- \pi^+ \pi^-$ decay mode is performed using an amplitude analysis. The measurement uses a sample of $pp$ collisions recorded by the LHCb experiment during 2011 and 2012, corresponding to an integrated luminosity of 3.0 fb$^{-1}$. The $D^0$ mesons are reconstructed from semileptonic

Itay Hen

In classical computing, analog approaches have sometimes appeared to be more powerful than they really are. This occurs when resources, particularly precision, are not appropriately taken into account. While the same should also hold for analog quantum computing, precision issues are often neglected from the analysis. In this work we present a classical anal

Anishi Mehta

There has been a lot of discussion on Net Neutrality and policies that various network service providers and distributors adopt, at times leading to greater network congestion and thus more debates. The aim of this project is to use congestion traffic data to look at correlations between different service providers and message requests for different AS (Auto

Ganesh C. Paul, SK Firoz Islam, Arijit Saha

We theoretically investigate the indirect signatures of the tilted anisotropic Dirac cones on Ruderman-Kittel-Kasuya-Yosida (RKKY) exchange interaction in a two dimensional polymorph of boron atoms. Unlike the case of isotropic non-tilted Dirac material-graphene, here we observe that the tilting of the Dirac cones exhibits a significant impact on the RKKY ex

Florian Staub

There are nowadays strong experimental constraints on supersymmetric theories from the Higgs measurements as well as from the null results in Sparticle searches. However, even the parameter spaces which are in agreement with experimental data can be further constrained by using theoretical considerations. Here, we discuss for the MSSM and NMSSM the impact of

Eugenio Valdano, Alex Arenas

With the advent of the big data era, generative models of complex networks are becoming elusive from direct computational simulation. We present an exact, linear-algebraic reduction scheme of generative models of networks. By exploiting the bilinear structure of the matrix representation of the generative model, we separate its null eigenspace, and reduce th

Elena Agliari, Francesco Alemanno, Adriano Barra, Alberto Fachechi

In this work we consider the {\em analog bipartite spin-glass} (or {\em real-valued restricted Boltzmann machine} in a neural network jargon), whose variables (those quenched as well as those dynamical) share standard Gaussian distributions. First, via Guerra's interpolation technique, we express its quenched free energy in terms of the natural order paramet

Abhisek Ghosal, Tanmay Mandal, Amlan K. Roy

We present a purely numerical approach in Cartesian grid, for efficient computation of Hartree-Fock (HF) exchange contribution in the HF and density functional theory models. This takes inspiration from a recently developed algorithm [Liu \emph{et al.}, J.~Chem.~Theor.~Comput.~ \textbf{13}, 2571 (2017)]. A key component is the accurate evaluation of electros

Aryan Mehboudi, Junghoon Yeom

Non-linear effects of the Navier-Stokes equations disappear under the Stokes regime of Newtonian fluid flows disallowing the fluid flow rectification. Here we show mathematically and experimentally that passive flow rectification of Newtonian fluids is obtainable under the Stokes regime of both compressible and incompressible flows by introducing nonlinearit

Giorgia Ramponi, Pavlos Protopapas, Marco Brambilla, Ryan Janssen

In this paper we propose a data augmentation method for time series with irregular sampling, Time-Conditional Generative Adversarial Network (T-CGAN). Our approach is based on Conditional Generative Adversarial Networks (CGAN), where the generative step is implemented by a deconvolutional NN and the discriminative step by a convolutional NN. Both the generat

Rafael Hernandez, Juan Miguel Nieto, Roberto Ruiz

We study minimal area world sheets ending on two concentric circumferences on the boundary of Euclidean $AdS_{3}$ with mixed R-R and NS-NS three-form fluxes. We solve the problem by reducing the system to a one-dimensional integrable model. We find that the NS-NS flux term either brings the surface near to the boundary or separates the circumferences. In the

Henk Bruin, Dalia Terhesiu, Mike Todd

We obtain limit theorems (Stable Laws and Central Limit Theorems, both Gaussian and non-Gaussian) and thermodynamic properties for a class of non-uniformly hyperbolic flows: almost Anosov flows, constructed here. The proofs of the limit theorems for these flows are applications of corresponding theorems in an abstract functional analytic framework, which may

Michele Lucente, Asmaa Abada, Giorgio Arcadi, Valerie Domcke

We provide the first systematic study of the viable parameter space for leptogenesis in the type-I seesaw model with three right-handed neutrinos whose Majorana masses lie below the electroweak scale. We highlight the very rich phenomenology of this scenario and discuss several mechanisms that can help to enhance the baryon asymmetry of the Universe. This al

V. Gol'dshtein, V. Pchelintsev, A. Ukhlov

We study spectral stability estimates of the Dirichlet eigenvalues of the Laplacian in non-convex domains $\Omega\subset\mathbb R^2$. With the help of these estimates we obtain asymptotically sharp inequalities of ratios of eigenvalues in the frameworks of the Payne-P\'olya-Weinberger inequalities. These estimates are equivalent to spectral gap estimates of

Linda Anticoli, Masoud Gharahi Ghahi

The notion of entanglement is the most well-known nonclassical correlation in quantum mechanics and a fundamental resource in quantum information and computation. This correlation, which is displayed by certain classes of quantum states, is of utmost importance when dealing with protocols such as quantum teleportation, cryptography, and quantum key distribut

Mariana Moreira, Jorge Vieira, Patric Muggli

We use particle-in-cell (PIC) simulations to study the effects of variations of the incoming 400 GeV proton bunch parameters on the amplitude and phase of the wakefields resulting from a seeded self-modulation (SSM) process. We find that these effects are largest during the growth of the SSM, i.e. over the first five to six meters of plasma with an electron

Vishal Sharma, Yongho Ko, Jiyoon Kim, Ilsun You

Security is a primary concern for the networks aiming at the utilization of Cellular (C) services for connecting Vehicles to Everything (V2X). At present, C-V2X is observing a paradigm shift from Long Term Evolution (LTE) - Evolved Universal Terrestrial Radio Access Network (E-UTRAN) to Fifth Generation (5G) based functional architecture. However, security a

Jamie Farnes, Ben Mort, Fred Dulwich, Stef Salvini

The Square Kilometre Array (SKA) will be both the largest radio telescope ever constructed and the largest Big Data project in the known Universe. The first phase of the project will generate on the order of 5 zettabytes of data per year. A critical task for the SKA will be its ability to process data for science, which will need to be conducted by science p

Enrique N. Miranda, G. Mora Barzaga

The question here is whether the Debye model is suited to evaluate the specific heat of nanocrystals. For this, the simplest possible nanocrystal is considered: a basic cubic structure made of atoms that interact through a harmonic potential. This simple model can be solved exactly. This allows the dispersion relation of the mechanical waves to be determined

Robyn Worsley, Lorenzo Pimpolari, Daryl McManus, Ning Ge

A well-defined insulating layer is of primary importance in the fabrication of passive (e.g. capacitors) and active (e.g. transistors) components in integrated circuits. One of the most widely known 2-Dimensional (2D) dielectric materials is hexagonal boron nitride (hBN). Solution-based techniques are cost-effective and allow simple methods to be used for de

Tomislav Petković, David Puljiz, Ivan Marković, Björn Hein

With the substantial growth of logistics businesses the need for larger warehouses and their automation arises, thus using robots as assistants to human workers is becoming a priority. In order to operate efficiently and safely, robot assistants or the supervising system should recognize human intentions in real-time. Theory of mind (ToM) is an intuitive hum

Manoj Choudhuri, C. R. E. Raja

A connected Lie group admitting an expansive automorphism is known to be nilpotent, but all nilpotent Lie groups do not admit expansive automorphism. In this article, we find sufficient conditions for a class of nilpotent Lie groups to admit expansive automorphism.

Jan Becker, Takahiro Deguchi, Alexander Jügler, Ronny Förster

Lenses are designed to fulfill Fermats principle such that all light interferes constructively in its focus, guaranteeing its maximum concentration. It can be shown that imaging via an unmodified full pupil yields the maximum transfer strength for all spatial frequencies transferable by the system. Seemingly also the signal-to-noise ratio (SNR) is optimal. T

Andreas Knauf

Asymptotic velocity is defined as the Ces\`aro limit of velocity. As such, its existence has been proven for bounded interaction potentials. This is known to be wrong in celestial mechanics with four or more bodies. Here we show for a class of pair potentials including the homogeneous ones of degree -a for 0<a<2, that asymptotic velocities exist for up to fo

Sergio Caracciolo, Andrea Di Gioacchino, Enrico M. Malatesta, Carlo Vanoni

The traveling-salesman problem is one of the most studied combinatorial optimization problems, because of the simplicity in its statement and the difficulty in its solution. We study the traveling salesman problem when the positions of the cities are chosen at random in the unit interval and the cost associated to the travel between two cities is their dista

Yong-Lu Li, Siyuan Zhou, Xijie Huang, Liang Xu

Human-Object Interaction (HOI) Detection is an important problem to understand how humans interact with objects. In this paper, we explore Interactiveness Knowledge which indicates whether human and object interact with each other or not. We found that interactiveness knowledge can be learned across HOI datasets, regardless of HOI category settings. Our core

Yu-Hao Shen, Wen-Yi Tong, He Hu, Chun-Gang Duan

Twistronics rooted in the twist operation towards bilayer van der Waals crystals is of both theoretical and technological importance. The realize of the correlated electronic behaviors under this operation encourages enormous effort to the research on magic-angle systems which possess sensitive response to the external field. Here, a giant dielectric differe

Ali K. Uncu

We focus on writing closed forms of generating functions for the number of partitions with gap conditions as double sums starting from a combinatorial construction. Some examples of the sets of partitions with gap conditions to be discussed here are the set of Rogers--Ramanujan, G\"ollnitz--Gordon, and little G\"ollnitz partitions. This work also includes fi

Esteban Roulet

I describe some of the results on ultrahigh-energy cosmic rays that have been obtained with the Pierre Auger Observatory. These include measurements of the spectrum, composition and anisotropies. Possible astrophysical scenarios that account for these results are discussed.

Mahmoud Sadek, Hussein Aluie

We show that the spectrum of a flow field can be extracted within a local region by straightforward filtering in physical space. We find that for a flow with a certain level of regularity, the filtering kernel must have a sufficient number of vanishing moments in order for the "filtering spectrum" to be meaningful. Our derivation follows a similar analysis b

O Budrigă, E d'Humières, L E Ionel, M Martiş

We propose new nanotargets as nano-layered flat-top cone targets to be used for future laser-ion acceleration experiments at ELI-NP. We study their behaviour at the interaction with an ultra-high intensity laser pulse by performing Particle-In-Cell simulations. We analyze spatio-temporal the electromagnetic field based on the finite-difference time-domain me

Shaohua Li, Kaiping Xue, Chenkai Ding, Xindi Gao

Machine learning as a service has been widely deployed to utilize deep neural network models to provide prediction services. However, this raises privacy concerns since clients need to send sensitive information to servers. In this paper, we focus on the scenario where clients want to classify private images with a convolutional neural network model hosted i

Pierre Heidmann

We build the first family of smooth bubbling microstate geometries that are asymptotic to the near-horizon region of extremal five-dimensional Kerr black holes (NHEK). These black holes arise as extremal non-supersymmetric highly-rotating D1-D5-P solutions in type IIB string theory on T$^4\times$S$^1$. Our solutions are asymptotically NHEK in the UV and end

Johannes Bock

In the past decade many researchers have proposed new optimal portfolio selection strategies to show that sophisticated diversification can outperform the na\"ive 1/N strategy in out-of-sample benchmarks. Providing an updated review of these models since DeMiguel et al. (2009b), I test sixteen strategies across six empirical datasets to see if indeed progres

Taro Fujisawa, Chikara Nakayama

We prove that a projective vertical exact log smooth morphism of fs log analytic spaces with a base of log rank one yields polarized log Hodge structures in the canonical way.

Pablo M. Piaggi, Michele Parrinello

We present a method for performing multithermal-multibaric molecular dynamics simulations that sample entire regions of the temperature-pressure (TP) phase diagram. The method uses a variational principle [Valsson and Parrinello, Phys. Rev. Lett. 113, 090601 (2014)] in order to construct a bias that leads to a uniform sampling in energy and volume. The inter

Oren Solomon, Regev Cohen, Yi Zhang, Yi Yang

Contrast enhanced ultrasound is a radiation-free imaging modality which uses encapsulated gas microbubbles for improved visualization of the vascular bed deep within the tissue. It has recently been used to enable imaging with unprecedented subwavelength spatial resolution by relying on super-resolution techniques. A typical preprocessing step in super-resol

Aloys Krieg, Joana Rodriguez, Annalena Wernz

Let $\mathcal{\scriptstyle{O}}_K$ be the ring of integers of an imaginary quadratic number field $K$. In this paper we give a new description of the maximal discrete extension of the group $SL_2(\mathcal{\scriptstyle{O}}_K)$ inside $SL_2(\mathbb{C})$, which uses generalized Atkin-Lehner involutions. Moreover we find a natural characterization of this group i