February 2019 arXiv papers — page 102

Ujjal Debnath, Kazuharu Bamba

We explore non-canonical scalar field model in the background of non-flat $D$-dimensional fractal Universe with cosmological constant $Λ$ on the condition that the matter and scalar field are separately conserved. The potential $V$, scalar field $ϕ$, function $f$, densities, Hubble parameter and deceleration parameter can be expressed in terms of the redshif

Mikel Artetxe, Gorka Labaka, Eneko Agirre

While machine translation has traditionally relied on large amounts of parallel corpora, a recent research line has managed to train both Neural Machine Translation (NMT) and Statistical Machine Translation (SMT) systems using monolingual corpora only. In this paper, we identify and address several deficiencies of existing unsupervised SMT approaches by expl

Thomas Gutsche, Valery E. Lyubovitskij, Ivan Schmidt, Andrey Yu. Trifonov

We derive a holographic soft-wall approach in five dimensional AdS-Schwarzschild space for the description of mesons at finite temperature. In this first application we consider the small temperature limit and derive analytical expression for the mass spectrum of mesons with adjustable quantum numbers $n$ (radial number), $L$ (angular orbital momentum) and $

Olivier Martin

We study orbits for rational equivalence of zero-cycles on very general abelian varieties by adapting a method of Voisin to powers of abelian varieties. We deduce that, for $k$ at least $3$, a very general abelian variety of dimension at least $2k-2$ has covering gonality greater than $k$. This settles a conjecture of Voisin. We also discuss how upper bounds

Gaurav Duggal, Shelly Vishwakarma, Kumar Vijay Mishra, Shobha Sundar Ram

We present an ultra-short range IEEE 802.11ad-based automotive joint radar-communications (JRC) framework, wherein we improve the radar's Doppler resilience by incorporating Prouhet-Thue-Morse sequences in the preamble. The proposed processing reveals detailed micro-features of common automotive objects verified through extended scattering center models

Beatrice Pozzetti, Andrés Sambarino, Anna Wienhard

In this paper we investigate the Hausdorff dimension of limit sets of Anosov representations. In this context we revisit and extend the framework of hyperconvex representations and establish a convergence property for them, analogue to a differentiability property. As an application of this convergence, we prove that the Hausdorff dimension of the limit set

Joontae Kim

We prove that a real Lagrangian submanifold in a closed symplectic manifold is unique up to cobordism. We then discuss the classification of real Lagrangians in $\mathbb{C} P^2$ and $S^2\times S^2$. In particular, we show that a real Lagrangian in $\mathbb{C} P^2$ is unique up to Hamiltonian isotopy and that a real Lagrangian in $S^2\times S^2$ is either Ham

Corina Ciobotaru, Vladimir Finkelshtein, Cagri Sert

We investigate analogues of some of the classical results in homogeneous dynamics in non-linear setting. Let $G$ be a closed subgroup of the group of automorphisms of a biregular tree and $Γ<G$ a discrete subgroup. For a large class of groups $G$ we give a classification of probability measures on $G/Γ$ invariant under horospherical subgroups. When $Γ$ is a

Thomas Haubner, Alexander Schmidt, Walter Kellermann

In this paper, we address the task of active acoustic source tracking as part of robotic path planning. It denotes the planning of sequences of robotic movements to enhance tracking results of acoustic sources, e.g., talking humans, by fusing observations from multiple positions. Essentially, two strategies are possible: short-term planning, which results in

Hugo Pfister, Marta Volonteri, Yohan Dubois, Massimo Dotti

The dynamics of black hole seeds in high redshift galaxies is key to understand their ability to grow via accretion and to pair in close binaries during galactic mergers. To properly follow the dynamics of black holes we develop a physically motivated model to capture unresolved dynamical friction from stars, dark matter and gas. We first validate the model

Evan Baker, Peter Challenor, Matt Eames

Computer models, also known as simulators, can be computationally expensive to run, and for this reason statistical surrogates, known as emulators, are often used. Any statistical model, including an emulator, should be validated before being used, otherwise resulting decisions can be misguided. We discuss how current methods for validating Gaussian process

Poompong Chaiwongkhot, Katanya B. Kuntz, Yanbao Zhang, Anqi Huang

The ability of an eavesdropper (Eve) to perform an intercept-resend attack on a free-space quantum key distribution (QKD) receiver by precisely controlling the incidence angle of an attack laser has been previously demonstrated. However, such an attack could be ineffective in the presence of atmospheric turbulence due to beam wander and spatial mode aberrati

James Haglund, Philip B. Zhang

The binomial Eulerian polynomials, introduced by Postnikov, Reiner, and Williams, are $γ$-positive polynomials and can be interpreted as $h$-polynomials of certain flag simplicial polytopes. Recently, Athanasiadis studied analogs of these polynomials for colored permutations. In this paper, we generalize them to $\mathbf{s}$-inversion sequences and prove tha

Carlos Pérez-Espigares, Pablo I. Hurtado

Interacting particle systems with many degrees of freedom may undergo phase transitions to sustain atypical fluctuations of dynamical observables such as the current or the activity. This leads in some cases to symmetry-broken space-time trajectories which enhance the probability of such events due to the emergence of ordered structures. Despite their concep

Martin Sundermeyer, Zoltan-Csaba Marton, Maximilian Durner, Manuel Brucker

We propose a real-time RGB-based pipeline for object detection and 6D pose estimation. Our novel 3D orientation estimation is based on a variant of the Denoising Autoencoder that is trained on simulated views of a 3D model using Domain Randomization. This so-called Augmented Autoencoder has several advantages over existing methods: It does not require real,

Adel Bibi, El Houcine Bergou, Ozan Sener, Bernard Ghanem

We consider the problem of unconstrained minimization of a smooth objective function in $\R^n$ in a setting where only function evaluations are possible. While importance sampling is one of the most popular techniques used by machine learning practitioners to accelerate the convergence of their models when applicable, there is not much existing theory for th

Erik Fransson, Fredrik Eriksson, Paul Erhart

Linear models, such as force constant (FC) and cluster expansions, play a key role in physics and materials science. While they can in principle be parametrized using regression and feature selection approaches, the convergence behavior of these techniques, in particular with respect to thermodynamic properties is not well understood. Here, we therefore anal

Oleksandr Balabanov, Henrik Johannesson

Time-periodic external drives have emerged as a powerful tool to artificially create topological phases of matter. Prime examples are Floquet topological insulators (FTIs), where a gapped bulk supports in-gap edge states, protected against symmetry-preserving local perturbations. Similar to an ordinary static topological insulator, the robustness of an edge

Antonio Segatti, Juan Luis Vázquez

This paper deals with a nonlinear degenerate parabolic equation of order $α$ between 2 and 4 which is a kind of fractional version of the Thin Film Equation. Actually, this one corresponds to the limit value $α=4$ while the Porous Medium Equation is the limit $α=2$. We prove existence of a nonnegative weak solution for a general class of initial data, and es

Gabriele Benedetti, Jungsoo Kang

We apply a local systolic-diastolic inequality for contact forms and odd-symplectic forms on three-manifolds to bound the magnetic length of closed curves with prescribed geodesic curvature (also known as magnetic geodesics) on an oriented closed surface. Our results hold when the prescribed curvature is either close to a Zoll one or large enough.

Gabriele Benedetti, Jungsoo Kang

The aim of this paper is to formulate a local systolic inequality for odd-symplectic forms (also known as Hamiltonian structures) and to establish it in some basic cases. Let $Ω$ be an odd-symplectic form on an oriented closed manifold $Σ$ of odd dimension. We say that $Ω$ is Zoll if the trajectories of the flow given by $Ω$ are the orbits of a free $S^1$-ac

Justin R. Pierel, Steven A. Rodney

Recently, there have been two landmark discoveries of gravitationally lensed supernovae: the first multiply-imaged SN, &#34;Refsdal&#34;, and the first Type Ia SN resolved into multiple images, SN iPTF16geu. Fitting the multiple light curves of such objects can deliver measurements of the lensing time delays, which are the difference in arrival times for the

Daniël Boer, Ruud Peeters, Sybrand Zeinstra

In the literature measures of fine-tuning have been discussed as one of the tools to assess the feasibility of beyond the Standard Model theories. In this paper we focus on two specific measures and investigate what kind of fine-tuning they actually quantify. First we apply both measures to the two Higgs doublet model, for which one can analyze the numerical

Vesna Vuksanović

This study aims to investigate topological organization of cortical thickness and functional networks by cortical lobes. First, I demonstrated modular organization of these networks by the cortical surface frontal, temporal, parietal and occipital divisions. Secondly, I mapped the overlapping edges of cortical thickness and functional networks for positive a

Rui Wang, Lie-Wen Chen, Zhen Zhang

The lattice Hamiltonian method is developed for solving the Vlasov equation with nuclear mean-field based on the Skyrme pseudopotential up to next-to-next-to-next-to leading order. The ground states of nuclei are obtained through varying the total energy with respect to the density distribution of nucleons. Owing to the self-consistent treatment of initial n

David Berger

For a Lévy basis $L$ on $\mathbb{R}^d$ and a suitable kernel function $f:\mathbb{R}^d \to \mathbb{R}$, consider the continuous spatial moving average field $X=(X_t)_{t\in \mathbb{R}^d}$ defined by $X_t = \int_{\mathbb{R}^d} f(t-s) \, dL(s)$. Based on observations on finite subsets $Γ_n$ of $\mathbb{Z}^d$, we obtain central limit theorems for the sample mean

Gabriele Benedetti, Jungsoo Kang

Let $α$ be a contact form on a connected closed three-manifold $Σ$. The systolic ratio of $α$ is defined as $ρ_{\mathrm{sys}}(α):=\tfrac{1}{\mathrm{Vol}(α)}T_{\min}(α)^2$, where $T_{\min}(α)$ and $\mathrm{Vol}(α)$ denote the minimal period of periodic Reeb orbits and the contact volume. The form $α$ is said to be Zoll if its Reeb flow generates a free $S^1$-

Claudio Maggi, Matteo Paoluzzi

Many natural and social phenomena are characterized by synchronization. The Kuramoto model, taking into account the basic ingredients for observing synchronized states, allows to study mathematically synchronization in a simplified but nontrivial picture. Here we study how a noise that is correlated on a finite time-scale $τ$ impacts the ability of the Kuram

S. Saxena, J. M. Kosterlitz

Wavenumber selection in pattern forming systems remains a long standing puzzle in physics. Previous studies have shown that external noise is a possible mechanism for wavenumber selection. We conduct an extensive numerical study of the noisy stabilized Kuramoto Sivashinsky equation. We use a fast spectral method of integration, which enables us to investigat

Etienne Boursier, Emilie Kaufmann, Abbas Mehrabian, Vianney Perchet

We study a multiplayer stochastic multi-armed bandit problem in which players cannot communicate, and if two or more players pull the same arm, a collision occurs and the involved players receive zero reward. We consider the challenging heterogeneous setting, in which different arms may have different means for different players, and propose a new and effici

Marco Oesting, Alexander Schnurr

In this paper, we investigate temporal clusters of extremes defined as subsequent exceedances of high thresholds in a stationary time series. Two meaningful features of these clusters are the probability distribution of the cluster size and the ordinal patterns within a cluster. Since these patterns take only the ordinal structure of consecutive data points

Fernando Lucatelli Nunes

Let $\mathbb{A}$ be a $2$-category with suitable opcomma objects and pushouts. We give a direct proof that, provided that the codensity monad of a morphism $p$ exists and is preserved by a suitable morphism, the factorization given by the lax descent object of the higher cokernel of $p$ is up to isomorphism the same as the semantic factorization of $p$, eith

Basabendu Barman, Subhaditya Bhattacharya, Purusottam Ghosh, Saurabh Kadam

Fermion dark matter (DM) as an admixture of additional singlet and doublet vector like fermions provides an attractive and allowed framework by relic density and direct search constraints within TeV scale, although limited by its discovery potential at the Large Hadron Collider (LHC). An extension of the model with scalar triplet can yield neutrino masses an

Sabyasachi Chatterjee, Subhajit Goswami

2D Total Variation Denoising (TVD) is a widely used technique for image denoising. It is also an important nonparametric regression method for estimating functions with heterogenous smoothness. Recent results have shown the TVD estimator to be nearly minimax rate optimal for the class of functions with bounded variation. In this paper, we complement these wo

D. Hazra, A. Moorti, A. Upadhyay, J. A. Chakera

An experimental study on 55fs laser driven plasma accelerator using mixed gas-jet target with varying plasma density is used to identify the role of different acceleration mechanisms, viz. Direct Laser Acceleration (DLA) and wakefield. At lower electron density electron acceleration could be attributed mainly to DLA with ionization induced injection. With in

Eli Waxman, Eran O. Ofek, Doron Kushnir

We discuss the late time (tens of days) emission from the radioactive ejecta of mergers involving neutron stars, when the ionization energy loss time of beta-decay electrons and positrons exceeds the expansion time. We show that if the e$^\pm$ are confined to the plasma (by magnetic fields), then the time dependence of the plasma heating rate, $\dot{\varepsi

Patrick Schlachter, Yiwen Liao, Bin Yang

This paper introduces a generic method which enables to use conventional deep neural networks as end-to-end one-class classifiers. The method is based on splitting given data from one class into two subsets. In one-class classification, only samples of one normal class are available for training. During inference, a closed and tight decision boundary around

Michał T. Seweryn

Joret et al. proved that posets with cover graphs of treewidth at most 2 have dimension at most 1276. Their proof is long and very complex. We give a short and much simpler proof that the dimension of such posets is at most 12.

Noam Soker

I construct the class of supernovae and supernova progenitors that result from fatal common envelope evolution (CEE). The fatal CEE progenitors are stellar binary systems where a companion spirals-in inside the envelope of a giant star and merges with the core. The companion can be a neutron star (NS; or a black hole) that destroys the core and by that forms

Lorenzo Gaudio, Mari Kobayashi, Björn Bissinger, Giuseppe Caire

We consider a joint radar estimation and communication system using orthogonal frequency division multiplexing (OFDM) and orthogonal time frequency space (OTFS) modulations. The scenario is motivated by vehicular applications where a vehicle equipped with a mono-static radar wishes to communicate data to its target receiver, while estimating parameters of in

Wei-Hung Weng, Yu-An Chung, Peter Szolovits

As patients&#39; access to their doctors&#39; clinical notes becomes common, translating professional, clinical jargon to layperson-understandable language is essential to improve patient-clinician communication. Such translation yields better clinical outcomes by enhancing patients&#39; understanding of their own health conditions, and thus improving patien

Pascal de Koster, Roel Tielen, Elizaveta Wobbes, Matthias Möller

The Material Point Method (MPM) is a numerical technique that combines a fixed Eulerian background grid and Lagrangian point masses to simulate materials which undergo large deformations. Within the original MPM, discontinuous gradients of the piecewise-linear basis functions lead to so-called `grid-crossing errors&#39; when particles cross element boundarie

Qiya Hu, Rongrong Song

In this paper we are concerned with numerical methods for nonhomogeneous Helmholtz equations in inhomogeneous media. We design a least squares method for discretization of the considered Helmholtz equations. In this method, an auxiliary unknown is introduced on the common interface of any two neighboring elements and a quadratic subject functional is defined

Zhen Liang, Huo-Jun Ruan

In this paper, we present a general framework to construct recurrent fractal interpolation surfaces (RFISs) on rectangular grids. Then we introduce bilinear RFISs, which are easy to be generated while there are no restrictions on interpolation points and vertical scaling factors. We also obtain the box dimension of bilinear RFISs under certain constraints, w

Caroline Geiersbach, Estefania Loayza, Kathrin Welker

In this paper, a shape optimization problem constrained by a random elliptic partial differential equation with a pure Neumann boundary is presented. The model is motivated by applications in interface identification, where we assume coefficients and inputs are subject to uncertainty. The problem is posed as a minimization of the expectation of a random obje

Leon Rueckert, Annette Zippelius, Reiner Kree

We consider a liquid droplet which is propelled solely by internal flow. In a simple model, this flow is generated by an autonomous actuator, which moves on a prescribed trajectory inside the droplet. In a biological system, the device could represent a motor, carrying cargo and moving on a filamentary track. We work out the general framework to compute the

Jane Tan

A 4-regular planar graph $G$ is said to be circle representable if there exists a collection of circles drawn on the plane such that the touching and crossing points correspond to the vertices of $G$, and the circular arcs between those points correspond to the edges of $G$. Lovász (1970) conjectured that every 4-regular planar graph has a circle representat

Diego Zabaljauregui, Luciano Campi

Starting from the Avellaneda-Stoikov framework, we consider a market maker who wants to optimally set bid/ask quotes over a finite time horizon, to maximize her expected utility. The intensities of the orders she receives depend not only on the spreads she quotes, but also on unobservable factors modelled by a hidden Markov chain. We tackle this stochastic c

Evgeny Feigin

The Littlewood-Richardson coefficients describe the decomposition of tensor products of irreducible representations of a simple Lie algebra into irreducibles. Assuming the number of factors is large, one gets a measure on the space of weights. This limiting measure was extensively studied by many authors. In particular, Kerov computed the corresponding densi

Alberto Marchisio, Muhammad Abdullah Hanif, Mohammad Taghi Teimoori, Muhammad Shafique

Deep Neural Networks (DNNs) have been established as the state-of-the-art algorithm for advanced machine learning applications. Recently, CapsuleNets have improved the generalization ability, as compared to DNNs, due to their multi-dimensional capsules. However, they pose high computational and memory requirements, which makes energy-efficient inference a ch

Marta Strzelecka

We prove estimates for $\mathbb{E} \| X: \ell_{p'}^n \to \ell_q^m\|$ for $p,q\ge 2$ and any random matrix $X$ having the entries of the form $a_{ij}Y_{ij}$, where $Y=(Y_{ij})_{1\le i\le m, 1\le j\le n}$ has i.i.d. isotropic log-concave rows. This generalises the result of Gu\'edon, Hinrichs, Litvak, and Prochno for Gaussian matrices with independent entries.

Jonathan Chapman

We show how multiplicatively syndetic sets can be used in the study of partition regularity of dilation invariant systems of polynomial equations. In particular, we prove that a dilation invariant system of polynomial equations is partition regular if and only if it has a solution inside every multiplicatively syndetic set. We also adapt the methods of Green

Rafael Pinot, Laurent Meunier, Alexandre Araujo, Hisashi Kashima

This paper investigates the theory of robustness against adversarial attacks. It focuses on the family of randomization techniques that consist in injecting noise in the network at inference time. These techniques have proven effective in many contexts, but lack theoretical arguments. We close this gap by presenting a theoretical analysis of these approaches

Alberto Marchisio, Giorgio Nanfa, Faiq Khalid, Muhammad Abdullah Hanif

Spiking Neural Networks (SNNs) claim to present many advantages in terms of biological plausibility and energy efficiency compared to standard Deep Neural Networks (DNNs). Recent works have shown that DNNs are vulnerable to adversarial attacks, i.e., small perturbations added to the input data can lead to targeted or random misclassifications. In this paper,

Chang-Kang Hu, Alan C. Santos, Jin-Ming Cui, Yun-Feng Huang

Quantum thermodynamics aims at investigating both the emergence and the limits of the laws of thermodynamics from a quantum mechanical microscopic approach. In this scenario, thermodynamic processes with no heat exchange, namely, adiabatic transformations, can be implemented through quantum evolutions in closed systems, even though the notion of a closed sys

Hiroyuki Kasai, Pratik Jawanpuria, Bamdev Mishra

Adaptive stochastic gradient algorithms in the Euclidean space have attracted much attention lately. Such explorations on Riemannian manifolds, on the other hand, are relatively new, limited, and challenging. This is because of the intrinsic non-linear structure of the underlying manifold and the absence of a canonical coordinate system. In machine learning

Stefan Hammer, Christian Günzel, Mario Mörl, Sven Findeiß

Artificial RNA molecules with novel functionality have many applications in synthetic biology, pharmacy and white biotechnology. The de novo design of such devices using computational methods and prediction tools is a resource-efficient alternative to experimental screening and selection pipelines. In this review, we describe methods common to many such comp

Wuhyun Sohn, James Fergusson

We present forecasts on the primordial non-Gaussianity parameter $f_\text{NL}$ of feature models for the future Cosmic Microwave Background Stage-4 (CMB-S4) experiments. The Fisher matrix of the bispectrum estimator was computed using noise covariances expected for preliminary CMB-S4 specifications including ones for the Simons Observatory. We introduce a no

Łukasz Rajkowski, John Noble

We investigate the geometry of the maximal a posteriori (MAP) partition in the Bayesian Mixture Model where the component and the base distributions are chosen from conjugate exponential families. We prove that in this case the clusters are separated by the contour lines of a linear functional of the sufficient statistic. As a particular example, we describe

Najda Villefranque, Fleur Couvreux, Richard Fournier, Stéphane Blanco

Interactions between clouds and radiation are at the root of many difficulties in numerically predicting future weather and climate and in retrieving the state of the atmosphere from remote sensing observations. The large range of issues related to these interactions, and in particular to three-dimensional interactions, motivated the development of accurate

Javier Cárcamo, Luis-Alberto Rodríguez, Antonio Cuevas

We show that various functionals related to the supremum of a real function defined on an arbitrary set or a measure space are Hadamard directionally differentiable. We specifically consider the supremum norm, the supremum, the infimum, and the amplitude of a function. The (usually non-linear) derivatives of these maps adopt simple expressions under suitable

Angelo Ferrando, Michael Winikoff, Stephen Cranefield, Frank Dignum

Interactions between agents are usually designed from a global viewpoint. However, the implementation of a multi-agent interaction is distributed. This difference can introduce issues. For instance, it is possible to specify protocols from a global viewpoint that cannot be implemented as a collection of individual agents. This leads naturally to the question

Tariq Syed

We study the cancellation property of projective modules of rank $2$ with a trivial determinant over Noetherian rings of dimension $\leq 4$. If $R$ is a smooth affine algebra of dimension $4$ over an algebraically closed field $k$ such that $6 \in k^{\times}$, then we prove that stably free $R$-modules of rank $2$ are free if and only if a Hermitian $K$-theo

Kui Zhao, Junhao Hua, Ling Yan, Qi Zhang

While marketing budget allocation has been studied for decades in traditional business, nowadays online business brings much more challenges due to the dynamic environment and complex decision-making process. In this paper, we present a novel unified framework for marketing budget allocation. By leveraging abundant data, the proposed data-driven approach can

Kaoru Mizuta, Kazuaki Takasan, Norio Kawakami

Prethermalization, where quasi-steady states are realized in the intermediate long time regime (prethermal regime), in periodically driven (Floquet) systems is an important phenomenon since it provides a platform of nontrivial Floquet many-body physics. In this Letter, we consider Floquet systems with dual energy scales: the Hamiltonian consists of two diffe

Alex Stockrahm, Valtteri Lahtinen, Jari J. J. Kangas, P. Robert Kotiuga

A wealth of literature exists on computing and visualizing cuts for the magnetic scalar potential of a current carrying conductor via Finite Element Methods (FEM) and harmonic maps to the circle. By a cut we refer to an orientable surface bounded by a given current carrying path (such that the flux through it may be computed) that restricts contour integrals

Pascal Neveu, Fabien Bretenaker, Fabienne Goldfarb, Etienne Brion

We study the propagation and storage of a quantum field using ultra-narrow Coherent Population Oscillations (CPO) in a $Λ-$type atomic medium. The predictions for classical fields are checked experimentally in a metastable vapor at room temperature. We derive the evolution of its squeezing spectrum in the presence of a large classical pump field which enable

Ivan Morera, Artur Polls, Bruno Juliá-Díaz

We consider a quantum simulator of the Heisenberg chain with ferromagnetic interactions based on the two-component 1D Bose-Hubbard model at filling equal to two in the strong coupling regime. The entanglement properties of the ground state are compared between the original spin model and the quantum simulator as the interspecies interaction approaches the in

Jin-Yi Pang, Jia-Jun Wu, H. -W. Hammer, Ulf-G. Meißner

Using the three-particle quantization condition recently obtained in the particle-dimer framework, the finite-volume energy shift of the two lowest three-particle scattering states is derived up to and including order $L^{-6}$. Furthermore, assuming that a stable dimer exists in the infinite volume, the shift for the lowest particle-dimer scattering state is

Tobias Weihrauch, Stefan Bachmann

We completely characterize when the free effective resistance of an infinite graph can be expressed in terms of simple hitting probabilities of the graphs random walk.

Angela Fan, Mike Lewis, Yann Dauphin

Writers generally rely on plans or sketches to write long stories, but most current language models generate word by word from left to right. We explore coarse-to-fine models for creating narrative texts of several hundred words, and introduce new models which decompose stories by abstracting over actions and entities. The model first generates the predicate

Nathan Sebastian Gass, Thomas Studer

The Logic of Proofs, LP, and other justification logics can have self-referential justifications of the form t:A. Such self-referential justifications are necessary for the realization of S4 in LP. Yu discovered prehistoric cycles in a particular Gentzen system as a necessary condition for S4 theorems that can only be realized using self-referentiality. It w

Jeffrey B. Parker, Navid C. Constantinou

Magnetic induction in magnetohydrodynamic fluids at magnetic Reynolds number (Rm) less than~1 has long been known to cause magnetic drag. Here, we show that when $\mathrm{Rm} \gg 1$ and the fluid is in a hydrodynamic-dominated regime in which the magnetic energy is much smaller than the kinetic energy, induction due to a mean shear flow leads to a magnetic e

Yuta Murotani, Ryo Shimano

In multiband superconductors, multiple collective modes exist associated with the multiple order parameters. Oscillations of the amplitude and the relative phase of the order parameters are called Higgs and Leggett modes, respectively. Recently, it has been suggested that nonmagnetic impurity scattering would enhance nonlinear coupling between the Higgs mode

Jialun Li, Frederic Naud, Wenyu Pan

Let $\Gamma$ be a Zariski dense Kleinian Schottky subgroup of PSL2(C). Let $\Lambda(\Gamma)$ be its limit set, endowed with a Patterson-Sullivan measure $\mu$ supported on $\Lambda(\Gamma)$. We show that the Fourier transform $\widehat{\mu}(\xi)$ enjoys polynomial decay as $\vert \xi \vert$ goes to infinity. This is a PSL2(C) version of the result of Bourgai

Zeév Rudnick, Sa&#39;ar Zehavi

A conjecture due to Cilleruelo states that for an irreducible polynomial $f$ with integer coefficients of degree $d\geq 2$, the least common multiple $L_f(N)$ of the sequence $f(1), f(2), \dots, f(N)$ has asymptotic growth $\log L_f(N)\sim (d-1)N\log N$ as $N\to \infty$. We establish a version of this conjecture for almost all shifts of a fixed polynomial, t

Julan Bailey, El Maati Ouhabaz

We solve the Kato square root problem for general elliptic operators and systems with measurable and complex coefficients on any domain of the Euclidean space. The operators are subject to Dirichlet boundary conditions. We also allow perturbations by general complex potentials.

Pablo Candela, Balázs Szegedy

We prove a general form of the regularity theorem for uniformity norms, and deduce an inverse theorem for these norms which holds for a class of compact nilspaces including all compact abelian groups, and also nilmanifolds; in particular we thus obtain the first non-abelian versions of such theorems. We derive these results from a general structure theorem f

Xintong Han, Zuxuan Wu, Weilin Huang, Matthew R. Scott

Visual compatibility is critical for fashion analysis, yet is missing in existing fashion image synthesis systems. In this paper, we propose to explicitly model visual compatibility through fashion image inpainting. To this end, we present Fashion Inpainting Networks (FiNet), a two-stage image-to-image generation framework that is able to perform compatible

Kazuo Ghoroku, Kouji Kashiwa, Yoshimasa Nakano, Motoi Tachibana

A holographic bottom-up model used in studying the superconducting system is applied to search for the color superconducting phase of supersymmetric Yang-Mills theory. We apply the probe analysis of this model to the supersymmetric Yang-Mills theory in both the confinement and deconfinement phases. In this analysis, we find the color superconductivity in bot

Yu-Ji Shi, Wei Wang, Zhen-Xing Zhao

We calculate the weak decay form factors of doubly-heavy baryons using three-point QCD sum rules. The Cutkosky rules are used to derive the double dispersion relations. We include perturbative contributions and condensation contributions up to dimension five, and point out that the perturbative contributions and condensates with lowest dimensions dominate. A

Tran Nhan Tam Quyen

This work is devoted to the nonlinear inverse problem of identifying the reaction coefficient in an elliptic boundary value problem from single Cauchy data on a part of the boundary. We then examine simultaneously two elliptic boundary value problems generated from the available Cauchy data. The output least squares method with the Tikhonov regularization is

Jarno Alanko, Giovanna D&#39;Agostino, Alberto Policriti, Nicola Prezza

Indexing strings via prefix (or suffix) sorting is, arguably, one of the most successful algorithmic techniques developed in the last decades. Can indexing be extended to languages? The main contribution of this paper is to initiate the study of the sub-class of regular languages accepted by an automaton whose states can be prefix-sorted. Starting from the r

Akshay Degwekar, Preetum Nakkiran, Vinod Vaikuntanathan

We continue the study of statistical/computational tradeoffs in learning robust classifiers, following the recent work of Bubeck, Lee, Price and Razenshteyn who showed examples of classification tasks where (a) an efficient robust classifier exists, in the small-perturbation regime; (b) a non-robust classifier can be learned efficiently; but (c) it is comput

Rupak Majumdar, Aman Mathur, Marcus Pirron, Laura Stegner

Systematic testing of autonomous vehicles operating in complex real-world scenarios is a difficult and expensive problem. We present Paracosm, a reactive language for writing test scenarios for autonomous driving systems. Paracosm allows users to programmatically describe complex driving situations with specific visual features, e.g., road layout in an urban

Agustinus Kristiadi, Sina Däubener, Asja Fischer

Despite the huge success of deep neural networks (NNs), finding good mechanisms for quantifying their prediction uncertainty is still an open problem. Bayesian neural networks are one of the most popular approaches to uncertainty quantification. On the other hand, it was recently shown that ensembles of NNs, which belong to the class of mixture models, can b

Andrea Signori

We consider a particular phase field system which physical context is that of tumor growth dynamics. The model we deal with consists of a Cahn-Hilliard type equation governing the evolution of the phase variable which takes into account the tumor cells proliferation in the tissue coupled with a reaction-diffusion equation for the nutrient. This model has alr

Alexandros Stergiou, Georgios Kapidis, Grigorios Kalliatakis, Christos Chrysoulas

Deep learning approaches have been established as the main methodology for video classification and recognition. Recently, 3-dimensional convolutions have been used to achieve state-of-the-art performance in many challenging video datasets. Because of the high level of complexity of these methods, as the convolution operations are also extended to additional

Suryansh Kumar

Given dense image feature correspondences of a non-rigidly moving object across multiple frames, this paper proposes an algorithm to estimate its 3D shape for each frame. To solve this problem accurately, the recent state-of-the-art algorithm reduces this task to set of local linear subspace reconstruction and clustering problem using Grassmann manifold repr

Sen Li, Hamidreza Tavafoghi, Kameshwar Poolla, Pravin Varaiya

We evaluate the impact of three proposed regulations of transportation network companies (TNCs) like Uber, Lyft and Didi: (1) a minimum wage for drivers, (2) a cap on the number of drivers or vehicles, and (3) a per-trip congestion tax. The impact is assessed using a queuing theoretic equilibrium model which incorporates the stochastic dynamics of the app-ba

Santtu Tikka, Antti Hyttinen, Juha Karvanen

Causal effect identification considers whether an interventional probability distribution can be uniquely determined without parametric assumptions from measured source distributions and structural knowledge on the generating system. While complete graphical criteria and procedures exist for many identification problems, there are still challenging but impor

Romain Ducasse

We study some anisotropic heterogeneous nonlinear integral equations arising in epidemiology. We focus on the case where the heterogeneities are spatially periodic. In the first part of the paper, we show that the equations we consider exhibit a &#34;threshold phenomenon&#34;. In the second part, we study the existence and non-existence of &#34;traveling wav

Elisabeth Gassiat, Sylvain Le Corff, Luc Lehéricy

This paper considers hidden Markov models where the observations are given as the sum of a latent state which lies in a general state space and some independent noise with unknown distribution. It is shown that these fully nonparametric translation models are identifiable with respect to both the distribution of the latent variables and the distribution of t

Wonseok Hwang, Jinyeong Yim, Seunghyun Park, Minjoon Seo

We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset. We revisit and discuss diverse popular methods in NL2SQL literature, take a full advantage of BERT {Devlin et al., 2018) through an effective table contextualization method, and coherently combine them, outperforming the previous state of the

Pin-Chi Hung, Meng Fai Lim

Let $p$ be an odd prime and $F_{\infty}$ a $p$-adic Lie extension of a number field $F$. Let $A$ be an abelian variety over $F$ which has ordinary reduction at every primes above $p$. Under various assumptions, we establish asymptotic upper bounds for the growth of Mordell-Weil rank of the abelian variety of $A$ in the said $p$-adic Lie extension. Our upper

Denis Bonheure, Jean Dolbeault, Maria J. Esteban, Ari Laptev

This paper is devoted to the symmetry and symmetry breaking properties of a two-dimensional magnetic Schr{ö}dinger operator involving an Aharonov-Bohm magnetic vector potential. We investigate the symmetry properties of the optimal potential for the corresponding magnetic Keller-Lieb-Thir-ring inequality. We prove that this potential is radially symmetric if

Ugo Bruzzo, Annamaria Fino, Pietro Fré, Pietro Antonio Grassi

As a continuation of a general program started in two previous publications, in the present paper we study the Kähler quotient resolution of the orbifold $\mathbb{C}^3/\mathbb{Z}_4$, comparing with the results of a toric description of the same. In this way we determine the algebraic structure of the exceptional divisor, whose compact component is the second

Joydeep Majhi, Subir Ghosh, Santanu K. Maiti

Motivated by recent interest in photon and electron vortex beams, we propose the construction of a relativistic anyon beam. Following Jackiw and Nair [Phys. Rev. D 43, 1933 (1991)] we derive explicit form of relativistic plane wave solution of a single anyon. Subsequently we construct the planar anyon beam by superposing these solutions. Explicit expressions

Alex Drlica-Wagner, Yao-Yuan Mao, Susmita Adhikari, Robert Armstrong

Astrophysical and cosmological observations currently provide the only robust, empirical measurements of dark matter. Future observations with Large Synoptic Survey Telescope (LSST) will provide necessary guidance for the experimental dark matter program. This white paper represents a community effort to summarize the science case for studying the fundamenta

Shi-Lin Li, Yuan-Yuan Liu, Wen-Du Li, Wu-Sheng Dai

In this paper, we solve the massive scalar field in the Reissner-Nordström spacetime. The scalar field in the Reissner-Nordström spacetime has both bound states and scattering states. For bound states, we solve the bound-state wave function and the eigenvalue spectrum. For scattering states, we solve the scattering wave function and give an explicit expressi