April 2019 arXiv papers — page 87

Gerard McCaul, Denys I. Bondar

The longstanding question of how stochastic behaviour arises from deterministic Hamiltonian dynamics is of great importance, and any truly holistic theory must be capable of describing this transition. In this review, we introduce the influence functional formalism in both the quantum and classical regimes. Using this technique, we demonstrate how irreversib

Tınaz Ekim, Mordechai Shalom, Oylum Şeker

It is known that any chordal graph on $n$ vertices can be represented as the intersection of $n$ subtrees in a tree on $n$ nodes. This fact is recently used in [2] to generate random chordal graphs on $n$ vertices by generating $n$ subtrees of a tree on $n$ nodes. It follows that the space (and thus time) complexity of such an algorithm is at least the sum o

Jeremy Attard, Jordan François, Serge Lazzarini, Thierry Masson

This work extends previous developments carried out by some of the authors on Ehresmann connections on Atiyah Lie algebroids. In this paper, we study Cartan connections in a framework relying on two Atiyah Lie algebroids based on a $H$-principal fiber bundle $\mathcal{P}$ and its associated $G$-principal fiber bundle $\mathcal{Q} := \mathcal{P} \times_H G$,

John Gertz

Numerous advantages may accrue to ET from the use of probes for the conveyance of information relative to the alternative of beaming information electromagnetically from its home star system. However, probes would benefit from a trans-galactic communications network to transmit information back to their progenitor civilization(s) and throughout the Galaxy. A

Patrick P. Potts, Peter Samuelsson

Thermodynamic uncertainty relations quantify how the signal-to-noise ratio of a given observable is constrained by dissipation. Fluctuation relations generalize the second law of thermodynamics to stochastic processes. We show that any fluctuation relation directly implies a thermodynamic uncertainty relation, considerably increasing their range of applicabi

Bryan Lim, Stefan Zohren, Stephen Roberts

While time series momentum is a well-studied phenomenon in finance, common strategies require the explicit definition of both a trend estimator and a position sizing rule. In this paper, we introduce Deep Momentum Networks -- a hybrid approach which injects deep learning based trading rules into the volatility scaling framework of time series momentum. The m

Silvia Müllner, Wayne Crump, Dirk Wulferding, Benjamin P. P. Mallett

We present a systematic study of the interplay between lattice parameters and the energy of the optical phonons as well as the antiferromagnetic coupling strength, $J$, in the high-$T_{\text{c}}$ superconducting cuprate $R$Ba$_2$Cu$_3$O$_{6+δ}$ (\mbox{R-123}, $R =$ Y, Dy, Gd, Sm, Nd) with hole-doping $p$ ($0.00<p \lesssim 0.04$). The energy of the $B_{1g}$-m

Seth Musser, Davide Proment, Miguel Onorato, William T. M. Irvine

We investigate superfluid flow around an airfoil accelerated to a finite velocity from rest. Using simulations of the Gross--Pitaevskii equation we find striking similarities to viscous flows: from production of starting vortices to convergence of airfoil circulation onto a quantized version of the Kutta-Joukowski circulation. We predict the number of quanti

Rodrigo Hernández-Gutiérrez

In this paper we consider the question of when the space $C_p(X)$ of continuous real-valued functions on $X$ with the pointwise convergence topology is countable dense homogeneous. In particular, we focus on the case when $X$ is countable with a unique non-isolated point $\infty$. In this case, $C_p(X)$ is countable dense homogeneous if and only if the filte

Olivia Dumitrescu, Motohico Mulase

Edge-contraction operations form an effective tool in various graph enumeration problems, such as counting Grothendieck&#39;s dessins d&#39;enfants and simple and double Hurwitz numbers. These counting problems can be solved by a mechanism known as topological recursion, which is a mirror B-model corresponding to these counting problems. We show that for the

D M L Barbato, J M A De Andrade, J J De Groote

Techniques for leaf-cutting ant control have been investigated in literature due to the importance of the damage they cause to agriculture. The effectiveness of different forms of control is explored in researches aimed at identifying the balance between pest control efficiency and environmental damage caused by the treatments applied. Plantations with large

Sean R. B. Bearden, Forrest C. Sheldon, Massimiliano Di Ventra

Memcomputing is a novel computing paradigm that employs time non-locality (memory) to solve combinatorial optimization problems. It can be realized in practice by means of non-linear dynamical systems whose point attractors represent the solutions of the original problem. It has been previously shown that during the solution search digital memcomputing machi

M. Lanzendörfer, J. Hron

The boundary conditions prescribing the constant traction or the so-called do-nothing conditions are frequently taken on artificial boundaries in the numerical simulations of steady flow of incompressible fluids, despite the fact that they do not facilitate a well-posed problem, not allowing to establish the standard energy estimates. In a pursuit to underst

S. Malko, X. Vaisseau, F. Perez, D. Batani

The double laser pulse approach to relativistic electron beam (REB) collimation has been investigated at the LULI-ELFIE facility. In this scheme, the magnetic field generated by the first laser-driven REB is used to guide a second delayed REB. We show how electron beam collimation can be controlled by properly adjusting laser parameters. By changing the rati

Davis Wertheimer, Bharath Hariharan

Traditional recognition methods typically require large, artificially-balanced training classes, while few-shot learning methods are tested on artificially small ones. In contrast to both extremes, real world recognition problems exhibit heavy-tailed class distributions, with cluttered scenes and a mix of coarse and fine-grained class distinctions. We show t

Francis Williams, Alexander Bock, Harish Doraiswamy, Cassandra Donatelli

The ScanAllFish project is a large-scale effort to scan all the world&#39;s 33,100 known species of fishes. It has already generated thousands of volumetric CT scans of fish species which are available on open access platforms such as the Open Science Framework. To achieve a scanning rate required for a project of this magnitude, many specimens are grouped t

Maxime Debiossac, David Grass, Jose Joaquin Alonso, Eric Lutz

Feedback control mechanisms are ubiquitous in science and technology, and play an essential role in regulating physical, biological and engineering systems. The standard second law of thermodynamics does not hold in the presence of measurement and feedback. Most studies so far have extended the second law for discrete, Markovian feedback protocols; however,

Nzar Rauf Abdullah, Chi-Shung Tang, Andrei Manolescu, Vidar Gudmundsson

Transport properties of a quantum dot coupled to a photon cavity are investigated using a quantum master equation in the steady-state regime. In the off-resonance regime, when the photon energy is smaller than the energy spacing between the lowest electron states of the quantum dot, we calculate the current that is generated by photon replica states as the e

Pedro Pérez-Aros, Emilio Vilches

The Baillon-Haddad theorem establishes that the gradient of a convex and continuously differentiable function defined in a Hilbert space is $β$-Lipschitz if and only if it is $1/β$-cocoercive. In this paper, we extend this theorem to Gâteaux differentiable convex functions defined on an open convex set of a Hilbert space. Finally, we give a characterization

Daniela Carollo, Masashi Chiba, Miho Ishigaki, Ken Freeman

The Milky Way is a unique laboratory, where stellar properties can be measured and analyzed in detail. In particular, stars in the older populations encode information on the mechanisms that led to the formation of our Galaxy. In this article, we analyze the kinematics, spatial distribution, and chemistry of a large number of stars in the Solar Neighborhood,

W. O. Obonyo, S. L. Lumsden, M. G. Hoare, S. J. D. Purser

Massive young stellar objects (MYSOs) have recently been shown to drive jets whose particles can interact with either the magnetic fields of the jet or ambient medium to emit non-thermal radiation. We report a search for non-thermal radio emission from a sample of 15 MYSOs to establish the prevalence of the emission in the objects. We used their spectra acro

Kamanasish Debnath, Yuan Zhang, Klaus Mølmer

We study collective effects in an inhomogeneously broadened ensemble of two-level emitters coupled to an optical cavity with narrow linewidth. Using second order mean field theory we find that the emitters within a few times the cavity linewidth exhibit synchronous behaviour and undergo collective Rabi oscillations. Under proper conditions, the synchronized

L. Benítez, L. Barberis, C. A. Condat

Cancer stem cells have been shown to be critical to the development of a variety of solid cancers. The precise interplay mechanisms between cancer stem cells and the rest of a tissue are still not elucidated. To shed light on the interactions between stem and non-stem cancer cell populations we develop a two-population mathematical model, which is suitable t

Mingyuan Zhou, Yu Ji, Yuqi Ding, Jinwei Ye

Recovering the shape and reflectance of non-Lambertian surfaces remains a challenging problem in computer vision since the view-dependent appearance invalidates traditional photo-consistency constraint. In this paper, we introduce a novel concentric multi-spectral light field (CMSLF) design that is able to recover the shape and reflectance of surfaces with a

O. B. Zaslavskii

We consider collisions of electrically neutral particles in the background of axially symmetric rotating space-times. For reactions of the kind 1+2$% \rightarrow $3+4 we give full classification of possible scenarios based on exact expressions for dynamic characteristics of particles 3 and 4 depending on particles 1 and 2. There are five nonequivalent scenar

P. B. Covas, Alicia M. Sintes

Non-axysymmetric, fast-spinning unknown neutron stars in binary systems may emit continuous gravitational waves (nearly-monochromatic long-duration signals) which can be detected by ground-based detectors like LIGO and Virgo. In this paper we present a new pipeline, called $\textit{BinarySkyHough}$, that can carry out all-sky searches for neutron stars in bi

Vinh Tran, Yang Wang, Minh Hoai

We consider the task of training a neural network to anticipate human actions in video. This task is challenging given the complexity of video data, the stochastic nature of the future, and the limited amount of annotated training data. In this paper, we propose a novel knowledge distillation framework that uses an action recognition network to supervise the

Brian DeCleene, Steve Huntsman

Mobile wireless networks are intrinsically more prone to link congestion and outright failures than wired networks. In this paper, we elaborate the resilient routing reconfiguration method of \cite{WangEtAl} and generalize it to accomodate point-to-multipoint links and wireless networks. By reframing link failures as traffic uncertainties, this technique all

G. Gabrielse, S. E. Fayer, T. G. Myers, X. Fan

The electron and positron magnetic moments are the most precise prediction of the standard model of particle physics. The most accurate measurement of a property of an elementary particle has been made to test this result. A new experimental method is now being employed in an attempt to improve the measurement accuracy by an order of magnitude. Positrons fro

Athanasios Chatzistavrakidis, Clay J. Grewcoe, Larisa Jonke, Fech Scen Khoo

Courant sigma-models encode the geometric and non-geometric fluxes of compactified closed string theory as generalized Wess-Zumino terms and exhibit their relation to Courant algebroids. In recent work, we proposed a doubled membrane sigma-model that establishes the corresponding connection to double field theory and its algebroid structure. The strategy is

Ilija Buric, Volker Schomerus, Evgeny Sobko

In this work we launch a systematic theory of superconformal blocks for four-point functions of arbitrary supermultiplets. Our results apply to a large class of superconformal field theories including 4-dimensional models with any number $\mathcal{N}$ of supersymmetries. The central new ingredient is a universal construction of the relevant Casimir different

Alberto Hernández-Espinosa, Héctor Zenil, Narsis A. Kiani, Jesper Tegnér

The concept of information has emerged as a language in its own right, bridging several disciplines that analyze natural phenomena and man-made systems. Integrated information has been introduced as a metric to quantify the amount of information generated by a system beyond the information generated by its elements. Yet, this intriguing notion comes with the

Matthias Fey

We propose a dynamic neighborhood aggregation (DNA) procedure guided by (multi-head) attention for representation learning on graphs. In contrast to current graph neural networks which follow a simple neighborhood aggregation scheme, our DNA procedure allows for a selective and node-adaptive aggregation of neighboring embeddings of potentially differing loca

Fernando Marchesano, Max Wiesner

We consider geodesics of infinite length and constant 4d dilaton in the (classical) hypermultiplet moduli space of type II Calabi-Yau compactifications. When approaching such infinite distance points, a large amount of D-instantons develop an exponentially suppressed action, substantially modifying the moduli space metric. We consider a particular large volu

Johan Öinert

The three famous problems concerning units, zero-divisors and idempotents in group rings of torsion-free groups, commonly attributed to I. Kaplansky, have been around for more than 60 years and still remain open in characteristic zero. In this article, we introduce the corresponding problems in the considerably more general context of arbitrary rings graded

Eirik Holm Fyhn, Jacob Linder

When the impurity mean free path is short, only spin-polarized Cooper pairs which are non-locally and antisymmetrically correlated in time may exist in a half-metallic ferromagnet. As a consequence, the half-metal acts as an odd-frequency superconducting condensate. We demonstrate both analytically and numerically that quantum vortices can emerge in half-met

Lando Bosma, Benjamin Knorr, Frank Saueressig

A key incentive of quantum gravity is the removal of spacetime singularities plaguing the classical theory. We compute the non-perturbative momentum-dependence of a specific structure function within the gravitational asymptotic safety program which encodes the quantum corrections to the graviton propagator for momenta above the Planck scale. The resulting q

Ted Jacobson, Manus R. Visser

We derive the Einstein equation from the condition that every small causal diamond is a variation of a flat empty diamond with the same free conformal energy, as would be expected for a near-equilibrium state. The attractiveness of gravity hinges on the negativity of the absolute temperature of these diamonds, a property we infer from the generalized entropy

Charles J. Woodford, Michael Boyle, Harald P. Pfeiffer

We present a detailed study of the center-of-mass (c.m.) motion seen in simulations produced by the Simulating eXtreme Spacetimes (SXS) collaboration. We investigate potential physical sources for the large c.m. motion in binary black hole simulations and find that a significant fraction of the c.m. motion cannot be explained physically, thus concluding that

Klemen Čotar, Tomaž Zwitter, Gregor Traven, Janez Kos

The latest Gaia data release enables us to accurately identify stars that are more luminous than would be expected on the basis of their spectral type and distance. During an investigation of the 329 best Solar twin candidates uncovered among the spectra acquired by the GALAH survey, we identified 64 such over-luminous stars. In order to investigate their ex

Debasish Borah, Dibyendu Nanda, Abhijit Kumar Saha

We propose a minimal extension of the standard model of particle physics to accommodate cosmic inflation, dark matter and light neutrino masses. While the inflationary phase is obtained from a modified chaotic inflation scenario, consistent with latest cosmology data, the dark matter particle is a fermion singlet which remains out of equilibrium in the early

Boris Gaensicke, Martin Barstow, Amy Bonsor, John Debes

Practically all known planet hosts will evolve into white dwarfs, and large parts of their planetary systems will survive this transition - the same is true for the solar system beyond the orbit of Mars. Spectroscopy of white dwarfs accreting planetary debris provides the most accurate insight into the bulk composition of exo-planets. Ground-based spectrosco

Pieter van Dokkum, Asher Wasserman, Shany Danieli, Roberto Abraham

We present spatially-resolved stellar kinematics of the well-studied ultra diffuse galaxy (UDG) Dragonfly 44, as determined from 25.3 hrs of observations with the Keck Cosmic Web Imager. The luminosity-weighted dispersion within the half-light radius is $σ_{1/2}=33^{+3}_{-3}$ km/s. There is no evidence for rotation, with $V/σ<0.12$ (90% confidence) along the

Debasish Borah, Rishav Roshan, Arunansu Sil

We propose a minimal extension of the Standard Model to accommodate two-component dark matter (DM) and light neutrino mass. The symmetry of the Standard Model is enhanced by an unbroken $\mathbb{Z}_2 \times \mathbb{Z}&#39;_2$ such that being odd under each $\mathbb{Z}_2$, there exists one right handed neutrino and one inert scalar doublet. Therefore, each of

H. Sano, H. Matsumura, Y. Yamane, P. Maggi

RX J0046.5$-$7308 is a shell-type supernova remnant (SNR) in the Small Magellanic Cloud (SMC). We carried out new $^{12}$CO($J$ = 1-0, 3-2) observations toward the SNR using Mopra and the Atacama Submillimeter Telescope Experiment. We found eight molecular clouds (A-H) along the X-ray shell of the SNR. The typical cloud size and mass are $\sim$10-15 pc and $

Ning Bao, ChunJun Cao, Sebastian Fischetti, Cynthia Keeler

The Ryu-Takayanagi and Hubeny-Rangamani-Takayanagi formulae suggest that bulk geometry emerges from the entanglement structure of the boundary theory. Using these formulae, we build on a result of Alexakis, Balehowsky, and Nachman to show that in four bulk dimensions, the entanglement entropies of boundary regions of disk topology uniquely fix the bulk metri

Ying-Hsuan Lin, Shu-Heng Shao

We study the implications of &#39;t Hooft anomaly (i.e. obstruction to gauging) on conformal field theory, focusing on the case when the global symmetry is $\mathbb{Z_2}$. Using the modular bootstrap, universal bounds on (1+1)-dimensional bosonic conformal field theories with an internal $\mathbb{Z_2}$ global symmetry are derived. The bootstrap bounds depend

Michael Boyle, Daniel Hemberger, Dante A. B. Iozzo, Geoffrey Lovelace

Accurate models of gravitational waves from merging black holes are necessary for detectors to observe as many events as possible while extracting the maximum science. Near the time of merger, the gravitational waves from merging black holes can be computed only using numerical relativity. In this paper, we present a major update of the Simulating eXtreme Sp

Fabio Mascherpa, Andrea Smirne, Alejandro D. Somoza, Pelayo Fernández-Acebal

A method for the systematic construction of few-body damped harmonic oscillator networks accurately reproducing the effect of general bosonic environments in open quantum systems is presented. Under the sole assumptions of a Gaussian environment and regardless of the system coupled to it, an algorithm to determine the parameters of an equivalent set of inter

Yuhang Cao, Kai Chen, Chen Change Loy, Dahua Lin

It is a common paradigm in object detection frameworks to treat all samples equally and target at maximizing the performance on average. In this work, we revisit this paradigm through a careful study on how different samples contribute to the overall performance measured in terms of mAP. Our study suggests that the samples in each mini-batch are neither inde

Davide Rusca, Thomas van Himbeeck, Anthony Martin, Jonatan Bohr Brask

We present a scheme for a self-testing quantum random number generator. Compared to the fully device-independent model, our scheme requires an extra natural assumption, namely that the mean energy per signal is bounded. The scheme is self-testing, as it allows the user to verify in real-time the correct functioning of the setup, hence guaranteeing the contin

Quentin Menet

Given $\mathcal{A}$ the family of weights $a=(a_n)_n$ decreasing to $0$ such that the series $\sum_{n=0}^{\infty} a_n$ diverges, we show that the supremum on $\mathcal{A}$ of lower weighted densities coincides with the unweighted upper density and that the infimum on $\mathcal{A}$ of upper weighted densities coincides with the unweighted lower density. We th

Alexis Michelat, Tristan Rivière

We obtain in arbitrary codimension a removability result on the order of singularity of weak limits and bubbles of Willmore immersions measured by the second residue. This permits to reduce significantly the number of possible bubbling scenarii. As a consequence, out of the twelve families of non-planar minimal surfaces in $\mathbb{R}^3$ of total curvature g

Vedika Khemani, Rahul Nandkishore

We show how local constraints can globally &#34;shatter&#34; Hilbert space into subsectors, leading to an unexpected dynamics with features reminiscent of both many body localization and quantum scars. A crisp example of this phenomenon is provided by a &#34;fractonic circuit&#34; - a model of quantum circuit dynamics in one dimension constrained to conserve

Antoine Messager, Nicos Georgiou, Luc Berthouze

The robust detection of statistical dependencies between the components of a complex system is a key step in gaining a network-based understanding of the system. Because of their simplicity and low computation cost, pairwise statistics are commonly used in a variety of fields. Those approaches, however, typically suffer from one or more limitations such as l

Biplob Bhattacherjee, Swagata Mukherjee, Rhitaja Sengupta

Sophisticated machine learning techniques have promising potential in search for physics beyond Standard Model in Large Hadron Collider (LHC). Convolutional neural networks (CNN) can provide powerful tools for differentiating between patterns of calorimeter energy deposits by prompt particles of Standard Model and long-lived particles predicted in various mo

James Henegan, Erwin Miña-Díaz

Let $D$ be a domain obtained by removing, out of the unit disk $\{z:|z|<1\}$, finitely many mutually disjoint closed disks, and for each integer $n\geq 0$, let $P_n(z)=z^n+\cdots$ be the monic $n$th-degree polynomial satisfying the planar orthogonality condition $\int_D P_n(z)\overline{z^m}dxdy=0$, $0\leq m<n$. Under a certain assumption on the domain $D$, w

ATLAS Collaboration

Multi-particle azimuthal cumulants are measured as a function of centrality and transverse momentum using 470 $μ$b$^{-1}$ of Pb+Pb collisions at $\sqrt{s_{\mathrm{NN}}}=5.02$ TeV with the ATLAS detector at the LHC. These cumulants provide information on the event-by-event fluctuations of harmonic flow coefficients $v_n$ and correlated fluctuations between tw

Colin Defant

We consider the involutions known as &#34;toggles,&#34; which have been used to give simplified proofs of the fundamental properties of the promotion and evacuation maps. We transfer these involutions so that they generate a group $\mathscr P_n$ that acts on the set $S_n$ of permutations of $\{1,\ldots,n\}$. After characterizing its orbits in terms of permut

Paul Balister, Béla Bollobás, Robert Morris, Julian Sahasrabudhe

Introduced by Erd\H{o}s in 1950, a covering system of the integers is a finite collection of arithmetic progressions whose union is the set $\mathbb{Z}$. Many beautiful questions and conjectures about covering systems have been posed over the past several decades, but until recently little was known about their properties. Most famously, the so-called minimu

Jacques Kaiser, Alexander Friedrich, J. Camilo Vasquez Tieck, Daniel Reichard

Spike-based communication between biological neurons is sparse and unreliable. This enables the brain to process visual information from the eyes efficiently. Taking inspiration from biology, artificial spiking neural networks coupled with silicon retinas attempt to model these computations. Recent findings in machine learning allowed the derivation of a fam

X. Fan, S. E. Fayer, G. Gabrielse

Normal nuclear magnetic resonance (NMR) probes cannot be used to make high frequency resolution measurements in a cryogenic environment because they lose their frequency resolution when the liquid sample in the probe freezes. A gaseous $^3$He NMR probe, designed and constructed to work naturally in such cryogenic environments, is demonstrated at 4.2 K and 5.

Daniel Bragg, Max Lieblich

We describe a method to show that certain elliptic surfaces do not admit purely inseparable multisections (equivalently, that genus one curves over function fields admit no points over the perfect closure of the base field) and use it to show that any non-Jacobian elliptic structure on a very general supersingular K3 surface has no purely inseparable multise

Daniel Park, Haidar Khan, Bülent Yener

There has been an increased interest in the application of convolutional neural networks for image based malware classification, but the susceptibility of neural networks to adversarial examples allows malicious actors to evade classifiers. Adversarial examples are usually generated by adding small perturbations to the input that are unrecognizable to humans

Ravinder Kumar, B. Samantaray, Z. Hossain

Bismuth-doped Yttrium iron garnet (Bi:YIG) thin films known for large Magneto-optical activity with low losses still needs to get probed for its magnetization dynamics. We demonstrate a controlled tuning of magnetocrystalline anisotropy in Bi-doped Y_3 Fe_5 O_12 (Bi:YIG) films of high crystalline quality using growth induced epitaxial strain on [111]-oriente

Victor Goulart, Nicolau C. Saldanha

We study the lifting of the Schubert stratification of the homogeneous space of complete real flags of $R^{n+1}$ to its universal covering group $Spin_{n+1}$. We call the lifted strata the Bruhat cells of $Spin_{n+1}$, in keeping with the homonymous classical decomposition of reductive algebraic groups. We present explicit parameterizations for these Bruhat

Tarek M. Elgindi

It has been known since work of Lichtenstein [42] and Gunther [29] in the 1920&#39;s that the $3D$ incompressible Euler equation is locally well-posed in the class of velocity fields with Hölder continuous gradient and suitable decay at infinity. It is shown here that these local solutions can develop singularities in finite time, even for some of the simple

Ushasi Chaudhuri, Biplab Banerjee, Avik Bhattacharya, Mihai Datcu

We address the problem of cross-modal information retrieval in the domain of remote sensing. In particular, we are interested in two application scenarios: i) cross-modal retrieval between panchromatic (PAN) and multi-spectral imagery, and ii) multi-label image retrieval between very high resolution (VHR) images and speech based label annotations. Notice tha

Vojtech Kejzlar, Léo Neufcourt, Taps Maiti, Frederi Viens

This article studies Bayesian model averaging (BMA) in the context of competing expensive computer models in a typical nuclear physics setup. While it is well known that BMA accounts for the additional uncertainty of the model itself, we show that it also decreases the posterior variance of the prediction errors via an explicit decomposition. We extend BMA t

Pedro Rodriguez, Shi Feng, Mohit Iyyer, He He

Scholastic trivia competitions test knowledge and intelligence through mastery of question answering. Modern question answering benchmarks are one variant of the Turing test. Specifically, answering a set of questions as well as a human is a minimum bar towards demonstrating human-like intelligence. This paper makes the case that the format of one competitio

Vida Dujmović, Gwenaël Joret, Piotr Micek, Pat Morin

We show that planar graphs have bounded queue-number, thus proving a conjecture of Heath, Leighton and Rosenberg from 1992. The key to the proof is a new structural tool called layered partitions, and the result that every planar graph has a vertex-partition and a layering, such that each part has a bounded number of vertices in each layer, and the quotient

Markus Freitag, Isaac Caswell, Scott Roy

In this work, we train an Automatic Post-Editing (APE) model and use it to reveal biases in standard Machine Translation (MT) evaluation procedures. The goal of our APE model is to correct typical errors introduced by the translation process, and convert the &#34;translationese&#34; output into natural text. Our APE model is trained entirely on monolingual d

P. S. Bhupal Dev, Rabindra N. Mohapatra, Yongchao Zhang

Two of the important implications of the seesaw mechanism are: (i) a simple way to understand the small neutrino masses, and (ii) the origin of matter-anti-matter asymmetry in the universe via the leptogenesis mechanism. For TeV-scale seesaw models, successful leptogenesis requires that the right-handed neutrinos (RHNs) must be quasi-degenerate and if they h

Louigi Addario-Berry, Marie Albenque

Fix $p\geq 5$ an odd integer integer. Let $M_n$ be a uniform $p$-angulation with $n$ vertices and endowed with the uniform probability measure on its vertices. We prove that, there exists $C_p\in \mathbb{R}_+$ such that, after rescaling distances by $C_p/n^{1/4}$, $M_n$ converges in distribution for the Gromov-Hausdorff-Prokhorov topology towards the Brownia

Paolo Buttà, Carlo Marchioro

We study the time evolution of an incompressible fluid with axisymmetry without swirl when the vorticity is sharply concentrated. In particular, we consider $N$ disjoint vortex rings of size $\varepsilon$ and intensity of the order of $|\log\varepsilon|^{-1}$. We show that in the limit $\varepsilon\to 0$, when the density of vorticity becomes very large, the

Jianping Zhu, Rui Hou, XiaoFeng Wang, Wenhao Wang

There is an urgent demand for privacy-preserving techniques capable of supporting compute and data intensive (CDI) computing in the era of big data. However, none of existing TEEs can truly support CDI computing tasks, as CDI requires high throughput accelerators like GPU and TPU but TEEs do not offer security protection of such accelerators. This paper pres

Youjia Wu, Katherine Freese, Chris Kelso, Patrick Stengel

Direct detection experiments have set increasingly stringent limits on the cross section for spin-independent dark matter-nucleon interactions. In obtaining such limits, experiments primarily assume the standard halo model (SHM) as the distribution of dark matter in our Milky Way. Three astrophysical parameters are required to define the SHM: the local dark

Sheng Liu, Mark Cheng, Hayley Brooks, Wayne Mackey

We propose a nonparametric model for time series with missing data based on low-rank matrix factorization. The model expresses each instance in a set of time series as a linear combination of a small number of shared basis functions. Constraining the functions and the corresponding coefficients to be nonnegative yields an interpretable low-dimensional repres

Tianyang Zhao, Yifei Xu, Mathew Monfort, Wongun Choi

Accurate prediction of others&#39; trajectories is essential for autonomous driving. Trajectory prediction is challenging because it requires reasoning about agents&#39; past movements, social interactions among varying numbers and kinds of agents, constraints from the scene context, and the stochasticity of human behavior. Our approach models these interact

Gregor Pasemann, Wilhelm Stannat

A parameter estimation problem for a class of semilinear stochastic evolution equations is considered. Conditions for consistency and asymptotic normality are given in terms of growth and continuity properties of the nonlinear part. Emphasis is put on the case of stochastic reaction-diffusion systems. Robustness results for statistical inference under model

M. ElMassalami, M. B. Silva Neto

Identifying universal scaling relations between two or more variables in a complex system plays a pivotal role in understanding various phenomena in different branches of science. Examples include the allometric scaling among food webs in biology, the scaling relationship between fluid flow and fracture stiffness in geophysics, and the gap-to-$T_c$ ratio, be

James Oldfield, Yannis Panagakis, Mihalis A. Nicolaou

Recently, a multitude of methods for image-to-image translation have demonstrated impressive results on problems such as multi-domain or multi-attribute transfer. The vast majority of such works leverages the strengths of adversarial learning and deep convolutional autoencoders to achieve realistic results by well-capturing the target data distribution. Neve

Julian Iseringhausen, Michael Weinmann, Weizhen Huang, Matthias B. Hullin

Parquetry is the art and craft of decorating a surface with a pattern of differently colored veneers of wood, stone or other materials. Traditionally, the process of designing and making parquetry has been driven by color, using the texture found in real wood only for stylization or as a decorative effect. Here, we introduce a computational pipeline that dra

Shinya Sasa, Akimi Watanabe, Yutaka Matsuo

Free fermion system is the simplest quantum field theory which has the symmetry of Ding-Iohara-Miki algebra (DIM). DIM has S-duality symmetry, known as Miki automorphism which defines the transformation of generators. In this note, we introduce the second set of the fermionic basis (S-dual basis) which implement the duality transformation. It may be interpre

Song Fang, Mikael Skoglund, Karl Henrik Johansson, Hideaki Ishii

In this paper, we obtain generic bounds on the variances of estimation and prediction errors in time series analysis via an information-theoretic approach. It is seen in general that the error bounds are determined by the conditional entropy of the data point to be estimated or predicted given the side information or past observations. Additionally, we disco

Benjamin Audoux, Jean-Baptiste Meilhan

The reduced peripheral system was introduced by Milnor in the fifties for the study of links up to link-homotopy, i.e. up to isotopies and crossing changes within each link component. However, for four or more components, this invariant does not yield a complete link-homotopy invariant. This paper provides two characterizations of links having the same reduc

Bhairav Mehta, Manfred Diaz, Florian Golemo, Christopher J. Pal

Domain randomization is a popular technique for improving domain transfer, often used in a zero-shot setting when the target domain is unknown or cannot easily be used for training. In this work, we empirically examine the effects of domain randomization on agent generalization. Our experiments show that domain randomization may lead to suboptimal, high-vari

Alexander I. Jordan, Anja Mühlemann, Johanna F. Ziegel

In general, the solution to a regression problem is the minimizer of a given loss criterion, and depends on the specified loss function. The nonparametric isotonic regression problem is special, in that optimal solutions can be found by solely specifying a functional. These solutions will then be minimizers under all loss functions simultaneously as long as

Hongliang Jiang, Alessandro Sfondrini, Gabriele Tartaglino-Mazzucchelli

We investigate the behaviour of two-dimensional quantum field theories with $\mathcal{N}=(0,2)$ supersymmetry under a deformation induced by the `$T\bar{T}$&#39; composite operator. We show that the deforming operator can be defined by a point-splitting regularisation in such a way as to preserve $\mathcal{N}=(0,2)$ supersymmetry. As an example of this const

Mikhail Hlushchanka

A rational map $f:\widehat{\mathbb{C}}\to\widehat{\mathbb{C}}$ on the Riemann sphere $\widehat{\mathbb{C}}$ is called critically fixed if each critical point of $f$ is fixed under $f$. In this article, we study the properties of a combinatorial invariant, called the Tischler graph, associated with such a map. We show that the Tischler graph of a critically f

M. Sammon, Mitali Banerjee, B. I. Shklovskii

We analyze the data of the recent paper Nature 559, 205 (2018) and show that it contains an observation of thermal and electric conductivities of the doping layers in GaAs/AlGaAs heterostructures which violates the Wiedemann-Franz law. Namely, the measured thermal conductivity of the doping layers is similar to that of a metal while the electrical conductivi

Xiaobo Qu, Yihui Huang, Hengfa Lu, Tianyu Qiu

Nuclear magnetic resonance (NMR) spectroscopy serves as an indispensable tool in chemistry and biology but often suffers from long experimental time. We present a proof-of-concept of application of deep learning and neural network for high-quality, reliable, and very fast NMR spectra reconstruction from limited experimental data. We show that the neural netw

Dylan J. Foster, Spencer Greenberg, Satyen Kale, Haipeng Luo

We present a study of generalization for data-dependent hypothesis sets. We give a general learning guarantee for data-dependent hypothesis sets based on a notion of transductive Rademacher complexity. Our main result is a generalization bound for data-dependent hypothesis sets expressed in terms of a notion of hypothesis set stability and a notion of Radema

Krishan Kumar, Quan Liu, Jonas Hiller, Christine Schedel

We report an optically gated transistor composed of CdSe nanocrystals (NCs), sensitized with the dye Zinc beta-tetraaminophthalocyanine for operation in the first telecom window. This device shows a high ON/OFF ratio of six orders of magnitude in the red spectral region and an unprecedented 4.5 orders of magnitude at 847 nm. By transient absorption spectrosc

Aibek Alanov, Max Kochurov, Denis Volkhonskiy, Daniil Yashkov

We propose a novel multi-texture synthesis model based on generative adversarial networks (GANs) with a user-controllable mechanism. The user control ability allows to explicitly specify the texture which should be generated by the model. This property follows from using an encoder part which learns a latent representation for each texture from the dataset.

Zhaojun Qin, Shenyu Dai, Viktor G. Hadjiev, Chong Wang

Zero dimensional perovskite Cs4PbBr6 has attracted considerable attention recently not only because of its highly efficient green photoluminescence (PL), but also its two highly debated opposing mechanisms of the luminescence: embedded CsPbBr3 nanocrystals versus intrinsic Br vacancy states. After a brief discussion on the root cause of the controversy, we p

Pierluigi Zama Ramirez, Alessio Tonioni, Samuele Salti, Luigi Di Stefano

Recent works have proven that many relevant visual tasks are closely related one to another. Yet, this connection is seldom deployed in practice due to the lack of practical methodologies to transfer learned concepts across different training processes. In this work, we introduce a novel adaptation framework that can operate across both task and domains. Our

Avadhut V Purohit

The canonical theory of gravity together with the scalar field is written as a combined variable theory in ADM form, in the classical and quantum theory. FLRW $κ= 0$ cosmology is rewritten in the combined variable theory.

Ahmad Rashid, Alan Do-Omri, Md. Akmal Haidar, Qun Liu

Latent space based GAN methods and attention based sequence to sequence models have achieved impressive results in text generation and unsupervised machine translation respectively. Leveraging the two domains, we propose an adversarial latent space based model capable of generating parallel sentences in two languages concurrently and translating bidirectiona

Wanying Kang

We investigate how obliquity affects stratospheric humidity using a 3D general circulation model and find the stratosphere under high obliquity could be over 3 orders of magnitude moister than under the low obliquity equivalent, even with the same global annual mean surface temperature. Three complexities that only exist under high obliquity are found to be