January 2019 arXiv papers — page 12

Baiwei Wang, Daniel Gall

Ti1-xMgxN(001) layers with 0.00 {\leq} x {\leq} 0.49 are deposited on MgO(001) by reactive magnetron co-sputtering from titanium and magnesium targets in 5 mTorr pure N2 at 600 {\deg}C. X-ray diffraction {\omega}-2{\theta} scans, {\omega}-rocking curves, {\phi}-scans, and high resolution reciprocal space maps show that the Ti1-xMgxN layers are rock-salt stru

Ron Levie, Elvin Isufi, Gitta Kutyniok

This paper focuses on spectral filters on graphs, namely filters defined as elementwise multiplication in the frequency domain of a graph. In many graph signal processing settings, it is important to transfer a filter from one graph to another. One example is in graph convolutional neural networks (ConvNets), where the dataset consists of signals defined on

Ninoy Rahman, Oliver Just, H. -Thomas Janka

We present the new code NADA-FLD to solve multi-dimensional neutrino-hydrodynamics in full general relativity (GR) in spherical polar coordinates. The energy-dependent neutrino transport assumes the flux-limited diffusion (FLD) approximation and evolves the neutrino energy densities measured in the frame comoving with the fluid. Operator splitting is used to

Adam B. Mantz

The finite sensitivity of instruments or detection methods means that data sets in many areas of astronomy, for example cosmological or exoplanet surveys, are necessarily systematically incomplete. Such data sets, where the population being investigated is of unknown size and only partially represented in the data, are called "truncated" in the statistical l

Zhana Kuncheva, Giovanni Montana

The analysis of temporal networks has a wide area of applications in a world of technological advances. An important aspect of temporal network analysis is the discovery of community structures. Real data networks are often very large and the communities are observed to have a hierarchical structure referred to as multi-scale communities. Changes in the comm

Carlos Floyd, Garegin A. Papoian, Christopher Jarzynski

In modeling the interior of cells by simulating a reaction-diffusion master equation over a grid of compartments, one employs the assumption that the copy numbers of various chemical species are small, discrete quantities. We show that in this case, textbook expressions for the change in Gibbs free energy accompanying a chemical reaction or diffusion between

Francesco Mainardi, Enrico Masina

In this paper we survey the properties of the Schelkunoff modification of the Exponential integral and we generalize it with the Mittag-Leffler function. So doing we get a new special function (as far as we know) that may be relevant in linear viscoelasticity because of its complete monotonicity properties in the time domain. We also consider the generalized

V. A. Birulia, V. V. Strelkov

The high-order harmonic spectrum generated in two-color intense laser field under certain conditions has a pronounced maximum caused by the so called spectral caustic. Using a numerical solution of the 3D time-dependent Schr\"odinger equation we study the width of the maximum and the degree of the generation enhancement due to the caustic as a function of th

Sang Michael Xie, Stefano Ermon

Many machine learning tasks require sampling a subset of items from a collection based on a parameterized distribution. The Gumbel-softmax trick can be used to sample a single item, and allows for low-variance reparameterized gradients with respect to the parameters of the underlying distribution. However, stochastic optimization involving subset sampling is

Guobin Fang, Huimin Ma, Michelle Xia, Bo Zhang

In this paper, We propose a new style panel data factor stochastic volatility model with observable factors and unobservable factors based on the multivariate stochastic volatility model, which is mainly composed of three parts, such as the mean equation, volatility equation and factor volatility evolution. The stochastic volatility equation is a 1-step forw

A. Yu. Cherny, E. M. Anitas, V. A. Osipov, A. I. Kuklin

Small-angle scattering (SAS) of X-rays, neutrons or light from ensembles of randomly oriented and placed deterministic fractal structures are studied theoretically. In the standard analysis, a very few parameters can be determined from SAS data: the fractal dimension, and the lower and upper limits of the fractal range. The self-similarity of deterministic s

Pascal Mettes, Elise van der Pol, Cees G. M. Snoek

This paper introduces hyperspherical prototype networks, which unify classification and regression with prototypes on hyperspherical output spaces. For classification, a common approach is to define prototypes as the mean output vector over training examples per class. Here, we propose to use hyperspheres as output spaces, with class prototypes defined a pri

Meixin Zhu, Yinhai Wang, Ziyuan Pu, Jingyun Hu

A model used for velocity control during car following was proposed based on deep reinforcement learning (RL). To fulfil the multi-objectives of car following, a reward function reflecting driving safety, efficiency, and comfort was constructed. With the reward function, the RL agent learns to control vehicle speed in a fashion that maximizes cumulative rewa

Nic Ford, Justin Gilmer, Nicolas Carlini, Dogus Cubuk

Over the last few years, the phenomenon of adversarial examples --- maliciously constructed inputs that fool trained machine learning models --- has captured the attention of the research community, especially when the adversary is restricted to small modifications of a correctly handled input. Less surprisingly, image classifiers also lack human-level perfo

Biplav Acharya, Caitlin M. Seed, Donald W. Brenner, Alex I. Smirnov

The use of electrophoretic forces to tune friction at material-nanoparticle-liquid interfaces with static or low frequency (0.6-50 mHz) electric fields is reported for the first time. External electric fields were employed to reposition negatively charged TiO2 or positively charged Al2O3 nanoparticles suspended in water in directions perpendicular to a plana

Michael Allen, Nicholas Anderson, Asimina Hamakiotes, Ben Oltsik

From the Modularity Theorem proven by Wiles, Taylor, et al, we know that all elliptic curves are modular. It has been shown by Martin and Ono exactly which are represented by eta-quotients, and some examples of elliptic curves represented by modular forms that are linear combinations of eta-quotients have been given by Pathakjee, RosnBrick, and Yoong. In thi

Noah H Paulson, Brandon J Bocklund, Richard A Otis, Zi-Kui Liu

Phase fractions, compositions and energies of the stable phases as a function of macroscopic composition, temperature, and pressure (X-T-P) are the principle correlations needed for the design of new materials and improvement of existing materials. They are the outcomes of thermodynamic modeling based on the CALculation of PHAse Diagrams (CALPHAD) approach.

Hamza Adnane, Matteo Bina, Francesco Albarelli, Abdelhakim Gharbi

We address quantum state engineering of single- and two-mode states by means of non-deterministic noiseless linear amplifiers (NLAs) acting on Gaussian states. In particular, we show that NLAs provide an effective scheme to generate highly non-Gaussian and non-classical states. Additionally, we show that the amplification of a two-mode squeezed vacuum state

Fengchun Zhang, Wei Fan

Of the wide palette of 5G features, ultra-wide bandwidth and large-scale antenna configuration are regarded as the essential enabling technology components at millimeter wave (mmWave) communication. Accurate knowledge of delay and angle information of multipath components is essential for many applications in mmWave systems. There is a strong need for a low

Irfan Alam

The coordinates along any fixed direction(s), of points on the sphere $S^{n-1}(\sqrt{n})$, roughly follow a standard Gaussian distribution as $n$ approaches infinity. We revisit this classical result from a nonstandard analysis perspective, providing a new proof by working with hyperfinite dimensional spheres. We also set up a nonstandard theory for the asym

Mark Mace, Vladimir V. Skokov, Prithwish Tribedy, Raju Venugopalan

It was argued in arXiv:1805.09342 and arXiv:1807.00825 that the systematics of the azimuthal anisotropy coefficients $v_{2,3}$ measured in ultrarelativistic light-heavy ion collisions at RHIC and the LHC can be described in an initial state dilute-dense Color Glass Condensate (CGC) framework. We elaborate here on the discussion in these papers and provide fu

A. Murat Ozbayoglu, Nuri Durlu, N. Kaan Caliskan

In this study an automated software model using digital image processing techniques is proposed for extracting the image characteristics and contiguity of liquid phase sintered tungsten heavy alloys. The developed model takes a typical image as input and processes it with no human intervention and provides the corresponding image characteristics and contigui

Preetam Nandy, Kinjal Basu, Shaunak Chatterjee, Ye Tu

Design of experiments and estimation of treatment effects in large-scale networks, in the presence of strong interference, is a challenging and important problem. Most existing methods' performance deteriorates as the density of the network increases. In this paper, we present a novel strategy for accurately estimating the causal effects of a class of treatm

Micheal S. Berger, Maria Dawid

Superheavy neutrinos can, via the seesaw model, provide a mechanism for lepton number violation. If they are combined with flavor violation as characterized by the Froggatt-Nielsen mechanism, then the phenomenology for the neutrinos in oscillation experiments, neutrinoless double beta decay, and other experiments can be described by a relatively few number o

Vivien Sainte Fare Garnot, Loic Landrieu, Sebastien Giordano, Nesrine Chehata

In this article, we investigate several structured deep learning models for crop type classification on multi-spectral time series. In particular, our aim is to assess the respective importance of spatial and temporal structures in such data. With this objective, we consider several designs of convolutional, recurrent, and hybrid neural networks, and assess

Tibor Rakovszky, Frank Pollmann, C. W. von Keyserlingk

We investigate the dynamics of quantum entanglement after a global quench and uncover a qualitative difference between the behavior of the von Neumann entropy and higher R\'enyi entropies. We argue that the latter generically grow \emph{sub-ballistically}, as $\propto\sqrt{t}$, in systems with diffusive transport. We provide strong evidence for this in both

Hao Wang, Berk Ustun, Flavio P. Calmon

When the performance of a machine learning model varies over groups defined by sensitive attributes (e.g., gender or ethnicity), the performance disparity can be expressed in terms of the probability distributions of the input and output variables over each group. In this paper, we exploit this fact to reduce the disparate impact of a fixed classification mo

Yunhao Tang, Shipra Agrawal

In this work, we show that discretizing action space for continuous control is a simple yet powerful technique for on-policy optimization. The explosion in the number of discrete actions can be efficiently addressed by a policy with factorized distribution across action dimensions. We show that the discrete policy achieves significant performance gains with

Boris Braverman, Akio Kawasaki, Edwin Pedrozo-Peñafiel, Simone Colombo

Spin squeezing can improve atomic precision measurements beyond the standard quantum limit (SQL), and unitary spin squeezing is essential for improving atomic clocks. We report substantial and nearly unitary spin squeezing in $^{171}$Yb, an optical lattice clock atom. The collective nuclear spin of $\sim 10^3$ atoms is squeezed by cavity feedback, using ligh

Wei-Shu Hou, Rishabh Jain, Chung Kao, Masaya Kohda

In a general two Higgs doublet model, we study flavor changing neutral Higgs (FCNH) decays into leptons at hadron colliders, $pp \to \phi^0 \to \tau^\mp\mu^\pm +X$, where $\phi^0$ could be a CP-even scalar ($h^0$, $H^0$) or a CP-odd pseudoscalar ($A^0$). The light Higgs boson $h^0$ is found to resemble closely the Standard Model Higgs boson at the Large Hadr

Giulio Bonelli, Fabrizio Del Monte, Pavlo Gavrylenko, Alessandro Tanzini

In this paper we study the extension of Painlev\'e/gauge theory correspondence to circular quivers by focusing on the special case of $SU(2)$ $\mathcal{N}=2^*$ theory. We show that the Nekrasov-Okounkov partition function of this gauge theory provides an explicit combinatorial expression and a Fredholm determinant formula for the tau-function describing isom

Trond Linjordet, Krisztian Balog

It is held as a truism that deep neural networks require large datasets to train effective models. However, large datasets, especially with high-quality labels, can be expensive to obtain. This study sets out to investigate (i) how large a dataset must be to train well-performing models, and (ii) what impact can be shown from fractional changes to the datase

Ranjani Seshadri, Anirban Dutta, Diptiman Sen

We study the effects of periodic driving on a variant of the Bernevig-Hughes-Zhang (BHZ) model defined on a square lattice. In the absence of driving, the model has both topological and nontopological phases depending on the different parameter values. We also study the anisotropic BHZ model and show that, unlike the isotropic model, it has a nontopological

Farinaldo S. Queiroz, Clarissa Siqueira

Dark matter annihilations have been fiercely restricted by the non-observation of excess events in indirect detection probes. Typically the interactions that dictate annihilation are also present in the dark matter-nucleon scattering cross section, also severely constrained by direct detection experiments. Semi-annihilations arise as a possible way to amelio

Ivan Garozzo, Gabriele Lo Monaco, Noppadol Mekareeya

A local SL(2,Z) transformation on the Type IIB brane configuration gives rise to an interesting class of superconformal field theories, known as the S-fold CFTs. Previously it has been proposed that the corresponding quiver theory has a link involving the T(U(N)) theory. In this paper, we generalise the preceding result by studying quivers that contain a T(G

Niklas Mueller, Raju Venugopalan

We discuss an ab initio world-line approach to constructing phase space distributions in systems with internal symmetries. Starting from the Schwinger-Keldysh real time path integral in quantum field theory, we derive the most general extension of the Wigner phase space distribution to include color and spin degrees of freedom in terms of dynamical Grassmann

Murray Brightman, Fiona A. Harrison, Matteo Bachetti, Yanjun Xu

Ultraluminous X-ray (ULX) pulsars are a new class of object powered by apparent super-critical accretion onto magnetized neutron stars. Three sources in this class identified so far; M82 X-2, NGC 5907 ULX-1 and NGC 7793 P13, have been found to have two properties in common; $\sim1$-s spin periods, and for NGC 5907 ULX-1 and NGC 7793 P13 periodic X-ray flux m

David Izquierdo-Villalba, Silvia Bonoli, Daniele Spinoso, Yetli Rosas-Guevara

We study the cosmological build-up of pseudobulges using the LGalaxies semi-analytical model for galaxy formation with a new approach for following separately the assembly of classical bulges and pseudobulges. Classical bulges are assumed to be the result of violent processes (i.e., mergers and starbursts), while the formation of pseudobulges is connected to

Jonathan J. Heckman, Craig Lawrie, Ling Lin, Jeremy Sakstein

We study the phenomenology of a recent string construction with a quantum mechanically stable dark energy. A mild supersymmetry protects the vacuum energy but also allows $O(10 - 100)$ TeV scale superpartner masses. The construction is holographic in the sense that the 4D spacetime is generated from "pixels" originating from five-branes wrapped over metastab

Johannes Kölbl, Arne Barfuss, Mark Kaspercyzk, Lucas Thiel

We demonstrate the use of shortcuts to adiabaticity protocols for initialisation, readout, and coherent control of dressed states generated by closed-contour, coherent driving of a single spin. Such dressed states have recently been shown to exhibit efficient coherence protection, beyond what their two-level counterparts can offer. Our state transfer protoco

Yoshiki Matsuoka, Masafusa Onoue, Nobunari Kashikawa, Michael A. Strauss

We report the discovery of a quasar at z = 7.07, which was selected from the deep multi-band imaging data collected by the Hyper Suprime-Cam (HSC) Subaru Strategic Program survey. This quasar, HSC J124353.93+010038.5, has an order of magnitude lower luminosity than do the other known quasars at z > 7. The rest-frame ultraviolet absolute magnitude is M1450 =

Albert T. Schmitz, Sheng-Jie Huang, Abhinav Prem

The entanglement spectrum (ES) provides a barometer of quantum entanglement and encodes physical information beyond that contained in the entanglement entropy. In this paper, we explore the ES of stabilizer codes, which furnish exactly solvable models for a plethora of gapped quantum phases of matter. Studying the ES for stabilizer Hamiltonians in the presen

Eslam Khalaf, Alex J. Kruchkov, Grigory Tarnopolsky, Ashvin Vishwanath

When two monolayers of graphene are stacked with a small relative twist angle, the resulting band structure exhibits a remarkably flat pair of bands at a sequence of 'magic angles' where correlation effects can induce a host of exotic phases. Here, we study a class of related models of $n$-layered graphene with alternating relative twist angle $\pm \theta$ w

Ivo de Medeiros Varzielas, Jim Talbert

We study the implications of single leptoquark extensions of the Standard Model (SM) under the assumption that their enhanced Yukawa sectors are invariant under global Abelian flavour symmetries already present in SM mass terms. Such symmetries, assumed to be the `residual' subgroups of an ultra-violet flavour theory, have previously been considered in order

Pavel Fileviez Perez, Clara Murgui

We discuss the visibility of gamma lines from dark matter annihilation. We point out a class of theories for dark matter which predict the existence of gamma lines with striking features. In these theories, the final state radiation processes are highly suppressed and one could distinguish easily the gamma lines from the continuum spectrum. We discuss the ma

Chenxing Dong, Justin S. Spilker, Anthony H. Gonzalez, Yordanka Apostolovski

We present Atacama Large Millimeter/submillimeter Array (ALMA) observations of high-J CO lines ($J_\mathrm{up}=6$, 7, 8) and associated dust continuum towards five strongly lensed, dusty, star-forming galaxies (DSFGs) at redshift $z = 2.7$-5.7. These galaxies, discovered in the South Pole Telescope survey, are observed at $0.2''$-$0.4''$ resolution with ALMA

Yuan Li, Greg L. Bryan, Eliot Quataert

Asymptotic Giant Branch (AGB) winds from evolved stars not only provide a non-trivial amount of mass and energy return, but also produce dust grains in massive elliptical galaxies. Due to the fast stellar velocity and the high ambient temperature, the wind is thought to form a comet-like tail, similar to Mira in the Local Bubble. Many massive elliptical gala

Michael J. Baker, Javier Fuentes-Martin, Gino Isidori, Matthias König

We present a detailed analysis of the collider signatures of TeV-scale massive vector bosons motivated by the hints of lepton flavour non-universality observed in $B$-meson decays. We analyse three representations that necessarily appear together in a large class of ultraviolet-complete models: a colour-singlet ($Z'$), a colour-triplet (the $U_1$ leptoquark)

T. Eftekhari, E. Berger, B. Margalit, P. K. Blanchard

We present the detection of an unresolved radio source coincident with the position of the Type I superluminous supernova (SLSN) PTF10hgi ($z=0.098$) about 7.5 years post-explosion, with a flux density of $F_\nu(6\,\,{\rm GHz)}\approx 47.3\ \mu Jy$ and a luminosity of $L_\nu(6\,\,{\rm GHz})\approx 1.1\times 10^{28}$ erg s$^{-1}$ Hz$^{-1}$. This represents th

Orr Abramoff, Liron Barak, Itay M. Bloch, Luke Chaplinsky

We present new direct-detection constraints on eV-to-GeV dark matter interacting with electrons using a prototype detector of the Sub-Electron-Noise Skipper-CCD Experimental Instrument. The results are based on data taken in the MINOS cavern at the Fermi National Accelerator Laboratory. We focus on data obtained with two distinct readout strategies. For the

Ken Makino, Yutaka Fujita, Kumiko Nobukawa, Hironori Matsumoto

Recent discovery of the X-ray neutral iron line (Fe I K\alpha at 6.40 keV) around several supernova remnants (SNRs) show that MeV cosmic-ray (CR) protons are distributed around the SNRs and are interacting with neutral gas there. We propose that these MeV CRs are the ones that have been accelerated at the SNRs together with GeV-TeV CRs. In our analytical mod

Riccardo Adami, Simone Dovetta, Alice Ruighi

We summarize features and results on the problem of the existence of Ground States for the Nonlinear Schr\"odinger Equation on doubly-periodic metric graphs. We extend the results known for the two--dimensional square grid graph to the honeycomb, made of infinitely-many identical hexagons. Specifically, we show how the coexistence between one--dimensional an

Peng Qi, Timothy Dozat, Yuhao Zhang, Christopher D. Manning

This paper describes Stanford's system at the CoNLL 2018 UD Shared Task. We introduce a complete neural pipeline system that takes raw text as input, and performs all tasks required by the shared task, ranging from tokenization and sentence segmentation, to POS tagging and dependency parsing. Our single system submission achieved very competitive performance

Helene Gertov, Ann E. Nelson, Ashley Perko, Devin G. E. Walker

We give an explicit example of a composite Higgs model with a pseudo-Nambu-Goldstone Higgs in which the top Yukawa coupling is generated via the partial compositeness mechanism. This mechanism requires composite top partners which are relatively light compared to the typical mass scale of the strongly coupled theory. While most studies of the phenomenology o

William I. Cowley, Karina I. Caputi, Smaran Deshmukh, Matthew L. N. Ashby

In this work, we use measurements of galaxy stellar mass and two-point angular correlation functions to constrain the stellar-to-halo mass ratios (SHMRs) of passive and \np\ galaxies at $z\sim2-3$, as identified in the \emph{Spitzer} Matching Survey of the UltraVISTA ultra-deep Stripes (SMUVS). We adopt a sophisticated halo modeling approach to statistically

Ved V. Datar, Vamsi Pritham Pingali

We provide a moment map interpretation for the coupled K\"ahler-Einstein equations introduced by Hultgren and Witt Nystr\"om, and in the process introduce a more general system of equations, which we call coupled cscK equations. A differentio-geometric formulation of the corresponding Futaki invariant is obtained and a notion of K-polystability is defined fo

Diego Díaz-Domínguez, Travis Gagie, Gonzalo Navarro

Converting a set of sequencing reads into a lossless compact data structure that encodes all the relevant biological information is a major challenge. The classical approaches are to build the string graph or the de Bruijn graph. Each has advantages over the other depending on the application. Still, the ideal setting would be to have an index of the reads t

Ahsan S. Alvi, Binxin Ru, Jan Calliess, Stephen J. Roberts

Batch Bayesian optimisation (BO) has been successfully applied to hyperparameter tuning using parallel computing, but it is wasteful of resources: workers that complete jobs ahead of others are left idle. We address this problem by developing an approach, Penalising Locally for Asynchronous Bayesian Optimisation on $k$ workers (PLAyBOOK), for asynchronous pa

Alexandre Ern, Jean-Luc Guermond

In this paper we investigate the approximation of a diffusion model problem with contrasted diffusivity and the error analysis of various nonconforming approximation methods. The essential difficulty is that the Sobolev smoothness index of the exact solution may be just barely larger than one. The lack of smoothness is handled by giving a weak meaning to the

L. Elisa Celis, Anay Mehrotra, Nisheeth K. Vishnoi

Online advertising platforms are thriving due to the customizable audiences they offer advertisers. However, recent studies show that advertisements can be discriminatory with respect to the gender or race of the audience that sees the ad, and may inadvertently cross ethical and/or legal boundaries. To prevent this, we propose a constrained ad auction framew

Yunlong Wang, Ahmed Fadhil, Harald Reiterer

Unhealthy lifestyles could cause many chronic diseases, which bring patients and their families much burden. Research has shown the potential of digital technologies for supporting health behavior change to help us prevent these chronic diseases. The HCI community has contributed to the research on health behavior change for more than a decade. In this paper

A. Sergyeyev, A. Wojnar

Two exact solutions for $n=0$ and $n=1$ of the Palatini-modified Lane-Emden equation are found. We have employed these solutions to describe a Palatini-Newtonian neutron star and compared the result with the pure Newtonian counterpart. It turned out that for the negative parameter of the Starobinsky model the star is heavier and larger.

Jusak Tandean

We explore the strangeness-changing decays of the lightest hyperons into another baryon plus missing energy within and beyond the standard model (SM). In the SM these processes arise from the loop-induced quark transition $s\to d\nu\bar\nu$ and their branching fractions are estimated to be less than $10^{-11}$. In the presence of new physics (NP) the rates o

Gong Cheng, Brian Swingle

We study scrambling in a model consisting of a number $N$ of $M$-component quantum rotors coupled by random infinite-range interactions. This model is known to have both a paramagnetic phase and a spin glass phase separated by second order phase transition. We calculate in perturbation theory the squared commutator of rotor fields at different sites in the p

Daniel Goldwater, Peter Barker, Angelo Bassi, Sandro Donadi

We present a technique for recovering the spectrum of a non-Markovian bosonic bath and/or non-Markovian noises coupled to an harmonic oscillator. The treatment is valid under the conditions that the environment is large and hot compared to the oscillator, and that its temporal auto-correlation functions are symmetric with respect to time translation and refl

John Wieting, Douwe Kiela

We explore various methods for computing sentence representations from pre-trained word embeddings without any training, i.e., using nothing but random parameterizations. Our aim is to put sentence embeddings on more solid footing by 1) looking at how much modern sentence embeddings gain over random methods---as it turns out, surprisingly little; and by 2) p

L. Elisa Celis, Vijay Keswani

Motivated by concerns that machine learning algorithms may introduce significant bias in classification models, developing fair classifiers has become an important problem in machine learning research. One important paradigm towards this has been providing algorithms for adversarially learning fair classifiers (Zhang et al., 2018; Madras et al., 2018). We fo

Bo wang, Hao Hu, Caixia Zhang

It is well known that the P3P problem could have 1, 2, 3 and at most 4 positive solutions under different configurations among its 3 control points and the position of the optical center. Since in any real applications, the knowledge on the exact number of possible solutions is a prerequisite for selecting the right one among all the possible solutions, the

Mohammad. Mohammadi, Rohollah. Gheisari

In this paper, extended Klein-Gordon field systems will be introduced. Theoretically, it will be shown that for a special example of these systems, it is possible to have a single zero rest mass soliton solution, which is forced to move at the speed of light provided it is considered a non-deformed rigid object. This special soliton solution has the minimum

Tatyana Ivanova, Dimiter Vakarelov

Contact algebra is one of the main tools in the region-based theory of space. It is an extension of Boolean algebra with a relation called contact. The elements of the Boolean algebra are considered as formal representations of physical bodies. The contact relation is used also to define some other important mereotopological relations like non-tangential inc

S. de Franciscis, J. Pascual-Granado, J. C. Suárez, A. García Hernández

Fractal fingerprints have been found recently in the light curves of several {\delta} Scuti stars observed by CoRoT satellite. This sole fact might pose a problem for the detection of pulsation frequencies using classical pre-whitening techniques, but it is also a potentially rich source for information about physical mechanisms associated to stellar variabi

Robert Beverly, Mark Allman

Obtaining sound inferences over remote networks via active or passive measurements is difficult. Active measurement campaigns face challenges of load, coverage, and visibility. Passive measurements require a privileged vantage point. Even networks under our own control too often remain poorly understood and hard to diagnose. As a step toward the democratizat

Radhesh Krishnan Konoth, Rolf van Wegberg, Veelasha Moonsamy, Herbert Bos

In this study, we examine the behavior and profitability of modern malware that mines cryptocurrency. Unlike previous studies, we look at the cryptocurrency market as a whole, rather than just Bitcoin. We not only consider PCs, but also mobile phones, and IoT devices. In the past few years, criminals have attacked all these platforms for the purpose of crypt

ATLAS Collaboration

This paper presents a measurement of forward-forward and forward-central dijet azimuthal angular correlations and conditional yields in proton-proton ($pp$) and proton-lead ($p$+Pb) collisions as a probe of the nuclear gluon density in regions where the fraction of the average momentum per nucleon carried by the parton entering the hard scattering is low. In

Aleksandra Słapik, Jerzy Łuczka, Peter Hänggi, Jakub Spiechowicz

A prerequisite for isolating diseased cells requires a mechanism for effective mass-based separation. This objective, however, is generally rather challenging because typically no valid correlation exists between the size of the particles and their mass value. We consider an inertial Brownian particle moving in a symmetric periodic potential and subjected to

Vighnesh Birodkar, Hossein Mobahi, Samy Bengio

Large datasets have been crucial to the success of deep learning models in the recent years, which keep performing better as they are trained with more labelled data. While there have been sustained efforts to make these models more data-efficient, the potential benefit of understanding the data itself, is largely untapped. Specifically, focusing on object r

Charlotte Kirchhoff-Lukat

Generalized complex (GC) geometry interpolates between ordinary symplectic and complex geometry. Stable generalized complex manifolds (first introduced by Cavalcanti, Gualtieri in 2015) carry a Poisson structure which is generically symplectic, but degenerates on a (real) codimension-2 submanifold. Up to gauge equivalence, the stable generalized complex stru

Piotr Sapiezynski, Wesley Zeng, Ronald E. Robertson, Alan Mislove

In this work, we introduce a novel metric for auditing group fairness in ranked lists. Our approach offers two benefits compared to the state of the art. First, we offer a blueprint for modeling of user attention. Rather than assuming a logarithmic loss in importance as a function of the rank, we can account for varying user behaviors through parametrization

Michele Merler, Nalini Ratha, Rogerio S. Feris, John R. Smith

Face recognition is a long standing challenge in the field of Artificial Intelligence (AI). The goal is to create systems that accurately detect, recognize, verify, and understand human faces. There are significant technical hurdles in making these systems accurate, particularly in unconstrained settings due to confounding factors related to pose, resolution

Y. Liao, A. Vakanski, M. Xian

Computer-aided assessment of physical rehabilitation entails evaluation of patient performance in completing prescribed rehabilitation exercises, based on processing movement data captured with a sensory system. Despite the essential role of rehabilitation assessment toward improved patient outcomes and reduced healthcare costs, existing approaches lack vers

M. Beretta, L. Cardani, N. Casali, L. Gironi

The CUPID-0 experiment searches for neutrinoless double beta decay ($0\nu\beta\beta$) using the first array of enriched Zn$^{82}$Se scintillating bolometers with double (heat and light) read-out. To further enhance the CUPID-0 detector performances, the heat-light correlation has been exploited to improve the energy resolution. Different decorrelation algori

Jaume Alonso, Sonja Hohloch

Semitoric systems are a special class of four-dimensional completely integrable systems where one of the first integrals generates an $\mathbb{S}^1$-action. They were classified by Pelayo & Vu Ngoc in terms of five symplectic invariants about a decade ago. We give a survey over the recent progress which has been mostly focused on the explicit computation of

John Franks, Bryna Kra

Let ${\mathcal P}\subset{\mathbb Z}^2$ be a convex polygon with each vertex in it labeled by an element from a finite set and such that the labeling of each vertex $v\in {\mathcal P}$ is uniquely determined by the labeling of all other points in the polygon. We introduce a class of ${\mathbb Z}^2$-shift systems, the {\em polygonal shifts}, determined by such

Juš Lozej, Dejan Štepec, Vitomir Štruc, Peter Peer

Despite the rise of deep learning in numerous areas of computer vision and image processing, iris recognition has not benefited considerably from these trends so far. Most of the existing research on deep iris recognition is focused on new models for generating discriminative and robust iris representations and relies on methodologies akin to traditional iri

Felix Wu, Angela Fan, Alexei Baevski, Yann N. Dauphin

Self-attention is a useful mechanism to build generative models for language and images. It determines the importance of context elements by comparing each element to the current time step. In this paper, we show that a very lightweight convolution can perform competitively to the best reported self-attention results. Next, we introduce dynamic convolutions

Duc Minh Nguyen, Robert Calderbank, Nikos Deligiannis

The problem of completing high-dimensional matrices from a limited set of observations arises in many big data applications, especially, recommender systems. Existing matrix completion models generally follow either a memory- or a model-based approach, whereas, geometric matrix completion models combine the best from both approaches. Existing deep-learning-b

Giacomo Guarnieri, Gabriel T. Landi, Stephen R. Clark, John Goold

Autonomous engines operating at the nano-scale can be prone to deleterious fluctuations in the heat and particle currents which increase, for fixed power output, the more reversible the operation regime is. This fundamental trade-off between current fluctuations and entropy production forms the basis of the recently formulated thermodynamic uncertainty relat

Kunnath Sandeep, Cyril TIntarev

For many known non-compact embeddings of two Banach spaces $E\hookrightarrow F$, every bounded sequence in $E$ has a subsequence that takes form of a \emph{profile decomposition} - a sum of clearly structured terms with asymptotically disjoint supports plus a remainder that vanishes in the norm of $F$. In this paper we construct a profile decomposition for a

Manuel Pulido, Peter Jan vanLeeuwen, Derek J. Posselt

Recently, some works have suggested methods to combine variational probabilistic inference with Monte Carlo sampling. One promising approach is via local optimal transport. In this approach, a gradient steepest descent method based on local optimal transport principles is formulated to transform deterministically point samples from an intermediate density to

Chad A. Madsen, Jenna E. Samra, Giulio Del Zanna, Edward E. DeLuca

We present coordinated coronal observations of the August 21, 2017 total solar eclipse with the Airborne Infrared Spectrometer (AIR-Spec) and the Extreme-ultraviolet Imaging Spectrometer (EIS). These instruments provide an unprecedented view of the solar corona in two disparate wavelength regimes, the near to mid infrared (IR) and the extreme ultraviolet (EU

Tobias Graß

Using a field-theoretic approach within the Schwinger-Keldysh formalism, we study a Bose-Hubbard model in the presence of a driving field and dissipation due to one-body losses. We recover the bistability diagram from the Gross-Pitaevski equation and analyze the different phases with respect to their elementary excitations and correlations. We find the low-d

Peter Mitrano, Jordan Burklund, Michael Giancola, Carlo Pinciroli

We present a decentralized algorithm to achieve segregation into an arbitrary number of groups with swarms of autonomous robots. The distinguishing feature of our approach is in the minimalistic assumptions on which it is based. Specifically, we assume that (i) Each robot is equipped with a ternary sensor capable of detecting the presence of a single nearby

Dan Zhang, Anna Khoreva

Training of Generative Adversarial Networks (GANs) is notoriously fragile, requiring to maintain a careful balance between the generator and the discriminator in order to perform well. To mitigate this issue we introduce a new regularization technique - progressive augmentation of GANs (PA-GAN). The key idea is to gradually increase the task difficulty of th

Jakob Schwichtenberg

Gauge symmetries are often highlighted as a fundamental cornerstone of modern physics. But at the same time, it is commonly emphasized that gauge symmetries are not a fundamental feature of nature but merely redundancies in our description. We argue that this paradoxical situation can be resolved by a proper definition of the relevant notions like "local", "

Severino T. Melo

A C*algebra A generated by a class of zero-order classical pseudodifferential operator on a cylinder RxB, where B is a compact riemannian manifold, containing operators with periodic symbols, is considered. A description of the K-theory index map associated to the continuous extension to A of the principal-symbol map is given. That index map takes values in

Szymon Knop, Marcin Mazur, Jacek Tabor, Igor Podolak

In this paper we discuss a class of AutoEncoder based generative models based on one dimensional sliced approach. The idea is based on the reduction of the discrimination between samples to one-dimensional case. Our experiments show that methods can be divided into two groups. First consists of methods which are a modification of standard normality tests, wh

Moritz Helias, David Dahmen

These notes attempt a self-contained introduction into statistical field theory applied to neural networks of rate units and binary spins. The presentation consists of three parts: First, the introduction of fundamental notions of probabilities, moments, cumulants, and their relation by the linked cluster theorem, of which Wick's theorem is the most importan

Juncai He, Jinchao Xu

We develop a unified model, known as MgNet, that simultaneously recovers some convolutional neural networks (CNN) for image classification and multigrid (MG) methods for solving discretized partial differential equations (PDEs). This model is based on close connections that we have observed and uncovered between the CNN and MG methodologies. For example, poo

Mojtaba Dehmollaian, Guillaume Lavigne, Christophe Caloz

This paper compares Tensor Boundary Conditions (TBCs), which were introduced to model multilayered dielectric structures, with Generalized Sheet Transition Conditions (GSTCs), which have been recently used to model metasurfaces. It shows that TBCs, with their 3 scalar parameters, are equivalent to the direct-isotropic -- cross-antiisotropic, reciprocal and n

Julian Renner, Sven Puchinger, Antonia Wachter-Zeh

We propose and analyze an interleaved variant of Loidreau's rank-metric cryptosystem based on rank multipliers. We analyze and adapt several attacks on the system, propose design rules, and study weak keys. Finding secure instances requires near-MRD rank-metric codes which are not investigated in the literature. Thus, we propose a random code construction th