November 2018 arXiv papers — page 53

Miguel N. Walsh

We establish sharp estimates that adapt the polynomial method to arbitrary varieties. These include a partitioning theorem, estimates on polynomials vanishing on fixed sets and bounds for the number of connected components of real algebraic varieties. As a first application, we provide a general incidence estimate that is tight in its dependence on the size,

Khashayar Gatmiry, Manuel Gomez-Rodriguez

The standard greedy algorithm has been recently shown to enjoy approximation guarantees for constrained non-submodular nondecreasing set function maximization. While these recent results allow to better characterize the empirical success of the greedy algorithm, they are only applicable to simple cardinality constraints. In this paper, we study the problem o

Erik Wallace

We generalize the lemmas of Thomas Kretschmer to arbitrary number fields, and apply them with a 2-descent argument to obtain bounds for families of elliptic curves over certain imaginary quadratic number fields with class number 1. One such family occurs in the congruent number problem. We consider the congruent number problem over these quadratic number fie

Kevin Gilboy, Khaled Sayed, Niteesh Sundaram, Kara Bocan

Development of fast methods to conduct in silico experiments using computational models of cellular signaling is a promising approach toward advances in personalized medicine. However, software-based cellular network simulation has run-times plagued by wasted CPU cycles and unnecessary processes. Hardware-based simulation affords substantial speedup, but pri

Zura Kakushadze

We propose factor models for the cross-section of daily cryptoasset returns and provide source code for data downloads, computing risk factors and backtesting them out-of-sample. In "cryptoassets" we include all cryptocurrencies and a host of various other digital assets (coins and tokens) for which exchange market data is available. Based on our empirical a

Pankaj Bodani, Kumar Shreshtha, Shashikant Sharma

This paper addresses the task of semantic segmentation of orthoimagery using multimodal data e.g. optical RGB, infrared and digital surface model. We propose a deep convolutional neural network architecture termed OrthoSeg for semantic segmentation using multimodal, orthorectified and coregistered data. We also propose a training procedure for supervised tra

Theo Torres, Sam Patrick, Maurício Richartz, Silke Weinfurtner

The late stages of the relaxation process of a black hole are expected to depend only on its mass and angular momentum and not on the details of its formation process. Inspired by recent analogue gravity experiments, which demonstrate that certain black hole processes take place in gravitational and hydrodynamical systems alike, we conduct an experiment to s

Vicente Atal, Cristiano Germani

We re-analyse current single-field inflationary models related to primordial black holes formation. We do so by taking into account recent developments on the estimations of their abundances and the influence of non-gaussianities. We show that, for all of them, the gaussian approximation, which is typically used to estimate the primordial black holes abundan

Tamás Király, Yu Yokoi

Matchings and coverings are central topics in graph theory. The close relationship between these two has been key to many fundamental algorithmic and polyhedral results. For mixed graphs, the notion of matching forest was proposed as a common generalization of matchings and branchings. In this paper, we propose the notion of mixed edge cover as a covering co

Neelima

In this article, well-posedness of stochastic anisotropic $p$-Laplace equation driven by L\'evy noise is shown. Such an equation in deterministic setting was considered by Lions [7]. The results obtained in this article can be applied to solve a large class of semilinear and quasilinear stochastic partial differential equations.

Viviana del Barco, Luiz A. B. San Martin

Let $\mathbb{F}_{\Theta }=G/P_{\Theta }$ be a flag manifold associated to a non-compact real simple Lie group $G$ and the parabolic subgroup $% P_{\Theta }$. This is a closed subgroup of $G$ determined by a subset $% \Theta $ of simple restricted roots of $\mathfrak{g}=Lie(G)$. This paper computes the second de Rham cohomology group of $\mathbb{F}_\Theta$. W

Jasabanta Patro, Sabyasachee Baruah, Vivek Gupta, Monojit Choudhury

In this paper, we consider a dataset comprising press releases about health research from different universities in the UK along with a corresponding set of news articles. First, we do an exploratory analysis to understand how the basic information published in the scientific journals get exaggerated as they are reported in these press releases or news artic

Bob de Ruiter, George Kachergis

Detecting deception in natural language has a wide variety of applications, but because of its hidden nature there are currently no public, large-scale sources of labeled deceptive text. This work introduces the Mafiascum dataset [1], a collection of over 700 games of Mafia, in which players are randomly assigned either deceptive or non-deceptive roles and t

Vladimir V. Konotop, Dmitry A. Zezyulin

We describe one-dimensional stationary scattering of a two-component wave field by a non-Hermitian matrix potential which features odd-$PT$ symmetry, i.e., symmetry with $(PT)^2=-1$. The scattering is characterized by a $4\times 4$ transfer matrix. The main attention is focused on spectral singularities which are classified into two types. Weak spectral sing

Ruben A. Hidalgo

Recently, Gareth Jones observed that every finite group $G$ can be realized as the group of automorphisms of some dessin d'enfant ${\mathcal D}$. In this paper, complementing Gareth's result, we prove that for every possible action of $G$ as a group of orientation-preserving homeomorphisms on a closed orientable surface of genus $g \geq 2$, there is a dessin

Nathan Dowlin

A well-known conjecture of Rasmussen states that for any knot $K$ in $S^{3}$, the rank of the reduced Khovanov homology of $K$ is greater than or equal to the rank of the reduced knot Floer homology of $K$. This rank inequality is supposed to arise as the result of a spectral sequence from Khovanov homology to knot Floer homology. Using an oriented cube of r

Rashmi Ballamajalu, Srijith Nair, Shayal Chhabra, Sumit K Monga

Air pollution is ranked as the second most serious risk for public health in India after malnutrition. The lack of spatially and temporally distributed air quality information prevents a scientific study on its impact on human health and on the national economy. In this paper, we present our initial efforts toward SATVAM, Streaming Analytics over Temporal Va

Christian Herrmann

We study the computational complexity of satisfiability problems for classes of simple finite height (ortho)complemented modular lattices $L$. For single finite $L$, these problems are shown tobe $\mc{NP}$-complete; for $L$ of height at least $3$, equivalent to a feasibility problem for the division ring associated with $L$. Moreover, it is shown that the eq

Jérémie Bettinelli

We unify and extend previous bijections on plane quadrangulations to bipartite and quasibipartite plane maps. Starting from a bipartite plane map with a distinguished edge and two distinguished corners (in the same face or in two different faces), we build a new plane map with a distinguished vertex and two distinguished half-edges directed toward the vertex

Panagiotis Polymerakis

We prove that if a Riemannian covering preserves the bottom of the spectrum of a Schr\"{o}dinger operator, which belongs to the discrete spectrum of the operator on the base manifold, then the covering is amenable.

Peter Hintz

We prove microlocal estimates at the trapped set of asymptotically Kerr spacetimes: these are spacetimes whose metrics decay inverse polynomially in time to a stationary subextremal Kerr metric. This combines two independent results. The first one is purely dynamical: we show that the stable and unstable manifolds of a decaying perturbation of a time-transla

Bander Alsulami, Spiros Mancoridis

Behavioral malware detection aims to improve on the performance of static signature-based techniques used by anti-virus systems, which are less effective against modern polymorphic and metamorphic malware. Behavioral malware classification aims to go beyond the detection of malware by also identifying a malware's family according to a naming scheme such as t

Ben Hoare, Fiona K. Seibold

We construct supergravity backgrounds for the integrable eta-deformations of the AdS2 x S2 x T6 and AdS5 x S5 superstring sigma models. The eta-deformation is governed by an R-matrix that solves the non-split modified classical Yang-Baxter equation on the superisometry algebra of the model. Such R-matrices include those of Drinfel'd-Jimbo type, which are con

Christian Herrmann, Martin Ziegler

For finite dimensional hermitean inner product spaces $V$, over $*$-fields $F$, and in the presence of orthogonal bases providing form elements in the prime subfield of $F$, we show that quantifier free definable relations in the subspace lattice $L(V)$ with involution by taking orthogonals, admit quantifier free descriptions within $F$, also in terms of Gra

Laurent Dardelet, Sio-Hoi Ieng, Ryad Benosman

This paper presents a new event-based method for detecting and tracking features from the output of an event-based camera. Unlike many tracking algorithms from the computer vision community, this process does not aim for particular predefined shapes such as corners. It relies on a dual intertwined iterative continuous -- pure event-based -- estimation of the

Akram Yazdani, Azam Yazdani, Raúl Méndez Giráldez, David Aguilar

Heart failure is a major cause for premature death. Given heterogeneity of the heart failure syndrome, identifying genetic determinants of cardiac function and structure may provide greater insights into heart failure. Despite progress in understanding the genetic basis of heart failure through genome wide association studies, heritability of heart failure i

Xavier Tolsa

In this paper the jump formulas for the double layer potential and other singular integrals are proved for arbitrary rectifiable sets, by defining suitable non-tangential limits. The arguments are quite straightforward and only require some Calder\'on-Zygmund techniques.

Anzar Ali, Gyaneshwar Sharma, Yogesh Singh

The spinel NiCr$_2$O$_4$ is known to show a ferrimagnetic transition at $T_c = 70$~K, and magneto-structural transitions at $T_s = 30$~K and $T_o = 20$~K\@. We present a detailed magnetic and magnetocaloric effect (MCE $= -\Delta S_{M}(T)$) study across these transitions. The $-\Delta S_{M}(T)$ shows a positive anomaly at $T_c$, $T_s$, and $T_o$. In addition

Ye-Hua Liu, David Poulin

Belief-propagation (BP) decoders play a vital role in modern coding theory, but they are not suitable to decode quantum error-correcting codes because of a unique quantum feature called error degeneracy. Inspired by an exact mapping between BP and deep neural networks, we train neural BP decoders for quantum low-density parity-check (LDPC) codes with a loss

Mark Podolskij, Bezirgen Veliyev, Nakahiro Yoshida

In this paper we present the Edgeworth expansion for the Euler approximation scheme of a continuous diffusion process driven by a Brownian motion. Our methodology is based upon a recent work \cite{Yoshida2013}, which establishes Edgeworth expansions associated with asymptotic mixed normality using elements of Malliavin calculus. Potential applications of our

Wojciech Nadara

The theoretical notions of graph classes with bounded expansion and that are nowhere dense are meant to capture structural sparsity of real world networks that can be used to design efficient algorithms. In the area of sparse graphs, the flagship problems are Dominating Set and its generalization r-Dominating Set. They have been precursors for model checking

Alberto Canonaco, Mattia Ornaghi, Paolo Stellari

We prove that the localizations of the categories of dg categories, of cohomologically unital and strictly unital $A_\infty$ categories with respect to the corresponding classes of quasi-equivalences are all equivalent. Moreover we show that the last two localizations are equivalent to the corresponding quotients by the relation of being isomorphic in the co

Simón Lunagómez, Marios Papamichalis, Patrick J. Wolfe, Edoardo M. Airoldi

Some of the most used sampling mechanisms that implicitly leverage a social network depend on tuning parameters; for instance, Respondent-Driven Sampling (RDS) is specified by the number of seeds and maximum number of referrals. We are interested in the problem of optimizing these sampling mechanisms with respect to their tuning parameters in order to optimi

Jong-Hyeon Jeong

To combine the proportions from different studies for meta-analysis, Freeman and Tukey double arcsine tranformation can be useful for normalization and variance stabilization. The inverse function of the double arcsine transformation has been also derived in the literature to recover the original scale of the proportion after aggregation. In this brief note,

Federico Cornalba

Stochastic conservation laws are often challenging when it comes to proving existence of non-negative solutions. In a recent work by J. Fischer and G. Gr\"un (2018, Existence of positive solutions to stochastic thin-film equations, SIAM J. Math. Anal.), existence of positive martingale solutions to a conservative stochastic thin-film equation is established

Wilmer Leal, Guillermo Restrepo, Peter F. Stadler, Jürgen Jost

In contrast to graph-based models for complex networks, hypergraphs are more general structures going beyond binary relations of graphs. For graphs, statistics gauging different aspects of their structures have been devised and there is undergoing research for devising them for hypergraphs. Forman-Ricci curvature is a statistics for graphs, which is based on

Koen van den Dungen

We study the Kasparov product on (possibly non-compact and incomplete) Riemannian manifolds. Specifically, we show on a submersion of Riemannian manifolds that the tensor sum of a regular vertically elliptic operator on the total space and an elliptic operator on the base space represents the Kasparov product of the corresponding classes in KK-theory. This c

M. Paściak, P. Ondrejkovic, P. Vanek, J. Drahokoupil

Neutron pair distribution function analysis and first principles calculations have been employed to study short-range correlations in heavily disordered dielectric material Sr$_x$Ba$_{1-x}$Nb$_2$O$_6$ ($x=0.35, 0.5$ and 0.61). The combination of methods has been fruitful in pinpointing main local-structure features, their temperature behaviour and interrelat

Pietro Baldi, Emanuele Haus, Carlo Mantegazza

We rigorously show the existence of a rotationally and centrally symmetric "lens-shaped" cluster of three surfaces, meeting at a smooth common circle, forming equal angles of 120 degrees, self-shrinking under the motion by mean curvature.

Jian Ding, Zongming Ma, Yihong Wu, Jiaming Xu

Random graph matching refers to recovering the underlying vertex correspondence between two random graphs with correlated edges; a prominent example is when the two random graphs are given by Erd\H{o}s-R\'{e}nyi graphs $G(n,\frac{d}{n})$. This can be viewed as an average-case and noisy version of the graph isomorphism problem. Under this model, the maximum l

D. Gruner, R. Hainich, A. A. C. Sander, T. Shenar

HD 93129A was classified as the earliest O-type star in the Galaxy (O2~If*) and is considered as the prototype of its spectral class. However, interferometry shows that this object is a binary system, while recent observations even suggest a triple configuration. None of the previous spectral analyses of this object accounted for its multiplicity. With new h

Dibya Ghosh, Abhishek Gupta, Sergey Levine

Representation learning is a central challenge across a range of machine learning areas. In reinforcement learning, effective and functional representations have the potential to tremendously accelerate learning progress and solve more challenging problems. Most prior work on representation learning has focused on generative approaches, learning representati

S. Terzo, M. Benoit, E. Cavallaro, R. Casanova

Monolithic active pixel sensors produced in High Voltage CMOS (HV-CMOS) technology are being considered for High Energy Physics applications due to the ease of production and the reduced costs. Such technology is especially appealing when large areas to be covered and material budget are concerned. This is the case of the outermost pixel layers of the future

Markus Wallerberger, Sergei Iskakov, Alexander Gaenko, Joseph Kleinhenz

The open source ALPS (Algorithms and Libraries for Physics Simulations) project provides a collection of physics libraries and applications, with a focus on simulations of lattice models and strongly correlated electron systems. The libraries provide a convenient set of well-documented and reusable components for developing condensed matter physics simulatio

James Jackaman, Tristan Pryer

In this note we examine the a priori and a posteriori analysis of discontinuous Galerkin finite element discretisations of semilinear elliptic PDEs with polynomial nonlinearity. We show that optimal a priori error bounds in the energy norm are only possible for low order elements using classical a priori error analysis techniques. We make use of appropriate

J. -Y. Kim, T. P. Krichbaum, A. P. Marscher, S. G. Jorstad

We report results from a deep polarization imaging of the nearby radio galaxy 3C$\,$84 (NGC$\,$1275). The source was observed with the Global Millimeter VLBI Array (GMVA) at 86$\,$GHz at an ultra-high angular resolution of $50\mu$as (corresponding to 250$R_{s}$). We also add complementary multi-wavelength data from the Very Long Baseline Array (VLBA; 15 & 43

P. P. Ferreira, T. T. Dorini, F. B. Santos, A. J. S. Machado

MV$_2$Ga$_4$ (M = Sc, Zr, Hf) compounds belong to an emerging class of materials showing a unique combination of unusual superconducting behavior with extended linear chains in the crystal structure. In order to gain insights {into} its mechanical and thermal properties, we have performed first-principles electronic-structure calculations in the framework of

Palak Dugar, Chih-Chun Chien

The second law of thermodynamics requires the overall thermal current to flow from hot to cold. However, it does not forbid a local thermal current from flowing from cold to hot. By coupling a harmonic system of three masses connected by a few springs to two Langevin reservoirs at different temperatures, a local atypical thermal current is found to flow from

A. Kovács, C. Sánchez, J. García-Bellido, J. Elvin-Poole

The largest structures in the cosmic web probe the dynamical nature of dark energy through their integrated Sachs-Wolfe imprints. In the strength of the signal, typical cosmic voids have shown good consistency with expectation $A_{\rm ISW}=\Delta T^{\rm data} / \Delta T^{\rm theory}=1$, given the substantial cosmic variance. Discordantly, large-scale hills i

F. Hébert, Bo Xiao, V. G. Rousseau, R. T. Scalettar

The Hubbard-Holstein model describes fermions on a discrete lattice, with on-site repulsion between fermions and a coupling to phonons that are localized on sites. Generally, at half-filling, increasing the coupling $g$ to the phonons drives the system towards a Peierls charge density wave state whereas increasing the electron-electron interaction $U$ drives

Mihaela Vatasescu

We characterize both entanglement and quantum coherence in a molecular system by connecting the linear entropy of electronic-nuclear entanglement with Wigner-Yanase skew information measuring vibronic coherence and local quantum uncertainty on electronic energy. Linear entropy of entanglement and quantifiers of quantum coherence are derived for a molecular s

Massimiliano Gubinelli, Herbert Koch, Tadahiro Oh

Using ideas from paracontrolled calculus, we prove local well-posedness of a renormalized version of the three-dimensional stochastic nonlinear wave equation with quadratic nonlinearity forced by an additive space-time white noise on a periodic domain. There are two new ingredients as compared to the parabolic setting. (i) In constructing stochastic objects,

Tian Xu, Jiayu Zhan, Oliver G. B. Garrod, Philip H. S. Torr

Deep Convolutional Neural Networks (CNNs) have been one of the most influential recent developments in computer vision, particularly for categorization. There is an increasing demand for explainable AI as these systems are deployed in the real world. However, understanding the information represented and processed in CNNs remains in most cases challenging. W

Damien Trinh, Francesco Pace, Richard A. Battye, Boris Bolliet

We investigate generalized Einstein-Aether theories that are compatible with the Planck Cosmic Microwave Background (CMB) temperature anisotropy, polarisation, and lensing data. For a given dark energy equation of state, $w_{\rm de}$, we formulate a designer approach and we investigate their impact on the CMB temperature anisotropy and matter power spectra.

Brice Saint-Michel, Marc Georgelin, Sylvain Deville, Alain Pocheau

We address the mechanical effect of rigid boundaries on freezing suspensions. For this we perform the directional solidification of monodispersed suspensions in thin samples and we document the thickness h of the dense particle layer that builds up at the solidification front. We evidence a change of regime in the evolution of h with the solidification veloc

Jean-Matthieu Maro, Ryad Benosman

This paper introduces a framework of gesture recognition operating on the output of an event based camera using the computational resources of a mobile phone. We will introduce a new development around the concept of time-surfaces modified and adapted to run on the limited computational resources of a mobile platform. We also introduce a new method to remove

Miki E. Verma, Robert A. Bridges, Samuel C. Hollifield

Modern vehicles contain scores of Electrical Control Units (ECUs) that broadcast messages over a Controller Area Network (CAN). Vehicle manufacturers rely on security through obscurity by concealing their unique mapping of CAN messages to vehicle functions which differs for each make, model, year, and even trim. This poses a major obstacle for after-market m

Christos Sourdis

We confirm a prediction that the recently introduced shadow kink defect in the theory of light-matter interaction in nematic liquid crystals is described to main order by a solution of the Painlev\'e-II equation which changes sign once in the whole real line. Our result implies that such a solution of the latter equation is energy minimizing with respect to

Katrina C. Litke, Daniel P. Marrone, Justin S. Spilker, Manuel Aravena

SPT0346-52 is one of the most most luminous and intensely star-forming galaxies in the universe, with L_FIR > 10^13 L_sol and Sigma_SFR ~ 4200 M_sol yr^-1 kpc^-2. In this paper, we present ~0.15'' ALMA observations of the [CII]158micron emission line in this z=5.7 dusty star-forming galaxy. We use a pixellated lensing reconstruction code to spatially and kin

Moritz Wiese, Holger Boche

A novel type of functions called biregular irreducible functions is introduced and applied as security components (instead of, e.g., universal hash functions) in seeded modular wiretap coding schemes, whose second component is an error-correcting code. These schemes are called modular BRI schemes. An upper bound on the semantic security information leakage o

Lei Li, Jian-Guo Liu, Pu Yu

In this paper, we consider the mean field limit of Brownian particles with Coulomb interaction in 3D space. In particular, using a symmetrization technique, we show that the limit measure almost surely is a weak solution to the limiting nonlinear Fokker-Planck equation. By proving that the energy almost surely is bounded by the initial energy, we improve the

S. N. Klimin, J. Tempere, H. Kurkjian

We study the phononic collective modes of the pairing field $\Delta$ and their corresponding signature in both the order-parameter and density response functions for a superfluid Fermi gas at all temperatures below $T_c$ in the collisionless regime. The spectra of collective modes are calculated within the Gaussian Pair Fluctuation approximation. We deal wit

Elena Cordero, S. Ivan Trapasso

The Wigner distribution is a milestone of Time-frequency Analysis. In order to cope with its drawbacks while preserving the desirable features that made it so popular, several kind of modifications have been proposed. This contributions fits into this perspective. We introduce a family of phase-space representations of Wigner type associated with invertible

Jan Jurcak, Jana Kasparova, Michal Svanda, Lucia Kleint

The \ion{Fe}{i} lines observed by the Hinode/SOT spectropolarimeter were always seen in absorption, apart from the extreme solar limb. Here we analyse a unique dataset capturing these lines in emission during a solar white-light flare. We analyse the temperature stratification in the solar photosphere during a white-light flare and compare it with the post-w

Hassan Issa

The manuscript is devoted to the construction of $\Psi^\star$- algebras containing the Bergman projection on the unit ball $B_n$ of $\mathbb C^n$. We consider the $C^\star$-algebra $\mathcal{L}(L^2(B_n))$ of bounded operator acting on the Hilbert space of square integrable functions on $B_n$ with respect to the standard probability measure. We search for spe

P. B. Silva, M. J. Leamy, M. G. D. Geers, V. G. Kouznetsova

In this paper, the effect of weak nonlinearities in 1D locally resonant metamaterials is investigated via the method of multiple scales. Commonly employed to the investigate the effect of weakly nonlinear interactions on the free wave propagation through a phononic structure or on the dynamic response of a Duffing oscillator, the method of multiple scales is

Jianxin Lin, Tiankuang Zhou, Zhibo Chen

We present \emph{Deep Image Retargeting} (\emph{DeepIR}), a coarse-to-fine framework for content-aware image retargeting. Our framework first constructs the semantic structure of input image with a deep convolutional neural network. Then a uniform re-sampling that suits for semantic structure preserving is devised to resize feature maps to target aspect rati

Javier Franco-Pedroso, Joaquin Gonzalez-Rodriguez, Maria Planas, Jorge Cubero

This paper presents an evaluation framework that attempts to quantify the "degree of realism" of simulated financial time series, whatever the simulation method could be, with the aim of discover unknown characteristics that are not being properly reproduced by such methods in order to improve them. For that purpose, the evaluation framework is posed as a ma

David Fuentes-Jimenez, David Casillas-Perez, Daniel Pizarro, Toby Collins

We present Deep Shape-from-Template (DeepSfT), a novel Deep Neural Network (DNN) method for solving real-time automatic registration and 3D reconstruction of a deformable object viewed in a single monocular image.DeepSfT advances the state-of-the-art in various aspects. Compared to existing DNN SfT methods, it is the first fully convolutional real-time appro

S. Nojiri, S. D. Odintsov, V. K. Oikonomou

In this work we develop a theoretical framework for Gauss-Bonnet modified gravity theories, in which ghost modes can be eliminated at the equations of motion level. Particularly, after we present how the ghosts can occur at the level of equations of motion, we employ the Lagrange multipliers technique, and by means of constraints we are able to eliminate the

Varun Manjunatha, Nirat Saini, Larry S. Davis

Researchers have observed that Visual Question Answering (VQA) models tend to answer questions by learning statistical biases in the data. For example, their answer to the question "What is the color of the grass?" is usually "Green", whereas a question like "What is the title of the book?" cannot be answered by inferring statistical biases. It is of interes

A. J. Sojahrood, Q. Li, H. Haghi, R. Karshafian

Results of the measurements of sound speed and attenuation in a bubbly medium are reported. Monodisperse bubble solutions are sonicated with broadband ultrasound pulses with pressure amplitudes ranging between 12.5-100 kPa. Fundamental relationships between the frequency dependent attenuation, sound speed and pressure are established. A new model for the est

Aurélien Alfonsi, Benjamin Jourdain

In this paper, we remark that any optimal coupling for the quadratic Wasserstein distance $W^2_2(\mu,\nu)$ between two probability measures $\mu$ and $\nu$ with finite second order moments on $\mathbb{R}^d$ is the composition of a martingale coupling with an optimal transport map ${\mathcal T}$. We check the existence of an optimal coupling in which this map

Oscar Ramos, Enrico Barausse

Ho\v{r}ava gravity breaks Lorentz symmetry by introducing a preferred spacetime foliation, which is defined by a timelike dynamical scalar field, the khronon. The presence of this preferred foliation makes black hole solutions more complicated than in General Relativity, with the appearance of multiple distinct event horizons: a matter horizon for light/matt

P. Barmby

Observational astrophysics uses sophisticated technology to collect and measure electromagnetic and other radiation from beyond the Earth. Modern observatories produce large, complex datasets and extracting the maximum possible information from them requires the expertise of specialists in many fields beyond physics and astronomy, from civil engineers to sta

Evan A. Rich, John P. Wisniewski, Thayne Currie, Misato Fukagawa

We present H-band polarized scattered light imagery and JHK high-contrast spectroscopy of the protoplanetary disk around HD 163296 observed with the HiCIAO and SCExAO/CHARIS instruments at Subaru Observatory. The polarimetric imagery resolve a broken ring structure surrounding HD 163296 that peaks at a distance along the major axis of 0.65 (66 AU) and extend

Gabriel Andreas Dill

Following and generalizing unpublished work of Ange, we prove a generalized version of R\'emond's generalized Vojta inequality. This generalization can be applied to arbitrary products of irreducible positive-dimensional projective varieties, defined over the field of algebraic numbers, instead of powers of one fixed such variety. The proof runs closely alon

Matthias Ebenbeck, Patrik Knopf

In this paper, we study a distributed optimal control problem for a diffuse interface model for tumor growth. The model consists of a Cahn-Hilliard type equation for the phase field variable coupled to a reaction diffusion equation for the nutrient and a Brinkman type equation for the velocity. The system is equipped with homogeneous Neumann boundary conditi

Shiyi Lan, Ruichi Yu, Gang Yu, Larry S. Davis

Recent advances in deep convolutional neural networks (CNNs) have motivated researchers to adapt CNNs to directly model points in 3D point clouds. Modeling local structure has been proven to be important for the success of convolutional architectures, and researchers exploited the modeling of local point sets in the feature extraction hierarchy. However, lim

Jay Roberts, Steve Shkoller, Thomas C. Sideris

The affine motion of two-dimensional (2d) incompressible fluids surrounded by vacuum can be reduced to a completely integrable and globally solvable Hamiltonian system of ordinary differential equations for the deformation gradient in ${\rm SL}(2,{\mathbb R})$. In the case of perfect fluids, the motion is given by geodesic flow in ${\rm SL}(2,{\mathbb R})$ w

Sepehr Assadi, Michael Kapralov, Sanjeev Khanna

In the subgraph counting problem, we are given a input graph $G(V, E)$ and a target graph $H$; the goal is to estimate the number of occurrences of $H$ in $G$. Our focus here is on designing sublinear-time algorithms for approximately counting occurrences of $H$ in $G$ in the setting where the algorithm is given query access to $G$. This problem has been stu

Marcin Pilipczuk, Michał Ziobro

In the recent years we have witnessed a rapid development of new algorithmic techniques for parameterized algorithms for graph separation problems. We present experimental evaluation of two cornerstone theoretical results in this area: linear-time branching algorithms guided by half-integral relaxations and kernelization (preprocessing) routines based on rep

M. A. Zubkov, Z. V. Khaidukov

Using the derivative expansion applied to the Wigner transform of the two - point Green function this is possible to derive the response of various nondissipative currents to the external gauge fields. The corresponding currents are proportional to the momentum space topological invariants. This allows to analyse systematically various anomalous transport ph

Matthew E. Trusheim, Benjamin Pingault, Noel H Wan, Mustafa Gundogan

Solid-state quantum emitters that couple coherent optical transitions to long-lived spin qubits are essential for quantum networks. Here we report on the spin and optical properties of individual tin-vacancy (SnV) centers in diamond nanostructures. Through cryogenic magneto-optical and spin spectroscopy, we verify the inversion-symmetric electronic structure

D. Barbato, A. Sozzetti, K. Biazzo, L. Malavolta

Statistical studies of exoplanets have shown that giant planets are more commonly hosted by metal-rich dwarf stars than low-metallicity ones, while such a correlation is not evident for lower-mass planets. The search for giant planets around metal-poor stars and the estimate of their occurrence $f_p$ is an important element in providing support to models of

Henk Bruin, Ian Melbourne, Dalia Terhesiu

Gouezel and Sarig introduced operator renewal theory as a method to prove sharp results on polynomial decay of correlations for certain classes of nonuniformly expanding maps. In this paper, we apply the method to planar dispersing billiards and multidimensional nonMarkovian intermittent maps.

Guomin Liu

In this paper, we study the well-posedness of multi-dimensional backward stochastic differential equations driven by $G$-Brownian motion ($G$-BSDEs) with diagonal generators, the $z$ parts of whose $l$-th components only depend on the $l$-th columns. The existence and uniqueness of solutions are obtained via a contraction argument for $Y$ component and a bac

Geoffrey K. Vallis, Douglas J. Parker, Steven M. Tobias

Raylaigh-Benard convection is one of the most well-studied models in fluid mechanics. Atmospheric convection, one of the most important components of the climate system, is by comparison complicated and poorly understood. A key attribute of atmospheric convection is the buoyancy source provided by the condensation of water vapour, but the presence of radiati

Anton S. Becker, Lukas Jendele, Ondrej Skopek, Nicole Berger

$\textbf{Purpose}$ To train a cycle-consistent generative adversarial network (CycleGAN) on mammographic data to inject or remove features of malignancy, and to determine whether these AI-mediated attacks can be detected by radiologists. $\textbf{Material and Methods}$ From the two publicly available datasets, BCDR and INbreast, we selected images from cance

Reinhard Stock, Francesco Becattini, Marcus Bleicher, Jan Steinheimer

In high multiplicity nucleus-nucleus collisions baryon-antibaryon annihilation and regeneration occur during the final hadronic expansion phase, thus distorting the initial equilibrium multiplicity ratios. We quantify the modifications employing the hybrid UrQMD transport model and apply them to the grand canonical partition functions of the Statistical Hadr

Seth Neel, Aaron Roth, Zhiwei Steven Wu

We develop theory for using heuristics to solve computationally hard problems in differential privacy. Heuristic approaches have enjoyed tremendous success in machine learning, for which performance can be empirically evaluated. However, privacy guarantees cannot be evaluated empirically, and must be proven --- without making heuristic assumptions. We show t

V. Medvedev, E. Zhuzhoma

Given closed topological $n$-manifold $M^n$, $n\geq 2$, one introduces the classes of Smale regular $SRH(M^n)$ and Smale semi-regular $SsRH(M^n)$ homeomorphisms of $M^n$ with $SRH(M^n)\subset~SsRH(M^n)$. The class $SRH(M^n)$ contains all Morse-Smale diffeomorphisms, while $SsRH(M^n)$ contains A-diffeomorphisms with trivial and some nontrivial basic sets prov

Raphaël Féraud, Réda Alami, Romain Laroche

We consider the decentralized exploration problem: a set of players collaborate to identify the best arm by asynchronously interacting with the same stochastic environment. The objective is to insure privacy in the best arm identification problem between asynchronous, collaborative, and thrifty players. In the context of a digital service, we advocate that t

Qi Yao, Jun Zhang, Xiao-feng Yi, Li You

Dynamical decoupling (DD) is an active and effective method for suppressing decoherence of a quantum system from its environment. In contrast to the nominal biaxial DD,this work presents a uniaxial decoupling protocol that requires a significantly reduced number of pulses and a much lower bias field satisfying the "magic" condition.We show this uniaxial DD p

Maciej Pawlikowski, Agata Chorowska

We present a detailed description of our submission for the M4 forecasting competition, in which it ranked 3rd overall. Our solution utilizes several commonly used statistical models, which are weighted according to their performance on historical data. We cluster series within each type of frequency with respect to the existence of trend and seasonality. Ev

J. Ph. Guillet, E. Pilon, Y. Shimizu, M. S. Zidi

This article is the third and last of a series presenting an alternative method to compute the one-loop scalar integrals. It extends the results of first two articles to the infrared divergent case. This novel method enjoys a couple of interesting features as compared with the methods found in the literature. It directly proceeds in terms of the quantities d

Clodoaldo Grotta Ragazzo

This paper contains a review of Clairaut's theory with focus on the determination of a gravitational rigidity modulus $\gamma$ defined as $\left(\frac{C-I_o}{I_o}\right)\gamma=\frac{2}{3}\Omega^2$, where $C$ and $I_o$ are the polar and mean moment of inertia of the body and $\Omega$ is the body spin.The constant $\gamma$ is related to the static fluid Love n

Peng Wang, Houwen Wu, Haitang Yang

In previous works, we have developed an approach to fix the leading behaviors of the pure AdS$_3$ and BTZ black hole from the entanglement entropies of the free CFT$_2$ and finite temperature CFT$_2$, respectively. We exclusively use holographic principle only and make no restriction about the bulk geometry, not only the kinematics but also the dynamics. In

A. Ferran Pousa, A. Martinez de la Ossa, R. Brinkmann, R. W. Assmann

The extreme electromagnetic fields sustained by plasma-based accelerators allow for energy gain rates above 100 GeV/m but are also an inherent source of correlated energy spread. This severely limits the usability of these devices. Here we propose a novel compact concept which compensates the induced energy correlation by combining plasma accelerating stages

Ritchie Zhao, Yuwei Hu, Jordan Dotzel, Christopher De Sa

We propose unitary group convolutions (UGConvs), a building block for CNNs which compose a group convolution with unitary transforms in feature space to learn a richer set of representations than group convolution alone. UGConvs generalize two disparate ideas in CNN architecture, channel shuffling (i.e. ShuffleNet) and block-circulant networks (i.e. CirCNN),