March 2020 arXiv papers — page 77

Yutao Liu

This is an expository paper about a $\mathcal{C}_2$-equivariant analog of the bar construction. We will explain its construction and prove how it acts as a $σ$-fold delooping machine on twisted monoids, where $σ$ denotes the sign representation.

Julia Elyseeva

In this paper we establish new renormalized oscillation theorems for discrete symplectic eigenvalue problems with Dirichlet boundary conditions. These theorems present the number of finite eigenvalues of the problem in arbitrary interval $(a,b]$ using number of focal points of a transformed conjoined basis associated with Wronskian of two principal solutions

Lukas Rammelmüller, Joaquín E. Drut, Jens Braun

We study spin- and mass-imbalanced mixtures of spin-$\tfrac{1}{2}$ fermions interacting via an attractive contact potential in one spatial dimension. Specifically, we address the influence of unequal particle masses on the pair formation by means of the complex Langevin method. By computing the pair-correlation function and the associated pair-momentum distr

S. S. Aleshin, I. S. Durandina, D. S. Kolupaev, D. S. Korneev

We verify a recently proposed method for obtaining a $β$-function of ${\cal N}=1$ supersymmetric gauge theories regularized by higher derivatives by an explicit calculation. According to this method, a $β$-function can be found by calculating specially modified vacuum supergraphs instead of a much larger number of the two-point superdiagrams. The result is p

Shuqiang Zhu

For the curved n-body problem, we show that the set of ordinary central configurations is away from most singular configurations in H^3, and away from a subset of singular configurations in S^3. We also show that each of the n!/2 geodesic ordinary central configurations for n masses has Morse index n-2. Then we get a direct corollary that there are at least

Davoud Masoumi, Leila Shahkarami, Farid Charmchi

The response of a QCD-like gauge theory, holographically dual to a deformed $\mathrm{AdS}_5$ model, to constant electromagnetic fields is thoroughly investigated. The calculations in this paper are performed for three different cases, i.e., with only a quadratic correction, with only a logarithmic correction, and with both quadratic and logarithmic correctio

Fan Ma, Linchao Zhu, Yi Yang, Shengxin Zha

In this paper, we study an intermediate form of supervision, i.e., single-frame supervision, for temporal action localization (TAL). To obtain the single-frame supervision, the annotators are asked to identify only a single frame within the temporal window of an action. This can significantly reduce the labor cost of obtaining full supervision which requires

Zipeng Ye, Mengfei Xia, Yanan Sun, Ran Yi

Caricature is a type of artistic style of human faces that attracts considerable attention in the entertainment industry. So far a few 3D caricature generation methods exist and all of them require some caricature information (e.g., a caricature sketch or 2D caricature) as input. This kind of input, however, is difficult to provide by non-professional users.

Kewei Zhang, Chuyu Zhou

In this paper, we will give a precise formula to compute delta invariants of projective bundles and projective cones of Fano type.

Pablo Aguado-Puente, Stephen Fahy, Myrta Grüning

We calculate the electronic structure of the narrow gap semiconductors PbTe, SnTe and GeTe in the cubic phase using density functional theory (DFT) and the $G_0W_0$ method. Within DFT, we show that the band ordering obtained with a conventional semilocal exchange-correlation approximation is correct for SnTe and GeTe but wrong for PbTe. The correct band orde

Yunfei Meng, Zhiqiu Huang, Senzhang Wang, Guohua Shen

To effectively tackle the security threats towards the Internet of things, we propose a SOM-based DDoS defense mechanism using software-defined networking (SDN) in this paper. The main idea of the mechanism is to deploy a SDN-based gateway to protect the device services in the Internet of things. The gateway provides DDoS defense mechanism based on SOM neura

Ho Fai Po, Chi Ho Yeung, David Saad

Optimizing traffic flow is essential for easing congestion. However, even when globally-optimal, coordinated and individualized routes are provided, users may choose alternative routes which offer lower individual costs. By analyzing the impact of selfish route-choices on performance using the cavity method, we find that a small ratio of selfish route-choice

Cihan A. Bayındır

We investigate the Zeno dynamics of quantum chirps. More specifically, we analyze the Zeno dynamics of a chirped solitary wave solution of the non-dimensional nonlinear Schr\"odinger equation (NLSE) with a gain/loss term. We show that the motion of the quantum chirp can be inhibited by frequent measurements in the observation domain. In order to assess the e

Ellen Baake, Frederic Alberti

The deterministic selection-recombination equation describes the evolution of the genetic type composition of a population under selection and recombination in a law of large numbers regime. So far, an explicit solution has seemed out of reach; only in the special case of three sites with selection acting on one of them has an approximate solution been found

Nicola Cufaro Petroni, Piergiacomo Sabino

We investigate the distributional properties of two generalized Ornstein-Uhlenbeck (OU) processes whose stationary distributions are the gamma law and the bilateral gamma law, respectively. The said distributions turn out to be related to the self-decomposable gamma and bilateral gamma laws, and their densities and characteristic functions are here given in

Reggie C. Pantig, Emmanuel T. Rodulfo

In this paper, we examine the effect of dark matter to a Kerr black hole of mass $m$. The metric is derived using the Newman-Janis algorithm, where the seed metric originates from the Schwarzschild black hole surrounded by a spherical shell of dark matter with mass $M$ and thickness $Δr_{s}$. The seed metric is also described in terms of a piecewise mass fun

Akram Youssry, Gerardo A. Paz-Silva, Christopher Ferrie

The ability to use quantum technology to achieve useful tasks, be they scientific or industry related, boils down to precise quantum control. In general it is difficult to assess a proposed solution due to the difficulties in characterising the quantum system or device. These arise because of the impossibility to characterise certain components in situ, and

Zhengxian Li, Wei Xia, Hao Su, Zhenhai Yu

The van der Waals ferromagnet Fe5GeTe2 has a Curie temperature TC of about 270 K, which can be raised above room temperature by tuning the Fe deficiency content. To achieve insights into its ferromagnetic exchange, we have studied the critical behavior by measuring the magnetization in bulk Fe5GeTe2 crystal around the ferromagnetic to paramagnetic phase tran

Rafael I. Nepomechie

We propose a Q-system for the $A_m^{(1)}$ quantum integrable spin chain. We also find compact determinant expressions for all the Q-functions, both for the rational and trigonometric cases.

Won Sang Cho, Hyung Do Kim, Dongsub Lee

We propose a novel method in that quark-gluon tagging of the jets emitted as initial state radiation (ISR) can boost searches of invisible Higgs from gluon fusion processes against irreducible electroweak vector boson productions. While quark ISR typically takes up a dominant portion than gluon in the background processes mainly by frequent quark-gluon initi

Amir Rahimi, Amirreza Shaban, Ching-An Cheng, Richard Hartley

Predicting calibrated confidence scores for multi-class deep networks is important for avoiding rare but costly mistakes. A common approach is to learn a post-hoc calibration function that transforms the output of the original network into calibrated confidence scores while maintaining the network's accuracy. However, previous post-hoc calibration techni

Yakov Varshavsky

The goal of this note is to show that in the case of transversal intersections the "true local terms" appearing in the Lefschetz trace formula equal to the "naive local terms". To prove the result we extend the method of [Va], where the case of contracting correspondences is treated. Our new ingredients are the observation of Verdier that specialization of a

Xiao Yang, Yinpeng Dong, Tianyu Pang, Hang Su

As billions of personal data being shared through social media and network, the data privacy and security have drawn an increasing attention. Several attempts have been made to alleviate the leakage of identity information from face photos, with the aid of, e.g., image obfuscation techniques. However, most of the present results are either perceptually unsat

Danial Shafizade, Majid Shalchian, Farzan Jazaeri

This brief proposes an analytical approach to model the dc electrical behavior of extremely narrow cylindrical junctionless nanowire field-effect transistor (JLNW-FET). The model includes explicit expressions, taking into account the first-order perturbation theory for calculating eigenstates and corresponding wave functions obtained by the Schrodinger equat

Thierry Dumas, Franck Galpin, Philippe Bordes

This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising from the codec partitioning of images, each paired with its context. Then, iteratively, blocks are collected from the partitioning of images via the codec including the neural netwo

Wael Bahsoun, Carlangelo Liverani

Given any smooth Anosov map we construct a Banach space on which the associated transfer operator is quasi-compact. The peculiarity of such a space is that in the case of expanding maps it reduces exactly to the usual space of functions of bounded variation which has proven particularly successful in studying the statistical properties of piecewise expanding

Julian Berberich, Johannes Köhler, Matthias A. Müller, Frank Allgöwer

We propose a purely data-driven model predictive control (MPC) scheme to control unknown linear time-invariant systems with guarantees on stability and constraint satisfaction in the presence of noisy data. The scheme predicts future trajectories based on data-dependent Hankel matrices, which span the full system behavior if the input is persistently excitin

Ralf R. Müller

This paper presents a method to calculate the exact average block error probability of some random code ensembles under maximum-likelihood decoding. The proposed method is applicable to various channels and ensembles. The focus is on both spherical and Gaussian random codes on the additive white Gaussian noise channel as well as binary random codes on both t

Niels G. Gresnigt

Building upon previous works, it is shown that two minimal left ideals of the complex Clifford algebra $\mathbb{C}\ell(6)$ and two minimal right ideals of $\mathbb{C}\ell(4)$ transform as one generation of leptons and quarks under the gauge symmetry $SU(3)_C\times U(1)_{EM}$ and $SU(2)_L\times U(1)_Y$ respectively. The $SU(2)_L$ weak symmetries are naturally

Yanbo Li, Xiaolin Shi

We provide a necessary and sufficient condition for a type D Temperley-Lieb algebra ${\rm TLD}_n(\delta)$ being semi-simple by studying branching rule for cell modules. As a byproduct, our result is used to study the so-called forked Temperley-Lieb algebra, which is a quotient algebra of ${\rm TLD}_n(\delta)$.

M. A. Lisitsyna, S. V. Avgustinovich, O. G. Parshina

A coloring of vertices of a given graph is called perfect if the color structure of each ball of radius $1$ in the graph depends only on the color of the ball center. Let $n$ be a positive integer. We consider a lexicographic product of the infinite path graph and a graph $G$ that can be either the complete or empty graph on $n$ vertices. We give a complete

Bertrand Jayles, Clément Sire, Ralf H. J. M Kurvers

The recent developments of social networks and recommender systems have dramatically increased the amount of social information shared in human communities, challenging the human ability to process it. As a result, sharing aggregated forms of social information is becoming increasingly popular. However, it is unknown whether sharing aggregated information im

Anton Osokin, Denis Sumin, Vasily Lomakin

In this paper, we consider the task of one-shot object detection, which consists in detecting objects defined by a single demonstration. Differently from the standard object detection, the classes of objects used for training and testing do not overlap. We build the one-stage system that performs localization and recognition jointly. We use dense correlation

Thomas Ruedas, Doris Breuer

We derive synthetic electrical conductivity, seismic velocity, and density distributions from the results of martian mantle convection models affected by basin-forming meteorite impacts. The electrical conductivity features an intermediate minimum in the strongly depleted topmost mantle, sandwiched between higher conductivities in the lower crust and a smoot

Leonid Karlinsky, Joseph Shtok, Amit Alfassy, Moshe Lichtenstein

Few-shot detection and classification have advanced significantly in recent years. Yet, detection approaches require strong annotation (bounding boxes) both for pre-training and for adaptation to novel classes, and classification approaches rarely provide localization of objects in the scene. In this paper, we introduce StarNet - a few-shot model featuring a

Simen Kvaal, Andre Laestadius, Tilmann Bodenstein

A wide class of coupled-cluster methods is introduced, based on Arponen's extended coupled-cluster theory. This class of methods is formulated in terms of a coordinate transformation of the cluster operators. The mathematical framework for the error analysis of coupled-cluster methods based on Arponen's bivariational principle is presented, in which the conc

Akshay J. Dave, Annalisa Manera

The metering of gas-liquid flows is difficult due to the non-linear relationship between flow regimes and fluid properties, flow orientation, channel geometry, etc. In fact, a majority of commercial multiphase flow meters have a low accuracy, limited range of operation or require a physical separation of the phases. We introduce the inference of gas-liquid f

Omri Tal, Tat Dat Tran

Models of adaptive bet-hedging commonly adopt insights from Kelly's famous work on optimal gambling strategies and the financial value of information. In particular, such models seek evolutionary solutions that maximize long term average growth rate of lineages, even in the face of highly stochastic growth trajectories. Here, we argue for extensive depar

Syed Waqas Zamir, Aditya Arora, Salman Khan, Munawar Hayat

With the goal of recovering high-quality image content from its degraded version, image restoration enjoys numerous applications, such as in surveillance, computational photography, medical imaging, and remote sensing. Recently, convolutional neural networks (CNNs) have achieved dramatic improvements over conventional approaches for image restoration task. E

Nami Uchikata, Tatsuya Narikawa, Kazuki Sakai, Hirotaka Takahashi

Ringdown gravitational waves of compact binary mergers are an important target to test general relativity. The main components of the ringdown waveform after merger are black hole quasinormal modes. In general relativity, all multipolar quasinormal modes of a black hole should give the same values of black hole parameters. Although the observed binary black

A. Sai Venkata Ramana, Saif Eddin Jabari

We study heterogeneous traffic dynamics by introducing quenched disorders in all the parameters of Newell's car-following model. Specifically, we consider randomness in the free-flow speed, the jam density, and the backward wave speed. The quenched disorders are modeled using beta distributions. It is observed that, at low densities, the average platoon

Yahui Liu, Marco De Nadai, Jian Yao, Nicu Sebe

Unsupervised image-to-image translation (UNIT) aims at learning a mapping between several visual domains by using unpaired training images. Recent studies have shown remarkable success for multiple domains but they suffer from two main limitations: they are either built from several two-domain mappings that are required to be learned independently, or they g

Navdeep Rana, Prasad Perlekar

We investigate coarsening dynamics in the two-dimensional, incompressible Toner-Tu equation. We show that coarsening proceeds via vortex merger events, and the dynamics crucially depend on the Reynolds number Re. For low Re, the coarsening process has similarities to Ginzburg-Landau dynamics. On the other hand, for high Re, coarsening shows signatures of tur

Christos N. Efrem, Athanasios D. Panagopoulos

The utilization of extremely high frequency (EHF) bands can achieve very high throughput in satellite networks (SatNets). Nevertheless, the severe rain attenuation at EHF bands imposes strict limitations on the system availability. Smart gateway diversity (SGD) is considered indispensable in order to guarantee the required availability with reasonable cost.

Shao-Wen Wei, Ke Yang, Yu-Xiao Liu

In [Phys. Rev. Lett. 124, 101103 (2020)], a universal relation between corrections to entropy and extremality was proposed. The relation was also found to exactly hold for the four-dimensional charged AdS black hole. In this paper, we extend the study to the rotating BTZ and Kerr-AdS black holes when a constant correction to General Relativity is considered

Huanhuan Li, Jiangsheng Hu, Yuefei Zheng

Let $R$ be an Artin algebra and $e$ an idempotent of $R$. Assume that ${\rm Tor}_i^{eRe}(Re,G)=0$ for any $G\in{\rm GProj} eRe$ and $i$ sufficiently large. Necessary and sufficient conditions are given for the Schur functor $S_e$ to induce a triangle-equivalence $\mathbb{D}_{def}(R)\simeq\mathbb{D}_{def}(eRe)$. Combine this with a result of Psaroudakis-Skart

Xingyu Zhang, Xiaoguang Wang

The interacting model describing the Rabi transition is essential in studying atom-photon interactions, where the kinetic energy term is often neglected for the convenience of analysis. We first study the approximation through the fidelity approach and verify its valid region in the parameter space of detuning and momentum. We find that as the radiation fiel

Mark Collier, Basil Mustafa, Efi Kokiopoulou, Rodolphe Jenatton

Datasets with noisy labels are a common occurrence in practical applications of classification methods. We propose a simple probabilistic method for training deep classifiers under input-dependent (heteroscedastic) label noise. We assume an underlying heteroscedastic generative process for noisy labels. To make gradient based training feasible we use a tempe

Chi Zhang, Yujun Cai, Guosheng Lin, Chunhua Shen

In this work, we develop methods for few-shot image classification from a new perspective of optimal matching between image regions. We employ the Earth Mover's Distance (EMD) as a metric to compute a structural distance between dense image representations to determine image relevance. The EMD generates the optimal matching flows between structural elements

Yao-Ming Dong, Ya-Hui Zhai, Dong-Xing Zheng, Jing Wang

We investigate the impacts of combination of fermion-fermion interactions and impurity scatterings on the low-energy stabilities of two-dimensional asymmetric materials with a quadratic band crossing point by virtue of the renormalization group that allows us to treat distinct sorts of physical ingredients on the same footing. The coupled flow evolutions of

Zhi Yang, Xu Cao, Yu-Tie Liang, Jia-Jun Wu

We study the electroproduction of the LHCb pentaquark states with the assumption that they are resonant states. The main concern here is to investigate the final state distribution in the phase space in order to extract the feeble pentaquark signal from the large non-resonant background. Our results show that the ratio of the signal to background would incre

Dan Yang, Jiajun Xian, Liming Pan, Wei Wang

Promoting some typical spreading dynamics, for instance, the spreading of information, commercial message, vaccination guidance, innovation, and political movement, can bring benefits to all aspects of the socio-economic systems. In this study, we propose a strategy for promoting the spreading of the susceptible-infected-recovered model, which is widely appl

Dingshan Deng, Yang Sun, Mingjie Jian, Biwei Jiang

Early-type stars are short lived and scarce in comparison with other types. Based on the recently released catalogs of early type stars from the largest LAMOST spectroscopic survey, the intrinsic colors of the stars with effective temperature up to 32,000\,K are determined for the bands from ultraviolet to infrared by using the blue-edge method. Analytic rel

Lei Wang, Wenbin Huang, Yuanpeng Li, Julian Evans

Predicting and modeling human behavior and finding trends within human decision-making processes is a major problem of social science. Rock Paper Scissors (RPS) is the fundamental strategic question in many game theory problems and real-world competitions. Finding the right approach to beat a particular human opponent is challenging. Here we use an AI (artif

Taras Banakh, Saak Gabriyelyan

We define a locally convex space $E$ to have the $Josefson$-$Nissenzweig$ $property$ (JNP) if the identity map $(E',\sigma(E',E))\to ( E',\beta^\ast(E',E))$ is not sequentially continuous. By the classical Josefson-Nissenzweig theorem, every infinite-dimensional Banach space has the JNP. A characterization of locally convex spaces with the JNP is given. We t

Bin Han, Swaraj Paul, Niraj K. Shukla

Sobolev wavefront sets and $2$-microlocal spaces play a key role in describing and analyzing the singularities of distributions in microlocal analysis and solutions of partial differential equations. Employing the continuous shearlet transform to Sobolev spaces, in this paper we characterize the microlocal Sobolev wavefront sets, the $2$-microlocal spaces, a

Zedu Chen, Bineng Zhong, Guorong Li, Shengping Zhang

Most of the existing trackers usually rely on either a multi-scale searching scheme or pre-defined anchor boxes to accurately estimate the scale and aspect ratio of a target. Unfortunately, they typically call for tedious and heuristic configurations. To address this issue, we propose a simple yet effective visual tracking framework (named Siamese Box Adapti

Takumu Ooi

We obtain sharp two-sided heat kernel estimates on spaces with varying dimension, in which two spaces of general dimension are connected at one point. On these spaces, if the dimensions of the two constituent parts are different, the volume doubling property fails with respect to the measure induced by the associated Lebesgue measures. Thus the parabolic Har

Tetsuya Hosaka

In this paper, we study the Reconstruction Conjecture for finite simple graphs. Let $\Gamma$ and $\Gamma'$ be finite simple graphs with at least three vertices such that there exists a bijective map $f:V(\Gamma) \rightarrow V(\Gamma')$ and for any $v\in V(\Gamma)$, there exists an isomorphism $\phi_v:\Gamma-v \to \Gamma'-f(v)$. Then we define the associated

Arturo J. Nic May, Eric J. Avila Vales

In this paper we will consider a mathematical model that describes, the tritrophic interaction between plants, herbivores and their natural enemies, where volatiles organic compounds (VOCs) released by plants play an important role. We show positivity and boundedness of the system solutions, existence of positive equilibrium and its local stability, we analy

Shohreh Abdolrahimi, Robert B. Mann, Christos Tzounis

We investigate how a static and neutral distribution of external matter distorts a 5-dimensional static black ring. We obtain a general expression for the distorted metric in terms of the background metric functions and the distortion fields, and find a multipole expansion for the latter. We demonstrate that the gravitational field of these external sources

Kazuhiro Kogai, Yuichiro Tada

In the context of string theory, several conjectural conditions have been proposed for low energy effective field theories not to be in swampland, the UV-incomplete class. The recent ones represented by the de Sitter and trans-Planckian censorship conjectures in particular seem to conflict with the inflation paradigm of the early universe. We first point out

Shidi Li

Several model-based and model-free methods have been proposed for the robot trajectory learning task. Both approaches have their benefits and drawbacks. They can usually complement each other. Many research works are trying to integrate some model-based and model-free methods into one algorithm and perform well in simulators or quasi-static robot tasks. Diff

Yiding Qiu, Anwesan Pal, Henrik I. Christensen

Direct search for objects as part of navigation poses a challenge for small items. Utilizing context in the form of object-object relationships enable hierarchical search for targets efficiently. Most of the current approaches tend to directly incorporate sensory input into a reward-based learning approach, without learning about object relationships in the

Qingchao Zhang, Xiaojing Ye, Hongcheng Liu, Yunmei Chen

Optimization algorithms for solving nonconvex inverse problem have attracted significant interests recently. However, existing methods require the nonconvex regularization to be smooth or simple to ensure convergence. In this paper, we propose a novel gradient descent type algorithm, by leveraging the idea of residual learning and Nesterov's smoothing te

Jie J. Bao, Chen Zhou, Zoltan Varga, Siriluk Kanchanakungwankul

Multiconfiguration pair-density functional theory (MC-PFDT) has previously been applied successfully to carry out ground-state and excited-state calculations. However, because it includes no interaction between electronic states, MC-PDFT calculations can give an unphysical double crossing of potential energy surfaces (PESs) in a region near a conical interse

James MacLaurin

We study the dynamics of symmetric and asymmetric spin-glass models of size $N$. The analysis is in terms of the double empirical process: this contains both the spins, and the field felt by each spin, at a particular time (without any knowledge of the correlation history). It is demonstrated that in the large $N$ limit, the dynamics of the double empirical

Esther Rolf, Max Simchowitz, Sarah Dean, Lydia T. Liu

While real-world decisions involve many competing objectives, algorithmic decisions are often evaluated with a single objective function. In this paper, we study algorithmic policies which explicitly trade off between a private objective (such as profit) and a public objective (such as social welfare). We analyze a natural class of policies which trace an em

Vassilis N. Ioannidis, Antonio G. Marques, Georgios B. Giannakis

The era of "data deluge" has sparked renewed interest in graph-based learning methods and their widespread applications ranging from sociology and biology to transportation and communications. In this context of graph-aware methods, the present paper introduces a tensor-graph convolutional network (TGCN) for scalable semi-supervised learning (SSL) from data

Alex Olshevsky

We consider whether distributed subgradient methods can achieve a linear speedup over a centralized subgradient method. While it might be hoped that distributed network of $n$ nodes that can compute $n$ times more subgradients in parallel compared to a single node might, as a result, be $n$ times faster, existing bounds for distributed optimization methods a

Yasuyuki Kato, Shang-Shun Zhang, Yusuke Nishida, C. D. Batista

Universality is a powerful concept that arises from the divergence of a characteristic length scale. For condensed matter systems, this length scale is typically the correlation length, which diverges at critical points separating two different phases. Few-particle systems exhibit a simpler form of universality when the $s$-wave scattering length diverges. A

Jin-Ping Zhu, Yuan-Pei Yang, Liang-Duan Liu, Yan Huang

In this paper, we present a numerical method to study the predicted lightcurves as a function of viewing angle. We extrapolate the fitting formulae for the mass and velocity of tidal dynamical ejecta across a wide range of mass ratio validated with 66 simulations and use them in the calculations of the kilonova lightcurves. The calculated peak luminosity of

Mayuko Yamashita

We give a new construction of strict deformation quantization of symplectic manifolds equipped with a proper Lagrangian fiber bundle structure, whose representation spaces are the quantum Hilbert spaces obtained by geometric quantization. The construction can be regarded as a "lattice approximation of the correspondence between differential operators and

Mourad E. H. Ismail, Nasser Saad

We introduce a finite difference and $q$-difference analogues of the Asymptotic Iteration Method of Ciftci, Hall, and Saad. We give necessary, and sufficient condition for the existence of a polynomial solution to a general linear second-order difference or $q$-difference equation subject to a "terminating condition", which is precisely defined. When

Türkü Özlüm Çelik, Asgar Jamneshan, Guido Montúfar, Bernd Sturmfels

An independence model for discrete random variables is a Segre-Veronese variety in a probability simplex. Any metric on the set of joint states of the random variables induces a Wasserstein metric on the probability simplex. The unit ball of this polyhedral norm is dual to the Lipschitz polytope. Given any data distribution, we seek to minimize its Wasserste

Robert E. Tuzun, Adam S. Sikora

Extending upon our previous work, we verify the Jones Unknot Conjecture for all knots up to $24$ crossings. We describe the method of our approach and analyze the growth of the computational complexity of its different components.

Niraj K. Nepal, Santosh Adhikari, Bimal Neupane, Shiqi Ruan

Small-wavevector excitations in Coulomb-interacting systems can be decomposed into the high-energy collective longitudinal plasmon and the low-energy single-electron excitations. At the critical wavevector and corresponding frequency where the plasmon branch merges with the single-electron excitation region, the collective energy of the plasmon dissipates in

Shion Takeno, Yuhki Tsukada, Hitoshi Fukuoka, Toshiyuki Koyama

Information regarding precipitate shapes is critical for estimating material parameters. Hence, we considered estimating a region of material parameter space in which a computational model produces precipitates having shapes similar to those observed in the experimental images. This region, called the lower-error region (LER), reflects intrinsic information

Tsumoru Shintake

Viruses such as SARS-CoV-2 and Influenza are lipophilic, enveloped viruses, and are relatively easy to inactivate by exposure to alcohols. The envelope mainly consists of the lipid bilayer, taken from the host cells at assembly/budding stage of the viral life cycle. Therefore the constitution of the lipid bilayer should be common in all SARS, MERS and influe

Jonathan A. Weyn, Dale R. Durran, Rich Caruana

We present a significantly-improved data-driven global weather forecasting framework using a deep convolutional neural network (CNN) to forecast several basic atmospheric variables on a global grid. New developments in this framework include an offline volume-conservative mapping to a cubed-sphere grid, improvements to the CNN architecture, and the minimizat

Alexander Lipton

Answers to interview questions sent to a selected group of former physicists working in finance. The interview will be published as part of a Special Issue on Physics and Derivatives by The Journal of Derivatives in the second half of 2020.

N. K. -R. Kevlahan, R. A. Khan

We mathematically derive the sensitivity of data assimilation results for tsunami modelling, to perturbations in the observation operator. We consider results of variational data assimilation schemes on the one dimensional shallow water equations for (i) initial condition reconstruction, and (ii) bathymetry detection as presented in Kevlahan et al. (2019, 20

A. Moscoso-Mártir, J. Koch, J. Müller, S. Sharif Azadeh

We analyze the implementation and capabilities of a silicon photonics transmitter capable of modulating and multiplexing groups of four solitons with different frequency and time spacing based on the nonlinear Fourier transform.

Andre Mendes, Julian Togelius, Leandro dos Santos Coelho

We present a novel framework that can combine multi-domain learning (MDL), data imputation (DI) and multi-task learning (MTL) to improve performance for classification and regression tasks in different domains. The core of our method is an adversarial autoencoder that can: (1) learn to produce domain-invariant embeddings to reduce the difference between doma

Haytham H. Elmousalami, Aboul Ella Hassanien

In mid of March 2020, Coronaviruses such as COVID-19 is declared as an international epidemic. More than 125000 confirmed cases and 4,607 death cases have been recorded around more than 118 countries. Unfortunately, a coronavirus vaccine is expected to take at least 18 months if it works at all. Moreover, COVID -19 epidemics can mutate into a more aggressive

Wen-Yan Lin

It has long been noticed that high dimension data exhibits strange patterns. This has been variously interpreted as either a "blessing" or a "curse", causing uncomfortable inconsistencies in the literature. We propose that these patterns arise from an intrinsically hierarchical generative process. Modeling the process creates a web of constra

V. Medvedev, E. Zhuzhoma

We describe the topological structure of closed manifolds of dimension no less than four which admit Morse-Smale diffeomorphisms such that its non-wandering set contains any number of sink periodic points, and any number of source periodic points, and few saddle periodic points.

Chun-Fang Li

Polarization of light beams is one of the most important physical phenomena. But up till now it was only described in the paraxial approximation in which it is considered to be a single degree of freedom that is characterized by the local Stokes parameters over the transverse plane. Based on such a description, vector vortex beams are considered to be entang

Jingyi Zhu

This work analyzes the stochastic approximation algorithm with non-decaying gains as applied in time-varying problems. The setting is to minimize a sequence of scalar-valued loss functions $f_k(\cdot)$ at sampling times $τ_k$ or to locate the root of a sequence of vector-valued functions $g_k(\cdot)$ at $τ_k$ with respect to a parameter $θ\in R^p$. The avail

Yue Yu, Behçet Açıkmeşe

We consider distributed optimization on undirected connected graphs. We propose a novel distributed conditional gradient method with (O(1/\sqrt{k})) convergence. Compared with existing methods, each iteration of our method uses both communication and linear minimization step only once rather than multiple times. We further extend our results to cases with co

C. Q. Geng, J. N. Ng

We investigate some consequences if neutrinoless double beta decays of nuclei are dominated by short range interactions. To illustrate our results, we assume that such decays proceed mainly through short range interactions involving two-W-bosons exchanges and confine ourselves to only include new scalars without new gauge interactions for SM fermions. For th

Marta Mucientes, Robert McNair, Adrian Peasey, Shouqi Shao

Graphene (GR) remarkable mechanical and electrical properties - such as its Young's modulus, low mass per unit area, natural atomic flatness and electrical conductance - would make it an ideal material for micro and nanoelectromechanical systems (MEMS and NEMS). However, the difficulty of attaching GR to supports coupled with naturally occurring internal

Alberto Aleta, Guilherme Ferraz de Arruda, Yamir Moreno

The modeling of the spreading of communicable diseases has experienced significant advances in the last two decades or so. This has been possible due to the proliferation of data and the development of new methods to gather, mine and analyze it. A key role has also been played by the latest advances in new disciplines like network science. Nonetheless, curre

Nguyen Tran, Rupali Mankar, David Mayerich, Zhu Han

Spectral imaging enables spatially-resolved identification of materials in remote sensing, biomedicine, and astronomy. However, acquisition times require balancing spectral and spatial resolution with signal-to-noise. Hyperspectral imaging provides superior material specificity, while multispectral images are faster to collect at greater fidelity. We propose

Marcello Abbrescia, Giacinto De Cataldo, Antonio di Mauro, Paolo Martinengo

A review of the current progress in developments and tests of supersensitive gaseous detectors of open flame, sparks and smoke is given. A focus on the latest developments is on flat panel type sensors. This design, after further modification, will allow building not only a high efficiency detector but also offers UV imaging capability for flame visualizatio

Jorge Villavicencio, Alberto Hernández-Maldonado

Transient phenomena of phase modulated cut-off wavepackets are explored by deriving an exact general solution to Schrödinger's equation for finite range potentials involving arbitrary initial quantum states. We show that the dynamical features of the probability density are governed by a virtual \textit{self-induced two-level system} with energies $E_{+}

Peter Langfield, Bernd Krauskopf, Hinke M. Osinga

Phase resetting is a common experimental approach to investigating the behaviour of oscillating neurons. Assuming repeated spiking or bursting, a phase reset amounts to a brief perturbation that causes a shift in the phase of this periodic motion. The observed effects not only depend on the strength of the perturbation, but also on the phase at which it is a

Abbass Gorgi, Mourad El Ouali, Anand Srivastav, Mohamed Hachimi

Let $\mathcal{H}=(V,\mathcal{E})$ be a hypergraph with maximum edge size $\ell$ and maximum degree $Δ$. For given numbers $b_v\in \mathbb{N}_{\geq 2}$, $v\in V$, a set multicover in $\mathcal{H}$ is a set of edges $C \subseteq \mathcal{E}$ such that every vertex $v$ in $V$ belongs to at least $b_v$ edges in $C$. Set Multicover is the problem of finding a min

Gianmarco Pinton

Simulations of three dimensional ultrasound propagation in heterogeneous media are computationally intensive due to the constraints arising from the large size of the domain, which is on the order of hundreds of wavelengths, and the small size of scatterers, which are much smaller than a wavelength. Consequently, three dimensional ultrasound imaging simulati

Amirhoshang Hoseinpour Dehkordi, Majid Alizadeh, Pegah Derakhshan, Peyman Babazadeh

The 2019-Novel-Coronavirus (COVID-19) has affected 116 countries (By March 12) and out of more than 118,000 confirmed cases. Understanding the transmission dynamics of the infection in each country which affected on a daily basis and evaluating the effectiveness of control policies is critical for our further actions. To date, the statistics of COVID-19 repo