February 2019 arXiv papers — page 46

Alberto Guandalini, Carlo Andrea Rozzi, Esa Räsänen, Stefano Pittalis

We show that the fundamental gaps of quantum dots can be accurately estimated at the computational effort of a standard ground-state calculation supplemented with a non self-consistent step of negligible cost, all performed within density-functional theory at the level of the local-density approximation.

João Lita da Silva

In this paper we express the eigenvalues of real anti-tridiagonal Hankel matrices as the zeros of given rational functions. We still derive eigenvectors for these structured matrices at the expense of prescribed eigenvalues.

Hao Hao Tan

In this paper, we present the strategy of Agent Madoff, which is a heuristic-based negotiation agent that won 2nd place at the Automated Negotiating Agents Competition (ANAC 2017). Agent Madoff is implemented to play the game Diplomacy, which is a strategic board game that mimics the situation during World War I. Each player represents a major European power

Belma Turkovic, Jorik Oostenbrink, Fernando Kuipers

The ability to detect, in real-time, heavy hitters is beneficial to many network applications, such as DoS and anomaly detection. Through programmable languages as P4, heavy hitter detection can be implemented directly in the data-plane, allowing custom actions to be applied to packets as they are processed at a network node. This enables networks to immedia

Rizwan A. Shah, Mamoona N. Asghar, Saima Abdullah, Martin Fleury

To avoid delays arising from a need to decrypt a video prior to transcoding and then re-encrypt it afterwards, this paper assesses a selective encryption (SE) content protection scheme. The scheme is suited to both recent standardized codecs, namely H.264/Advanced Video Coding (AVC) and High Efficiency Video Coding (HEVC). Specifically, the paper outlines a

Ashik Ikbal Sheikh, Zubayer Ahammed, M. G. Mustafa

We consider the effect of the stochastic color field fluctuations in addition to the collisional as well as the radiative energy losses in the propagation of charm quarks in the hot and dense deconfined medium of quarks and gluons created in ultra-relativistic heavy-ion collisions. These fluctuations lead to energy gain of the propagating charm quarks. We co

Nicolas Burq, Joachim Krieger

We introduce a novel data randomisation for the free wave equation which leads to the same range of Strichartz estimates as for radial data, albeit in a non-radial context. We then use these estimates to establish global well-posedness for a wave maps type nonlinear wave equation for certain supercritical data, provided the data are suitably small and random

Johannes Kombe, Jean-Sebastien Bernier, Michael Köhl, Corinna Kollath

We investigate the non-equilibrium behavior of BCS superconductors subjected to slow ramps of their internal interaction strength. We identify three dynamical regimes as a function of ramp duration. For short ramp times, these systems become non-superconducting; however, fermions with opposite momenta remain paired albeit with reduced amplitudes, and the ass

Xiaodong Chen, Chundong Xue, Gongqing Hu

We study the breakup of confined fluid threads at low flow rates to understand instability mechanisms. To determine the critical conditions between the earlier quasi-stable necking stage and the later unstable collapse stage, simulations and experiments are designed to operate at an extremely low flow rate. Critical mean radii at neck centres are identified

M. Caleb, C. Flynn, B. Stappers

The discovery of fast radio bursts (FRBs) about a decade ago opened up new possibilities for probing the ionization history of the Intergalactic Medium (IGM). In this paper we study the use of FRBs for tracing the epoch of HeII reionization, using simulations of their dispersion measures. We model dispersion measure contributions from the Milky Way, the IGM

Juozas Vaicenavicius, David Widmann, Carl Andersson, Fredrik Lindsten

Probabilistic classifiers output a probability distribution on target classes rather than just a class prediction. Besides providing a clear separation of prediction and decision making, the main advantage of probabilistic models is their ability to represent uncertainty about predictions. In safety-critical applications, it is pivotal for a model to possess

Michael Burt, Kasra Amini, Jason W. L. Lee, Lars Christiansen

The gas-phase structures of four difluoroiodobenzene and two dihydroxybromobenzene isomers were identified by correlating the emission angles of atomic fragment ions created following femtosecond laser-induced Coulomb explosion. The structural determinations were facilitated by confining the most polarizable axis of each molecule to the detection plane prior

Thomas Lugrin, Anthony C. Davison, Jonathan A. Tawn

Models for extreme values are generally derived from limit results, which are meant to be good enough approximations when applied to finite samples. Depending on the speed of convergence of the process underlying the data, these approximations may fail to represent subasymptotic features present in the data, and thus may introduce bias. The case of univariat

François Lavallée, Charline Smadi, Isabelle Alvarez, Björn Reineking

Invasive alien species are a growing threat for environment and health. They also have a major economic impact, as they can damage many infrastructures. The Japanese knotweed (Fallopia japonica), present in North America, Northern and Central Europe as well as in Australia and New Zealand, is listed by the World Conservation Union as one of the world's w

Maria Colombo, Gianluca Crippa, Marie Graff, Laura V. Spinolo

We provide an informal overview of recent developments concerning the singular local limit of nonlocal conservation laws. In particular, we discuss some counterexamples to convergence and we highlight the role of numerical viscosity in the numerical investigation of the nonlocal-to-local limit. We also state some open questions and describe recent related pr

Gh. Haghighatdoost, R. Ayoubi

In this paper, some of formulations of Hamilton-Jacobi equations for Hamiltonian system on Lie algebroids are given. Here we use the general properties of Lie algebroids to express and prove two geometric version of the Hamilton-Jacobi theorem for Hamiltonian system on Lie algebroids. Then this results are generalized and two types of time-dependent Hamilton

Y. V. Kudryavtsev, A. E. Perekos, N. V. Uvarov, M. R. Kolchiba

Magnetic and transport properties of near-stoichiometric metastable FexMnyGaz alloys (46<x<52, 17<y25, 26<z<30) with face-centered cubic (FCC), body-centered cubic (BCC), and two-phase (FCC+BCC) structures are investigated. The experimental results are analyzed in terms of first-principles calculations of stoichiometric Fe2MnGa alloy with the L21, L12, and t

Yang Liu, Junfeng Wu, Ian R. Manchester, Guodong Shi

A distributed computing protocol consists of three components: (i) Data Localization: a network-wide dataset is decomposed into local datasets separately preserved at a network of nodes; (ii) Node Communication: the nodes hold individual dynamical states and communicate with the neighbors about these dynamical states; (iii) Local Computation: state recursion

Ankita Shukla, Shagun Uppal, Sarthak Bhagat, Saket Anand

Deep generative models like variational autoencoders approximate the intrinsic geometry of high dimensional data manifolds by learning low-dimensional latent-space variables and an embedding function. The geometric properties of these latent spaces has been studied under the lens of Riemannian geometry; via analysis of the non-linearity of the generator func

Brandon Annesi, Enzo Marinari, Gleb Oshanin

The question how the extremal values of a stochastic process achieved on different time intervals are correlated to each other has been discussed within the last few years on examples of the running maximum of a Brownian motion, of a Brownian Bridge and of a Slepian process. Here, we focus on the two-time correlations of the running range of Brownian motion

Mariam Nouh, Jason R. C. Nurse, Helena Webb, Michael Goldsmith

Cybercrime investigators face numerous challenges when policing online crimes. Firstly, the methods and processes they use when dealing with traditional crimes do not necessarily apply in the cyber-world. Additionally, cyber criminals are usually technologically-aware and constantly adapting and developing new tools that allow them to stay ahead of law enfor

Stasis Chuchurka, Andrei Benediktovitch, Aliaksandr Leonau, Sergey Galyamin

X-ray radiation of relativistic electrons passing through the crystal lattice (in case of channeling radiation) requires electrons with energies just from tens up to hundreds MeV, but has a drawback: low number of emitted X-ray quanta. However, the brightness of such a source could be potentially increased if the current density of the electron bunch is high

Fedor V. Fomin, Petr A. Golovach, Daniel Lokshtanov, Saket Saurabh

Perturbed graphic matroids are binary matroids that can be obtained from a graphic matroid by adding a noise of small rank. More precisely, r-rank perturbed graphic matroid M is a binary matroid that can be represented in the form I +P, where I is the incidence matrix of some graph and P is a binary matrix of rank at most r. Such matroids naturally appear in

Paul J. Hancock, Natasha Hurley-Walker, Tim E. White

We present Robbie: a general work-flow for the detection and characterization of radio variability and transient events in the image domain. Robbie is designed to work in a batch processing paradigm with a modular design so that components can be swapped out or upgraded to adapt to different input data, whilst retaining a consistent and coherent methodologic

J. E. Geach, J. A. Peacock, A. D. Myers, R. C. Hickox

We measure the average deflection of cosmic microwave background photons by quasars at $\langle z \rangle =1.7$. Our sample is selected from the Sloan Digital Sky Survey to cover the redshift range $0.9\leq z\leq2.2$ with absolute i-band magnitudes of $M_i\leq-24$ (K-corrected to z=2). A stack of nearly 200,000 targets reveals an 8$σ$ detection of Planck&#39

Li-yao Xia, Dominic Orchard, Meng Wang

Software frequently converts data from one representation to another and vice versa. Naively specifying both conversion directions separately is error prone and introduces conceptual duplication. Instead, bidirectional programming techniques allow programs to be written which can be interpreted in both directions. However, these techniques often employ unfam

Naoki Sato, Michio Yamada

Object of the present paper is the local theory of solution for steady ideal Euler flows and ideal MHD equilibria. The present analysis relies on the Lie-Darboux theorem of differential geometry and the local theory of representation and construction of Beltrami fields developed in [1]. A theorem for the construction of harmonic orthogonal coordinates is pro

Deborah Baker, Lidia van Driel-Gesztelyi, David H. Brooks, Gherardo Valori

Understanding elemental abundance variations in the solar corona provides an insight into how matter and energy flow from the chromosphere into the heliosphere. Observed variations depend on the first ionization potential (FIP) of the main elements of the Sun&#39;s atmosphere. High-FIP elements (>10 eV) maintain photospheric abundances in the corona, whereas

P. Cumani, M. Hernanz, J. Kiener, V. Tatischeff

The different background components in a low-Earth orbit have been modeled in the 10 keV to 100 GeV energy range. The model is based on data from previous instruments and it considers both primary and secondary particles, charged particles, neutrons and photons. The necessary corrections to consider the geomagnetic cutoff are applied to calculate the flux at

Fayçal Ait Aoudia, Jakob Hoydis

There is a recent interest in neural network (NN)-based communication algorithms which have shown to achieve (beyond) state-of-the-art performance for a variety of problems or lead to reduced implementation complexity. However, most work on this topic is simulation based and implementation on specialized hardware for fast inference, such as field-programmabl

Ce Wang, Zhangling Chen, Kun Shang

Generative Adversarial Networks (GANs) have achieved great success in generating realistic images. Most of these are conditional models, although acquisition of class labels is expensive and time-consuming in practice. To reduce the dependence on labeled data, we propose an un-conditional generative adversarial model, called K-Means-GAN (KM-GAN), which incor

Leonid Matyushin, Alexey Zaytsev, Oleg Alenkin, Andrey Ustuzhanin

The key idea of Bayesian optimization is replacing an expensive target function with a cheap surrogate model. By selection of an acquisition function for Bayesian optimization, we trade off between exploration and exploitation. The acquisition function typically depends on the mean and the variance of the surrogate model at a given point. The most common Gau

Tong-Xing Zheng, Hui-Ming Wang, Derrick Wing Kwan Ng, Jinhong Yuan

This paper studies multi-antenna-aided covert communications coexisting with randomly located wardens and interferers, considering both centralized and distributed antenna systems (CAS/DAS). The throughput performance of the covert communication is analyzed and optimized under a stochastic geometry framework, where the joint impact of the small-scale channel

Cheng-Shang Chang, Yeh-Cheng Chang, Jang-Ping Sheu

The multichannel rendezvous problem that asks two secondary users to rendezvous on a common available channel in a cognitive radio network (CRN) has received a lot of attention lately. Most rendezvous algorithms in the literature focused on constructing channel hopping (CH) sequences that guarantee finite maximum time-to-rendezvous (MTTR). However, these alg

Chaojie Zhao, Peng Zhang, Jian Zhu, Chengrui Wu

A challenge in speech production research is to predict future tongue movements based on a short period of past tongue movements. This study tackles speaker-dependent tongue motion prediction problem in unlabeled ultrasound videos with convolutional long short-term memory (ConvLSTM) networks. The model has been tested on two different ultrasound corpora. Con

Ha Son Vu, Daisuke Ueta, Kiyoshi Hashimoto, Kazuki Maeno

Semi-supervised and unsupervised Generative Adversarial Networks (GAN)-based methods have been gaining popularity in anomaly detection task recently. However, GAN training is somewhat challenging and unstable. Inspired from previous work in GAN-based image generation, we introduce a GAN-based anomaly detection framework - Adversarial Dual Autoencoders (ADAE)

Xueqing Deng, Yi Zhu, Shawn Newsam

This paper develops a deep-learning framework to synthesize a ground-level view of a location given an overhead image. We propose a novel conditional generative adversarial network (cGAN) in which the trained generator generates realistic looking and representative ground-level images using overhead imagery as auxiliary information. The generator is an encod

Michael Hoefnagel

In universal algebra, it is well known that varieties admitting a majority term admit several Mal&#39;tsev-type characterizations. The main aim of this paper is to establish categorical counterparts of some of these characterizations for regular categories. We prove a categorical version of Bergman&#39;s Double-projection Theorem: a regular category is a maj

Yafei Song, Yonghong Tian, Gang Wang, Mingyang Li

It is a significant problem to predict the 2D LiDAR map at next moment for robotics navigation and path-planning. To tackle this problem, we resort to the motion flow between adjacent maps, as motion flow is a powerful tool to process and analyze the dynamic data, which is named optical flow in video processing. However, unlike video, which contains abundant

Anubhab Ray, Saikat Roy, Satya Bagchi, Debmalya Sain

We introduce the concept of weak L-P property for a pair of Banach spaces, in the study of extreme contractions. We give examples of pairs of Banach spaces (not) satisfying weak L-P property and apply the concept to compute the exact number of extreme contractions between a particular pair of polygonal Banach spaces. We also study the optimality of our resul

Adil E. Rajput, Akila Sarirete, Tamer F. Desouky

Social Media provides researchers with an unprecedented opportunity to gain insight into various facets of human life. Health practitioners put a great emphasis on pinpointing socioeconomic status (SES) of individuals as they can use to it to predict certain diseases. Crowdsourcing is a term coined that entails gathering intelligence from a user community on

Runyu Jiang, Andrey Elagin

We present a technique for separating double beta-decay from $^8$B solar neutrino interactions in a liquid scintillator detector. The technique uses position and time of photo-electrons (PEs) to separate directional Cherenkov light from isotropic sintillation light in the reconstruction of the kinematics of candidate events. Here we introduce a Cherenkov-sci

M. Tripathi

Here, we describe the prototype for precisely scaled temperature assisted magnetic recording scheme utilizing the characteristics of thermo-remnant magnetization (TRM) in bulk SmCrO$_3$ as a memory media. The TRM response can be exploited in completely reversible bipolar switching performances either by tuning the temperature only across a sharp thermal wind

Eitam Luz, Vitaly Lutsky, Er&#39;el Granot, Boris A. Malomed

The real spectrum of bound states produced by PT-symmetric Hamiltonians usually suffers breakup at a critical value of the strength of gain-loss terms, i.e., imaginary part of the complex potential. On the other hand, it is known that the PT-symmetry can be made unbreakable in a one-dimensional (1D) model with self-defocusing nonlinearity whose strength grow

Jinhwi Lee, Younggil Cho, Changjoo Nam, Jonghyeon Park

We present an algorithm that produces a plan for relocating obstacles in order to grasp a target in clutter by a robotic manipulator without collisions. We consider configurations where objects are densely populated in a constrained and confined space. Thus, there exists no collision-free path for the manipulator without relocating obstacles. Since the probl

Mohammad Golshani

We give a detailed proof of the properties of the usual Prikry type forcing notion for turning a measurable cardinal into $\aleph_ω$.

Ashadul Halder, Shibaji Banerjee, Debasish Majumdar

The gravitational waves (GWs) has been a topic of interest for its versatile capabilities of probing several aspects of cosmology and early Universe. Gravitational lensing enhances further the extent of this sort of waves and upgrade our understanding to a next level. Besides several similarities with optical waves, GWs are capable of passing through optical

Lyuboslav Panchev

We present progress in trying to verify a long-standing conjecture by Mark Mahowald on the $v_{1}$-periodic component of the classical Adams spectral sequence for a Moore space $M$. The approach we follow was proposed by John Palmieri in his work on the stable category of $A$-comodules. We improve on Palmieri&#39;s work by working with the endomorphism ring

Svetlana V. Butler

When $X$ is locally compact, a quasi-integral (also called a quasi-linear functional) on $ C_c(X)$ is a homogeneous, positive functional that is only assumed to be linear on singly-generated subalgebras. We study simple and almost simple quasi-integrals, i.e., quasi-integrals whose corresponding compact-finite topological measures assume exactly two values.

Chandramouli Chowdhury, Susmita Das, Surojit Dalui, Bibhas Ranjan Majhi

We re-advocated the conjecture of indistinguishability between the quantum fluctuation observed from a Rindler frame and a real thermal bath, for the case of a free massless scalar field. To clarify the robustness and how far such is admissible, in this paper, we investigate the issue from two different non-inertial observers&#39; perspective. A detailed ana

Fang Zhang, You-Chao Kong, Rui Pang, Liang Hu

The Goodenough-Kanamori-Anderson (GKA) rules have been widely applied for explaining the magnetic properties induced by super-exchange interaction. As conclusions of the super-exchange theory, they reveal the antiferromagnetic (ferromagnetic) ordering along with bond angle of 180 degrees (90 degrees) in the cation-anion-cation interaction path, in which the

Sudhir Kumar Sahu, Jaykumar Vaidya, Felix Schmidt, Digambar Jangade

In this report, we present nanoelectromechanical resonators fabricated with thin exfoliated crystals of a high-T$_c$ cuprate superconductor Bi$_2$Sr$_2$Ca$_1$Cu$_2$O$_{8+δ}$. The mechanical readout is performed by capacitively coupling their motion to a coplanar waveguide microwave cavity fabricated with a superconducting alloy of molybdenum-rhenium. We demo

Zhi Lü, Wei Wang, Li Yu

This paper is a survey on the Lickorish type construction of some kind of closed manifolds over simple convex polytopes. Inspired by Lickorish&#39;s theorem, we propose a method to describe certain families of manifolds over simple convex polytopes with torus action. Under this construction, many classical classification results of these families of manifold

Chen Yuan, Yi Lu, Wei Feng, Guangyi Liu

Power flow analysis plays a fundamental and critical role in the energy management system (EMS). It is required to well accommodate large and complex power system. To achieve a high performance and accurate power flow analysis, a graph computing based distributed power flow analysis approach is proposed in this paper. Firstly, a power system network is divid

Jing Zhong, Li Chen, M. B. N. Kouwenhoven, Lu Li

In order to study the stellar population and possible substructures in the outskirts of Double Cluster $h$ and $χ$ Persei, we investigate using the GAIA DR2 data a sky area of about 7.5 degrees in radius around the Double Cluster cores. We identify member stars using various criteria, including their kinematics (viz, proper motion), individual parallaxes, as

Nasser Kazemi, Daniel Trad, Kris Innanen, Roman Shor

Least-squares migration can, in theory, reduce the acquisition footprint and improve the illumination of the subsurface structures. It can also recover the amplitudes of the events to some extent. However, the migration operator is not complete. In other words, the operator does not span the full range of the model and the portion of the model that is in the

Xiaotao Jia, Jianlei Yang, Pengcheng Dai, Runze Liu

Bayesian inference is an effective approach for solving statistical learning problems, especially with uncertainty and incompleteness. However, Bayesian inference is a computing-intensive task whose efficiency is physically limited by the bottlenecks of conventional computing platforms. In this work, a spintronics based stochastic computing approach is propo

Shuang Wang, De-Yong He, Zhen-Qiang Yin, Feng-Yu Lu

With the help of quantum key distribution (QKD), two distant peers are able to share information-theoretically secure key bits. Increasing key rate is ultimately significant for the applications of QKD in lossy channel. However, it has proved that there is a fundamental rate-distance limit, named linear bound, which limits the performance of all existing rep

Alexander J. Silenko, Pengming Zhang, Liping Zou

For a twisted (vortex) Dirac particle in nonuniform electric and magnetic fields, the relativistic Foldy-Wouthuysen Hamiltonian is derived including high order terms describing new effects. The result obtained shows for the first time that a twisted spin-1/2 particle possesses a tensor magnetic polarizability and a measurable (spectroscopic) electric quadrup

Atul Rungta, Nicholas Rewkowski, Roberta Klatzky, Dinesh Manocha

We introduce a novel, perceptually derived metric (P-Reverb) that relates the just-noticeable difference (JND) of the early sound field(also called early reflections) to the late sound field (known as late reflections or reverberation). Early and late reflections are crucial components of the sound field and provide multiple perceptual cues for auditory disp

Mitchell Krock, William Kleiber, Stephen Becker

Many modern spatial models express the stochastic variation component as a basis expansion with random coefficients. Low rank models, approximate spectral decompositions, multiresolution representations, stochastic partial differential equations and empirical orthogonal functions all fall within this basic framework. Given a particular basis, stochastic depe

Nouamane Laanait, Qian He, Albina Y. Borisevich

Deep learning has demonstrated superb efficacy in processing imaging data, yet its suitability in solving challenging inverse problems in scientific imaging has not been fully explored. Of immense interest is the determination of local material properties from atomically-resolved imaging, such as electron microscopy, where such information is encoded in subt

Junchao Ma, Ke Deng, Lu Zheng, Sanfeng Wu

We review recent experimental progresses on layered topological materials, mainly focusing on transitional metal dichalcogenides with various lattice types including 1T, Td and 1T&#39; structural phases. Their electronic quantum states are interestingly rich, and many appear to be topological nontrivial, such as Dirac/Weyl semimetallic phase in multilayers a

Andre Neumann, Jessica Lindlau, Manuel Nutz, Aditya D. Mohite

We study spatial photoluminescence characteristics of neutral and charged excitons across extended monolayer MoS$_2$ synthesized by chemical vapor deposition. Using two-dimensional hyperspectral photoluminescence mapping at cryogenic temperatures we identify regions with increased emission from charged excitons associated with both spin-orbit split valence s

Sergio Acosta, Jorge E. Camargo

Safety perception measurement has been a subject of interest in many cities of the world. This is due to its social relevance, and to its effect on some local economic activities. Even though people safety perception is a subjective topic, sometimes it is possible to find out common patterns given a restricted geographical and sociocultural context. This pap

Tan Zheng Hui Ernest, A S Madhukumar, Rajendra Prasad Sirigina, Anoop Kumar Krishna

Unmanned aerial vehicles (UAVs) are set to feature heavily in upcoming fifth generation (5G) networks. Yet, the adoption of multi-UAV networks means that spectrum scarcity in UAV communications is an issue in need of urgent solutions. Towards this end, downlink non-orthogonal multiple access (NOMA) is investigated in this paper for multi-UAV networks to impr

Chenchao Xu, Qijin Chen, Chao Cao

The relationship between magnetism and superconductivity has been one of the most discussed topics in iron-based superconductors. Using the first-principles calculations, we have studied the electronic structure of 1144-type iron-based superconductor EuRbFe$_4$As$_4$. We find the crystal field splitting of EuRbFe$_4$As$_4$ is unique, such that the $d_{z^2}$

Roman Pop, Ali Hassan, Kenneth Bruninx, Michael Chertkov

This paper describes a step-by-step procedure that converts a physical model of a building into a Markov Process that characterizes energy consumption of this and other similar buildings. Relative to existing thermo-physics-based building models, the proposed procedure reduces model complexity and depends on fewer parameters, while also maintaining accuracy

Ali Fatih Demir, Z. Esat Ankarali, Qammer H. Abbasi, Yang Liu

In vivo wireless medical devices have the potential to play a vital role in future healthcare technologies by improving the quality of human life. In order to fully exploit the capabilities of such devices, it is necessary to characterize and model the in vivo wireless communication channel. Utilization of this model will have a significant role in improving

N. Harrison, J. B. Betts, M. R. Wartenbe, F. F. Balakirev

(Pu) has an unusually rich phase diagram that includes seven distinct solid state phases and an unusually large 25% collapse in volume from its delta phase to its low temperature alpha phase via a series of structural transitions. Despite considerable advances in our understanding of strong electronic correlations within various structural phases of Pu and o

Andre Neumann, Jessica Lindlau, Léo Colombier, Manuel Nutz

Transition metal dichalcogenide semiconductors represent elementary components of layered heterostructures for emergent technologies beyond conventional opto-electronics. In their monolayer form they host electrons with quantized circular motion and associated valley polarization and valley coherence as key elements of opto-valleytronic functionality. Here,

Chen Change Loy, Dahua Lin, Wanli Ouyang, Yuanjun Xiong

This paper presents a review of the 2018 WIDER Challenge on Face and Pedestrian. The challenge focuses on the problem of precise localization of human faces and bodies, and accurate association of identities. It comprises of three tracks: (i) WIDER Face which aims at soliciting new approaches to advance the state-of-the-art in face detection, (ii) WIDER Pede

Debajyoti Bera, Tharrmashastha P.

We give a technique to reduce the error probability of quantum algorithms that determine whether its input has a specified property of interest. The standard process of reducing this error is statistical processing of the results of multiple independent executions of an algorithm. Denoting by $ρ$ an upper bound of this probability (wlog., assume $ρ\le \frac{

Anton Galajinsky, Olaf Lechtenfeld

As is known, any realization of SU(2) in the phase space of a dynamical system can be generalized to accommodate the exceptional supergroup $D(2,1;α)$, which is the most general $\mathcal{N}{=}\,4$ supersymmetric extension of the conformal group in one spatial dimension. We construct novel spinning extensions of $D(2,1;α)$ superconformal mechanics by adjusti

Hao Jia

We give an elementary proof of sharp decay rates and the linear inviscid damping near monotone shear flow in a periodic channel, first obtained in [14]. We shall also obtain the precise asymptotics of the solutions, measured in the space $L^{\infty}$.

François Rottenberg, Rui Wang, Jianzhong Zhang, Andreas F. Molisch

Downlink channel estimation in massive MIMO systems is well known to generate a large overhead in frequency division duplex (FDD) mode as the amount of training generally scales with the number of transmit antennas. Using instead an extrapolation of the channel from the measured uplink estimates to the downlink frequency band completely removes this overhead

Amir Hossein Yazdavar, Mohammad Saeid Mahdavinejad, Goonmeet Bajaj, William Romine

With ubiquity of social media platforms, millions of people are sharing their online persona by expressing their thoughts, moods, emotions, feelings, and even their daily struggles with mental health issues voluntarily and publicly on social media. Unlike the most existing efforts which study depression by analyzing textual content, we examine and exploit mu

Jose Luis Gracia, Eugene O&#39;Riordan

Numerical approximations to the solutions of three different problem classes of singularly perturbed parabolic reaction-diffusion problems, each with a discontinuity in the bound\-ary-initial data, are generated. For each problem class, an analytical function associated with the discontinuity in the data, is identified. Parameter-uniform numerical approximat

Yang Liu, Junfeng Wu, Ian Manchester, Guodong Shi

In the first part of the paper, we have studied the computational privacy risks in distributed computing protocols against local or global dynamics eavesdroppers, and proposed a Privacy-Preserving-Summation-Consistent (PPSC) mechanism as a generic privacy encryption subroutine for consensus-based distributed computations. In this part of this paper, we show

Fabian Mager, Dominik Baumann, Romain Jacob, Lothar Thiele

Closing feedback loops fast and over long distances is key to emerging applications; for example, robot motion control and swarm coordination require update intervals of tens of milliseconds. Low-power wireless technology is preferred for its low cost, small form factor, and flexibility, especially if the devices support multi-hop communication. So far, howe

Dehao Wu, Maziar Nekovee, Yue Wang

Deep learning (DL) based autoencoder has shown great potential to significantly enhance the physical layer performance. In this paper, we present a DL based autoencoder for interference channel. Based on a characterization of a k-user Gaussian interference channel, where the interferences are classified as different levels from weak to very strong interferen

Sergio Andraus, Michael Voit

Bessel processes $(X_{t,k})_{t\ge0}$ in $N$ dimensions are classified via associated root systems and multiplicity constants $k\ge0$. They describe interacting Calogero-Moser-Suther\-land particle systems with $N$ particles and are related to $\beta$-Hermite and $\beta$-Laguerre ensembles. Recently, several central limit theorems were derived for fixed $t>0$

Carlos Hernandez-Suarez

There are known expressions to calculate the moments of the first passage time in Markov chains. Nevertheless, it is commonly forgotten that in most applications the parameters of the Markov chain are constructed using estimates based upon empirical data and in those cases the data sample size should play an important role in estimating the variance. Here we

Carlos Florentino, Azizeh Nozad, Alfonso Zamora

With G=GL(n,C), let $\mathcal{X}_{\Gamma}G$ be the G-character variety of a given finitely presented group $\Gamma$, and let $\mathcal{X}^{irr}_{\Gamma}G \subset \mathcal{X}_{\Gamma}G$ be the locus of irreducible representation conjugacy classes. We provide a concrete relation, in terms of plethystic functions, between the generating series for E- polynomial

Tian Xie, Arthur France-Lanord, Yanming Wang, Yang Shao-Horn

Understanding the dynamical processes that govern the performance of functional materials is essential for the design of next generation materials to tackle global energy and environmental challenges. Many of these processes involve the dynamics of individual atoms or small molecules in condensed phases, e.g. lithium ions in electrolytes, water molecules in

Christina Goldschmidt, Simon Griffiths, Alex Scott

The main contribution of this article is an asymptotic expression for the rate associated with moderate deviations of subgraph counts in the Erd\H{o}s-R\'enyi random graph $G(n,m)$. Our approach is based on applying Freedman's inequalities for the probability of deviations of martingales to a martingale representation of subgraph count deviations. In additio

Gustavo Montes Cabrera, David Davalos, Thomas Gorin

We study quantum processes, as one parameter families of differentiable completely positive and trace preserving (CPTP) maps. Using different representations of the generator, and the Sylvester criterion for positive semi-definite matrices, we obtain conditions for the divisibility of the process into completely positive (CP-divisibility) and positive (P-div

Leonardo Novelli, Patricia Wollstadt, Pedro Mediano, Michael Wibral

Network inference algorithms are valuable tools for the study of large-scale neuroimaging datasets. Multivariate transfer entropy is well suited for this task, being a model-free measure that captures nonlinear and lagged dependencies between time series to infer a minimal directed network model. Greedy algorithms have been proposed to efficiently deal with

Jason Liang, Elliot Meyerson, Babak Hodjat, Dan Fink

Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of its architecture and hyperparameters. Such a configuration is difficult and as a result, DNNs are often not used to their full potential. In addition, DNNs in commercial applications of

Samuel F. Potter, Maria K. Cameron

We present a family of fast and accurate Dijkstra-like solvers for the eikonal equation and factored eikonal equation which compute solutions on a regular grid by solving local variational minimization problems. Our methods converge linearly but compute significantly more accurate solutions than competing first order methods. In 3D, we present two different

Syed Arbab Mohd Shihab, Caleb Logemann, Deepak-George Thomas, Peng Wei

Revenue management can enable airline corporations to maximize the revenue generated from each scheduled flight departing in their transportation network by means of finding the optimal policies for differential pricing, seat inventory control and overbooking. As different demand segments in the market have different Willingness-To-Pay (WTP), airlines use di

D. Dell&#39;Aquila, S. Sweany, K. W. Brown, Z. Chajecki

The light output produced by light ions (Z<=4) in CsI(Tl) crystals is studied over a wide range of detected energies (E<=300 MeV). Energy-light calibration data sets are obtained with the 10 cm crystals in the recently upgraded High-Resolution Array (HiRA10). We use proton recoil data from 40,48Ca + CH2 at 28 MeV/u, 56.6 MeV/u, 39 MeV/u and 139.8 MeV/u and d

Thomas Breuer, Kay Magaard, Robert A. Wilson

We show the details of certain computations that are described in [BMW19].

Yoni Choukroun, Eli Kravchik, Fan Yang, Pavel Kisilev

Recent machine learning methods use increasingly large deep neural networks to achieve state of the art results in various tasks. The gains in performance come at the cost of a substantial increase in computation and storage requirements. This makes real-time implementations on limited resources hardware a challenging task. One popular approach to address th

B. G. C. Lackenby, V. A. Dzuba, V. V. Flambaum

We use recently developed efficient versions of the configuration interaction method to perform {\em ab initio} calculations of the spectra of superheavy elements seaborgium (Sg, $Z=106$), bohrium (Bh, $Z=107$), hassium (Hs, $Z=108$) and meitnerium (Mt, $Z=109$). We calculate energy levels, ionization potentials, isotope shifts and electric dipole transition

Hayato Ushijima-Mwesigwa, Jeffrey D. Hyman, Aric Hagberg, Ilya Safro

We present a topology-based method for mesh-partitioning in three-dimensional discrete fracture network (DFN) simulations that take advantage of the intrinsic multi-level nature of a DFN. DFN models are used to simulate flow and transport through low-permeability fractured media in the subsurface by explicitly representing fractures as discrete entities. The

Panagiotis Papadopoulos, Peter Snyder, Dimitrios Athanasakis, Benjamin Livshits

Funding the production of quality online content is a pressing problem for content producers. The most common funding method, online advertising, is rife with well-known performance and privacy harms, and an intractable subject-agent conflict: many users do not want to see advertisements, depriving the site of needed funding. Because of these negative aspect

Efrain J Ferrer, Vivian de la Incera

We investigate the stability of the Magnetic Dual Chiral Density Wave (MDCDW) phase of cold and dense QCD against collective low-energy fluctuations of the order parameter. The appearance of additional structures in the system free-energy due to the explicit breaking of the rotational and isospin symmetries by the external magnetic field and the field-induce

Abraham Martin del Campo, Frank Sottile, Robert Williams

We classify Schubert problems in the Grassmannian of 4-planes in 9-dimensional space by their Galois groups. Of the 31,806 essential Schubert problems in this Grassmannian, there are only 149 whose Galois group does not contain the alternating group. We identify the Galois groups of these 149 -- each is an imprimitive permutation group. These 149 fall into t

Samuel C. Gutekunst, David P. Williamson

We consider the integrality gap of the subtour LP relaxation of the Traveling Salesman Problem restricted to circulant instances. De Klerk and Dobre conjectured that the value of the optimal solution to the subtour LP on these instances is equal to an entirely combinatorial lower bound from Van der Veen, Van Dal, and Sierksma. We prove this conjecture by giv