November 2018 arXiv papers — page 117

Donghyun Gouk, Miryeong Kwon, Jie Zhang, Sungjoon Koh

SSDs become a major storage component in modern memory hierarchies, and SSD research demands exploring future simulation-based studies by integrating SSD subsystems into a full-system environment. However, several challenges exist to model SSDs under a full-system simulations; SSDs are composed upon their own complete system and architecture, which employ al

Emmanuel Trélat, Gengsheng Wang, Yashan Xu

Given a linear control system in a Hilbert space with a bounded control operator, we establish a characterization of exponential stabilizability in terms of an observability inequality. Such dual characterizations are well known for exact (null) controllability. Our approach exploits classical Fenchel duality arguments and, in turn, leads to characterization

Gilles Ferrand, Don Warren

On 21 April 2018, the citizens of Wako, Japan, interacted in a novel way with research being carried out at the Astrophysical Big Bang Laboratory (ABBL) at RIKEN. They were able to explore a model of a supernova and its remnant in an immersive three-dimentional format by using virtual reality (VR) technology. In this article, we explain how this experience w

Bingli Jiao, Yuli Yang, Mingxi Yin

The present paper proposes a novel transmission strategy, referred to as cocktail BPSK, whereat two independent BPSKs are superposed with the non-orthogonal basis in a parallel transmission. In contrast to the conventional signal superpositions, the proposed scheme avoids the interference between the two symbols, allows the symbol-energy-reuse of each other

Yanyan Zhu, Karim Aissou, David Andelman, Xingkun Man

We explore the relative stability of three possible orientations of cylinder-forming di-block copolymer on a sinusoidally corrugated substrate. The cylinders can be aligned either parallel to the substrate, with their long axis being oriented along or orthogonal to the corrugation trenches, or perpendicular to the substrate. Using self-consistent field theor

Romain Horsin

We consider time discretizations of the two-dimensional Euler equation written in vorticity form. The discretization method uses a Crouch-Grossman integrator that proceeds in two stages: first freezing the velocity vector field at the beginning of the time step, and then solve the resulting elementary transport equation by using a symplectic integrator to di

Dhananjaya Thakur

At LHC energies, the charged-particle multiplicity dependence of particle production is a topic of considerable interest in $pp$ collisions. It has been argued that multiple partonic interactions play an important role in particle production mechanisms, not only affecting the soft processes but also the hard processes. Recently, ALICE has measured $J/ψ$ prod

Rüdiger Göbl, Diana Mateus, Christoph Hennersperger, Maximilian Baust

Freehand three-dimensional ultrasound (3D-US) has gained considerable interest in research, but even today suffers from its high inter-operator variability in clinical practice. The high variability mainly arises from tracking inaccuracies as well as the directionality of the ultrasound data, being neglected in most of today's reconstruction methods. By

Hassan Ismail Fawaz, Germain Forestier, Jonathan Weber, Lhassane Idoumghar

Transfer learning for deep neural networks is the process of first training a base network on a source dataset, and then transferring the learned features (the network's weights) to a second network to be trained on a target dataset. This idea has been shown to improve deep neural network's generalization capabilities in many computer vision tasks su

Hyeonbae Kang, KiHyun Yun

A field excited by an emitter can be enhanced due to presence of closely located inclusions. In this paper we consider such field enhancement when inclusions are disks of the same radii, and the emitter is of dipole type and located in the narrow region between two inclusions. We derive quantitatively precise estimates of the field enhancement in the narrow

A. S. Sefiedgar, M. Mirzazadeh

In an accelerated expanding universe, one can expect the existence of an event horizon. It may be interesting to study the thermodynamics of the Friedmann-Robertson-Walker (FRW) universe at the event horizon. Considering the usual Hawking temperature, the first law of thermodynamics does not hold on the event horizon. To satisfy the first law of thermodynami

R. Sasaki, Y. Nii, Y. Onose

We observed surface acoustic wave (SAW) propagation on a multiferroic material CuB$_2$O$_4$ with use of two interdigital transducers (IDTs). The period of IDT fingers is as short as 1.6 $μ$m so that the frequency of SAW is 3 GHz, which is comparable with that of magnetic resonance. In antiferromagnetic phase, the SAW excitation intensity varied with the magn

Maryam Sultana, Arif Mahmood, Sajid Javed, Soon Ki Jung

Video object segmentation is a fundamental step in many advanced vision applications. Most existing algorithms are based on handcrafted features such as HOG, super-pixel segmentation or texture-based techniques, while recently deep features have been found to be more efficient. Existing algorithms observe performance degradation in the presence of challenges

R. B. Salako, W. Shen

The current work is the third of a series of three papers devoted to the study of asymptotic dynamics in the space-time dependent logistic source chemotaxis system, $$ \begin{cases} \partial_tu=Δu-χ\nabla\cdot(u\nabla v)+u(a(x,t)-b(x,t)u),\quad x\in R^N,\cr 0=Δv-λv+μu ,\quad x\in R^N, \end{cases} (0.1) $$ where $N\ge 1$ is a positive integer, $χ, λ$ and $μ$

Goo Ishikawa

In this paper we introduce the notion of cofrontal mappings, as the dual objects to frontal mappings, and study their basic local and global properties. Cofrontals are very special mappings and far from generic nor stable except for the case of submersions. It is observed that any smooth mapping can be $C^0$-approximated by a possibly \lq\lq unfair" cofr

Jiajun Zhang, Rui An, Shihong Liao, Wentao Luo

We devise a fully self-consistent simulation pipeline for the first time to study the interaction between dark matter and dark energy. We perform convergence tests and show that our code is accurate on different scales. Using the parameters constrained by Planck, Type Ia Supernovae, Baryon Acoustic Oscillations (BAO) and Hubble constant observations, we perf

Matthew Colless

I review the insights emerging from recent large kinematic surveys of galaxies at low redshift, with particular reference to the SAMI, CALIFA and MaNGA surveys. These new observations provide a more comprehensive picture of the angular momentum properties of galaxies over wide ranges in mass, morphology and environment in the present-day universe. I focus on

Jeff Greensite, Kazue Matsuyama

The property of color confinement ("C confinement"), meaning that all asymptotic particle states are color neutral, holds not only in QCD, but also in gauge-Higgs theories deep in the Higgs regime. In this talk we describe a new and stronger confinement criterion, separation-of-charge confinement or "S$_c$ confinement," which is an extension

Laura K McKemmish, Jasmin Borsovszky, Katie L Goodhew, Samuel Sheppard

Zirconium oxide(ZrO) is an important astrophysical molecule that defines the S-star classification class for cool giant stars. Accurate, empirical rovibronic energy levels, with associated labels and uncertainties, are reported for 9 low-lying electronic states of the diatomic 90Zr16O molecule. These 8088 empirical energy levels are determined using the Marv

B. Zuckerman

The reality of a field Argus Association has been doubted in some papers in the literature. We apply Gaia DR2 data to stars previously suggested to be Argus members and conclude that a true association exists with age 40-50 Myr and containing many stars within 100 pc of Earth; Beta Leo and 49 Cet are two especially interesting members. Based on youth and pro

H. Baumgardt, M. Hilker, A. Sollima, A. Bellini

We have derived the mean proper motions and space velocities of 154 Galactic globular clusters and the velocity dispersion profiles of 141 globular clusters based on a combination of Gaia DR2 proper motions with ground-based line-of-sight velocities. Combining the velocity dispersion profiles derived here with new measurements of the internal mass functions

Hao Jia, Xiaotong Ding

In this paper, we study the dynamical properties of two coupled quantum harmonic oscillators coupled with bosonic non-Markovian environment both in position and momentum. We deduce the exact analytical master equation using Quantum State Diffusion method and give the quantum trajectory description when the control is added to the system by applying interacti

Jia Li, Cong Fang, Zhouchen Lin

We propose a new optimization method for training feed-forward neural networks. By rewriting the activation function as an equivalent proximal operator, we approximate a feed-forward neural network by adding the proximal operators to the objective function as penalties, hence we call the lifted proximal operator machine (LPOM). LPOM is block multi-convex in

Hanqing Guo, Nan Zhang, Saeed AlQarni, Shaoen Wu

In-band full duplex wireless is of utmost interest to future wireless communication and networking due to great potentials of spectrum efficiency. IBFD wireless, however, is throttled by its key challenge, namely self-interference. Therefore, effective self-interference cancellation is the key to enable IBFD wireless. This paper proposes a real-time non-line

Maria Luísa Morgado, Luís Filipe Morgado

In this work we use tempered fractional advection-diffusion equations to model the dispersive transport in disordered materials. A numerical method is derived to approximate the solution of such differential models and we prove that it is convergent and stable. Two numerical examples are presented. The first one, with known analytical solution, is given to i

Frank G. Schröder

Antenna arrays are beginning to make important contributions to high energy astroparticle physics supported by recent progress in the radio technique for air showers. This article provides an update to my more extensive review published in Prog. Part. Nucl. Phys. 93 (2017) 1 [arXiv: 1607.08781]. It focuses on current and planned radio arrays for atmospheric

Wenwei Xu, Shari Matzner

Clean energy from oceans and rivers is becoming a reality with the development of new technologies like tidal and instream turbines that generate electricity from naturally flowing water. These new technologies are being monitored for effects on fish and other wildlife using underwater video. Methods for automated analysis of underwater video are needed to l

P. Fanto, G. F. Bertsch, Y. Alhassid

A basic prediction of the statistical model of compound nucleus reactions is that the partial widths for decay into any open channel channel fluctuate according to the Porter-Thomas distribution (PTD). A recent experiment on $s$- and $p$-wave neutron scattering from platinum isotopes found that the experimental $s$-wave partial neutron width distributions de

Aditya Potukuchi

We study hypergraph discrepancy in two closely related random models of hypergraphs on $n$ vertices and $m$ hyperedges. The first model, $\mathcal{H}_1$, is when every vertex is present in exactly $t$ randomly chosen hyperedges. The premise of this is closely tied to, and motivated by the Beck-Fiala conjecture. The second, perhaps more natural model, $\mathc

Sviatoslav Covanov, Davood Mohajerani, Marc Moreno-Maza, Lin-Xiao Wang

Fast algorithms for integer and polynomial multiplication play an important role in scientific computing as well as in other disciplines. In 1971, Sch{ö}nhage and Strassen designed an algorithm that improved the multiplication time for two integers of at most $n$ bits to $\mathcal{O}(\log n \log \log n)$. In 2007, Martin Fürer presented a new algorithm that

Ki-Hoon Hong, Ulugbek Yakhshiev, Hyun-Chul Kim

Changes of baryon properties in nuclear matter are investigated within the framework of an in-medium modified SU(3) Skyrme model. Introducing the medium functionals in the SU(2) sector and considering the alteration of kaon properties in nuclear medium, we are able to examine the medium modification of the nucleon and hyperons. The functionals introduced in

H. J. Xia, X. Y. Wu, H. Mei, J. M. Yao

We develop both relativistic mean field and beyond approaches for hypernuclei with possible quadrupole-octupole deformation or pear-like shapes based on relativistic point-coupling energy density functionals. The symmetries broken in the mean-field states are recovered with parity, particle-number, and angular momentum projections. We take $^{21}_Λ$Ne as an

Jia-Jia He, Sheng-Bang Qian, B. Soonthornthum, A. Aungwerojwit

Four-color charge-coupled device (CCD) light curves in $B$, $V$, $Rc$ and $Ic$ bands of the total-eclipsing binary system, V1853 Ori, are presented. By comparing our light curves with those published by previous investigators, it is detected that the O'Connell effect on the light curves is disappeared. By analyzing those multi-color light curves with the

Jixue Liu, Jiuyong Li, Lin Liu, Thuc Duy Le

Predictive models such as decision trees and neural networks may produce discrimination in their predictions. This paper proposes a method to post-process the predictions of a predictive model to make the processed predictions non-discriminatory. The method considers multiple protected variables together. Multiple protected variables make the problem more ch

L. P. Kaptari, B. Kaempfer, P. Zhang

We suggest a framework based on the rainbow approximation with effective parameters adjusted to lattice data. The analytic structure of the gluon and ghost propagators of QCD in Landau gauge is analyzed by means of numerical solutions of the coupled system of truncated Dyson-Schwinger equations. We find that the gluon and ghost dressing functions are singula

Kohei Yamamoto

We consider Bernoulli bond percolation on the product graph of a regular tree and a line. We show that the triangle condition does not hold at the uniqueness threshold.

Helmut Haberzettl, Kanzo Nakayama, Yongseok Oh

A theory of two-pion photo- and electroproduction off the nucleon is derived considering all explicit three-body mechanisms of the interacting $ππN$ system. The full three-body dynamics of the interacting $ππN$ system is accounted for by the Faddeev-type ordering structure of the Alt-Grassberger-Sandhas equations. The formulation is valid for hadronic two-po

Kensuke Sakai, Tatsuya Ohno, Keisuke Goto, Yoshimasa Takabatake

Given a string $T$ of length $N$, the goal of grammar compression is to construct a small context-free grammar generating only $T$. Among existing grammar compression methods, RePair (recursive paring) [Larsson and Moffat, 1999] is notable for achieving good compression ratios in practice. Although the original paper already achieved a time-optimal algorithm

Takami Tohyama, Riku Ogura, Kensuke Yoshinaga, Shin Naito

We synthesize a new titanium-oxide compound AlTi2O5 with pseudobrookite-type structure. The formal valence of Ti is 3.5+ that is the same as the Magneli compound Ti4O7 and the spinel compound LiTi2O4. AlTi2O5 exhibits insulating behavior in resistivity. Using experimentally determined crystal structure, we perform the first-principles calculations for the el

Xudong Zhang

Functional data analysis has been a growing field of study in recent decades, and one fundamental task in functional data analysis is estimating the sample location. A notion called statistical depth has been extended from multivariate data to functional data, and it can provide a center-outward order for each observation within a sample of functional curves

Najmeh Sadoughi, Greg P. Finley, James Fone, Vignesh Murali

A ubiquitous task in processing electronic medical data is the assignment of standardized codes representing diagnoses and/or procedures to free-text documents such as medical reports. This is a difficult natural language processing task that requires parsing long, heterogeneous documents and selecting a set of appropriate codes from tens of thousands of pos

Michelle Edwards, Lewis Mitchell, Jonathan Tuke, Matthew Roughan

Analysing narratives through their social networks is an expanding field in quantitative literary studies. Manually extracting a social network from any narrative can be time consuming, so automatic extraction methods of varying complexity have been developed. However, the effect of different extraction methods on the analysis is unknown. Here we model and c

Vu Nguyen, Sunil Gupta, Santu Rana, Cheng Li

Bayesian optimization (BO) and its batch extensions are successful for optimizing expensive black-box functions. However, these traditional BO approaches are not yet ideal for optimizing less expensive functions when the computational cost of BO can dominate the cost of evaluating the blackbox function. Examples of these less expensive functions are cheap ma

Faiq Khalid, Muhammad Abdullah Hanif, Semeen Rehman, Muhammad Shafique

The exponential increase in dependencies between the cyber and physical world leads to an enormous amount of data which must be efficiently processed and stored. Therefore, computing paradigms are evolving towards machine learning (ML)-based systems because of their ability to efficiently and accurately process the enormous amount of data. Although ML-based

Rustin Domingos, Kareemullah M. Shaik, Burkhard Militzer

Crystal structure prediction with theoretical methods is particularly challenging when unit cells with many atoms need to be considered. Here we employ a symmetry-driven structure search (SYDSS) method and combine it with density functional theory (DFT) to predict novel crystal structures at high pressure. We sample randomly from all 1,506 Wyckoff positions

Giuseppe Izzo, Zdzislaw Jackiewicz

For many systems of differential equations modeling problems in science and engineering, there are often natural splittings of the right hand side into two parts, one of which is non-stiff or mildly stiff, and the other part is stiff. Such systems can be efficiently treated by a class of implicit-explicit (IMEX) diagonally implicit multistage integration met

Simon Maretzke

Coherent wave-propagation in the near-field Fresnel-regime is the underlying contrast-mechanism to (propagation-based) X-ray phase contrast imaging (XPCI), an emerging lensless technique that enables 2D- and 3D-imaging of biological soft tissues and other light-element samples down to nanometer-resolutions. Mathematically, propagation is described by the Fre

Simon Baumstark, Katharina Schratz

We present a novel class of oscillatory integrators for the Klein-Gordon-Zakharov system which are uniformly accurate with respect to the plasma frequency $c$. Convergence holds from the slowly-varying low-plasma up to the highly oscillatory high-plasma frequency regimes without any step size restriction and, especially, uniformly in $c$. The introduced sche

J. Thomas Beale, Wenjun Ying

Several important problems in partial differential equations can be formulated as integral equations. Often the integral operator defines the solution of an elliptic problem with specified jump conditions at an interface. In principle the integral equation can be solved by replacing the integral operator with a finite difference calculation on a regular grid

Naren Srivaths Raman, Prabir Barooah

Flexible loads, especially heating, ventilation, and air-conditioning (HVAC) systems can be used to provide a battery-like service to the power grid by varying their demand up and down over a baseline. Recent work has reported that providing virtual energy storage with HVAC systems lead to a net loss of energy, akin to a low round-trip efficiency (RTE) of a

Dirk Pauly

We prove that for bounded and convex domains in arbitrary dimensions, the Maxwell constants are bounded from below and above by Friedrichs' and Poincare's constants, respectively. Especially, the second positive Maxwell eigenvalues in ND are bounded from below by the square root of the second Neumann-Laplace eigenvalue.

Xinshao Wang, Yang Hua, Elyor Kodirov, Guosheng Hu

Deep metric learning aims to learn a deep embedding that can capture the semantic similarity of data points. Given the availability of massive training samples, deep metric learning is known to suffer from slow convergence due to a large fraction of trivial samples. Therefore, most existing methods generally resort to sample mining strategies for selecting n

Jakob N. Foerster, Francis Song, Edward Hughes, Neil Burch

When observing the actions of others, humans make inferences about why they acted as they did, and what this implies about the world; humans also use the fact that their actions will be interpreted in this manner, allowing them to act informatively and thereby communicate efficiently with others. Although learning algorithms have recently achieved superhuman

Gennaro Notomista, Magnus Egerstedt

In this paper we present a reformulation--framed as a constrained optimization problem--of multi-robot tasks which are encoded through a cost function that is to be minimized. The advantages of this approach are multiple. The constraint-based formulation provides a natural way of enabling long-term robot autonomy applications, where resilience and adaptabili

A. Rouco Escorial, J. van den Eijnden, R. Wijnands

We present our Swift monitoring campaign of the slowly rotating neutron star Be/X-ray transient GX 304-1 (spin period of ~275 s) when the source was not in outburst. We found that between its type-I outbursts the source recurrently exhibits a slowly decaying low-luminosity state (with luminosities of 10^(34-35) erg/s). This behaviour is very similar to what

Rui Sakano, Akira Oguri, Yunori Nishikawa, Eisuke Abe

We study spin-entanglement of the quasiparticles of the local Fermi liquid excited in nonlinear current through a quantum dot described by the Anderson impurity model with two degenerate orbitals coupled to each other via an exchange interaction. Applying the renormalized perturbation theory, we obtain the precise form of the cumulant generating function and

M. O. Brown, T. Thiele, C. Kiehl, T. -W. Hsu

We show that with a purely blue-detuned cooling mechanism we can densely load single neutral atoms into large arrays of shallow optical tweezers. With this ability, more efficient assembly of larger ordered arrays will be possible - hence expanding the number of particles available for bottom-up quantum simulation and computation with atoms. Using Lambda-enh

Faiq Khalid, Syed Rafay Hasan, Osman Hasan, Muhammad Shafique

Timely detection of Hardware Trojans (HTs) has become a major challenge for secure integrated circuits. We present a run-time methodology for HT detection that employs a multi-parameter statistical traffic modeling of the communication channel in a given System-on-Chip (SoC), named as SIMCom. The main idea is to model the communication using multiple side-ch

Yue Chang, Yu-Hao Guo, Jie Qin

Alkali-metal-vapor magnetometers, using coherent precession of polarized atomic spins for magnetic field measurement, have become one of the most sensitive magnetic field detectors. Their application areas range from practical uses such as detections of NMR signals to fundamental physics research such as searches for permanent electric dipole moments. One of

Hassan Ali, Faiq Khalid, Hammad Tariq, Muhammad Abdullah Hanif

In this paper, we introduce a novel technique based on the Secure Selective Convolutional (SSC) techniques in the training loop that increases the robustness of a given DNN by allowing it to learn the data distribution based on the important edges in the input image. We validate our technique on Convolutional DNNs against the state-of-the-art attacks from th

Zhao Song, David P. Woodruff, Peilin Zhong

There are a number of approximation algorithms for NP-hard versions of low rank approximation, such as finding a rank-$k$ matrix $B$ minimizing the sum of absolute values of differences to a given $n$-by-$n$ matrix $A$, $\min_{\textrm{rank-}k~B}\|A-B\|_1$, or more generally finding a rank-$k$ matrix $B$ which minimizes the sum of $p$-th powers of absolute va

Peter K. F. Kuhfittig

This paper generalizes an earlier result by the author based on well-established embedding theorems that connect the classical theory of relativity to higher-dimensional spacetimes. In particular, an $n$-dimensional Riemannian space is said to be of embedding class $m$ if $m+n$ is the lowest dimension of the flat space in which the given space can be embedde

Faiq Khalid, Hassan Ali, Hammad Tariq, Muhammad Abdullah Hanif

Adversarial examples have emerged as a significant threat to machine learning algorithms, especially to the convolutional neural networks (CNNs). In this paper, we propose two quantization-based defense mechanisms, Constant Quantization (CQ) and Trainable Quantization (TQ), to increase the robustness of CNNs against adversarial examples. CQ quantizes input p

Paolo Aceto, Daniele Celoria, JungHwan Park

We consider the question of when a rational homology 3-sphere is rational homology cobordant to a connected sum of lens spaces. We prove that every rational homology cobordism class in the subgroup generated by lens spaces is represented by a unique connected sum of lens spaces whose first homology embeds in any other element in the same class. As a first co

Jean-Christophe Mourrat

We argue that Hamilton-Jacobi equations provide a convenient and intuitive approach for studying the large-scale behavior of mean-field disordered systems. This point of view is illustrated on the problem of inference of a rank-one matrix. We compute the large-scale limit of the free energy by showing that it satisfies an approximate Hamilton-Jacobi equation

Shifa Zhang, Anne Kim, Dianbo Liu, Sandeep C. Nuckchady

Artificial Intelligence (AI) incorporating genetic and medical information have been applied in disease risk prediction, unveiling disease mechanism, and advancing therapeutics. However, AI training relies on highly sensitive and private data which significantly limit their applications and robustness evaluation. Moreover, the data access management after sh

Jingwei Liang, Tao Luo, Carola-Bibiane Schönlieb

The "fast iterative shrinkage-thresholding algorithm", a.k.a. FISTA, is one of the most well-known first-order optimisation scheme in the literature, as it achieves the worst-case $O(1/k^2)$ optimal convergence rate in terms of objective function value. However, despite such an optimal theoretical convergence rate, in practice the (local) oscillatory

Cody Carroll, Hans-Georg Müller, Alois Kneip

Multivariate functional data are becoming ubiquitous with advances in modern technology and are substantially more complex than univariate functional data. We propose and study a novel model for multivariate functional data where the component processes are subject to mutual time warping. That is, the component processes exhibit a similar shape but are subje

Peng Sun, Bin Yan, C. -P. Yuan

We study the soft gluon radiation effects for the $s$-channel single top quark production at the LHC. By applying the transverse momentum dependent factorization formalism, the large logarithms about the small total transverse momentum ($q_\perp$) of the single-top plus one-jet final state system, are resummed to all orders in the expansion of the strong int

Hadley Black, Deeparnab Chakrabarty, C. Seshadhri

We describe a $\tilde{O}(d^{5/6})$-query monotonicity tester for Boolean functions $f:[n]^d \to \{0,1\}$ on the $n$-hypergrid. This is the first $o(d)$ monotonicity tester with query complexity independent of $n$. Motivated by this independence of $n$, we initiate the study of monotonicity testing of measurable Boolean functions $f:\mathbb{R}^d \to \{0,1\}$

Luke Broemeling, Rasul Shafikov

Rationally convex topological embeddings of compact surfaces (closed or with boundary) into $\mathbb{C}^2$ are constructed.

A. V. Nazarov, A. A. Mikheev, A. P. Melnikov

We use a new variant of Molecular Static method for simulation of the atomic structure near nanovoids. In our model an iterative procedure is employed, in which the atomic structure in the void vicinity and the parameter determining the displacement of atoms embedded into an elastic continuum are obtained in a self-consistent manner. Results show that the at

Dan Alistarh, James Aspnes, Faith Ellen, Rati Gelashvili

We introduce extension-based proofs, a class of impossibility proofs that includes valency arguments. They are modelled as an interaction between a prover and a protocol. Using proofs based on combinatorial topology, it has been shown that it is impossible to deterministically solve k-set agreement among n > k > 1 processes in a wait-free manner in certain a

Erhan Bayraktar, Yan Dolinsky, Jia Guo

In this paper we find tight sufficient conditions for the continuity of the value of the utility maximization problem from terminal wealth with respect to the convergence in distribution of the underlying processes. We also establish a weak convergence result for the terminal wealths of the optimal portfolios. Finally, we apply our results to the computation

Xiaohao Cai, Marcelo Pereyra, Jason D. McEwen

Inverse problems play a key role in modern image/signal processing methods. However, since they are generally ill-conditioned or ill-posed due to lack of observations, their solutions may have significant intrinsic uncertainty. Analysing and quantifying this uncertainty is very challenging, particularly in high-dimensional problems and problems with non-smoo

I. A. Aleksandrov, G. Plunien, V. M. Shabaev

In the present investigation we revisit the widely-used locally-constant field approximation (LCFA) in the context of the pair-production phenomenon in strong electromagnetic backgrounds. By means of nonperturbative numerical calculations, we assess the validity of the LCFA considering several spatially homogeneous field configurations and a number of space-

Xu Liu, Steven W. Chen, Chenhao Liu, Shreyas S. Shivakumar

We present a cheap, lightweight, and fast fruit counting pipeline that uses a single monocular camera. Our pipeline that relies only on a monocular camera, achieves counting performance comparable to state-of-the-art fruit counting system that utilizes an expensive sensor suite including LiDAR and GPS/INS on a mango dataset. Our monocular camera pipeline beg

Nestor Leon Delgado

This document is a reorganization of the results on the Master Thesis of the same title written by the author under the supervision of Dr. Christian Blohmann at the University of Bonn in 2014. There are three main results in this document. The first one is a construction of a high L-infinity algebra out of any Gerstenhaber algebra. The second one uses a coch

Martin Becker, Samarjit Chakraborty

Measuring and analyzing the performance of software has reached a high complexity, caused by more advanced processor designs and the intricate interaction between user programs, the operating system, and the processor's microarchitecture. In this report, we summarize our experience about how performance characteristics of software should be measured when

Subhra Mazumdar, Sushmita Ruj

Permissioned Blockchain has become quite popular with enterprises forming consortium since it prioritizes trust over privacy. One of the popular platforms for distributed ledger solution, Hyperledger Fabric, requires a transaction to be endorsed or approved by a group of special members known as endorsers before undergoing validation. To endorse a transactio

Shmuel Gurvitz

Using a new developed Single-Electron approach, we derive the Landauer-type formula for electron transport in arbitrary time-dependent potentials. This formula is applied for randomly fluctuating potentials represented by a dichotomic noise. We found that the noise can produce dc-current in quantum system under zero-bias voltage by breaking the time-reversal

Yaroslav Balytskyi

Rare decays of light mesons may be a discovery window for a new weakly coupled forces hidden at low energy QCD scale. BES-III Collaboration reported the observation of the rare decay $η'\rightarrowπ^0γγ$. The observed decay width disagrees with the preliminary theoretical estimations. We show that this tension may be attributed to the New Physics, presum

Ayan Kumar Bhunia, Perla Sai Raj Kishore, Pranay Mukherjee, Abhirup Das

With the large-scale explosion of images and videos over the internet, efficient hashing methods have been developed to facilitate memory and time efficient retrieval of similar images. However, none of the existing works uses hashing to address texture image retrieval mostly because of the lack of sufficiently large texture image databases. Our work address

Aslı Pekcan

We first study coupled Hirota-Iwao modified KdV (HI-mKdV) systems and give all possible local and nonlocal reductions of these systems. We then present Hirota bilinear forms of these systems and give one-soliton solutions of them with the help of pfaffians. By using the soliton solutions of the coupled HI-mKdV systems for $N=2,3,$ and $N=4$ we find one-solit

Peifeng Wang, Jialong Han, Chenliang Li, Rong Pan

Knowledge graph embedding aims at modeling entities and relations with low-dimensional vectors. Most previous methods require that all entities should be seen during training, which is unpractical for real-world knowledge graphs with new entities emerging on a daily basis. Recent efforts on this issue suggest training a neighborhood aggregator in conjunction

Lei Chen, Dai-Wei Qu, Han Li, Bin-Bin Chen

The anomalous thermodynamic properties of the paradigmatic frustrated spin-1/2 triangular lattice Heisenberg antiferromagnet (TLH) has remained an open topic of research over decades, both experimentally and theoretically. Here we further the theoretical understanding based on the recently developed, powerful exponential tensor renormalization group (XTRG) m

Ayan Kumar Bhunia, Abhirup Das, Ankan Kumar Bhunia, Perla Sai Raj Kishore

Handwritten Word Recognition and Spotting is a challenging field dealing with handwritten text possessing irregular and complex shapes. The design of deep neural network models makes it necessary to extend training datasets in order to introduce variations and increase the number of samples; word-retrieval is therefore very difficult in low-resource scripts.

Ayan Kumar Bhunia, Ankan Kumar Bhunia, Shuvozit Ghose, Abhirup Das

Logo detection in real-world scene images is an important problem with applications in advertisement and marketing. Existing general-purpose object detection methods require large training data with annotations for every logo class. These methods do not satisfy the incremental demand of logo classes necessary for practical deployment since it is practically

Koichi Tojo, Taro Yoshino

In this paper, we give a method to construct "good" exponential families systematically by representation theory. More precisely, we consider a homogeneous space $G/H$ as a sample space and construct an exponential family invariant under the transformation group $G$ by using a representation of $G$. The method generates widely used exponential families such

Roman Plyatsko, Volodymyr Panat, Mykola Fenyk

In this paper analytical solutions of the Mathisson-Papapetrou equations that describe nonequatorial circular orbits of a spinning particle in the Schwarzschild-de Sitter background are studied, and the role of the cosmological constant is emphasized. It is shown that generally speaking a highly relativistic velocity of the particle is a necessary condition

Daniel Omeiza, Jemima Owusu-Tweneboah

Web security has become an important subject; many companies and organizations are becoming more security conscious as they build web applications to render online services and increase web presence. Unfortunately, many of these web applications are still susceptible to threats as they lack strong immunity to malicious attacks. This poses potential danger to

B. Opanchuk, L. Rosales-Zárate, R. Y. Teh, B. J. Dalton

Using criteria based on superselection rules, we analyze the quantum correlations between the two condensate modes of the Bose-Einstein condensate interferometer of Egorov et al. [Phys. Rev. A 84, 021605 (2011)]. In order to determine the two-mode correlations, we develop a multi-mode theory that describes the dynamics of the condensate atoms and the thermal

Shaohan Wu, Brian L. Hughes

This paper considers a hybrid approach to joint estimation of channel information and antenna impedance, for single-input, single-output channels. Based on observation of training sequences via synchronously switched load at the receiver, we derive joint maximum a posteriori and maximum-likelihood (MAP/ML) estimators for channel and impedance over multiple p

Xilong Fan, Jin Li, Xin Li, Yuanhong Zhong

In this paper, we study an application of deep learning to the advanced LIGO and advanced Virgo coincident detection of gravitational waves (GWs) from compact binary star mergers. This deep learning method is an extension of the Deep Filtering method used by George and Huerta (2017) for multi-inputs of network detectors. Simulated coincident time series data

Xi Deng, Yuya Shimizu, Feng Xiao

A novel 5th-order shock capturing scheme is presented in this paper. The scheme, so-called P4-THINC-BVD (4th degree polynomial and THINC reconstruction based on BVD algorithm), is formulated as a two-stage cascade BVD (Boundary Variation Diminishing) algorithm following the BVD principle that minimizes the jumps of reconstructed values at cell boundaries. In

Matias Martinez, Thomas Durieux, Romain Sommerard, Jifeng Xuan

Defects4J is a large, peer-reviewed, structured dataset of real-world Java bugs. Each bug in Defects4J comes with a test suite and at least one failing test case that triggers the bug. In this paper, we report on an experiment to explore the effectiveness of automatic test-suite based repair on Defects4J. The result of our experiment shows that the considere

Ruby Byrne, Miguel F. Morales, Bryna Hazelton, Wenyang Li

Precise instrument calibration is critical to the success of 21 cm Cosmology experiments. Unmitigated errors in calibration contaminate the Epoch of Reionization (EoR) signal, precluding a detection. Barry et al. 2016 characterizes one class of inherent errors that emerge from calibrating to an incomplete sky model, however it has been unclear if errors in t

Yongbin Ruan, Ming Zhang

Motivated by Witten's work (arXiv:hep-th/9312104), we propose the Verlinde/Grassmannian correspondence which relates the GL Verlinde numbers to the K-theoretic quasimap invariants of the Grassmannian. We recover these two types of invariants by imposing different stability conditions on the gauged linear sigma model associated to the Grassmannian. We con

Kohki Mametani, Tsuneo Kato, Seiichi Yamamoto

Recent studies have introduced end-to-end TTS, which integrates the production of context and acoustic features in statistical parametric speech synthesis. As a result, a single neural network replaced laborious feature engineering with automated feature learning. However, little is known about what types of context information end-to-end TTS extracts from t

A. Chakravarty, J. H. Mentink, C. S. Davies, K. T. Yamada

The explosive growth of data and its related energy consumption is pushing the need to develop energy-efficient brain-inspired schemes and materials for data processing and storage. Here, we demonstrate experimentally that Co/Pt films can be used as artificial synapses by manipulating their magnetization state using circularly-polarized ultrashort optical pu