April 2019 arXiv papers — page 118

Arnaud Mignan, Marco Broccardo

29 August 2018: "Artificial intelligence nails predictions of earthquake aftershocks". This Nature News headline is based on the results of DeVries et al. (2018) who forecasted the spatial distribution of aftershocks using Deep Learning (DL) and static stress feature engineering. Using receiver operating characteristic (ROC) curves and the area under

WenBin He, Xi-Wen Guan

Motivated by recent experimental study on coherent dynamics transfer in three interacting atoms or electron spins \cite{Barredo:2015,Rosenfeld:2018}, here we study entanglement entropy transfer in three interacting qubits. We analytically calculate time evolutions of wave function, density matrix and entanglement of the system. We find that initially entangl

Eun Kyung Park, Pyung Seong Kwon

We find a background solution of the string theory which has a special property distinguished from the usual background solutions. This background solution does not produce the NS-NS two-form fields under T-duality and therefore the background vacua described by this solution essentially do not involve NS-NS type branes in their configurations, unlikely to t

Matteo Giordano, Attila Pásztor

We study different estimators of the radius of convergence of the Taylor series of the pressure in finite density QCD. We adopt the approach in which the radius of convergence is estimated first in a finite volume, and the infinite-volume limit is taken later. This requires an estimator for the radius of convergence that is reliable in a finite volume. Based

Matthew J. Hooton, Ernst J. W. de Mooij, Christopher A. Watson, Neale P. Gibson

WASP-12b is one of the most well-studied transiting exoplanets, as its highly-inflated radius and its 1.1 day orbit around a G0-type star make it an excellent target for atmospheric categorisation through observation during its secondary eclipse. We present two new secondary eclipse observations of WASP-12b, acquired a year apart with the Wide Field Camera o

Nataliya Le Vine, Matthew Zeigenfuse, Mark Rowan

Extracting information from tables in documents presents a significant challenge in many industries and in academic research. Existing methods which take a bottom-up approach of integrating lines into cells and rows or columns neglect the available prior information relating to table structure. Our proposed method takes a top-down approach, first using a gen

S. B. Porter, M. Venkatesan, P. Dunne, B. Doudin

The magnetic dead layers in films a few nanometers thick are investigated for La$_{0.7}$Sr$_{0.3}$MnO$_3$ on (001)-oriented SrTiO$_3$ (STO), LaAlO$_3$ (LAO) and (LaAlO$_3$)$_{0.3}$(Sr$_2$TaAlO$_6$)$_{0.7}$ (LSAT) substrates. An anomalous moment found to persist above the Curie temperature of the La$_{0.7}$Sr$_{0.3}$MnO$_3$ films is not attributed to the film

Adrien Gola, Guang-Ping Zhang, Lars Pastewka, Ruth Schwaiger

We carried out matched experiments and molecular dynamics simulations of the compression of nanopillars prepared from Cu$\vert$Au nanolaminates with 25 nm layer thickness. The stress-strain behavior obtained from both techniques are in excellent agreement. Variation of the layer thickness in simulations reveals an increase of the strength with decreasing lay

Youngmin Baek, Bado Lee, Dongyoon Han, Sangdoo Yun

Scene text detection methods based on neural networks have emerged recently and have shown promising results. Previous methods trained with rigid word-level bounding boxes exhibit limitations in representing the text region in an arbitrary shape. In this paper, we propose a new scene text detection method to effectively detect text area by exploring each cha

Hiroyuki Tajima, Pascal Naidon

We investigate color superfluidity and trimer formation in resonantly interacting SU(3) Fermi gases with a finite interaction range. The finite range is crucial to avoid the Thomas collapse and treat the Efimov effect occurring in this system. Using the Skorniakov-Ter-Martirosian (STM) equation with medium effects, we show the effects of the atomic Fermi dis

Shuohang Wang, Sheng Zhang, Yelong Shen, Xiaodong Liu

Commonsense reasoning is fundamental to natural language understanding. While traditional methods rely heavily on human-crafted features and knowledge bases, we explore learning commonsense knowledge from a large amount of raw text via unsupervised learning. We propose two neural network models based on the Deep Structured Semantic Models (DSSM) framework to

Chao Ning, Fengqi You

This paper reviews recent advances in the field of optimization under uncertainty via a modern data lens, highlights key research challenges and promise of data-driven optimization that organically integrates machine learning and mathematical programming for decision-making under uncertainty, and identifies potential research opportunities. A brief review of

Jinze Bai, Chang Zhou, Junshuai Song, Xiaoru Qu

Product bundling, offering a combination of items to customers, is one of the marketing strategies commonly used in online e-commerce and offline retailers. A high-quality bundle generalizes frequent items of interest, and diversity across bundles boosts the user-experience and eventually increases transaction volume. In this paper, we formalize the personal

Sergey A. Koldobskiy, Veronica Bindi, Claudio Corti, Gennady A. Kovaltsov

The newly published spectra of protons and helium over time directly measured in space by the AMS-02 experiment for the period 2011--2017 provide a unique opportunity to calibrate ground-based neutron monitors (NMs). Here, calibration of several stable sealevel NMs (Inuvik, Apatity, Oulu, Newark, Moscow, Hermanus, Athens) was performed using these spectra. F

J. Hrtánková, N. Barnea, E. Friedman, A. Gal

A hypothesis of absolutely stable strange hadronic matter composed of $Λ(1405)$ baryons, here denoted $Λ^*$, is tested within many-body calculations performed using the Relativistic Mean-Field approach. In our calculations, we employed the $Λ^*Λ^*$ interaction compatible with the $Λ^*Λ^*$ binding energy $B_{Λ^*Λ^*}=40$~MeV given by the phenomenological energ

Meijuan Cheng, Shunqing Wu, Zi-Zhong Zhu, Guang-Yu Guo

Trigonal selenium and tellurium crystalize in helical chain-like structures and thus possess interesting properties such as current-induced spin polarization, gyrotropic effects and nonlinear optical responses. By performing systematic ab initio calculations based on density functional theory in the generalized gradient approximation plus scissors correction

Javier Falcó, Karl-G. Grosse-Erdmann

We show that the multiples of the backward shift operator on the spaces $\ell_{p}$, $1\leq p<\infty$, or $c_{0}$, when endowed with coordinatewise multiplication, do not possess frequently hypercyclic algebras. More generally, we characterize the existence of algebras of $\mathcal{A}$-hypercyclic vectors for these operators. We also show that the differentia

Bernhard Gäde, Ali Bereyhi, Saba Asaad, Ralf R. Müller

Both antenna selection and spatial modulation allow for low-complexity MIMO transmitters when the number of RF chains is much lower than the number of transmit antennas. In this manuscript, we present a quantitative performance comparison between these two approaches by taking into account implementational restrictions, such as antenna switching. We consider

Edurne Sagasta, Yasutomo Omori, Miren Isasa, YoshiChika Otani

We employ the spin absorption technique in lateral spin valves to extract the spin diffusion length of Permalloy (Py) as a function of temperature and resistivity. A linear dependence of the spin diffusion length with conductivity of Py is observed, evidencing that Elliott-Yafet is the dominant spin relaxation mechanism in Permalloy. Completing the data set

Ahti Kalervo, Juha Ylioinas, Markus Häikiö, Antti Karhu

Better understanding and modelling of building interiors and the emergence of more impressive AR/VR technology has brought up the need for automatic parsing of floorplan images. However, there is a clear lack of representative datasets to investigate the problem further. To address this shortcoming, this paper presents a novel image dataset called CubiCasa5K

Paolo Vecchiotti, Ning Ma, Stefano Squartini, Guy J. Brown

A novel end-to-end binaural sound localisation approach is proposed which estimates the azimuth of a sound source directly from the waveform. Instead of employing hand-crafted features commonly employed for binaural sound localisation, such as the interaural time and level difference, our end-to-end system approach uses a convolutional neural network (CNN) t

Edurne Sagasta, Juan Borge, Luis Esteban, Yasutomo Omori

Oxide interfaces are a source of spin-orbit coupling which can lead to novel spin-to-charge conversion effects. In this work the contribution of the Bi$_2$O$_3$ interface to the anomalous Hall effect of Co is experimentally studied in Co/Bi$_2$O$_3$ bilayers. We evidence a variation of 40% in the AHE of Co when a Bi$_2$O$_3$ capping layer is added to the fer

Sergey Nechayev, Peter Banzer

We demonstrate that electric-dipole scatterers can mimic chiral light-matter interaction by generating far-field circular polarization upon scattering, even though the optical chirality of the incident field as well as that of the scattered light is zero. The presented effect originates from the fact that electric-dipole scatterers respond selectively only t

Pierre Falez, Pierre Tirilly, Ioan Marius Bilasco, Philippe Devienne

Spiking neural networks (SNNs) are good candidates to produce ultra-energy-efficient hardware. However, the performance of these models is currently behind traditional methods. Introducing multi-layered SNNs is a promising way to reduce this gap. We propose in this paper a new threshold adaptation system which uses a timestamp objective at which neurons shou

Francois Chapeau-Blondeau

For parameter estimation from an $N$-component composite quantum system, it is known that a separable preparation leads to a mean-squared estimation error scaling as $1/N$ while an entangled preparation can in some conditions afford a smaller error with $1/N^2$ scaling. This quantum superefficiency is however very fragile to noise or decoherence, and typical

Giuseppe Bevilacqua, Valerio Biancalana, Yordanka Dancheva, Leonardo Stiaccini

Nuclear magnetic resonance detection in ultra low field regime enables the measurement of different components of a spurious remanence in the polymeric material constituting the sample container. A differential atomic magnetometer detects simultaneously the static field generated by the container and the time-dependent signal from the precessing nuclei. The

Juriaan Lucassen, Mariëlle J. Meijer, Fabian Kloodt-Twesten, Robert Frömter

Chiral magnetism has gained enormous interest in recent years because of the anticipated wealth of applications in nanoelectronics. The demonstrated stabilization of chiral magnetic domain walls and skyrmions has been attributed to the actively investigated Dzyaloshinskii-Moriya interaction. Recently, however, predictions were made that suggest dipolar inter

Tobias Eichinger, Felix Beierle, Sumsam Ullah Khan, Robin Middelanis

In the field of social networking services, finding similar users based on profile data is common practice. Smartphones harbor sensor and personal context data that can be used for user profiling. Yet, one vast source of personal data, that is text messaging data, has hardly been studied for user profiling. We see three reasons for this: First, private text

Stefano Almi, Matteo Negri

We consider a class of separately convex phase field energies employed in fracture mechanics, featuring non-interpenetration and a general softening behavior. We analyze the time-discrete evolutions generated by a staggered minimization scheme, where fracture irreversibility is modeled by a monotonicity constraint on the phase field variable. After recasting

Subir Sen, Charanpreet Singh, Prashanta K. Mukharjee, Ramesh Nath

Topologically stable nontrivial spin structures, such as skyrmions and antiskyrmions, display a large topological Hall effect owing to their quantized topological charge. Here, we present the finding of a large topological Hall effect beyond room temperature in the tetragonal phase of a Mn-Ni-Ga based ferrimagnetic Heusler shape memory alloy system. The orig

F. Columbro, E. S. Battistelli, A. Coppolecchia, G. D&#39;Alessandro

In this paper we investigate the impact of using a polarization modulator in the Short Wavelenght Instrument for the Polarization Explorer (SWIPE) of the Large Scale Polarization Explorer (LSPE). The experiment is optimized to measure the linear polarization of the Cosmic Microwave Background at large angular scales during a circumpolar long-duration stratos

A. Paiella, E. S. Battistelli, M. G. Castellano, I. Colantoni

Kinetic Inductance Detectors (KIDs) are superconductive low$-$temperature detectors useful for astrophysics and particle physics. We have developed arrays of lumped elements KIDs (LEKIDs) sensitive to microwave photons, optimized for the four horn-coupled focal planes of the OLIMPO balloon-borne telescope, working in the spectral bands centered at 150 GHz, 2

M. McAllister, S. P. Littlefair, S. G. Parsons, V. S. Dhillon

We present measurements of the component masses in 15 Cataclysmic Variables (CVs) - 6 new estimates and 9 improved estimates. We provide new calibrations of the relationship between superhump period excess and mass ratio, and use this relation to estimate donor star masses for 225 superhumping CVs. With an increased sample of donor masses we revisit the impl

Yunhua Xue, Yanfei Feng, Chunlin Wu

Group sparsity combines the underlying sparsity and group structure of the data in problems. We develop a proximally linearized algorithm InISSAPL for the non-Lipschitz group sparse $\ell_{p,q}$-$\ell_r$ optimization problem.

Mahmoud Aldababsa, Oğuz Kucur

The antenna selection (AS) in non-orthogonal multiple access (NOMA) networks is still a challenging problem since finding optimal AS solution may not be available for all channel realizations and has quite computational complexity when it exists. For this reason, in this paper, we develop a new suboptimal solution, majority based transmit antenna selection (

Ivan Bravi, Simon Lucas, Diego Perez-Liebana, Jialin Liu

Game-based benchmarks have been playing an essential role in the development of Artificial Intelligence (AI) techniques. Providing diverse challenges is crucial to push research toward innovation and understanding in modern techniques. Rinascimento provides a parameterised partially-observable multiplayer card-based board game, these parameters can easily mo

Tatiana Tatarenko, Maryam Kamgarpour

We consider multi-agent decision making where each agent&#39;s cost function depends on all agents&#39; strategies. We propose a distributed algorithm to learn a Nash equilibrium, whereby each agent uses only obtained values of her cost function at each joint played action, lacking any information of the functional form of her cost or other agents&#39; costs

D. Virganavičius, V. J. Cadarso, R. Kirchner, L. Stankevičius

Patterning of diamond-like carbon (DLC) and DLC:metal nanocomposites is of interest for an increasing number of applications. We demonstrate a nanoimprint lithography process based on silicon containing thermoplastic resist combined with plasma etching for straightforward patterning of such films. A variety of different structures with few hundred nanometer

Sarveshwar Sharma, N. Sirse, A. Sen, J. S. Wu

The effects of the discharge voltage on the formation and nature of electric field transients in a symmetric, collisionless, very high frequency, capacitively coupled plasma are studied using a self-consistent particle-in-cell (PIC) simulation code. At a driving frequency of 60 MHz and 5 mTorr of argon gas pressure, the discharge voltage is varied from 10V t

Ugo Andral, Julien Fatome, Bertrand Kibler, Christophe Finot

We theoretically and experimentally demonstrate a new electro-optic linear approach to generate high repetition-rate picosecond pulse trains. This simple cavity-free method is based on a temporal sinusoidal phase modulation combined with a triangular spectral phase processing. Experimental results validate the concept at repetition rates ranging from 10 GHz

Hlib Babii, Andrea Janes, Romain Robbes

When building machine learning models that operate on source code, several decisions have to be made to model source-code vocabulary. These decisions can have a large impact: some can lead to not being able to train models at all, others significantly affect performance, particularly for Neural Language Models. Yet, these decisions are not often fully descri

Shanshan Zhao, Huan Fu, Mingming Gong, Dacheng Tao

Supervised depth estimation has achieved high accuracy due to the advanced deep network architectures. Since the groundtruth depth labels are hard to obtain, recent methods try to learn depth estimation networks in an unsupervised way by exploring unsupervised cues, which are effective but less reliable than true labels. An emerging way to resolve this dilem

Mehrdad Showkatbakhsh, Yasser Shoukry, Suhas Diggavi, Paulo Tabuada

This paper discusses the problem of estimating the state of a linear time-invariant system when some of its sensors and actuators are compromised by an adversarial agent. In the model considered in this paper, the malicious agent attacks an input (output) by manipulating its value arbitrarily, i.e., we impose no constraints (statistical or otherwise) on how

Philippe Laurençot

Existence of stationary solutions to the coagulation-fragmentation equation is shown when the coagulation kernel $K$ and the overall fragmentation rate $a$ are given by $K(x, y) = x^αy^β+ x^βy^α$ and $a(x) = x^γ$, respectively, with $0\le α\le β\le1$, $α+β\in [0, 1)$, and $γ> 0$. The proof requires two steps: a dynamical approach is first used to construct s

Raffaele Pastore, Marco Caggioni, Domenico Larobina, Luigi Santamaria Amato

Concentrated suspensions of Brownian hard-spheres in water are an epitome for understanding the glassy dynamics of both soft materials and supercooled molecular liquids. From an experimental point of view, such systems are especially suited to perform particle tracking easily, and, therefore, are a benchmark for novel optical techniques, applicable when prim

Seyed Amin Tabatabaei, Xixi Lu, Mark Hoogendoorn, Hajo A. Reijers

Grouping patients meaningfully can give insights about the different types of patients, their needs, and the priorities. Finding groups that are meaningful is however very challenging as background knowledge is often required to determine what a useful grouping is. In this paper we propose an approach that is able to find groups of patients based on a small

Manash Saha, Clément Menuet, Qi-Jian Sun, Peter Burke

Respiratory modulation of sympathetic nerve activity (respSNA) was studied in a hypertensive rodent model of chronic kidney disease (CKD) using Lewis Polycystic Kidney (LPK) rats and Lewis controls. In adult animals under in vivo anaesthetised conditions (n=8-10/strain), respiratory modulation of splanchnic and renal nerve activity was compared under control

José L. Barros-Justo, Luisa Rincón, Ángela Villota, Wesley K. G. Assunção

The value of a systematic secondary study (a systematic mapping study (SMS) or a systematic literature review (SLR)) comes, directly, from its systematic nature. The formal, well-defined, objective and unbiased process guarantees that the results from these systematically conducted studies are valid. This process is embodied in an action protocol, which must

Rose Baker

Methods for generating new distributions from old can be thought of as techniques for simplifying integrals used in reverse. Hence integrating a probability density function (pdf) by parts provides a new way of modifying distributions; the resulting pdfs are integrals that sometimes require computation as special functions. Summation by parts can be used sim

M. Katsikini, V. Kachkanov, Pascal Boulet, P. Edwards

The structural properties of Er-doped AlNO epilayers grown by radio frequency magnetron sputtering were studied by Extended X-ray Absorption Fine Structure (EXAFS) spectra recorded at the Er L 3 edge. The analysis revealed that Er substitutes for Al in all the studied samples and the increase in Er concentration from 0.5 to 3.6 at.% is not accompanied by for

Navid Azizan, Babak Hassibi

Stochastic mirror descent (SMD) is a fairly new family of algorithms that has recently found a wide range of applications in optimization, machine learning, and control. It can be considered a generalization of the classical stochastic gradient algorithm (SGD), where instead of updating the weight vector along the negative direction of the stochastic gradien

Alexey Slunyaev, Anna Kokorina

The issue of accounting of the wave breaking phenomenon in direct numerical simulations of oceanic waves is discussed. It is emphasized that this problem is crucial for the deterministic description of waves, and also for the dynamical calculation of extreme wave statistical characteristics, such as rogue wave height probability, asymmetry, etc. The conditio

Jérôme Dedecker, Florence Merlevède, Emmanuel Rio

Let (X k) be a strictly stationary sequence of random variables with values in some Polish space E and common marginal $μ$, and (A k) k>0 be a sequence of Borel sets in E. In this paper, we give some conditions on (X k) and (A k) under which the events {X k $\in$ A k } satisfy the Borel-Cantelli (or strong Borel-Cantelli) property. In particular we prove tha

Giuseppe Arbia, Paolo Berta, Carrie B. Dolan

Spatial microeconometric studies typically suffer from various forms of inaccuracies that are not present when dealing with the classical regional spatial econometrics models. Among those, missing data, locational errors, sampling without a formal sample design, measurement errors and misalignment are the typical sources of inaccuracy that can affects the re

Nikolai A. Tyurin

In recent papers, summarized in survey [1], we construct a number of examples of non standard lagrangian tori on compact toric varieties and as well on certain non toric varieties which admit pseudotoric structures. Using this pseudotoric technique we explain how non standard lagrangian tori of Chekanov type can be constructed and what is the topological dif

Mythra V. Balakuntala, L. N. Vishnunandan Venkatesh, Jyothsna Padmakumar Bindu, Richard M. Voyles

Humans naturally &#34;program&#34; a fellow collaborator to perform a task by demonstrating the task few times. It is intuitive, therefore, for a human to program a collaborative robot by demonstration and many paradigms use a single demonstration of the task. This is a form of one-shot learning in which a single training example, plus some context of the ta

Toshikazu Sunada

The purpose of this essay is to trace the historical development of geometry while focusing on how we acquired mathematical tools for describing the &#34;shape of the universe.&#34; More specifically, our aim is to consider, without a claim to completeness, the origin of Riemannian geometry, which is indispensable to the description of the space of the unive

Raya Dastidar, Kuntal Misra, Mridweeka Singh, D. K. Sahu

We present photometry, polarimetry and spectroscopy of the Type II supernova ASASSN-16ab/SN 2016B in PGC 037392. The photometric and spectroscopic follow-up commenced about two weeks after shock breakout and continued until nearly six months. The light curve of SN 2016B exhibits intermediate properties between those of Type IIP and IIL. The early decline is

H. Rinnert, S. S. Hussain, Valerie Brien, P. Pigeat

Er-doped aluminum nitride films, containing different Er concentrations, were obtained at room temperature by reactive radio frequency magnetron sputtering. The prepared samples show a nano-columnar microstructure and the size of the columns is dependent on the magnetron power. The Er-related photoluminescence (PL) was studied in relation with the temperatur

Wojciech Florkowski

Recent theoretical developments in hydrodynamics of particles with spin 1/2 are briefly reviewed.

Nicolas Ratto, Martine Marion, Vitaly Volpert

The paper is devoted to the investigation of a reaction-diffusion system of equations describing the process of blood coagulation. Existence of pulses solutions, that is, positive stationary solutions with zero limit at infinity is studied. It is shown that such solutions exist if and only if the speed of the travelling wave described by the same system is p

Imre Ferenc Barna, Gabriella Bognár, Mohammed Guedda, Krisztián Hriczó

The one-dimensional Kardar-Parisi-Zhang dynamic interface growth equation with the self-similar Ansatz is analyzed. As a new feature additional analytic terms are added. From the mathematical point of view, these can be considered as various noise distribution functions. Six different cases were investigated among others Gaussian, Lorentzian, white or even p

Michel Coste, Seydou Moussa

We prove that the set of singular configurations of a general Gough Stewart platform has a rational parametrization. We introduce a reciprocal twist mapping which, for a general orientation of the platform, realizes the cubic surface of singularities as the blowing up of a quadric surface in five points.

Roman Drnovšek

In 1992, Szyld provided a sequence of lower bounds for the spectral radius of a nonnegative matrix $A$, based on the geometric symmetrization of powers of $A$. In 1998, Taşçi and Kirkland proved a companion result by giving a sequence of upper bounds for the spectral radius of $A$, based on the arithmetic symmetrization of powers of $A$. In this note, we ext

Andreas Mittermeier, Birgit Ertl-Wagner, Jens Ricke, Olaf Dietrich

Tracer-kinetic analysis of dynamic contrast-enhanced magnetic resonance imaging data is commonly performed with the well-known Tofts model and nonlinear least squares (NLLS) regression. This approach yields point estimates of model parameters, uncertainty of these estimates can be assessed e.g. by an additional bootstrapping analysis. Here, we present a Baye

Yichao Yan, Qiang Zhang, Bingbing Ni, Wendong Zhang

Person re-identification has achieved great progress with deep convolutional neural networks. However, most previous methods focus on learning individual appearance feature embedding, and it is hard for the models to handle difficult situations with different illumination, large pose variance and occlusion. In this work, we take a step further and consider e

Ning Wang, Yibing Song, Chao Ma, Wengang Zhou

We propose an unsupervised visual tracking method in this paper. Different from existing approaches using extensive annotated data for supervised learning, our CNN model is trained on large-scale unlabeled videos in an unsupervised manner. Our motivation is that a robust tracker should be effective in both the forward and backward predictions (i.e., the trac

Shingo Takeuchi

Generalized trigonometric functions (GTFs) are simple generalization of the classical trigonometric functions. GTFs are deeply related to the $p$-Laplacian, which is known as a typical nonlinear differential operator. Compared to GTFs with one parameter, there are few applications of GTFs with two parameters to differential equations. We will apply GTFs with

Mohammad Riyaz Belgaum, Shahrulniza Musa, Mazliham Mohd Su&#39;ud, Muhammad Alam

Routing protocols are used to transmit the packets from the source to the destination node in mobile ad hoc networks. The intruders seek chance to pierce into the network and becomes a cause of malfunctioning in the network. These protocols are always prone to attacks. During the phases of routing in different types of protocols, each of the attack finds a w

Quynh Ngoc Thi Do, Judith Gaspers

Typically, spoken language understanding (SLU) models are trained on annotated data which are costly to gather. Aiming to reduce data needs for bootstrapping a SLU system for a new language, we present a simple but effective weight transfer approach using data from another language. The approach is evaluated with our promising multi-task SLU framework develo

C. Kamal

We predict from DFT based electronic structure calculations that a monolayer made up of Carbon and Arsenic atoms, with a chemical composition (CAs3) forms an energetically and dynamically stable system. The optimized geometry of the monolayer is slightly different from the buckled geometric configuration observed for silicene and germanene. The results of el

Giulio Biroli, Alice Guionnet

We consider matrices formed by a random $N\times N$ matrix drawn from the Gaussian Orthogonal Ensemble (or Gaussian Unitary Ensemble) plus a rank-one perturbation of strength $θ$, and focus on the largest eigenvalue, $x$, and the component, $u$, of the corresponding eigenvector in the direction associated to the rank-one perturbation. We obtain the large dev

Kyung-Su Kim, Sae-Young Chung

A greedy algorithm called Bayesian multiple matching pursuit (BMMP) is proposed to estimate a sparse signal vector and its support given $m$ linear measurements. Unlike the maximum a posteriori (MAP) support detection, which was proposed by Lee to estimate the support by selecting an index with the maximum likelihood ratio of the correlation given by a norma

Markus Heydenreich, Christian Hirsch

In the classical preferential attachment model, links form instantly to newly arriving nodes and do not change over time. We propose a hierarchical random graph model in a spatial setting, where such a time-variability arises from an activity-based reinforcement mechanism. We show that the reinforcement mechanism converges, and prove rigorously that the resu

Daisuke Ikegami, Nam Trang

This paper studies structural consequences of supercompactness of $ω_1$ under $\sf{ZF}$. We show that the Axiom of Dependent Choice $(\sf{DC})$ follows from &#34;$ω_1$ is supercompact&#34;. &#34;$ω_1$ is supercompact&#34; also implies that $\sf{AD}^+$, a strengthening of the Axiom of Determinacy $(\sf{AD})$, is equivalent to $\sf{AD}_\mathbb{R}$. It is shown

Charles K. Chui, Shao-Bo Lin, Ding-Xuan Zhou

Based on the tree architecture, the objective of this paper is to design deep neural networks with two or more hidden layers (called deep nets) for realization of radial functions so as to enable rotational invariance for near-optimal function approximation in an arbitrarily high dimensional Euclidian space. It is shown that deep nets have much better perfor

Bertrand Lacroix-A-Chez-Toine, Jeyson Andres Monroy Garzon, Christopher Sebastian Hidalgo Calva, Isaac Perez Castillo

We study the Ginibre ensemble of $N \times N$ complex random matrices and compute exactly, for any finite $N$, the full distribution as well as all the cumulants of the number $N_r$ of eigenvalues within a disk of radius $r$ centered at the origin. In the limit of large $N$, when the average density of eigenvalues becomes uniform over the unit disk, we show

Kazutaka Nishiguchi, Tomonori Shirakawa, Hiroshi Watanabe, Ryotaro Arita

We study possible superconductivity in a carrier-doped iridium oxide insulator Sr$_{2}$IrO$_{4}$ based on an effective $t_{2g}$ three-orbital Hubbard model on the square lattice with a large spin-orbit coupling (SOC). Numerically solving the linearized Eliashberg equation for the superconducting (SC) gap function with the random phase approximation, we syste

Ziyang Qiu, Congcong Le, Zhiyu Liao, Bing Xu

The optical properties of YbMnSb2 have been measured in a broad frequency range from room temperature down to 7 K. With decreasing temperature, a flat region develops in the optical conductivity spectra at about 300cm-1, which can not be described by the well-known Drude-Lorentz model. A frequency-independent component has to be introduced to model the measu

Chirashree Lahiri

We have calculated astrophysical reaction cross-sections for $(γ,α)$ reactions of some nuclei important for the calculation of $p$-process reaction-decay network. Reaction rates for $α$-induced reactions are calculated with the semi-microscopic optical potential constructed using double folding method, where nuclear density distributions for finite nuclei al

Irfan Siddique, Ren-jie Wang, Shi Pu, Qun Wang

We study relativistic magnetohydrodynamics with longitudinal boost invariance in the presence of chiral magnetic effects and finite electric conductivity. With initial magnetic fields parallel or anti-parallel to electric fields, we derive the analytic solutions of electromagnetic fields and the chiral number and energy density in an expansion of several par

Edward Beeching, Christian Wolf, Jilles Dibangoye, Olivier Simonin

An important goal of research in Deep Reinforcement Learning in mobile robotics is to train agents capable of solving complex tasks, which require a high level of scene understanding and reasoning from an egocentric perspective. When trained from simulations, optimal environments should satisfy a currently unobtainable combination of high-fidelity photograph

Mingjie Xin, Wui Seng Leong, Zilong Chen, Shau-Yu Lan

Confining particles in hollow-core photonic crystal fibers has opened up new prospects to scale up the distance and time over which particles can be made to interact with light. However, maintaining long-lived quantum spin coherence and/or transporting it over macroscopic distances in a waveguide remain challenging. Here, we demonstrate coherent guiding of g

Jozef Strecka, Onofre Rojas, Sergio Martins de Souza

The mixed spin-(1/2, 3/2) Ising model on a decorated square lattice, which takes into account lattice vibrations of the spin-3/2 decorating magnetic ions at a quantum-mechanical level under the assumption of a perfect lattice rigidity of the spin-1/2 nodal magnetic ions, is examined via an exact mapping correspondence with the effective spin-1/2 Ising model

Baoyun Peng, Xiao Jin, Jiaheng Liu, Shunfeng Zhou

Most teacher-student frameworks based on knowledge distillation (KD) depend on a strong congruent constraint on instance level. However, they usually ignore the correlation between multiple instances, which is also valuable for knowledge transfer. In this work, we propose a new framework named correlation congruence for knowledge distillation (CCKD), which t

Sarika Jalan, Vasundhara Rathore, Ajay Deep Kachhvah, Alok Yadav

To date, explosive synchronization (ES) is shown to be originated from either degree-frequency correlation or inertia of phase oscillators. Of late, it has been shown that ES can be induced in a network by adaptively controlled phase oscillators. Here we show that ES is a generic phenomenon and can occur in any network by appropriately multiplexing it with a

Luca Calatroni, Alessandro Lanza, Monica Pragliola, Fiorella Sgallari

We propose a new space-variant anisotropic regularisation term for variational image restoration, based on the statistical assumption that the gradients of the target image distribute locally according to a bivariate generalised Gaussian distribution. The highly flexible variational structure of the corresponding regulariser encodes several free parameters w

Cuipo Jiang, Qing Wang

This paper is about the orbifold theory of affine and parafermion vertex operator algebras. It is known that the parafermion vertex operator algebra $K(sl_2,k)$ associated to the integrable highest weight modules for the affine Kac-Moody algebra $A_1^{(1)}$ is the building block of the general parafermion vertex operator $K(\mathfrak{g},k)$ for any finite di

Zhentao Jin, Yi Zhou

This article concerns the formation of finite-time singularities in solutions to quasilinear hyperbolic systems with small initial data. By constructing a special test function, we first present a simpler proof of the main result in Sideris&#39; &#34;Formation of singularities in three-dimensional compressible fluids&#34;: the global classical solution is no

Shengning Qiao, Bing Chen

Let $n\geq 6,k\geq 0$ be two integers. Let $H$ be a graph of order $n$ with $k$ components, each of which is an even cycle of length at least $6$ and $G$ be a bipartite graph with bipartition $(X,Y)$ such that $|X|=|Y|\geq n/2$. In this paper, we show that if the minimum degree of $G$ is at least $n/2-k+1$, then $G$ contains a subdivision of $H$. This genera

A. Rahaman, M. Chakraborty, T. Paramanik, R. K. Maurya

Using density-functional theory calculations and experimental investigations on structural, magnetic and dielectric properties, we have elucidated a unique tetragonal ground state for MnTi2O4, a Ti^{3+} (3d^1)-ion containing spinel-oxide. With lowering of temperature around 164 K, cubic MnTi2O4 undergoes a structural transition into a polar P4_1 tetragonal s

Tetsuro Habe

We investigate the electronic transport property of lateral heterojunctions of semiconducting and metallic transition-metal dichalcogenide monolayers, MoSe$_2$ and NbSe$_2$, respectively. We calculate the electronic transmission probability by using a multi-orbital tight-binding model based on the first-principles band structure. The transmission probability

Shaohua Gan, Zhixian Yu

This paper is concerned with the entire solutions of a two-dimensional nonlocal periodic lattice dynamical system. With bistable assumption, it is well known that the system has three different types of traveling fronts. The existence of merging-front entire solutions originating from two fronts for the system have been established by Dong, Li \& Zhang [{\it

Weiming Li, Chang Liu, Yajun Zhu, Jiwei Zhang

In this paper, we extend the unified gas-kinetic wave-particle (UGKWP) method to the multiscale photon transport. In this method, the photon free streaming and scattering processes are treated in an un-splitting way. The duality descriptions, namely the simulation particle and distribution function, are utilized to describe the photon. By accurately recoveri

Shichen Liu, Tianye Li, Weikai Chen, Hao Li

Rendering bridges the gap between 2D vision and 3D scenes by simulating the physical process of image formation. By inverting such renderer, one can think of a learning approach to infer 3D information from 2D images. However, standard graphics renderers involve a fundamental discretization step called rasterization, which prevents the rendering process to b

Jeongwoo Jae, Kyunghyun Baek, Junghee Ryu, Jinhyoung Lee

In order to analyze joint measurability of given measurements, we introduce a Hermitian operator-valued measure, called $W$-measure, such that it has marginals of positive operator-valued measures (POVMs). We prove that ${W}$-measure is a POVM {\em if and only if} its marginal POVMs are jointly measurable. The proof suggests to employ the negatives of ${W}$-

Jinbin Zhang, Heng Wang

Chinese word usage errors often occur in non-native Chinese learners&#39; writing. It is very helpful for non-native Chinese learners to detect them automatically when learning writing. In this paper, we propose a novel approach, which takes advantages of different auxiliary tasks, such as POS-tagging prediction and word log frequency prediction, to help the

Rui Liu, Yu Liu, Xinyu Gong, Xiaogang Wang

Flow-based generative models show great potential in image synthesis due to its reversible pipeline and exact log-likelihood target, yet it suffers from weak ability for conditional image synthesis, especially for multi-label or unaware conditions. This is because the potential distribution of image conditions is hard to measure precisely from its latent var

Abhinav Shukla, Shruti Shriya Gullapuram, Harish Katti, Mohan Kankanhalli

Advertisements (ads) often contain strong affective content to capture viewer attention and convey an effective message to the audience. However, most computational affect recognition (AR) approaches examine ads via the text modality, and only limited work has been devoted to decoding ad emotions from audiovisual or user cues. This work (1) compiles an affec

Heng Wang, Mingzhi Mao

The goal of knowledge representation learning is to embed entities and relations into a low-dimensional, continuous vector space. How to push a model to its limit and obtain better results is of great significance in knowledge graph&#39;s applications. We propose a simple and elegant method, Trans-DLR, whose main idea is dynamic learning rate control during