April 2020 arXiv papers — page 18

Mario Fusco Girard

It is shown that it is possible to construct the quantum wave functions for non-separable but integrable two-dimensional Hamiltonian systems, by solving suitable Dirichlet boundary values problems inside and outside the regions spanned by particular families of classical trajectories, in one-to-one correspondence with the quantum state. The method is applied

Hiroyasu Tajima, Ken Funo

Producing a large current typically requires large dissipation, as is the case in electric conduction, where Joule heating is proportional to the square of the current. Stochastic thermodynamics offers a framework to study nonequilibrium thermodynamics of small fluctuating systems, and quite recently, microscopic derivations and universal understanding of th

Emirhan Gürpınar, Andrei Romashchenko

It is known that the mutual information, in the sense of Kolmogorov complexity, of any pair of strings x and y is equal to the length of the longest shared secret key that two parties can establish via a probabilistic protocol with interaction on a public channel, assuming that the parties hold as their inputs x and y respectively. We determine the worst-cas

Vittorio Mazzia, Francesco Salvetti, Aleem Khaliq, Marcello Chiaberge

Real-time apple detection in orchards is one of the most effective ways of estimating apple yields, which helps in managing apple supplies more effectively. Traditional detection methods used highly computational machine learning algorithms with intensive hardware set up, which are not suitable for infield real-time apple detection due to their weight and po

Andreas Penzkofer, Bartosz Kusmierz, Angelo Capossele, William Sanders

In recent years several distributed ledger technologies based on directed acyclic graphs (DAGs) have appeared on the market. Similar to blockchain technologies, DAG-based systems aim to build an immutable ledger and are faced with security concerns regarding the irreversibility of the ledger state. However, due to their more complex nature and recent popular

Bryan Lim, Stefan Zohren

Numerous deep learning architectures have been developed to accommodate the diversity of time series datasets across different domains. In this article, we survey common encoder and decoder designs used in both one-step-ahead and multi-horizon time series forecasting -- describing how temporal information is incorporated into predictions by each model. Next,

Dan Segal, Katrin Tent

We show that for Chevalley groups G(R) of rank at least 2 over a ring R the root subgroups are essentially (nearly always) the double centralizers of corresponding root elements. In very many cases this implies that R and G(R) are bi-interpretable, yielding a new approach to bi-interpretability for algebraic groups over a wide range of rings and fields. For

Abhilash Nandy, Rachana Sathish, Debdoot Sheet

Various screening and diagnostic methods have led to a large reduction of cervical cancer death rates in developed countries. However, cervical cancer is the leading cause of cancer related deaths in women in India and other low and middle income countries (LMICs) especially among the urban poor and slum dwellers. Several sophisticated techniques such as cyt

Dibakar Dey

In the present paper, we introduce the notion of $\ast$-Miao-Tam critical equation on almost contact metric manifolds and studied on a class of almost Kenmotsu manifold. It is shown that if the metric of a $(2n + 1)$-dimensional $(k,\mu)'$-almost Kenmotsu manifold $(M,g)$ satisfies the $\ast$-Miao-Tam critical equation, then the manifold $(M,g)$ is $\ast$-Ri

Qingqing Zhang, Gang Wang, Jie Chen, Georgios B. Giannakis

Internet of things (IoT) is powering up smart cities by connecting all kinds of electronic devices. The power supply problem of IoT devices constitutes a major challenge in current IoT development, due to the poor battery endurance as well as the troublesome cable deployment. The wireless power transfer (WPT) technology has recently emerged as a promising so

S. Mironov, H. Meng, A. Buzdin

We demonstrate that a Josephson junction with a half-metallic weak link integrated into the superconducting loop enables the pumping of magnetic flux piercing the loop. In such junctions, the ground state phase $\psi$ is determined by the mutual orientation of magnetic moments in two ferromagnets surrounding the half-metal. Thus, the precession of magnetic m

Sauro Succi

A closure for the effective relaxation time of the Boltzmann-BGK kinetic equation for fluid turbulence is presented, based on a double-averaging procedure over both kinetic and turbulent fluctuations. The resulting effective relaxation time appears to agree with values obtained via a renormalization group treatment of the Navier-Stokes equation only at low v

Shilin Qu, Fajie Yuan, Guibing Guo, Liguang Zhang

Recently, Memory-based Neural Recommenders (MNR) have demonstrated superior predictive accuracy in the task of sequential recommendations, particularly for modeling long-term item dependencies. However, typical MNR requires complex memory access operations, i.e., both writing and reading via a controller (e.g., RNN) at every time step. Those frequent operati

M. A. Mendez, A. Gosset, B. Scheid, M. Balabane

The jet wiping process is a cost-effective coating technique that uses impinging gas jets to control the thickness of a liquid layer dragged along a moving strip. This process is fundamental in various coating industries (mainly in hot-dip galvanizing) and is characterized by an unstable interaction between the gas jet and the liquid film that results in wav

Erik Aas, Arvind Ayyer, Svante Linusson, Samu Potka

Let $W$ be a finite Weyl group and $\widetilde W$ the corresponding affine Weyl group. A random element of $\widetilde W$ can be obtained as a reduced random walk on the alcoves of $\widetilde W$. By a theorem of Lam (Ann. Prob. 2015), such a walk almost surely approaches one of $|W|$ many directions. We compute these directions when $W$ is $B_n$, $C_n$ and

R. N. Sen

In 1954, Ashkin, Page and Woodward (hereafter APW) reported on the first counter experiments to measure the electron-electron and electron-positron scattering cross-sections at low relativistic energies (0.6-1.7 MeV). Their aim was to look for the spin and exchange or virtual annihilation effects predicted by the Moller and Bhabha formulae. Their experiments

Nathaniel Joseph Tye, James Timothy Meech, Bilgesu Arif Bilgin, Phillip Stanley-Marbell

We introduce a new method for hardware non-uniform random number generation based on the transfer characteristics of graphene field-effect transistors (GFETs) which requires as few as two transistors and a resistor (or transimpedance amplifier). The method could be integrated into a custom computing system to provide samples from arbitrary univariate distrib

Matt Galton, Ian Melbourne

We give sufficient Gordin-type criteria for the iterated (enhanced) weak invariance principle to hold for deterministic dynamical systems. Such an invariance principle is intrinsically related to the interpretation of stochastic integrals. We illustrate this with examples of deterministic fast-slow systems where our iterated invariance principle yields conve

Hadi Hosseini, Ayumi Igarashi, Andrew Searns

We initiate the study of multi-layered cake cutting with the goal of fairly allocating multiple divisible resources (layers of a cake) among a set of agents. The key requirement is that each agent can only utilize a single resource at each time interval. Several real-life applications exhibit such restrictions on overlapping pieces; for example, assigning ti

Nicolas P. Campana, Manuel Iori, Mayron C. O. Moreira

This paper proposes new algorithms for the assembly line balancing problem with hierarchical worker assignment (ALBHW). The ALBHW appears in real industrial contexts where companies deal with a multi-skilled workforce. It considers task execution times that vary depending on the worker type to whom the task is assigned. Qualification levels among workers are

Severin Bunk, Lukas Müller, Richard J. Szabo

We study bundle gerbes on manifolds $M$ that carry an action of a connected Lie group $G$. We show that these data give rise to a smooth 2-group extension of $G$ by the smooth 2-group of hermitean line bundles on $M$. This 2-group extension classifies equivariant structures on the bundle gerbe, and its non-triviality poses an obstruction to the existence of

Stefano Fortunati, Alexandre Renaux, Frédéric Pascal

A general non-Gaussian semiparametric model is adopted to characterize the measurement vectors, i.e.\ the \textit{snapshots}, collected by a linear array. Moreover, the recently derived \textit{robust semiparametric efficient} $R$-estimator of the data covariance matrix is exploited to implement an original version of the MUSIC estimator. The efficiency of t

Yoh Yamamoto, Alan Salcedo, Carlos M. Diaz, Md Shamsul Alam

The Strongly Constrained and Appropriately Normed (SCAN) functional is a non-empirical meta-generalized-gradient approximation (meta-GGA) functional that satisfies all the known constraints that a meta-GGA functional can, but it also exhibits a great degree of sensitivity to numerical grids. Its numerical complexities are amplified when used in Perdew-Zunger

Seppo Laine, Lankeswar Dey, Mauri Valtonen, A. Gopakumar

Binary black hole (BH) central engine description for the unique blazar OJ 287 predicted that the next secondary BH impact-induced bremsstrahlung flare should peak on 2019 July 31. This prediction was based on detailed general relativistic modeling of the secondary BH trajectory around the primary BH and its accretion disk. The expected flare was termed the

K. von Arx, F. Forte, M. Horio, V. Granata

We present a combined oxygen $K$-edge x-ray absorption spectroscopy (XAS) and resonant inelastic x-ray scattering (RIXS) study of the bilayer ruthenate Ca$_3$Ru$_2$O$_7$. Our RIXS experiments on Ca$_3$Ru$_2$O$_7$ were carried out on the overlapping planar and inter-planar oxygen resonances, which are distinguishable from the apical one. Comparison to equival

Min Zhu, David G. M. Mitchell, Michael Lentmaier, Daniel J. Costello,

We investigate error propagation in sliding window decoding of braided convolutional codes (BCCs). Previous studies of BCCs have focused on iterative decoding thresholds, minimum distance properties, and their bit error rate (BER) performance at small to moderate frame length. Here, we consider a sliding window decoder in the context of large frame length or

Marc Rußwurm, Sherrie Wang, Marco Körner, David Lobell

The representations of the Earth's surface vary from one geographic region to another. For instance, the appearance of urban areas differs between continents, and seasonality influences the appearance of vegetation. To capture the diversity within a single category, like as urban or vegetation, requires a large model capacity and, consequently, large dataset

Garance Gourdel, Tomasz Kociumaka, Jakub Radoszewski, Tatiana Starikovskaya

In the problem of the longest common substring with $k$ mismatches we are given two strings $X, Y$ and must find the maximal length $\ell$ such that there is a length-$\ell$ substring of $X$ and a length-$\ell$ substring of $Y$ that differ in at most $k$ positions. The length $\ell$ can be used as a robust measure of similarity between $X, Y$. In this work,

Hang Dong, Jinshan Pan, Lei Xiang, Zhe Hu

In this paper, we propose a Multi-Scale Boosted Dehazing Network with Dense Feature Fusion based on the U-Net architecture. The proposed method is designed based on two principles, boosting and error feedback, and we show that they are suitable for the dehazing problem. By incorporating the Strengthen-Operate-Subtract boosting strategy in the decoder of the

Junichi Okamoto, Wen-Min Huang, Kyle Irwin, David K. Campbell

Cold atom experiments can now realize mixtures where different components move in different spatial dimensions. We investigate a fermion mixture where one species is constrained to move along a one-dimensional lattice embedded in a two-dimensional lattice populated by another species of fermions, and where all bare interactions are contact interactions. By f

Blaine Quackenbush, Tony Samuel, Matthew A. West

The subshift of finite type property (also known as the Markov property) is ubiquitous in dynamical systems and the simplest and most widely studied class of dynamical systems are $\beta$-shifts, namely transformations of the form $T_{\beta, \alpha} \colon x \mapsto \beta x + \alpha \bmod{1}$ acting on $[-\alpha/(\beta - 1), (1-\alpha)/(\beta - 1)]$, where $

Roberto Robles, Vladimír Zobač, Kwan Ho Au Yeung, Francesca Moresco

On a gold surface, supramolecules composed of 4-acetylbiphenyl molecules show structural directionality, reproducibility and robustness to external perturbations. We investigate the assembly of those molecules on the Au(111) surface and analyze how the observed supramolecular structures are the result of weak long-range dispersive forces stabilizing the 4-ac

Bogdan Bocse, Ioan Radu Jinga

The purpose of this paper is to outline a generalised model for representing hybrids of relational-categorical, symbolic, perceptual-sensory and perceptual-latent data, so as to embody, in the same architectural data layer, representations for the input, output and latent tensors. This variety of representation is currently used by various machine-learning m

Guido Homann, Jayson G. Cosme, Ludwig Mathey

We propose to induce a time crystalline state in a high-$T_c$ superconductor, by optically driving a sum resonance of the Higgs mode and a Josephson plasma mode. The generic cubic process that couples these fundamental excitations converts driving of the sum resonance into simultaneous resonant driving of both modes, resulting in an incommensurate subharmoni

N. Balakrishnan, E. Castilla, N. Martin, L. Pardo

In this paper, we develop robust estimators and tests for one-shot device testing under proportional hazards assumption based on divergence measures. Through a detailed Monte Carlo simulation study and a numerical example, the developed inferential procedures are shown to be more robust than the classical procedures, based on maximum likelihood estimators.

Kazuhiro Ishige, Paolo Salani, Asuka Takatsu

We introduce a notion of $F$-concavity which largely generalizes the usual concavity. By the use of the notions of closedness under positive scalar multiplication and closedness under positive exponentiation we characterize power concavity and power log-concavity among nontrivial $F$-concavities, respectively. In particular, we have a characterization of log

Yan Liu, Ya-Wen Sun

We show that gapless modes in relativistic hydrodynamics could become topologically nontrivial by weakly breaking the conservation of energy momentum tensor in a specific way. This system has topological semimetal-like crossing nodes in the spectrum of hydrodynamic modes that require the protection of a special combination of translational and boost symmetri

Simon Vandenhende, Stamatios Georgoulis, Wouter Van Gansbeke, Marc Proesmans

With the advent of deep learning, many dense prediction tasks, i.e. tasks that produce pixel-level predictions, have seen significant performance improvements. The typical approach is to learn these tasks in isolation, that is, a separate neural network is trained for each individual task. Yet, recent multi-task learning (MTL) techniques have shown promising

Niloofar Okati, Taneli Riihonen, Dani Korpi, Ilari Angervuori

As low Earth orbit (LEO) satellite communication systems are gaining increasing popularity, new theoretical methodologies are required to investigate such networks' performance at large. This is because deterministic and location-based models that have previously been applied to analyze satellite systems are typically restricted to support simulations only.

Qingqing Zhang, Xiaojun Shi, Qingwen Liu, Jun Wu

Distributed laser charging (DLC) is a wireless power transfer technology for mobile electronics. Similar to traditional wireless charging systems, the DLC system can only provide constant power to charge a battery. However, Li-ion battery needs dynamic input current and voltage, thus power, in order to optimize battery charging performance. Therefore, neithe

Simone Cerreia-Vioglio, Fabio Maccheroni, Massimo Marinacci, Aldo Rustichini

We provide two characterizations, one axiomatic and the other neuro-computational, of the dependence of choice probabilities on deadlines, within the widely used softmax representation \[ p_{t}\left( a,A\right) =\dfrac{e^{\frac{u\left( a\right) }{\lambda \left( t\right) }+\alpha \left( a\right) }}{\sum_{b\in A}e^{\frac{u\left( b\right) }{\lambda \left( t\rig

Matthew de Brecht

We show some basic results on the characterization of quasi-Polish spaces in terms of spaces of ideals, with an emphasis on the connections with computable topology.

Felix Schreiber, Lorenzo Baldrati, Christin Schmitt, Rafael Ramos

We demonstrate stable and reversible current induced switching of large-area ($> 100\;\mu m^2$) antiferromagnetic domains in NiO/Pt by performing concurrent transport and magneto-optical imaging measurements in an adapted Kerr microscope. By correlating the magnetic images of the antiferromagnetic domain changes and magneto-transport signal response in these

Maximilian Höb, Dieter Kranzlmüller

The upcoming exascale era will push the changes in computing architecture from classical CPU-based systems in hybrid GPU-heavy systems with much higher levels of complexity. While such clusters are expected to improve the performance of certain optimized HPC applications, it will also increase the difficulties for those users who have yet to adapt their code

N. Balakrishnan, E. Castilla, N. Martin, L. Pardo

Most work on one-shot devices assume that there is only one possible cause of device failure. However, in practice, it is often the case that the products under study can experience any one of various possible causes of failure. Robust estimators and Wald-type tests are developed here for the case of one-shot devices under competing risks. An extensive simul

Valentin Oreiller, Vincent Andrearczyk, Julien Fageot, John O. Prior

Locally Rotation Invariant (LRI) operators have shown great potential in biomedical texture analysis where patterns appear at random positions and orientations. LRI operators can be obtained by computing the responses to the discrete rotation of local descriptors, such as Local Binary Patterns (LBP) or the Scale Invariant Feature Transform (SIFT). Other stra

P. J. W. Koelewijn, G. Sales Mazzoccante, R. Tóth, S. Weiland

Recently, a number of counter examples have surfaced where Linear Parameter-Varying (LPV) control synthesis applied to achieve asymptotic output tracking and disturbance rejection for a nonlinear system, fails to achieve the desired asymptotic tracking and rejection behavior even when the scheduling variations remain in the bounded region considered during d

Yang Li, Xuanqin Mou

Structural similarity (SSIM)-based distortion $D_\text{SSIM}$ is more consistent with human perception than the traditional mean squared error $D_\text{MSE}$. To achieve better video quality, many studies on optimal bit allocation (OBA) and rate-distortion optimization (RDO) used $D_\text{SSIM}$ as the distortion metric. However, many of them failed to optim

Frank Tecker

After a short introduction of CLIC, the Compact Linear Collider, and its test facility CTF3 (CLIC Test Facility 3), this paper gives an overview and some examples of the diagnostics used at CTF3.

Gergő Nemes

A class of Schr\"odinger-type second-order linear differential equations with a large parameter $u$ is considered. Analytic solutions of this type of equations can be described via (divergent) formal series in descending powers of $u$. These formal series solutions are called the WKB solutions. We show that under mild conditions on the potential function of

Marcel Binz, Lukas Bruder, Lipeng Chen, Maxim F. Gelin

The effects of high pulse intensity and chirp on two-dimensional electronic spectroscopy signals are experimentally investigated in the highly non-perturbative regime using atomic rubidium vapor as clean model system. Data analysis is performed based on higher-order Feynman diagrams and non-perturbative numerical simulations of the system response. It is sho

K. M. Schoeffler, L. O. Silva

The expansion of plasma with non-parallel temperature and density gradients, and the generation of magnetic field via the Biermann battery is modeled using particle-in-cell simulations that include collisional effects via Monte Carlo methods. A scaling of the degree of collisionality shows that an anisotropy can be produced, and drive the Weibel instability,

Zhao Zhang, Wenda Jin, Jun Xu, Ming-Ming Cheng

Co-saliency detection (Co-SOD) aims to segment the common salient foreground in a group of relevant images. In this paper, inspired by human behavior, we propose a gradient-induced co-saliency detection (GICD) method. We first abstract a consensus representation for the grouped images in the embedding space; then, by comparing the single image with consensus

Cihan Emre Kement, Bulent Tavli, Hakan Gultekin, Halim Yanikomeroglu

In smart electricity grids, high time granularity (HTG) power consumption data can be decomposed into individual appliance load signatures via Nonintrusive Appliance Load Monitoring techniques to expose appliance usage profiles. Various methods ranging from load shaping to noise addition and data aggregation have been proposed to mitigate this problem. Howev

Martin Haug, Paavo Camps, Tobias Umland, Jan-Niklas Voigt-Antons

Technology can facilitate self-learning for academic and leisure activities such as music learning. In general, learning to play an unknown musical song at sight on the electric piano or any other instrument can be quite a chore. In a traditional self-learning setting, the musician only gets feedback in terms of what errors they can hear themselves by compar

Manuel Morante

When working with task-related fMRI data, one of the most crucial parts of the data analysis consists of determining a proper estimate of the BOLD response. The following document presents a lite model for the Hemodynamic Response Function HRF. Between other advances, the proposed model present less number of parameters compared to other similar HRF alternat

Julien Brasseur, Jérôme Coville

We consider a nonlocal semi-linear parabolic equation on a connected exterior domain of the form $\mathbb{R}^N\setminus K$, where $K\subset\mathbb{R}^N$ is a compact "obstacle". The model we study is motivated by applications in biology and takes into account long range dispersal events that may be anisotropic depending on how a given population perceives th

Cihan Emre Kement, Marija Ilic, Hakan Gultekin, Cihan Tugrul Cicek

Frequent metering of electricity consumption is crucial for demand side management in smart grids. However, metered data can be processed fairly easily by employing well-established nonintrusive appliance load monitoring techniques to infer appliance usage, which reveals information about consumers' private lives. Existing load shaping techniques for privacy

Xiangyu Chen, Zelin Ye, Jiankai Sun, Yuda Fan

Grasping in cluttered scenes is challenging for robot vision systems, as detection accuracy can be hindered by partial occlusion of objects. We adopt a reinforcement learning (RL) framework and 3D vision architectures to search for feasible viewpoints for grasping by the use of hand-mounted RGB-D cameras. To overcome the disadvantages of photo-realistic envi

Gaël Bringout, Wolfgang Erb, Jürgen Frikel

We derive a new 3D model for magnetic particle imaging (MPI) that is able to incorporate realistic magnetic fields in the reconstruction process. In real MPI scanners, the generated magnetic fields have distortions that lead to deformed magnetic low-field volumes (LFV) with the shapes of ellipsoids or bananas instead of ideal field-free points (FFP) or lines

Dmitry Grishchenko, Franck Iutzeler, Jérôme Malick

Many applications in machine learning or signal processing involve nonsmooth optimization problems. This nonsmoothness brings a low-dimensional structure to the optimal solutions. In this paper, we propose a randomized proximal gradient method harnessing this underlying structure. We introduce two key components: i) a random subspace proximal gradient algori

A. Bondar, E. Borisova, A. Buzulutskov, E. Frolov

Proportional electroluminescence (EL) in noble gases is used in two-phase detectors for dark matter search to record ionization signals in the gas phase induced by particle scattering in the liquid phase (S2 signals). In this work, the EL pulse-shapes in a two-phase argon detector have for the first time been studied systematically in a wide range of reduced

Jinwoo Ahn, Seungjin Lee, Jinhoon Lee, Yungwoo Ko

This paper demonstrates that SSDs, which perform device-level versioning, can be exposed to data tampering attacks when the retention time of data is less than the malware's dwell time. To deal with that threat, we propose SGX-SSD, a SGX-based versioning SSD which selectively preserves file history based on the given policy. The proposed system adopts Intel

Eva Löcherbach, Pierre Monmarché

We study a stochastic system of interacting neurons and its metastable properties. The system consists of $N$ neurons, each spiking randomly with rate depending on its membrane potential. At its spiking time, the neuron potential is reset to $0$ and all other neurons receive an additional amount $h/N$ of potential. In between successive spike times, each neu

A. Mikhalchan, J. J. Vilatela

This review summarizes progress on structural composites with carbon nanotube fibres. It starts by analyzing their development towards a macroscopic ensemble of elongated and aligned crystalline domains, alongside the evolution of the structure of traditional high-performance fibres. Literature on tensile properties suggests that there are two emerging grade

Kai Yang, Yong Zhou, Zhanpeng Yang, Yuanming Shi

Given the fast growth of intelligent devices, it is expected that a large number of high-stake artificial intelligence (AI) applications, e.g., drones, autonomous cars, tactile robots, will be deployed at the edge of wireless networks in the near future. As such, the intelligent communication networks will be designed to leverage advanced wireless techniques

N. Boaretto, J. Almenara, A. Mikhalchan, R. Marcilla

There is increasing interest in materials that combine energy-storing functions with augmented mechanical properties, ranging from flexibility in bending to stretchability to structural properties. In the case of lithium-ion batteries, these mechanical functions could enable their integration in emerging technologies such as wearable, free-form electronics a

I. Yildirim, E. Basar, I. Altunbas

In this work, we propose a new multiple-input multiple-output (MIMO) concept, which is called coordinate interleaved orthogonal design with media-based modulation (CIOD-MBM). The proposed two novel CIOD-MBM schemes provide improved data rates as well as diversity gain while enabling hardware simplicity using a single radio frequency (RF) chain. Moreover, usi

Morgan Görtz, Gustav Kettil, Axel Målqvist, Andreas Mark

Fiber network modeling can be used for studying mechanical properties of paper. The individual fibers and the bonds in-between constitute a detailed representation of the material. However, detailed microscale fiber network models must be resolved with efficient numerical methods. In this work, a numerical multiscale method for discrete network models is pro

Kei Nakagawa, Shuhei Noma, Masaya Abe

The problem of finding the optimal portfolio for investors is called the portfolio optimization problem. Such problem mainly concerns the expectation and variability of return (i.e., mean and variance). Although the variance would be the most fundamental risk measure to be minimized, it has several drawbacks. Conditional Value-at-Risk (CVaR) is a relatively

Tsunehide Kuroki

In the previous papers, it is pointed out that a supersymmetric double-well matrix model corresponds to a two-dimensional type IIA superstring theory on a Ramond-Ramond background at the level of correlation functions. This was confirmed by agreement between their planar correlation functions. The supersymmetry in the matrix model corresponds to the target s

Andrea Meo, Wasan Pantasri, Wassana Daeng-am, Samuel E. Rannala

Heat assisted magnetic recording (HAMR) technology represents the most promising candidate to replace the current perpendicular recording paradigm to achieve higher storage densities. To better understand HAMR dynamics in granular media we need to describe accurately the magnetisation dynamics up to temperatures close to the Curie point. To this end we propo

V. V. Mikhailenko, V. S. Mikhailenko, Hae June Lee

The stability theory of the inductively coupled plasma (ICP) is developed for the case when the electron quiver velocity in RF wave is of the order of or is larger than the electron thermal velocity. The theory predicts the existence the instabilities of the ICP which are driven by the current formed in the skin layer by the accelerated electrons, which move

Shufei Zhang, Zhuang Qian, Kaizhu Huang, Jimin Xiao

Generative adversarial networks (GANs) are powerful generative models, but usually suffer from instability and generalization problem which may lead to poor generations. Most existing works focus on stabilizing the training of the discriminator while ignoring the generalization properties. In this work, we aim to improve the generalization capability of GANs

Yiguang Liu

In this paper, complex-order derivative and integral filters are proposed, which are consistent with the filters with fractional derivative and integral orders. Compared with the filters designed only with real orders, complex order filters can reveal more details of input signals, and this can benefit a large number of tasks. The tremendous effect of the pr

Wangchunshu Zhou, Tao Ge, Ke Xu, Furu Wei

In this paper, we introduce DropHead, a structured dropout method specifically designed for regularizing the multi-head attention mechanism, which is a key component of transformer, a state-of-the-art model for various NLP tasks. In contrast to the conventional dropout mechanisms which randomly drop units or connections, the proposed DropHead is a structured

Nan Liu, Xuefan Niu, Yuxin Liu, Qinghua Zhang

Constructing heterostructures of a topological insulator (TI) with an undoped magnetic insulator (MI) is a clean and versatile approach to break the time-reversible symmetry in the TI surface states. Despite a lot of efforts, the strength of interfacial magnetic proximity effect (MPE) is still too weak to achieve the quantum anomalous Hall effect and many ot

Filippo Giubileo, Maurizio Passacantando, Francesca Urban, Alessandro Grillo

InSb nanowire arrays with different geometrical parameters, diameter and pitch, are fabricated by top-down etching process on Si(100) substrates. Field emission properties of InSb nanowires are investigated by using a nano-manipulated tungsten probe-tip as anode inside the vacuum chamber of a scanning electron microscope. Stable field emission current is rep

Fadi Philo

The classical Biot's theory provides the foundation of a fully dynamic poroelasticity model describing the propagation of elastic waves in fluid-saturated media. Multiple network poroelastic theory (MPET) takes into account that the elastic matrix (solid) can be permeated by one or several ($n\ge1$) superimposed interacting single fluid networks of possibly

Shuailiang Zhang, Hai Zhao, Junru Zhou

For natural language understanding tasks, either machine reading comprehension or natural language inference, both semantics-aware and inference are favorable features of the concerned modeling for better understanding performance. Thus we propose a Semantics-Aware Inferential Network (SAIN) to meet such a motivation. Taking explicit contextualized semantics

Chintamani Pai, Ankush Bhaskar, Vaibhav Rawoot

In this paper, we investigate the ongoing dynamics of COVID-19 in India after its emergence in Wuhan, China in December 2019. We discuss the effect of nationwide lockdown implemented in India on March 25, 2020 to prevent the spread of COVID-19. Susceptible-Exposed-Infectious-Recovered (SEIR) model is used to forecast active COVID-19 cases in India considerin

Yu. L. Bolotin, A. V. Tur, V. V. Yanovsky

The traditional formulation of the ultimate goal of physics (in the narrower sense of axiomatic theory) involves the derivation of physical laws from first principles. Though, such option doesn't make things easier since the task of the first principles finding is not less complicated versus to the original problem. The alternative path for understanding the

Yuanzhong Xu, HyoukJoong Lee, Dehao Chen, Hongjun Choi

In data-parallel synchronous training of deep neural networks, different devices (replicas) run the same program with different partitions of the training batch, but weight update computation is repeated on all replicas, because the weights do not have a batch dimension to partition. This can be a bottleneck for performance and scalability in typical languag

Alam Zaib, Tarig Ballal, Shahid Khattak, Tareq Y. Al-Naffouri

Linear discriminant analysis (LDA) based classifiers tend to falter in many practical settings where the training data size is smaller than, or comparable to, the number of features. As a remedy, different regularized LDA (RLDA) methods have been proposed. These methods may still perform poorly depending on the size and quality of the available training data

Byungik Ahn

Understanding the human brain is the biggest challenge for scientists in the twenty-first century. The Hodgkin-Huxley (HH) model is one of the most successful mathematical models for bio-realistic simulations of the brain. However, the simulation of HH neurons involves complex computation, which makes the implementation of large-scale brain networks difficul

Yoichi Nishiyama

As an alternative to the well-known methods of "chaining" and "bracketing" that have been developed in the study of random fields, a new method, which is based on a stochastic maximal inequality derived by using the Taylor expansion, is presented. The inequality dealing with finite-dimensional discrete-time martingales is pulled up to infinite-dimensional on

Stephan Zheng, Alexander Trott, Sunil Srinivasa, Nikhil Naik

Tackling real-world socio-economic challenges requires designing and testing economic policies. However, this is hard in practice, due to a lack of appropriate (micro-level) economic data and limited opportunity to experiment. In this work, we train social planners that discover tax policies in dynamic economies that can effectively trade-off economic equali

Henry Krumb, Sofie Hofmann, David Kügler, Ahmed Ghazy

Purpose: Electromagnetic Tracking (EMT) can potentially complement fluoroscopic navigation, reducing radiation exposure in a hybrid setting. Due to the susceptibility to external distortions, systematic error in EMT needs to be compensated algorithmically. Compensation algorithms for EMT in guidewire procedures are only practical in an online setting. Method

Lin-Lin Wang

Expansive open Fermi arcs covering most of the surface Brillouin zone (SBZ) are desirable for detection and control of many topological phenomena, but so far has been only reported for Kramers-Weyl points, or unconventional chiral fermions, pinned at time-reversal invariant momentum in chiral materials. Here using first-principles band structure calculations

Haobo Yan, Yuan Zhong, Yu-Xiao Liu, Kei-ichi Maeda

In this work, kink-antikink collision in a two-dimensional Lorentz-violating $\phi^4$ model is considered. It is shown that the Lorentz-violating term in the proposed model does not affect the structure of the linear perturbation spectrum of the standard $\phi^4$ model, and thus there exists only one vibrational mode. The Lorentz-violating term impacts, howe

Manish Shukla, Rajan M A, Sachin Lodha, Gautam Shroff

Contact tracing is a very powerful method to implement and enforce social distancing to avoid spreading of infectious diseases. The traditional approach of contact tracing is time consuming, manpower intensive, dangerous and prone to error due to fatigue or lack of skill. Due to this there is an emergence of mobile based applications for contact tracing. The

Ursula Laa, Dianne Cook, Andreas Buja, German Valencia

Multivariate data is often visualized using linear projections, produced by techniques such as principal component analysis, linear discriminant analysis, and projection pursuit. A problem with projections is that they obscure low and high density regions near the center of the distribution. Sections, or slices, can help to reveal them. This paper develops a

Niraj Aryal, Xilian Jin, Q. Li, A. M. Tsvelik

We use first-principles methods to reveal that in ZrTe$_5$, a layered van der Waals material like graphite, atomic displacements corresponding to five of the six zone-center A$_g$ (symmetry-preserving) phonon modes can drive a topological phase transition from strong to weak topological insulator with a Dirac semimetal state emerging at the transition, givin

S. W. Lovesey, D. D. Khalyavin

Cubic double perovskites that host heavy ions with total angular momentum J = 2 can exhibit a singular magnetic state epitomized by a lone octupole and bulk ferro-type magnetism. It exists in the Chen - Balents Hamiltonian with a quadrupole interaction and competing exchange forces between the ions. Our symmetry inspired analysis mirrors the Dzyaloshinskii -

Qianqian Wang, Xiaowei Zhou, Bharath Hariharan, Noah Snavely

Recent research on learned visual descriptors has shown promising improvements in correspondence estimation, a key component of many 3D vision tasks. However, existing descriptor learning frameworks typically require ground-truth correspondences between feature points for training, which are challenging to acquire at scale. In this paper we propose a novel w

Nicolas Brigouleix, Daniel Han-Kwan

We study in this paper the non-relativistic limit from Vlasov-Maxwell to Vlasov-Poisson, which corresponds to the regime where the speed of light is large compared to the typical velocities of particles. In contrast with \cite{Asano-Ukai-86-SMA}, \cite{Degond-86-MMAS}, \cite{Schaeffer-86-CMP} which handle the case of classical solutions, we consider measure-

Ali Zamani

We introduce the $\lambda$-mean transform $M_{\lambda}(T)$ of a Hilbert space operator $T$ as an extension of some operator transforms based on the Duggal transform $T^D$ by $M_{\lambda}(T) := \lambda T + (1-\lambda)T^D$, and present some of its essentially properties. Among other things, we obtain estimates for the operator norm and numerical radius of the

Ismail Bilgen, Goktug Guvercin, Islem Rekik

Autism spectrum disorder (ASD) affects the brain connectivity at different levels. Nonetheless, non-invasively distinguishing such effects using magnetic resonance imaging (MRI) remains very challenging to machine learning diagnostic frameworks due to ASD heterogeneity. So far, existing network neuroscience works mainly focused on functional (derived from fu

Shuyuan Yu, Han Zhou, Shaoyi Peng, Hussam Amrouch

In this paper, we propose a novel accuracy-reconfigurable stochastic computing (ARSC) framework for dynamic reliability and power management. Different than the existing stochastic computing works, where the accuracy versus power/energy trade-off is carried out in the design time, the new ARSC design can change accuracy or bit-width of the data in the run-ti

Mahfouth Alghamdi, Christoph Treude, Markus Wagner

Automatic text summarisation has drawn considerable interest in the area of software engineering. It is challenging to summarise the activities related to a software project, (1) because of the volume and heterogeneity of involved software artefacts, and (2) because it is unclear what information a developer seeks in such a multi-document summary. We present