February 2019 arXiv papers — page 31

Rashi Jain, S. Vig, S. K. Ghosh

Globular clusters represent stellar laboratories where observations can be used to validate models of stellar evolution. In this study, we put forth new ultraviolet (UV) photometric results of stars in the Galactic globular cluster NGC 2808. NGC 2808 is known to host multiple stellar populations that include at least four distinct groups of horizontal Branch

Thomas Creutzig, Tianshu Liu, David Ridout, Simon Wood

The unitary $N = 2$ superconformal minimal models have a long history in string theory and mathematical physics, while their non-unitary (and logarithmic) cousins have recently attracted interest from mathematicians. Here, we give an efficient and uniform analysis of all these models as an application of a type of Schur-Weyl duality, as it pertains to the we

Sanghyuk Moon, Woong-Tae Kim, Eve C. Ostriker

We present an accurate and efficient method to calculate the gravitational potential of an isolated system in three-dimensional Cartesian and cylindrical coordinates subject to vacuum (open) boundary conditions. Our method consists of two parts: an interior solver and a boundary solver. The interior solver adopts an eigenfunction expansion method together wi

Abhisek Saha, Soma Sanyal

We study the vorticity patterns in relativistic heavy ion collisions with respect to the collision energy. The collision energy is related to the chemical potential used in the thermal - statistical models that assume approximate chemical equilibrium after the relativistic collision. We use the multiphase transport model (AMPT) to study the vorticity in the

A. N. Ramaprakash, C. V. Rajarshi, H. K. Das, P. Khodade

We present the design and performance of RoboPol, a four-channel optical polarimeter operating at the Skinakas Observatory in Crete, Greece. RoboPol is capable of measuring both relative linear Stokes parameters $q$ and $u$ (and the total intensity $I$) in one sky exposure. Though primarily used to measure the polarization of point sources in the R-band, the

Farhad Shahrokhi

Let ${H}=(V, {E})$ be a hypergraph on the vertex set $V$ and edge set ${E}\subseteq 2^V$. We show that number of distinct {\it traces} on any $k-$ subset of $V$, is most $k.{\hat \alpha}(H)$, where ${\hat \alpha}(H)$ is the {\it degeneracy} of $H$. The result significantly improves/generalizes some of related results. For instance, the $vc$ dimension $H$ (or

Valery Ortiz Jimenez, Vijaysankar Kalappattil, Tatiana Eggers, Manuel Bonilla

Two-dimensional (2D) van der Waals ferromagnetic materials are emerging as promising candidates for applications in ultra-compact spintronic nanodevices, nanosensors, and information storage. Our recent discovery of the strong room temperature ferromagnetism in single layers of VSe2 grown on graphite or MoS2 substrate has opened new opportunities to explore

Muneya Matsui, Rasmus Søndergaard Pedersen

We provide new, mild conditions for strict stationarity and ergodicity of a class of BEKK processes. By exploiting that the processes can be represented as multivariate stochastic recurrence equations, we characterize the tail behavior of the associated stationary laws. Specifically, we show that the each component of the BEKK processes is regularly varying

S. V. Gusev

In this work we consider monoids as algebras with an associative binary operation and the nullary operation that fixes the identity element. We found an example of two varieties of monoids with finite subvariety lattices such that their join covers one of them and has a continuum cardinality subvariety lattice that violates the ascending chain condition and

Moacir Aloisio, Silas L. Carvalho, César R. de Oliveira

Stimulated by the category theorems of Eisner and Ser\'eny in the setting of unitary and isometric $C_0$-semigroups on separable Hilbert spaces, we prove category theorems for Schr\"odinger semigroups. Specifically, we show that, to a given class of Schr\"{o}dinger semigroups, Baire generically the semigroups are strongly stable but not exponentially stable.

Suhas S. Jain, Ken Kamrin, Ali Mani

Soft solids in fluids find wide range of applications in science and engineering, especially in the study of biological tissues and membranes. In this study, an Eulerian finite volume approach has been developed to simulate fully resolved incompressible hyperelastic solids immersed in a fluid. We have adopted the recently developed reference map technique (R

Min Young Ha, Tae Jun Yoon, Tsvi Tlusty, YongSeok Jho

The Supercritical Fluid (SCF) is known to exhibit salient dynamic and thermodynamic crossovers and inhomogeneous molecular distribution. But the question as to what basic physics underlies these microscopic and macroscopic anomalies remains open. Here, using an order parameter extracted by machine learning, the fraction of gas-like (or liquid-like) molecules

Long Cheng, Hans Liljestrand, Thomas Nyman, Yu Tsung Lee

Data-oriented attacks manipulate non-control data to alter a program's benign behavior without violating its control-flow integrity. It has been shown that such attacks can cause significant damage even in the presence of control-flow defense mechanisms. However, these threats have not been adequately addressed. In this SoK paper, we first map data-oriented

E. V. Gotthelf, J. P. Halpern, J. A. J. Alford, T. Mihara

We present the earliest X-ray observations of the 2018 outburst of XTE J1810-197, the first outburst since its 2003 discovery as the prototypical transient and radio-emitting anomalous X-ray pulsar (AXP). The Monitor of All-sky X-ray Image (MAXI) detected XTE J1810-197 immediately after a November 20-26 visibility gap, contemporaneous with its reactivation a

Xiaotao Li, Xuejing Chen, Fangfang Fan, Li Ning

The present review presents multiple techniques in which ocular assessments may serve as a noninvasive approach for the early diagnoses of various cognitive and psychiatric disorders, such as Alzheimer's disease (AD), autism spectrum disorder (ASD), schizophrenia (SZ), and major depressive disorder (MDD). Real-time ocular responses are tightly associated wit

Misako Tatsuuma, Akimasa Kataoka, Hidekazu Tanaka

Comets are thought to have information about the formation process of our solar system. Recently, detailed information about comet 67P/Churyumov-Gerasimenko has been found by a spacecraft mission Rosetta. It is remarkable that its tensile strength was estimated. In this paper, we measure and formulate the tensile strength of porous dust aggregates using nume

X. Xu, M. Tan, J. Wu, T. Nguyen

We demonstrate a photonic radio frequency (RF) transversal filter based on an integrated optical micro-comb source featuring a record low free spectral range of 49 GHz yielding 80 micro-comb lines across the C-band. This record-high number of taps, or wavelengths for the transversal filter results in significantly increased performance including a QRF factor

Sang-Woo Lee, Tong Gao, Sohee Yang, Jaejun Yoo

Answerer in Questioner's Mind (AQM) is an information-theoretic framework that has been recently proposed for task-oriented dialog systems. AQM benefits from asking a question that would maximize the information gain when it is asked. However, due to its intrinsic nature of explicitly calculating the information gain, AQM has a limitation when the solution s

Lou Zhao, Jiajia Guo, Zhiqiang Wei, Derrick Wing Kwan Ng

This paper proposes a distributed hybrid millimeter wave (mmWave) scheme to exploit the structure of a Densely Deployed Distributed (DDD) small-cell-base-stations (SBSs) system for serving multiple users in a geographic area. Both the SBSs and the users are equipped with full access hybrid architectures with multi-antenna arrays and multiple radio frequency

Ya Meng, Feng Mei, Gang Chen, Suotang Jia

We present a protocol to implement discrete-time quantum walks and simulate topological insulator phases in cavity-based quantum networks, where the single photon is the quantum walker and the cavity input-output process is employed to realize the state-dependent translation operation. Different topological phases can be simulated through tuning the single-p

Kai Lin, Wei-Liang Qian

In this paper, we provide a comprehensive survey of possible applications of the matrix method for black hole quasinormal modes. The proposed algorithm can generally be applied to various background metrics, and in particular, it accommodates for both analytic and numerical forms of the tortoise coordinates, as well as black hole spacetimes. Our discussions

Nigel Higson, Zelin Yi

The purpose of this article is to study Ezra Getzler's approach to the Atiyah-Singer index theorem from the perspective of Alain Connes' tangent groupoid. We shall construct a "rescaled" spinor bundle on the tangent groupoid, define a convolution operation on its smooth, compactly supported sections, and explain how the algebra so-obtained incorporates Getzl

Yuichi Kitamura, Jörg Stoye

We bound features of counterfactual choices in the nonparametric random utility model of demand, i.e. if observable choices are repeated cross-sections and one allows for unrestricted, unobserved heterogeneity. In this setting, tight bounds are developed on counterfactual discrete choice probabilities and on the expectation and c.d.f. of (functionals of) cou

Aswin Raghavan, Jesse Hostetler, Sek Chai

Our research is focused on understanding and applying biological memory transfers to new AI systems that can fundamentally improve their performance, throughout their fielded lifetime experience. We leverage current understanding of biological memory transfer to arrive at AI algorithms for memory consolidation and replay. In this paper, we propose the use of

Arturas Dubickas, Igor Pritsker

Weighted Fekete points are defined as those that maximize the weighted version of the Vandermonde determinant over a fixed set. They can also be viewed as the equilibrium distribution of the unit discrete charges in an external electrostatic field. While these points have many applications, they are very difficult to find explicitly, and are only known in a

Min Zhao, Jie Chen, Zhe He

Spectral unmixing is an important and challenging problem in hyperspectral data processing. This topic has been extensively studied and a variety of unmixing algorithms have been proposed in the literature. However, the lack of publicly available dataset with ground-truth makes it difficult to evaluate and compare the performance of unmixing algorithms in a

Jingyu Liu, Qing Zhao, Ning Wu

We investigate exciton transport through one-dimensional molecular aggregates interacting strongly with a cavity mode. Unlike several prior theoretical studies treating the monomers as simple two-level systems, exciton-vibration coupling is explicitly included in the description of open quantum dynamics of the system. In the framework of the Holstein-Tavis-C

Mauricio Ayala-Rincón, Maribel Fernández, Daniele Nantes-Sobrinho

We propose a new axiomatisation of the alpha-equivalence relation for nominal terms, based on a primitive notion of fixed-point constraint. We show that the standard freshness relation between atoms and terms can be derived from the more primitive notion of permutation fixed-point, and use this result to prove the correctness of the new $\alpha$-equivalence

Feng Mei, Ya-Fei Yu, Xun-Li Feng, Zhi-Ming Zhang

We propose a scheme for entanglement distribution among different single atoms trapped in separated cavities. In our scheme, by reflecting an input coherent optical pulse from a cavity with a single trapped atom, a controlled phase-shift gate between the atom and the coherent optical pulse is achieved. Based on this gate and homodyne detection, we construct

Yiren Wang, Fei Tian, Di He, Tao Qin

As a new neural machine translation approach, Non-Autoregressive machine Translation (NAT) has attracted attention recently due to its high efficiency in inference. However, the high efficiency has come at the cost of not capturing the sequential dependency on the target side of translation, which causes NAT to suffer from two kinds of translation errors: 1)

Tian Lin, Jiaqi Cong, Yu Zhu, Jun Zhang

Hybrid analog and digital beamforming (HBF) has recently emerged as an attractive technique for millimeter-wave (mmWave) communication systems. It well balances the demand for sufficient beamforming gains to overcome the propagation loss and the desire to reduce the hardware cost and power consumption. In this paper, the mean square error (MSE) is chosen as

Rajiv Bajpai, Devamanyu Hazarika, Kunal Singh, Sruthi Gorantla

With the multitude of companies and organizations abound today, ranking them and choosing one out of the many is a difficult and cumbersome task. Although there are many available metrics that rank companies, there is an inherent need for a generalized metric that takes into account the different aspects that constitute employee opinions of the companies. In

Masanori Yamada, Heecheol Kim, Kosuke Miyoshi, Hiroshi Yamakawa

We propose the factorized action variational autoencoder (FAVAE), a state-of-the-art generative model for learning disentangled and interpretable representations from sequential data via the information bottleneck without supervision. The purpose of disentangled representation learning is to obtain interpretable and transferable representations from data. We

Noah Stephens-Davidowitz

For $0 \leq \alpha \leq 1/2$, we show an algorithm that does the following. Given appropriate preprocessing $P(\mathcal{L})$ consisting of $N_\alpha := 2^{O(n^{1-2\alpha} + \log n)}$ vectors in some lattice $\mathcal{L} \subset \mathbb{R}^n$ and a target vector $\boldsymbol{t}\in \mathbb{R}^n$, the algorithm finds $\boldsymbol{y} \in \mathcal{L}$ such that $

Ricardo G. Landim, Thomas G. Rizzo

In this paper we show that the interaction between new light dark matter mediators and the SM particles can be naturally suppressed if one employs a single, flat extra dimension (ED). In this setup, the SM fields are localized in a finite width `fat' brane, similar to models of Universal Extra Dimensions (UED), while DM, in turn, is confined to a thin brane

Feng Mei, Jia-Bin You, Dan-Wei Zhang, X. C. Yang

We propose a simple method to simulate and detect topological insulators with cold atoms trapped in a one-dimensional bichromatic optical lattice subjected to a time-periodic modulation. The tight-binding form of this shaken system is equivalent to the periodically driven Aubry-Andre model. We demonstrate that this model can be mapped into a two-dimensional

Gavin Weiguang Ding, Kry Yik Chau Lui, Xiaomeng Jin, Luyu Wang

Neural networks are vulnerable to small adversarial perturbations. Existing literature largely focused on understanding and mitigating the vulnerability of learned models. In this paper, we demonstrate an intriguing phenomenon about the most popular robust training method in the literature, adversarial training: Adversarial robustness, unlike clean accuracy,

Xuan Cao, Shaojun Zhang

Covariance estimation and selection for multivariate datasets in a high-dimensional regime is a fundamental problem in modern statistics. Gaussian graphical models are a popular class of models used for this purpose. Current Bayesian methods for inverse covariance matrix estimation under Gaussian graphical models require the underlying graph and hence the or

Shunsuke C. Furuya, Masaaki Nakamura

We discuss the polarization amplitude of quantum spin systems in one dimension. In particular, we closely investigate it in gapless phases of those systems based on the two-dimensional conformal field theory. The polarization amplitude is defined as the ground-state average of a twist operator which induces a large gauge transformation attaching the unit amo

Lawrence H. Harper, Gene B. Kim, Neal Livesay

Over 50 years ago, Rota posted the following celebrated `Research Problem': prove or disprove that the partial order of partitions on an $n$-set (i.e., the refinement order) is Sperner. A counterexample was eventually discovered by Canfield in 1978. However, Harper and Kim recently proved that a closely related order --- i.e., the refinement order on the sym

Jia Wang, Xia-Ji Liu, Hui Hu

We theoretically investigate the quasiparticle (polaron) properties of an impurity immersing in a Bose-Einstein condensate with equal Rashba and Dresselhaus spin-orbit coupling at zero temperature. In the presence of spin-orbit coupling, all bosons can condense into a single plane-wave state with finite momentum, and the corresponding excitation spectrum sho

Xiaoxia Zhang, Youjun Lu

Radiative efficiency is an important physical parameter that describes the fraction of accretion material converted to radiative energy for accretion onto massive black holes (MBHs). With the simplest So{\l}tan argument, the radiative efficiency of MBHs can be estimated by matching the mass density of MBHs in the local universe to the accreted mass density b

Toni Annala

The purpose of this note is to extend some classical results on quasi-projective schemes to the setting of derived algebraic geometry. Namely, we want to show that any vector bundle on a derived scheme admitting an ample line bundle can be twisted to be globally generated. Moreover, we provide a presentation of $K^0(X)$ as the Grothendieck group of vector bu

Cody B. Stockdale

Two proofs of a weighted weak-type $\left(1,\ldots,1;\frac{1}{m}\right)$ estimate for multilinear Calder\'on-Zygmund operators are given. The ideas are motivated by different proofs of the classical weak-type $(1,1)$ estimate for Calder\'on-Zygmund operators. One proof uses the Calder\'on-Zygmund decomposition, and the other proof is motivated by ideas of Na

Jinyin Chen, Jian Zhang, Xuanheng Xu, Chengbo Fu

Predicting the potential relations between nodes in networks, known as link prediction, has long been a challenge in network science. However, most studies just focused on link prediction of static network, while real-world networks always evolve over time with the occurrence and vanishing of nodes and links. Dynamic network link prediction thus has been att

Nikolett Német, Alexander Carmele, Scott Parkins, Andreas Knorr

Using the example of the Jaynes-Cummings model, we present a comparison between time-delayed coherent feedback mediated by reservoirs with continuous and discrete mode structures and work out their qualitative differences. In contrast to the discrete-mode case, the continuous-mode case results in the well-known single-delay dynamics which can, e.g., stabiliz

Ting-Yao Hsu, Yen-Chia Hsu, Ting-Hao 'Kenneth' Huang

A significant body of research in Artificial Intelligence (AI) has focused on generating stories automatically, either based on prior story plots or input images. However, literature has little to say about how users would receive and use these stories. Given the quality of stories generated by modern AI algorithms, users will nearly inevitably have to edit

Ryosuke Doi, Takao Nakagawa, Naoki Isobe, Shunsuke Baba

We present a systematic study of the 3.0 um H2O ice and the 3.4 um aliphatic carbon absorption features toward 48 local ultraluminous infrared galaxies (ULIRGs) using spectra obtained by the AKARI Infrared Camera to investigate the UV environment in their star-forming regions. All the ULIRGs in our sample exhibit a ratio of optical depth of H2O ice to silica

Jawaher Alsobaie

The study of the Milky Way structure is vital importance for a better understanding of the universe. This study digs deeper into the structure of Milky Way Galaxys with emphasis to its spiral arms. Multiple data sources were sought including the NASA websites. As found out, the Milky Way is a disk shaped galaxy composed of four spiral arms, two large and the

Frederic Bapst, Wahid Bhimji, Paolo Calafiura, Heather Gray

The reconstruction of charged particles will be a key computing challenge for the high-luminosity Large Hadron Collider (HL-LHC) where increased data rates lead to large increases in running time for current pattern recognition algorithms. An alternative approach explored here expresses pattern recognition as a Quadratic Unconstrained Binary Optimization (QU

Paul M. Chesler, Ramesh Narayan, Erik Curiel

We study black holes produced by the collapse of a spherically symmetric charged scalar field in asymptotically flat space. We employ a late time expansion and show decaying fluxes of radiation through the event horizon imply the black hole must contain a null singularity on the Cauchy horizon and a central spacelike singularity.

Hideaki Iwasawa, Pavel Dudin, Kyosuke Inui, Takahiko Masui

The electron dynamics in the CuO chains has been elusive in Y-Ba-Cu-O cuprate systems by means of standard angle-resolved photoemission spectroscopy (ARPES); cleaved sample exhibits areas terminated by both CuO-chain or BaO layers, and the size of a typical beam results in ARPES signals that are superposed from both terminations. Here, we employ spatially-re

Christopher K. Wikle

Spatio-temporal data are ubiquitous in the agricultural, ecological, and environmental sciences, and their study is important for understanding and predicting a wide variety of processes. One of the difficulties with modeling spatial processes that change in time is the complexity of the dependence structures that must describe how such a process varies, and

Chee Kong Lee, Mojdeh Shikhali Najafabadi, Daniel Schumayer, Leong Chuan Kwek

Quantum entanglement is usually considered a fragile quantity and decoherence through coupling to an external environment, such as a thermal reservoir, can quickly destroy the entanglement resource. This doesn't have to be the case and the environment can be engineered to assist in the formation of entanglement. We investigate a system of qubits and higher d

Yongxin Chen, Giovanni Conforti, Tryphon T. Georgiou, Luigia Ripani

We consider the problem to identify the most likely flow in phase space, of (inertial) particles under stochastic forcing, that is in agreement with spatial (marginal) distributions that are specified at a set of points in time. The question raised generalizes the classical Schrodinger Bridge Problem (SBP) which seeks to interpolate two specified end-point m

Geoff Langdale, Daniel Lemire

JavaScript Object Notation or JSON is a ubiquitous data exchange format on the Web. Ingesting JSON documents can become a performance bottleneck due to the sheer volume of data. We are thus motivated to make JSON parsing as fast as possible. Despite the maturity of the problem of JSON parsing, we show that substantial speedups are possible. We present the fi

Menachem Stern, Matthew B. Pinson, Arvind Murugan

We contrast the distinct frameworks of materials design and physical learning in creating elastic networks with desired stable states. In design, the desired states are specified in advance and material parameters can be optimized on a computer with this knowledge. In learning, the material physically experiences the desired stable states in sequence, changi

Natalia B. Janson, Christopher J. Marsden

Optimization is finding the best solution, which mathematically amounts to locating the global minimum of some cost function. Optimization is traditionally automated with digital or quantum computers, each having their limitations and none guaranteeing an optimal solution. Here, we conceive a principle behind optimization based on delay-induced bifurcations,

Joel Hutchinson, Frank Marsiglio

The extended Hubbard model can host s-wave, d-wave and p-wave superconducting phases depending on the values of the on-site and nearest-neighbour interactions. Upon detailed examination of the free energy functional of the gap in this model, we show that these symmetries are often dependent on temperature. The critical points of this functional are constrain

A. Mello, C. S. Kubrusly

The residual spectrum of a power bounded operator lies in the open unit disk.

Christian M. Fuchs, Nadia M. Murillo, Aske Plaat, Erik van der Kouwe

Miniaturized satellites are currently not considered suitable for critical, high-priority, and complex multi-phased missions, due to their low reliability. As hardware-side fault tolerance (FT) solutions designed for larger spacecraft can not be adopted aboard very small satellites due to budget, energy, and size constraints, we developed a hybrid FT-approac

Shun Takeuchi, Takahiro Saito

Early fault detection using instrumented sensor data is one of the promising application areas of machine learning in industrial facilities. However, it is difficult to improve the generalization performance of the trained fault-detection model because of the complex system configuration in the target diagnostic system and insufficient fault data. It is not

Shun Takeuchi, Takuya Nishino, Takahiro Saito, Isamu Watanabe

In industrial systems, certain process variables that need to be monitored for detecting faults are often difficult or impossible to measure. Soft sensor techniques are widely used to estimate such difficult-to-measure process variables from easy-to-measure ones. Soft sensor modeling requires training datasets including the information of various states such

Gang Chen, Jintao Cui, Liwei Xu

The quad-curl problem arises in magnetohydrodynamics, inverse electromagnetic scattering and transform eigenvalue problems. In this paper we investigate a hybridizable discontinuous Galerkin method to solve the quad-curl problem based on a mixed formulation. The divergence-free condition is enforced by introducing a Lagrange multiplier into the system. The a

Oscar P. Bruno, Liwei Xu, Tao Yin

We present a novel approach for the numerical solution of problems of elastic scattering by open arcs in two dimensions. Our methodology relies on the composition of weighted versions of the classical operators associated with Dirichlet and Neumann boundary conditions in conjunction with a certain "open-arc elastic Calderón relation" whose validity i

Le Zheng, Marco Lops, Yonina C. Eldar, Xiaodong Wang

Increased amounts of bandwidth are required to guarantee both high-quality/high-rate wireless services (4G and 5G) and reliable sensing capabilities such as automotive radar, air traffic control, earth geophysical monitoring and security applications. Therefore, co-existence between radar and communication systems using overlapping bandwidths has been a prim

Stephen D. Farnham, Lixin Shen, Bruce W. Suter

In this paper, we consider approximations of principal component projection (PCP) without explicitly computing principal components. This problem has been studied in several recent works. The main feature of existing approaches is viewing the PCP matrix as a matrix function. This underlying function is the composition of a step function with a rational funct

Joel A. Tropp, Alp Yurtsever, Madeleine Udell, Volkan Cevher

This paper argues that randomized linear sketching is a natural tool for on-the-fly compression of data matrices that arise from large-scale scientific simulations and data collection. The technical contribution consists in a new algorithm for constructing an accurate low-rank approximation of a matrix from streaming data. This method is accompanied by an a

Yaser Ghaedsharaf, Milad Siami, Christoforos Somarakis, Nader Motee

We investigate notions of network centrality in terms of the underlying coupling graph of the network, structure of exogenous uncertainties, and communication time-delay. Our focus is on time-delay linear consensus networks, where uncertainty is modeled by structured additive noise on the dynamics of agents. The centrality measures are defined using the $\ma

J. F. van Diejen, E. Emsiz

We prove the Plancherel formula for a four-parameter family of discrete Fourier transforms and their multivariate generalizations stemming from corresponding generalized Schur polynomials. For special choices of the parameters, this recovers the sixteen classic discrete sine- and cosine transforms DST-1,...,DST-8 and DCT-1,...,DCT-8, as well as recently stud

Sven-Erik Ekström

It is known that the generating function $f$ of a sequence of Toeplitz matrices $\{T_n(f)\}_n$ may not describe the asymptotic distribution of the eigenvalues of $T_n(f)$ if $f$ is not real. In this paper, we assume as a working hypothesis that, if the eigenvalues of $T_n(f)$ are real for all $n$, then they admit an asymptotic expansion of the same type as c

Wentao Cai, Dongdong He, Kejia Pan

In this paper, we propose a linearized finite element method (FEM) for solving the cubic nonlinear Schrödinger equation with wave operator. In this method, a modified leap-frog scheme is applied for time discretization and a Galerkin finite element method is applied for spatial discretization. We prove that the proposed method keeps the energy conservation i

Jure Slak, Gregor Kosec

This paper considers a numerical solution of a linear elasticity problem, namely the Cauchy-Navier equation, using a strong form method based on a local Weighted Least Squares (WLS) approximation. The main advantage of the employed numerical approach, also referred to as a Meshless Local Strong Form method, is its generality in terms of approximation setup a

Jean-Paul Chehab, Marcos Raydan

We extend the geometrical inverse approximation approach for solving linear least-squares problems. For that we focus on the minimization of $1-\cos(X(A^TA),I)$, where $A$ is a given rectangular coefficient matrix and $X$ is the approximate inverse. In particular, we adapt the recently published simplified gradient-type iterative scheme MinCos to the least-s

Xue-lei Lin, Pin Lyu, Michael K. Ng, Hai-Wei Sun

In this paper, a second order finite difference scheme is investigated for time-dependent one-side space fractional diffusion equations with variable coefficients. The existing schemes for the equation with variable coefficients have temporal convergence rate no better than second order and spatial convergence rate no better than first order, theoretically.

Xiangrong Li, Nan Qi, Yufeng Nie, Weiwei Zhang

The properties and applications of superconvergence on size-guaranteed Delaunay triangulation generated by bubble placement method (BPM), are studied in this paper. First, we derive a mesh condition that the difference between the actual side length and the desired length $h$ is as small as ${\cal O}(h^{1+α})$ $(α>0)$. Second, the superconvergence estimation

Daniel Jodlbauer, Ulrich Langer, Thomas Wick

In this work, we present a framework for the matrix-free solution to a monolithic quasi-static phase-field fracture model with geometric multigrid methods. Using a standard matrix based approach within the Finite Element Method requires lots of memory, which eventually becomes a serious bottleneck. A matrix-free approach overcomes this problems and greatly r

Etika Agarwal, S. Sivaranjani, Vijay Gupta, Panos Antsaklis

We consider the problem of designing distributed controllers to ensure passivity of a large-scale interconnection of linear subsystems connected in a cascade topology. The control design process needs to be carried out at the subsystem-level with no direct knowledge of the dynamics of other subsystems in the interconnection. We present a distributed approach

Ganapati Bhat, Kunal Bagewadi, Hyung Gyu Lee, Umit Y. Ogras

The use of wearable and mobile devices for health monitoring and activity recognition applications is increasing rapidly. These devices need to maximize their accuracy and active time under a tight energy budget imposed by battery and small form-factor constraints. This paper considers energy harvesting devices that run on a limited energy budget to recogniz

Kathy Jang, Eugene Vinitsky, Behdad Chalaki, Ben Remer

Using deep reinforcement learning, we train control policies for autonomous vehicles leading a platoon of vehicles onto a roundabout. Using Flow, a library for deep reinforcement learning in micro-simulators, we train two policies, one policy with noise injected into the state and action space and one without any injected noise. In simulation, the autonomous

Yuting Zhu, Liyong Lin, Rong Su

In this paper, we propose and address the problem of supervisor obfuscation against actuator enablement attack, in a common setting where the actuator attacker can eavesdrop the control commands issued by the supervisor. We propose a method to obfuscate an (insecure) supervisor to make it resilient against actuator enablement attack in such a way that the be

Rüdiger Brecht, Werner Bauer, Alexander Bihlo, François Gay-Balmaz

We develop a variational integrator for the shallow-water equations on a rotating sphere. The variational integrator is built around a discretization of the continuous Euler-Poincaré reduction framework for Eulerian hydrodynamics. We describe the discretization of the continuous Euler-Poincaré equations on arbitrary simplicial meshes. Standard numerical test

Matthieu Bulté, Jonas Latz, Elisabeth Ullmann

In this tutorial we consider the non-linear Bayesian filtering of static parameters in a time-dependent model. We outline the theoretical background and discuss appropriate solvers. We focus on particle-based filters and present Sequential Importance Sampling (SIS) and Sequential Monte Carlo (SMC). Throughout the paper we illustrate the concepts and techniqu

Emiliano Cristiani, Elisa Iacomini

In this paper we present a new kind of model for traffic flow which couples a first-order macroscopic approach with a second-order microscopic approach, avoiding any interface or boundary conditions between them. The Euler-Godunov scheme associated to the model is conservative and it is able to reproduce typical traffic phenomena like stop & go waves.

Francisco M. Garcia, Bruno C. da Silva, Philip S. Thomas

In this paper we consider the problem of how a reinforcement learning agent tasked with solving a set of related Markov decision processes can use knowledge acquired early in its lifetime to improve its ability to more rapidly solve novel, but related, tasks. One way of exploiting this experience is by identifying recurrent patterns in trajectories obtained

Jeffrey Galkowski, Eike H. Müller, Euan A. Spence

We consider solving the exterior Dirichlet problem for the Helmholtz equation with the $h$-version of the boundary element method (BEM) using the standard second-kind combined-field integral equations. We prove a new, sharp bound on how the number of GMRES iterations must grow with the wavenumber $k$ to have the error in the iterative solution bounded indepe

Weinan E, Martin Hutzenthaler, Arnulf Jentzen, Thomas Kruse

We introduce a new family of numerical algorithms for approximating solutions of general high-dimensional semilinear parabolic partial differential equations at single space-time points. The algorithm is obtained through a delicate combination of the Feynman-Kac and the Bismut-Elworthy-Li formulas, and an approximate decomposition of the Picard fixed-point i

Jörn Sesterhenn, Amir Shahirpour

Temporal or spatial structures are readily extracted from complex data by modal decompositions like Proper Orthogonal Decomposition (POD) or Dynamic Mode Decomposition (DMD). Subspaces of such decompositions serve as reduced order models and define either spatial structures in time or temporal structures in space. On the contrary, convecting phenomena pose a

Ivo Trowitzsch, Jalil Taghia, Youssef Kashef, Klaus Obermayer

Computational auditory scene analysis is gaining interest in the last years. Trailing behind the more mature field of speech recognition, it is particularly general sound event detection that is attracting increasing attention. Crucial for training and testing reasonable models is having available enough suitable data -- until recently, general sound event d

YInjie Huang, Cong Li, Michael Georgiopoulos, Georgios C. Anagnostopoulos

We propose a new method for local distance metric learning based on sample similarity as side information. These local metrics, which utilize conical combinations of metric weight matrices, are learned from the pooled spatial characteristics of the data, as well as the similarity profiles between the pairs of samples, whose distances are measured. The main o

Gerald Handler, Andrzej Pigulski, Jadwiga Daszyńska-Daszkiewicz, Andreas Irrgang

We report an analysis of the first known Beta Cep pulsator observed by the TESS mission, the runaway star PHL 346 = HN Aqr. The star, previously known as a singly-periodic pulsator, has at least 34 oscillation modes excited, 12 of those in the g-mode domain and 22 p modes. Analysis of archival data implies that the amplitude and frequency of the dominant mod

Sirisha Rambhatla, Xingguo Li, Jineng Ren, Jarvis Haupt

We consider the decomposition of a data matrix assumed to be a superposition of a low-rank matrix and a component which is sparse in a known dictionary, using a convex demixing method. We consider two sparsity structures for the sparse factor of the dictionary sparse component, namely entry-wise and column-wise sparsity, and provide a unified analysis, encom

Rusel Cierto Trinidad, Alcides Bernardo Tello

Some people implement pattern and best practices without analyzing its efficiency on their projects. Consequently, our goal in this article is to convince software developers that it is worth to make an earnest effort to evaluate the use of best practices and software patterns. For such purpose, in this study we took a concrete case system for geographical l

Vasili K. Semenov, Yuri A. Polyakov, Sergey K. Tolpygo

Arrays of Vortex Transitional (VT) memory cells with functional density up to $1 Mbit/cm^2$ have been designed, fabricated, and successfully demonstrated. This progress is due to recent advances in design optimization and in superconductor electronics fabrication achieved at MIT Lincoln Laboratory. As a starting point, we developed a demo array of VT cells f

K. Kurita, H. Sakabayashi, R. Okazaki

To clarify the origin of the nontrivial thermoelectric properties observed in the delafossite oxide CuRhO$_2$ polycrystals, we have performed the systematic transport measurements on the single-crystalline CuRhO$_2$ samples. In the parent compound, we find a pronounced peak structure due to a phonon-drag effect in the temperature dependence of the Seebeck co

Andreas Buhr, Laura Iapichino, Mario Ohlberger, Stephan Rave

In this contribution we present a survey of concepts in localized model order reduction methods for parameterized partial differential equations. The key concept of localized model order reduction is to construct local reduced spaces that have only support on part of the domain and compute a global approximation by a suitable coupling of the local spaces. In

Lane A. Hemaspaandra

This chapter provides a hands-on tutorial on the important technique known as self-reducibility. Through a series of "Challenge Problems" that are theorems that the reader will---after being given definitions and tools---try to prove, the tutorial will ask the reader not to read proofs that use self-reducibility, but rather to discover proofs that use self-r

Takuro Mochizuki

We prove the Kobayashi-Hitchin correspondence between good wild harmonic bundles and polystable good filtered $\lambda$-flat bundles satisfying a vanishing condition. We also study the correspondence for good wild harmonic bundles with the homogeneity with respect to a group action, which is expected to provide another way to construct Frobenius manifolds.

Maher Nouiehed, Maziar Sanjabi, Tianjian Huang, Jason D. Lee

Recent applications that arise in machine learning have surged significant interest in solving min-max saddle point games. This problem has been extensively studied in the convex-concave regime for which a global equilibrium solution can be computed efficiently. In this paper, we study the problem in the non-convex regime and show that an \varepsilon--first

Argenis Mendez

We consider the initial value problem (IVP) for the fractional Korteweg-de Vries equation (fKdV) \begin{equation}\label{abstracteq1} \left\{ \begin{array}{ll} \partial_{t}u-D_{x}^{\alpha}\partial_{x}u+u\partial_{x}u=0, & x,t\in\mathbb{R},\,0<\alpha<1, \\ u(x,0)=u_{0}(x).& \\ \end{array} \right. \end{equation} It has been shown that the solutions to certain d