February 2019 arXiv papers — page 31

Aaron Hernandez-Perez, Yang Su, Astrid M. Veronig, Julia K. Thalmann

We report a detailed study of the pre-eruption activities that led to the occurrence of an M9.0 flare/CME event on 2012 October 20 in NOAA AR 11598. This includes the study of the preceding confined C2.4 flare that occurred on the same AR ~25 minutes earlier. We observed that the M9.0 flare occurred as a consequence of two distinct triggering events well sep

Pierre Le Boudec

We adopt a statistical point of view on the conjecture of Lang which predicts a lower bound for the canonical height of non-torsion rational points on elliptic curves defined over $\mathbb{Q}$. More specifically, we prove that among the family of all elliptic curves defined over $\mathbb{Q}$ and having positive rank, there is a density one subfamily of curve

Volodymyr Buriachok, Volodymyr Sokolov

The article introduces a new scheme of dynamic interference free channel allocation. The scheme is based on additional spectral analyzers in wireless networks IEEE 802.11. Design and implementation is presented.

Christian Schörner, Subhasis Adhikari, Markus Lippitz

Plasmonic waveguides are key elements in nanophotonic devices serving as optical interconnects between nanoscale light sources and detectors. Multimode operation in plasmonic two-wire transmission lines promises important degrees of freedom for near-field manipulation and information encoding. However, highly confined plasmon propagation in gold nanostructur

Øystein Sørensen, Marta Crispino, Qinghua Liu, Valeria Vitelli

BayesMallows is an R package for analyzing data in the form of rankings or preferences with the Mallows rank model, and its finite mixture extension, in a Bayesian probabilistic framework. The Mallows model is a well-known model, grounded on the idea that the probability density of an observed ranking decreases exponentially fast as its distance to the locat

Vanderson Martins do Rosario, Edson Borin, Mauricio Breternitz

We introduce Multi-Lane Capsule Networks (MLCN), which are a separable and resource efficient organization of Capsule Networks (CapsNet) that allows parallel processing, while achieving high accuracy at reduced cost. A MLCN is composed of a number of (distinct) parallel lanes, each contributing to a dimension of the result, trained using the routing-by-agree

Jeppe R. Andersen, Tuomas Hapola, Marian Heil, Andreas Maier

We present HEJ 2, a new implementation of the High Energy Jets formalism for high-energy resummation in hadron-collider processes as a flexible Monte Carlo event generator. In combination with a conventional fixed-order event generator, HEJ 2 can be used to obtain greatly improved predictions for a number of phenomenologically important processes by adding a

A. Albert, R. Alfaro, H. Ashkar, C. Alvarez

We outline the science motivation for SGSO, the Southern Gamma-Ray Survey Observatory. SGSO will be a next-generation wide field-of-view gamma-ray survey instrument, sensitive to gamma-rays in the energy range from 100 GeV to hundreds of TeV. Its science topics include unveiling galactic and extragalactic particle accelerators, monitoring the transient sky a

Clemens Huemer, Pablo Pérez-Lantero, Carlos Seara, Rodrigo I. Silveira

We consider matchings with diametral disks between two sets of points R and B. More precisely, for each pair of matched points p in R and q in B, we consider the disk through p and q with the smallest diameter. We prove that for any R and B such that |R|=|B|, there exists a perfect matching such that the diametral disks of the matched point pairs have a comm

Volodymyr Buriachok, Volodymyr Sokolov

This article attempts to create a software and hardware complex that can work autonomously and demonstrates the ease of implementation of attacks on denial of service on wireless networks, which in turn emphasizes the need to provide comprehensive protection of wireless networks.

Zakhar Kabluchko, Igor Wigman

We determine the true asymptotic behaviour for the expected number of connected components for a model of random lemniscates proposed recently by Lerario and Lundberg. These are defined as the subsets of the Riemann sphere, where the absolute value of certain random, $\text{SO}(3)$-invariant rational function of degree $n$ equals to $1$. We show that the exp

Naoki Nishida, Yuya Maeda

The grammar representation of a narrowing tree for a syntactically deterministic conditional term rewriting system and a pair of terms is a regular tree grammar that generates expressions for substitutions obtained by all possible innermost-narrowing derivations that start with the pair and end with particular non-narrowable terms. In this paper, under a cer

Manfred Schmidt-Schauß, Nils Dallmeyer

This paper is a contribution to exploring and analyzing space-improvements in concurrent programming languages, in particular in the functional process-calculus CHF. Space-improvements are defined as a generalization of the corresponding notion in deterministic pure functional languages. The main part of the paper is the O(n*log n) algorithm SpOptN for offli

Yoshiaki Kanazawa, Naoki Nishida

In this paper, we show a new approach to transformations of an imperative program with function calls and global variables into a logically constrained term rewriting system. The resulting system represents transitions of the whole execution environment with a call stack. More precisely, we prepare a function symbol for the whole environment, which stores va

David Sabel

We report on the automation of a technique to prove the correctness of program transformations in higher-order program calculi which may permit recursive let-bindings as they occur in functional programming languages. A program transformation is correct if it preserves the observational semantics of programs. In our LRSX Tool the so-called diagram method is

Andrei-Sebastian Buruiană, Ştefan Ciobâcă

We give a language-parametric solution to the problem of total correctness, by automatically reducing it to the problem of partial correctness, under the assumption that an expression whose value decreases with each program step in a well-founded order is provided. Our approach assumes that the programming language semantics is given as a rewrite theory. We

Djordjije Vujadinović

The main result of this paper refers to the boundedness of the orthogonal projection $P_α:L^{2}(\mathbb{R}^{n},dμ_α)\rightarrow \mathcal{H}_α^{2}, n\geq2 $ associated to the harmonic Fock space $\mathcal{H}_α^{2},$ where $dμ_α(x)=(πα)^{-n/2}e^{-\frac{|x|^2}α}dx.$ We prove that the operator $P_α$ is not bounded on $L^{p}(\mathbb{R}^{n},dμ_β)$ when $0<p< 1$ an

Alexandre Lazarescu, Tommaso Cossetto, Gianmaria Falasco, Massimiliano Esposito

Chemical reaction networks offer a natural nonlinear generalisation of linear Markov jump processes on a finite state-space. In this paper, we analyse the dynamical large deviations of such models, starting from their microscopic version, the chemical master equation. By taking a large-volume limit, we show that those systems can be described by a path integ

Hsing-Yin Chang, Andrew Alvarado, Trey Weber, Jaime Marian

Surface erosion and secondary electron emission (SEE) have been identified as the most critical life-limiting factors in channel walls of Hall-effect thrusters for space propulsion. Recent wall concepts based on micro-architected surfaces have been proposed to mitigate surface erosion and SEE. The idea behind these designs is to take advantage of very-high s

A. Boscaggin, W. Dambrosio, D. Papini

Given a smooth function $U(t,x)$, $T$-periodic in the first variable and satisfying $U(t,x) = \mathcal{O}(\vert x \vert^α)$ for some $α\in (0,2)$ as $\vert x \vert \to \infty$, we prove that the forced Kepler problem $$ \ddot x = - \dfrac{x}{|x|^3} + \nabla_x U(t,x),\qquad x\in {\mathbb{R}}^2, $$ has a generalized $T$-periodic solution, according to the defi

P. R. A. Souza, A. F. Santos, S. C. Ulhoa, F. C. Khanna

Small violation of Lorentz and CPT symmetries may emerge in models unifying gravity with other forces of nature. An extension of the standard model with all possible terms that violate Lorentz and CPT symmetries are included. Here a CPT-even non-minimal coupling term is added to the covariant derivative. This leads to a new interaction term that breaks the L

Mohamed Ishmael Belghazi, Maxime Oquab, Yann LeCun, David Lopez-Paz

We introduce the Neural Conditioner (NC), a self-supervised machine able to learn about all the conditional distributions of a random vector $X$. The NC is a function $NC(x \cdot a, a, r)$ that leverages adversarial training to match each conditional distribution $P(X_r|X_a=x_a)$. After training, the NC generalizes to sample from conditional distributions ne

Marcelo Daniel Gutierrez Mallea, Peter Meltzer, Peter J Bentley

Graph classification is a significant problem in many scientific domains. It addresses tasks such as the classification of proteins and chemical compounds into categories according to their functions, or chemical and structural properties. In a supervised setting, this problem can be framed as learning the structure, features and relationships between featur

A. R. Mirotin

In this paper several joint spectra for a finite commuting family of closed operators in Banach space are considered, some new relations between these spectra established (earlier only the inclusion of the Taylor spectrum in the commutant one was known), and in the case of semigroup generators spectral mapping theorems for such spectra are proved. Several of

Sinhwi Kim, Yuri Nikolayevsky, JeongHyeong Park

We classify totally geodesic submanifolds of Damek-Ricci spaces and show that they are either homogeneous (such submanifolds are known to be &#34;smaller&#34; Damek-Ricci spaces) or isometric to rank-one symmetric spaces of negative curvature. As a by-product, we obtain that a totally geodesic submanifold of any known harmonic manifold is by itself harmonic.

Robbin Bastiaansen, Arjen Doelman, Frank van Langevelde, Vivi Rottschäfer

Thermoregulation in honey bee colonies during winter is thought to be self-organised. We added mortality of individual honey bees to an existing model of thermoregulation to account for elevated losses of bees that are reported worldwide. The aim of analysis is to obtain a better fundamental understanding of the consequences of individual mortality during wi

Meysam Sadeghi, Erik G. Larsson

We show that end-to-end learning of communication systems through deep neural network (DNN) autoencoders can be extremely vulnerable to physical adversarial attacks. Specifically, we elaborate how an attacker can craft effective physical black-box adversarial attacks. Due to the openness (broadcast nature) of the wireless channel, an adversary transmitter ca

Woo Hyun Han, Sunghyun Kim, In-Ho Lee, Kee Joo Chang

The flat band has attracted a lot of attention because it gives rise to many exotic phases, as recently demonstrated in magic angle twisted bilayer graphene. Here, based on first-principles calculations, we identify a metal-insulator transition in boron triangular Kagome lattice with a spin-polarized flat band at 2/3-filling. This phase transition is accompa

Alexander E. Guterman, Dmitrii K. Kudryavtsev

We obtain a sharp upper bound for the length of arbitrary non-associative algebra and present an example demonstrating the sharpness of our bound. To show this we introduce a new method of characteristic sequences based on linear algebra technique. This method provides an efficient tool for computing the length function in non-associative case. Then we apply

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

Miroslava Poláková

Explicit formulas for complexity and unique invariant measure of the period-doubling subshift can be derived from those for the Thue-Morse subshift, obtained by Brlek, De Luca and Varricchio, and Dekking. In this note we give direct proofs based on combinatorial properties of the period-doubling sequence. We also derive explicit formulas for correlation inte

Akiko Ono, Hideki Uchiyama, Shigeo Yamauchi, Masayoshi Nobukawa

This paper reports the analysis procedure and results of simultaneous spectral fits of the Suzaku archive data for Sagittarius (Sgr) A East and the nearby Galactic center X-ray emission (GCXE). The results are that the mixed-morphology supernova remnant Sgr A East has a recombining plasma (RP) with Cr and Mn He$α$ lines, and a power-law component (PL) with a

Wenbo Lin, Yasutomo Ota, Satoshi Iwamoto, Yasuhiko Arakawa

In this study, we examine a photonic wire waveguide embedded with an ensemble of quantum dots that directionally emits into the waveguide depending on the spin state of the ensemble. This is accomplished through the aid of the spin-orbit interaction of light. The waveguide has a two-step stair-like cross section and embeds quantum dots (QDs) only in the uppe

Andrey Boris Khesin, Aleksandar Nikolov, Dmitry Paramonov

In the geometric transportation problem, we are given a collection of points $P$ in $d$-dimensional Euclidean space, and each point is given a supply of $μ(p)$ units of mass, where $μ(p)$ could be a positive or a negative integer, and the total sum of the supplies is $0$. The goal is to find a flow (called a transportation map) that transports $μ(p)$ units f

Vahram L. Grigoryan, Ke Xia

We propose thermal induced generation of monochromatic microwave radiation in magnon-polariton. Mechanism of thermal to microwave energy transformation is based on intrinsic energy loss compensation of coupled magnon and microwave cavity oscillators by thermal induced &#34;negative damping&#34;. A singularity at an exceptional point is achieved when at the c

Yu Wang, Siqi Wu, Bin Yu

We study the problem of globally recovering a dictionary from a set of signals via $\ell_1$-minimization. We assume that the signals are generated as i.i.d. random linear combinations of the $K$ atoms from a complete reference dictionary $D^*\in \mathbb R^{K\times K}$, where the linear combination coefficients are from either a Bernoulli type model or exact

Javed Rana, Shreya Anand, Sukanta Bose

In order to identify the rapidly-fading, optical transient counterparts of gravitational wave (GW) sources, an efficient follow-up strategy is required. Since most ground-based optical observatories aimed at following-up GW sources have a telescope with a small field-of-view (FOV) as compared to the GW sky error region, we focus on a search strategy that inv

B. L. S. Prakasa Rao

We study the problem of nonparametric estimation of linear multiplier function $θt)$ for processes satisfying stochastic differential equations of the type $dX_t=θ(t)X_tdt+\epsilond\bar W_t^H, X_0=x_0, 0\leq t \leq T$ where $\{\bar W_T^H, t \geq 0\}$ is a mixed fractional Brownian motion with known Hurst index $H$ and study the asymptotic behaviour of the es

Igor Labutov, Bishan Yang, Tom Mitchell

As humans, we often rely on language to learn language. For example, when corrected in a conversation, we may learn from that correction, over time improving our language fluency. Inspired by this observation, we propose a learning algorithm for training semantic parsers from supervision (feedback) expressed in natural language. Our algorithm learns a semant

Svetlana V. Butler

Topological measures and deficient topological measures generalize Borel measures and correspond to certain non-linear functionals. We study integration with respect to deficient topological measures on locally compact spaces. Such an integration over sets yields a new deficient topological measure if we integrate a nonnegative vanishing at infinity function

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

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

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

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.

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

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

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

Answerer in Questioner&#39;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 soluti

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

Nigel Higson, Zelin Yi

The purpose of this article is to study Ezra Getzler&#39;s approach to the Atiyah-Singer index theorem from the perspective of Alain Connes&#39; tangent groupoid. We shall construct a &#34;rescaled&#34; spinor bundle on the tangent groupoid, define a convolution operation on its smooth, compactly supported sections, and explain how the algebra so-obtained in

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

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

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

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

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

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,

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

Over 50 years ago, Rota posted the following celebrated `Research Problem&#39;: 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

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 Sołtan 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 by M

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

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

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&#39;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 high

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

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

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

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

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 &#34;Challenge Problems&#34; 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 us

Takuro Mochizuki

We prove the Kobayashi-Hitchin correspondence between good wild harmonic bundles and polystable good filtered $λ$-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

Songtao Lu, Ioannis Tsaknakis, Mingyi Hong, Yongxin Chen

The min-max problem, also known as the saddle point problem, is a class of optimization problems which minimizes and maximizes two subsets of variables simultaneously. This class of problems can be used to formulate a wide range of signal processing and communication (SPCOM) problems. Despite its popularity, most existing theory for this class has been mainl

Pavan R. Hebbar, Craig O. Heinke, Gregory R. Sivakoff, Aarran W. Shaw

Black holes in dwarf/bulgeless galaxies play a crucial role in studying the co-evolution of galaxies and their central black holes. Identifying massive black holes in dwarf galaxies suggests that the growth of black holes could precede that of galaxies. However, some of the most intriguing candidate active galactic nuclei (AGN) in small galaxies have such lo

Matthew Perron, Zeyuan Shang, Tim Kraska, Michael Stonebraker

Cost-based query optimizers remain one of the most important components of database management systems for analytic workloads. Though modern optimizers select plans close to optimal performance in the common case, a small number of queries are an order of magnitude slower than they could be. In this paper we investigate why this is still the case, despite de

Katie E. Severn, Ian L. Dryden, Simon P. Preston

Networks arise in many applications, such as in the analysis of text documents, social interactions and brain activity. We develop a general framework for extrinsic statistical analysis of samples of networks, motivated by networks representing text documents in corpus linguistics. We identify networks with their graph Laplacian matrices, for which we define

Dennis M. Feehan, Curtiss Cobb

Online data sources offer tremendous promise to demography and other social sciences, but researchers worry that the group of people who are represented in online datasets can be different from the general population. We show that by sampling and anonymously interviewing people who are online, researchers can learn about both people who are online and people

Hector Socas-Navarro

A recent study by Farnes (2018) proposed an alternative cosmological model in which both dark matter and dark energy are replaced with a single fluid of negative mass. This paper presents a critical review of that model. A number of problems and discrepancies with observations are identified. For instance, the predicted shape and density of galactic dark mat