February 2019 arXiv papers — page 36

Asuka Ito, Aya Iyonaga, Suro Kim, Jiro Soda

We study dressed inflation with a cuscuton and find a novel exact power-law solution. It is well known that the conventional power-law inflation is inconsistent with the Planck data. In contrast to this standard lore, we find that power-law inflation with a cuscuton can be reconciled with the Planck data. Moreover, we argue that the cuscuton generally amelio

Wei Yang, Xiaoyu Wang, Yongliang Yang, Zhun Lu

We study the single longitudinal-spin asymmetry of dihadron production in semi-inclusive deep inelastic scattering process. We consider the collinear picture in which the transverse momentum of the final-state hadron pair is integrated out, such that the $\sin \phi_R$ azimuthal asymmetry arises from the coupling $h_L\, H_{1}^{\sphericalangle}$ as well as the

Kazue Kudo

Constrained quantum annealing (CQA) is a quantum annealing approach that is designed so that constraints are satisfied without penalty terms. There is an analogy between the model for the CQA of graph coloring and a set of disordered spin chains. In the model for the CQA of graph coloring, disorder corresponds to the fluctuation of effective local fields tha

Sucheta Mondal, Saswati Barman, Anjan Barman

Magnetic analogue of electronic gates are advantageous in many ways. There is no electron leakage, higher switching speed and more energy saving in a magnetic logic device compared to a semiconductor one. Recently, we proposed a magnetic vortex transistor and fan-out out devices based on carefully coupled magnetic vortices in isolated nanomagnetic disks. Her

Takaaki Moriyama

We show that if a countable group $G$ is the free product of infinite abelian groups, then for every free, probability-measure-preserving (p.m.p.) action of $G$, its orbit equivalence class is weakly dense in the space of p.m.p. actions of $G$. This extends Lewis Bowen's result for free groups.

Remy van Dobben de Bruyn

We prove a precise version of a theorem of Siu and Beauville on morphisms to higher genus curves, and use it to show that if a variety $X$ in characteristic $p$ lifts to characteristic $0$, then any morphism $X \to C$ to a curve of genus $g \geq 2$ can be lifted along. We use this to construct, for every prime $p$, a smooth projective surface $X$ over $\bar{

Snigdha Panigrahi, Jonathan Taylor

Several strategies have been developed recently to ensure valid inference after model selection; some of these are easy to compute, while others fare better in terms of inferential power. In this paper, we consider a selective inference framework for Gaussian data. We propose a new method for inference through approximate maximum likelihood estimation. Our g

Hendrik De Bie, Hadewijch De Clercq

The Gasper and Rahman multivariate $(-q)$-Racah polynomials appear as connection coefficients between bases diagonalizing different abelian subalgebras of the recently defined higher rank $q$-Bannai-Ito algebra $\mathcal{A}_n^q$. Lifting the action of the algebra to the connection coefficients, we find a realization of $\mathcal{A}_n^q$ by means of differenc

Susobhan Paul, Asim Kumar Ghosh

Antikink dispersion of the asymmetric $J_1$-$J_2$ sawtooth spin-1/2 anisotropic Heisenberg antiferromagnetic chain has been derived. Value of spin-gap is obtained by estimating the minimum of dispersion relation variationally. The exact doubly-degenerate ground state energy has been derived at the symmetric point, $J_1=J_2$, for the whole anisotropic regime.

Thilo von Neumann, Keisuke Kinoshita, Marc Delcroix, Shoko Araki

Automatic meeting analysis comprises the tasks of speaker counting, speaker diarization, and the separation of overlapped speech, followed by automatic speech recognition. This all has to be carried out on arbitrarily long sessions and, ideally, in an online or block-online manner. While significant progress has been made on individual tasks, this paper pres

Xiahai Zhuang, Lei Li, Christian Payer, Darko Stern

Knowledge of whole heart anatomy is a prerequisite for many clinical applications. Whole heart segmentation (WHS), which delineates substructures of the heart, can be very valuable for modeling and analysis of the anatomy and functions of the heart. However, automating this segmentation can be arduous due to the large variation of the heart shape, and differ

Ji Guo

As an analogue of the Hadamard quotient problem in number theory, the quotient problem (in the sense of complex entire functions) for two sequences $F(n)=a_0+a_1f_1^n+\cdots+a_lf_l^n$ and $ G(n)=b_0+b_1g_1^n+\cdots+b_mg_m^n$, has been solved, where the $f_i$ and $g_j$ are nonconstant entire functions and $a_i$ and $b_j$ are non-zero constants except that $a_

Joseph Grant, Osamu Iyama

In this article we study higher preprojective algebras, showing that various known results for ordinary preprojective algebras generalize to the higher setting. We first show that the quiver of the higher preprojective algebra is obtained by adding arrows to the quiver of the original algebra, and these arrows can be read off from the last term of the bimodu

Lei Li, Fuping Wu, Guang Yang, Lingchao Xu

Late gadolinium enhancement magnetic resonance imaging (LGE MRI) appears to be a promising alternative for scar assessment in patients with atrial fibrillation (AF). Automating the quantification and analysis of atrial scars can be challenging due to the low image quality. In this work, we propose a fully automated method based on the graph-cuts framework, w

Ariel Edery, Yu Nakayama

Pure $R^2$ gravity has been shown to be equivalent to Einstein gravity with non-zero cosmological constant and a massless scalar field. We show that the Palatini formulation of pure $R^2$ gravity is equivalent to Einstein gravity with non-zero cosmological constant as before but with no massless scalar field. This is an important new development because the

Hong-Yuan Xu, Yu-Pin Luo, Ming-Chang Huang

The Brusselator model are used for the study of the intrinsic fluctuations of chemical reactions with different approaches. The equilibrium states of systems are assumed to be spirally stable in mean-field description, and two statistical measures of intrinsic fluctuations are analyzed by different theoretical methods, namely, the master, the Langevin, and t

Mariam Bouhmadi-López, Suddhasattwa Brahma, Che-Yu Chen, Pisin Chen

For any non-rotating effective quantum (uncharged) black hole model to be viable, its asymptotic structure of spacetime should reduce to that of a Schwarzschild black hole. After examining the asymptotic structure of quantum black holes proposed in Ashtekar et al., (2018), we find that the solution is actually not asymptotically flat. Departure from asymptot

Kieran Clancy, Michael Haythorpe, Alex Newcombe

There has been significant research dedicated towards computing the crossing numbers of families of graphs resulting from the Cartesian products of small graphs with arbitrarily large paths, cycles and stars. For graphs with four or fewer vertices, these have all been computed, but there are still various gaps for graphs with five or more vertices. We contri

Saeed Ahmadian, Ramin Farajifijani

Financial transmission right (FTR) is an important tool and an especially feature for stopping congestion charges in restructured electricity markets. Participants in the transmission market as players are assumed to be a generation company (Gencos) which also take part in an energy market and able to buy their require FTRs. In this regard, there are two typ

Fabian Parsch

We construct a geodesic net in the plane with four unbalanced (boundary) vertices that has 16 balanced vertices and does not contain proper geodesic subnets. This is the first example of an irreducible geodesic net in the Euclidean plane with 4 boundary vertices that is not a tree.

Andre Nies, Frank Stephan

We study algorithmic randomness properties for probability measures on Cantor space. We say that a measure $\mu$ on the space of infinite bit sequences is ML absolutely continuous if the non-ML-random bit sequences form a null set with respect to~$\mu$. We think of this as a weak randomness notion for measures. We begin with examples, and provide a robustnes

Qian He, Heng Jiang, Chengdan Tan, Rong Liu

The detected frequency response range of phase-sensitive optical time domain reflectometry is limited by the sensing fiber length. In this paper, we demonstrate an amplitude modulated pulses based phase-sensitive OTDR to detect vibrations with high spatial resolution and wide frequency response range. The amplitude modulated pulses consisting of narrow pulse

Qi Zhao, Gerui Wang, Xiao Yuan, Xiongfeng Ma

Entanglement is a key resource for quantum information processing. A widely used tool for detecting entanglement is entanglement witness, where the measurement of the witness operator is guaranteed to be positive for all separable states and can be negative for certain entangled states. In reality, due to the exponentially increasing the Hilbert-space dimens

Svetlana V. Butler

This paper focuses on various decompositions of topological measures, deficient topological measures, signed topological measures, and signed deficient topological measures. These set functions generalize measures and correspond to certain non-linear functionals. They may assume $\infty$ or $-\infty$. We introduce the concept of a proper signed deficient top

Peixiang Zhong, Chunyan Miao

In this paper we present our model on the task of emotion detection in textual conversations in SemEval-2019. Our model extends the Recurrent Convolutional Neural Network (RCNN) by using external fine-tuned word representations and DeepMoji sentence representations. We also explored several other competitive pre-trained word and sentence representations incl

Takashi Shiroto, Yasuhiko Sentoku

Mathematical symmetries of the Beliaev--Budker kernel are the most important structure of the relativistic Landau--Fokker--Planck equation. By preserving the beautiful symmetries, a mass-momentum-energy-conserving simulation has been demonstrated without any artificial constraints.

Artur F. Izmaylov

The problem of construction of projection operators on eigen-subspaces of symmetry operators is considered. This problem arises in many approximate methods for solving time-independent and time-dependent quantum problems, and its solution ensures proper physical symmetries in development of approximate methods. The projector form is sought as a function of s

Ramakrishna Vedantam, Karan Desai, Stefan Lee, Marcus Rohrbach

We propose a new class of probabilistic neural-symbolic models, that have symbolic functional programs as a latent, stochastic variable. Instantiated in the context of visual question answering, our probabilistic formulation offers two key conceptual advantages over prior neural-symbolic models for VQA. Firstly, the programs generated by our model are more u

Qingqiong Cai, Neng Fan, Yongtang Shi, Shunyu Yao

For a graph $G= (V,E)$, a double Roman dominating function (DRDF) is a function $f : V \to \{0,1,2,3\}$ having the property that if $f (v) = 0$, then vertex $v$ must have at least two neighbors assigned $2$ under $f$ or {at least} one neighbor $u$ with $f (u) = 3$, and if $f (v) = 1$, then vertex $v$ must have at least one neighbor $u$ with $f (u) \ge 2$. In

Xun Zou, Mehdi Ganji, Hamid Jafarkhani

Recent studies have demonstrated the superiority of non-orthogonal multiple access (NOMA) over orthogonal multiple access (OMA) in cooperative communication networks. In this paper, we propose a novel half-duplex cooperative asynchronous NOMA (C-ANOMA) framework with user relaying, where a timing mismatch is intentionally added in the broadcast signal. We de

Richard O. Moore, Mark A. Hoefer

The magnetic droplet soliton is a large amplitude, coherently precessing wave state that exists in ferromagnetic thin films with perpendicular magnetic anisotropy. To effectively sustain a droplet, magnetic damping can be locally compensated in a nanocontact region that imparts spin-transfer torque; this has been successfully deployed in experiment to direct

Jing Li, Chao Liu, Xiangxiang Xue, Jing Zhong

We use LAMOST DR4 M giants combined with Gaia DR2 proper motions and ALLWISE photometry to obtain an extremely pure sample of Sagittarius (Sgr) stream stars. Using TiO5 and CaH spectral indices as an indicator, we selected out a large sample of M giant stars from M dwarf stars in LAMOST DR4 spectra. Considering the position, distance, proper motion and the a

George Leu, Jiangjun Tang

The survivable network concept refers to contexts where the wireless communication between ground agents needs to be maintained as much as possible at all times, regardless of any adverse conditions that may arise. In this paper we propose a nature-inspired approach to survivable networks, in which we bring together swarm intelligence and evolutionary comput

Fangfei Wang, Dong Guan, Long Zhao, Kan Zheng

High-definition (HD) map transmission is considered as a key technology for automatic driving, which enables vehicles to obtain the precise road and surrounding environment information for further localization and navigation. Guaranteeing the huge requirement of HD map data, the objective of this paper is to reduce the power consumption of vehicular networks

X. Y. Yin, Hui Hu, Xia-Ji Liu

Two-component fermions are known to behave like a gas of molecules in the limit of Bose-Einstein condensation of diatomic pairs tightly bound with zero-range interactions. We discover that the formation of cluster states occurs when the effective range of two-body interaction exceeds roughly $0.46$ times the scattering length, regardless of the details of th

Roberto C. Sotero, Lazaro M. Sanchez-Rodriguez, Mehdy Dousty, Yasser Iturria-Medina

We studied the interactions between different temporal scales of diffusion processes on complex networks and found them to be stronger in scale-free (SF) than in Erdos-Renyi (ER) networks, especially for the case of phase-amplitude coupling (PAC)-the phenomenon where the phase of an oscillatory mode modulates the amplitude of another oscillation. We found th

Anupam Gupta, Haotian Jiang, Ziv Scully, Sahil Singla

Suppose there are $n$ Markov chains and we need to pay a per-step \emph{price} to advance them. The "destination" states of the Markov chains contain rewards; however, we can only get rewards for a subset of them that satisfy a combinatorial constraint, e.g., at most $k$ of them, or they are acyclic in an underlying graph. What strategy should we choose to a

Avinash Barnwal, Hari Pad Bharti, Aasim Ali, Vishal Singh

Predicting the direction of assets have been an active area of study and a difficult task. Machine learning models have been used to build robust models to model the above task. Ensemble methods is one of them showing results better than a single supervised method. In this paper, we have used generative and discriminative classifiers to create the stack, par

Peter A. Rose, Jacob J. Krich

We outline a novel numerical method, called Ultrafast Ultrafast (UF$^2$), for calculating the $n^\text{th}$-order wavepackets required for calculating n-wave mixing signals. The method is simple to implement, and we demonstrate that it is computationally more efficient than other methods in a wide range of use cases. Resulting spectra are identical to those

C. Carcy, S. Hoinka, M. G. Lingham, P. Dyke

We present an experimental study of the high-energy excitation spectra of unitary Fermi gases. Using focussed beam Bragg spectroscopy, we locally probe atoms in the central region of a harmonically trapped cloud where the density is nearly uniform, enabling measurements of the dynamic structure factor for a range of temperatures both below and above the supe

P. L. Robinson

We develop the theory of the lemniscatic functions sl and cl from their definition as solutions to an initial value problem.

M. H. Kim, B. Hong, Y. Goto, I. Nakagawa

Transverse single spin asymmetry, $A_{N}$, of very forward $\pi^{0}$ production from polarized $p + p$ collisions provides new information toward an understanding of its production mechanism. $A_{N}$ of forward $\pi^{0}$ in the pseudorapidity region of $3 < \eta < 4$ has been described by the partonic structure of the proton in the perturbative QCD framework

Yijie Mao, Bruno Clerckx, Victor O. K. Li

In a multi-user multi-antenna Simultaneous Wireless Information and Power Transfer (SWIPT) network, the transmitter sends information to the Information Receivers (IRs) and energy to Energy Receivers (ERs) concurrently. A conventional approach is based on Multi-User Linear Precoding (MU--LP) where each IR directly decodes the intended stream by fully treatin

A. J. Schwartz

We review measurements of semileptonic and leptonic charm meson decays performed by the Belle experiment, and we use these results to estimate the sensitivity of the follow-on Belle II experiment to these decays.

Alexandra Burashnikova, Yury Maximov, Massih-Reza Amini

In this paper, we propose a robust sequential learning strategy for training large-scale Recommender Systems (RS) over implicit feedback mainly in the form of clicks. Our approach relies on the minimization of a pairwise ranking loss over blocks of consecutive items constituted by a sequence of non-clicked items followed by a clicked one for each user. Param

Shuochao Yao, Ailing Piao, Wenjun Jiang, Yiran Zhao

Recent advances in deep learning motivate the use of deep neural networks in Internet-of-Things (IoT) applications. These networks are modelled after signal processing in the human brain, thereby leading to significant advantages at perceptual tasks such as vision and speech recognition. IoT applications, however, often measure physical phenomena, where the

Chengjie Li, Ruixuan Li, Haozhao Wang, Yuhua Li

Distributed asynchronous offline training has received widespread attention in recent years because of its high performance on large-scale data and complex models. As data are distributed from cloud-centric to edge nodes, a big challenge for distributed machine learning systems is how to handle native and natural non-independent and identically distributed (

J. D. Vega Sánchez, D. P. Moya Osorio, E. E. Benitez Olivo, H. Alves

In this paper, we derive closed-form exact expressions for the main statistics of the ratio of squared alpha-mu random variables, which are of interest in many scenarios for future wireless networks where generalized distributions are more suitable to fit with field data. Importantly, different from previous proposals, our expressions are general in the sens

Alistair Shilton, Sunil Gupta, Santu Rana, Svetha Venkatesh

In this paper we consider the problem of finding stable maxima of expensive (to evaluate) functions. We are motivated by the optimisation of physical and industrial processes where, for some input ranges, small and unavoidable variations in inputs lead to unacceptably large variation in outputs. Our approach uses multiple gradient Gaussian Process models to

Ngoc Linh Nguyen, He Ma, Marco Govoni, Francois Gygi

We present a method to compute optical spectra and exciton binding energies of molecules and solids based on the solution of the Bethe-Salpeter equation (BSE) and the calculation of the screened Coulomb interaction in finite field. The method does not require the explicit evaluation of dielectric matrices nor of virtual electronic states, and can be easily a

Prim Plansangkate

Under two separate symmetry assumptions, we demonstrate explicitly how the equations governing a general anti-self-dual conformal structure in four dimensions can be reduced to the Manakov-Santini system, which determines the three-dimensional Einstein-Weyl structure on the space of orbits of symmetry. The two symmetries investigated are a non-null translati

Roman Ya. Kezerashvili

This review focuses on the studies and computations of few-body systems of electrons and holes in condensed matter physics. We analyze and illustrate the application of a variety of methods for description of two- three- and four-body excitonic complexes such as an exciton, trion and biexciton in three-, two- and one-dimensional configuration spaces in vario

S. Ramkumar, C. Ganesa Moorthy

Two variations of classical Urysohn lemma for subsets of topological vector spaces are obtained in this article. The continuous functions constructed in these lemmas are of quasi-convex type.

Nalini Joshi, Nobutaka Nakazono

Discrete Painlev\'e equations are nonlinear, nonautonomous difference equations of second-order. They have coefficients that are explicit functions of the independent variable $n$ and there are three different types of equations according to whether the coefficient functions are linear, exponential or elliptic functions of $n$. In this paper, we focus on the

Arkady Bolotin

As per Einstein's design, particles are introduced into the double-slit experiment through a small hole in a plate which can either move up and down (and its momentum can be measured) or be stopped (and its position can be measured). Suppose one measures the position of the plate and this act verifies the statement that the interference pattern is observed i

Kei Fong Lam

We study the sharp interface limit of a non-mass-conserving Cahn--Hilliard--Darcy system with the weak compactness method developed in Chen (J. Differential Geometry, 1996). The source term present in the Cahn--Hilliard component is a product of the order parameter and a prescribed function with zero spatial mean, leading to non-conservation of mass. Further

Xinsong Du, Jae Min, Mattia Prosperi, Rohit Bishnoi

Febrile neutropenia (FN) has been associated with high mortality, especially among adults with cancer. Understanding the patient and provider level heterogeneity in FN hospital admissions has potential to inform personalized interventions focused on increasing survival of individuals with FN. We leverage machine learning techniques to disentangling the compl

Jeremy M. Dover

In 1992 Czerwinski and Oakden (The translation planes of order 25, J. Combin. Theory Ser. A, 59:193-217, 1992) provided an exhaustive list of all spreads of $PG(3,5)$ and thus of all translation planes of that order. At that time, the authors provided a partial correlation of these planes to those then-described in the literature, but the intervening years h

Zhihui Su, Ming Ye, Guohui Zhang, Lei Dai

Human pose estimation plays an important role in many computer vision tasks and has been studied for many decades. However, due to complex appearance variations from poses, illuminations, occlusions and low resolutions, it still remains a challenging problem. Taking the advantage of high-level semantic information from deep convolutional neural networks is a

Jan Bouwe van den Berg, Ray Sheombarsing

In this paper we present a computer-assisted procedure for proving the existence of transverse heteroclinic orbits connecting hyperbolic equilibria of polynomial vector fields. The idea is to compute high-order Taylor approximations of local charts on the (un)stable manifolds by using the Parameterization Method and to use Chebyshev series to parameterize th

Nikita Porwal, Simone Peli, P. J. Chen, Robert Shull

We have investigated the spin wave dynamics of Permalloy (Py) thin films with and without a Ta capping layer for varying Py thickness (15 nm, 20 nm and 30 nm) using all optical time-resolved magneto-optical Kerr effect measurements. XPS measurements confirm the oxidation of the originally-prepared samples and also that the removal of the Ta capping layer is

Yilun Zhou, Steven Schockaert, Julie A. Shah

In many applications, it is important to characterize the way in which two concepts are semantically related. Knowledge graphs such as ConceptNet provide a rich source of information for such characterizations by encoding relations between concepts as edges in a graph. When two concepts are not directly connected by an edge, their relationship can still be d

Di Feng, Christian Haase-Schütz, Lars Rosenbaum, Heinz Hertlein

Recent advancements in perception for autonomous driving are driven by deep learning. In order to achieve robust and accurate scene understanding, autonomous vehicles are usually equipped with different sensors (e.g. cameras, LiDARs, Radars), and multiple sensing modalities can be fused to exploit their complementary properties. In this context, many methods

Amarjit Budhiraja, Shu Lu, Yang Yu, Quoc Tran-Dinh

We consider the problem of choosing design parameters to minimize the probability of an undesired rare event that is described through the average of $n$ iid random variables. Since the probability of interest for near optimal design parameters is very small, one needs to develop suitable accelerated Monte-Carlo methods for estimating the objective function

Hsiang Hsu, Salman Salamatian, Flavio P. Calmon

Correspondence analysis (CA) is a multivariate statistical tool used to visualize and interpret data dependencies. CA has found applications in fields ranging from epidemiology to social sciences. However, current methods used to perform CA do not scale to large, high-dimensional datasets. By re-interpreting the objective in CA using an information-theoretic

Philip Beltracchi, Paolo Gondolo

We present a time-dependent uniform-density interior Schwarzschild solution, an exact solution to the Einstein field equations. Our solution describes the collapse (or the time-reversed expansion) of an object from an infinite radius to an intermediate radius of 9/8 of the Schwarzschild radius, at which time a curvature singularity appears at the origin, and

Horia Mania, Stephen Tu, Benjamin Recht

We study the performance of the certainty equivalent controller on Linear Quadratic (LQ) control problems with unknown transition dynamics. We show that for both the fully and partially observed settings, the sub-optimality gap between the cost incurred by playing the certainty equivalent controller on the true system and the cost incurred by using the optim

Yoojin Choi, Mostafa El-Khamy, Jungwon Lee

We consider the optimization of deep convolutional neural networks (CNNs) such that they provide good performance while having reduced complexity if deployed on either conventional systems with spatial-domain convolution or lower-complexity systems designed for Winograd convolution. The proposed framework produces one compressed model whose convolutional fil

William M. Steinhardt, Zhenzhong Shi, Anjana Samarakoon, Sachith Dissanayake

The quantum spin liquid (QSL) state is an exotic state of matter featuring a high degree of entanglement and lack of long-range magnetic order in the zero-temperature limit. The triangular antiferromagnet YbMgGaO4 is a candidate QSL host, and precise determination of the Hamiltonian parameters is critical to understanding the nature of the possible ground st

Yi Chen, Jing Dong, Hao Ni

Consider the fractional Brownian Motion (fBM) $B^H=\{B^H(t): t \in [0,1] \}$ with Hurst index $H\in (0,1)$. We construct a probability space supporting both $B^H$ and a fully simulatable process $\hat B_{\epsilon}^H $ such that $$\sup_{t\in [0,1]}|B^H(t)-\hat B_{\epsilon}^H(t)| \le \epsilon$$ with probability one for any user specified error parameter $\epsi

Lingxiao Huang, Nisheeth K. Vishnoi

Fair classification has been a topic of intense study in machine learning, and several algorithms have been proposed towards this important task. However, in a recent study, Friedler et al. observed that fair classification algorithms may not be stable with respect to variations in the training dataset -- a crucial consideration in several real-world applica

Makoto Itoh

In this paper, we show that the dynamics of a wide variety of nonlinear systems such as engineering, physical, chemical, biological, and ecological systems, can be simulated or modeled by the dynamics of memristor circuits. It has the advantage that we can apply nonlinear circuit theory to analyze the dynamics of memristor circuits. Applying an external sour

Yun Tang, Guohong Ding, Jing Huang, Xiaodong He

This paper aims to improve the widely used deep speaker embedding x-vector model. We propose the following improvements: (1) a hybrid neural network structure using both time delay neural network (TDNN) and long short-term memory neural networks (LSTM) to generate complementary speaker information at different levels; (2) a multi-level pooling strategy to co

Kang Huang, Wanchun Liu, Yonghui Li, Branka Vucetic

Real-time remote estimation is critical for mission-critical applications including industrial automation, smart grid, and the tactile Internet. In this paper, we propose a hybrid automatic repeat request (HARQ)-based real-time remote estimation framework for linear time-invariant (LTI) dynamic systems. Considering the estimation quality of such a system, th

Ching Wong

Fix $k \geq 6$. We prove that any large enough finite group $G$ contains $k$ elements which span quadratically many triples of the form $(a,b,ab) \in S \times G$, given any dense set $S \subseteq G \times G$. The quadratic bound is asymptotically optimal. In particular, this provides an elementary proof of a special case of a conjecture of Brown, Erd\H{o}s a

Joachim Niehren, David Sabel

This volume contains the formal proceedings of the 5th International Workshop on Rewriting Techniques for Program Transformations and Evaluation (WPTE 2018), held on 8th of Juli 2018 in Oxford, United Kingdom, and affiliated with FLoC 2018 and FSCD 2018. Scope of WPTE: Rewriting techniques are of great help for studying correctness of program transformations

Milad Roohi, Eric M. Hernandez, David Rosowsky

The authors propose a methodology to perform seismic damage assessment of instrumented wood-frame buildings using response measurements. The proposed methodology employs a nonlinear model-based state observer that combines sparse acceleration measurements and a nonlinear structural model of a building to estimate the complete seismic response including displ

Martin Corless, Ankush Chakrabarty

We consider the problem of estimating the state and unknown input for a large class of nonlinear systems subject to unknown exogenous inputs. The exogenous inputs themselves are modeled as being generated by a nonlinear system subject to unknown inputs. The nonlinearities considered in this work are characterized by multiplier matrices that include many comm

Ayan Mukhopadhyay, Geoffrey Pettet, Chinmaya Samal, Abhishek Dubey

The problem of dispatching emergency responders to service traffic accidents, fire, distress calls and crimes plagues urban areas across the globe. While such problems have been extensively looked at, most approaches are offline. Such methodologies fail to capture the dynamically changing environments under which critical emergency response occurs, and there

Min Hyung Cho, Jingfang Huang

In this paper, we present a numerical algorithm for the accurate and efficient computation of the convolution of the frequency domain layered media Green&#39;s function with a given density function. Instead of compressing the convolution matrix directly as in the classical fast multipole method, fast direct solvers, and fast H-matrix algorithms, the new alg

Ke Sun, Iñaki Esnaola, Antonia M. Tulino, H. Vincent Poor

The learning data requirements are analyzed for the construction of stealth attacks in state estimation. In particular, the training data set is used to compute a sample covariance matrix that results in a random matrix with a Wishart distribution. The ergodic attack performance is defined as the average attack performance obtained by taking the expectation

James Hook

In this paper we present new theory and algorithms for 2-norm regression over the max-plus semiring. As an application we also show how max-plus 2-norm regression can be used in system identification of max-plus linear dynamical systems with Gaussian noise. We also introduce and provide methods for solving a max-plus linear inverse problem with regularizatio

Girish Joshi, Girish Chowdhary

In this paper, we present a hybrid direct-indirect model reference adaptive controller (MRAC), to address a class of problems with matched and unmatched uncertainties. In the proposed architecture, the unmatched uncertainty is estimated online through a companion observer model. Upon convergence of the observer, the unmatched uncertainty estimate is remodele

Sören Bartels, Michael Růžička

The article addresses the convergence of implicit and semi-implicit, fully discrete approximations of a class of nonlinear parabolic evolution problems. Such schemes are popular in the numerical solution of evolutions defined with the $p$-Laplace operator since the latter lead to linear systems of equations in the time steps. The semi-implicit treatment of t

Juan Manzanero, Gonzalo Rubio, David A. Kopriva, Esteban Ferrer

We present a nodal Discontinuous Galerkin (DG) scheme for the Cahn-Hilliard equation that satisfies the summation-by-parts simultaneous-approximation-term (SBP-SAT) property. The latter permits us to show that the discrete free-energy is bounded, and as a result, the scheme is provably stable. The scheme and the stability proof are presented for general curv

Pin Lyu, Yuxiang Liang, Zhibo Wang

In this paper, we study a fast and linearized finite difference method to solve the nonlinear time-fractional wave equation with multi fractional orders. We first propose a discretization to the multi-term Caputo derivative based on the recently established fast L2-1σ formula and a weighted approach. Then we apply the discretization to construct a fully fast

Mashetti Ravibabu

This paper derives bounds for the ratio of residual norms in the refined and Rayleigh- Ritz projection methods. To do this, it uses the Least squares and line search projection method proposed in [6]. The bound derived in this paper is less costly to compute. Further, it is practically useful to assess the superiority of the refined and the Rayleigh-Ritz pro

Mashetti Ravibabu

This paper derives a necessary and sufficient condition for the coincidence of Harmonic residual vectors and the residual vector in GMRES. The properties of the harmonic Ritz values at the stagnation of GMRES were described in the Proposition-4.2 of [1]. Necessary and sufficient conditions basing on Harmonic Ritz vectors for the stagnation have derived in th

Hannes Vandecasteele, Przemysław Zieliński, Giovanni Samaey

We discuss through multiple numerical examples the accuracy and efficiency of a micro-macro acceleration method for stiff stochastic differential equations (SDEs) with a time-scale separation between the fast microscopic dynamics and the evolution of some slow macroscopic state variables. The algorithm interleaves a short simulation of the stiff SDE with ext

Mohamed A. Bamakhrama, Alejandro Arrizabalaga, Frank Overman, Jean-Paul Smeets

Extreme Ultraviolet (EUV) photolithography is seen as the key enabler for increasing transistor density in the next decade. In EUV lithography, 13.5 nm EUV light is illuminated through a reticle, holding a pattern to be printed, onto a silicon wafer. This process is performed about 100 times per wafer, at a rate of over a hundred wafers an hour. During this

V. Denysiuk

The method of constructing spline classes in the form of trigonometric Fourier series whose coefficients have a certain decreasing order are considered. in turn, this decrement determines the number of continuous derivatives of sum of this series. By grouping members of this series according with the effect of overlaying and introducing a multiplier that pro

Amir Valibeygi, Abdulelah H. Habib, Raymond A. de Callafon

A robust power scheduling algorithm is proposed to schedule power flow between the main electricity grid and a microgird with solar energy generation and battery energy storage subject to uncertainty in solar energy production. To avoid over-conservatism in power scheduling while guaranteeing robustness against uncertainties, time-varying &#34;soft&#34; cons

Dhairya Malhotra, Antoine Cerfon, Lise-Marie Imbert-Gérard, Michael O&#39;Neil

We present a boundary integral equation solver for computing Taylor relaxed states in non-axisymmetric solid and shell-like toroidal geometries. The computation of Taylor states in these geometries is a key element for the calculation of stepped pressure stellarator equilibria. The integral representation of the magnetic field in this work is based on the ge

Glen Chou, Dmitry Berenson, Necmiye Ozay

We extend the learning from demonstration paradigm by providing a method for learning unknown constraints shared across tasks, using demonstrations of the tasks, their cost functions, and knowledge of the system dynamics and control constraints. Given safe demonstrations, our method uses hit-and-run sampling to obtain lower cost, and thus unsafe, trajectorie

W. Dahmen, R. P. Stevenson

This paper is concerned with a posteriori error bounds for linear transport equations and related questions of contriving corresponding adaptive solution strategies in the context of Discontinuous-Petrov-Galerkin schemes. After indicating our motivation for this investigation in a wider context the first major part of the paper is devoted to the derivation a

Mingjie Liao, Ping Lin

A dynamical atomistic chain to simulate mechanical properties of a one-dimensional material with zero temperature may be modelled by the molecular dynamics (MD) model. Because the number of particles (atoms) is huge for a MD model, in practice one often takes a much smaller number of particles to formulate a coarse-grained approximation. We shall mainly cons

Diogo Oliveira e Silva, Christoph Thiele, Pavel Zorin-Kranich

Among the class of functions with Fourier modes up to degree 30, constant functions are the unique real-valued maximizers for the endpoint Tomas-Stein inequality on the circle.

V. V. Vesselinov, M. K. Mudunuru, S. Karra, D. O. Malley

Analysis of reactive-diffusion simulations requires a large number of independent model runs. For each high-fidelity simulation, inputs are varied and the predicted mixing behavior is represented by changes in species concentration. It is then required to discern how the model inputs impact the mixing process. This task is challenging and typically involves

Ben Adcock, Yi Sui

We consider the sparse polynomial approximation of a multivariate function on a tensor product domain from samples of both the function and its gradient. When only function samples are prescribed, weighted $\ell^1$ minimization has recently been shown to be an effective procedure for computing such approximations. We extend this work to the gradient-augmente

Albert Haque, Michelle Guo, Prateek Verma, Li Fei-Fei

We propose spoken sentence embeddings which capture both acoustic and linguistic content. While existing works operate at the character, phoneme, or word level, our method learns long-term dependencies by modeling speech at the sentence level. Formulated as an audio-linguistic multitask learning problem, our encoder-decoder model simultaneously reconstructs