May 2020 arXiv papers — page 30

Felipe Linares, João P. G. Ramos

We prove a high-dimensional version of the Strichartz estimates for the unitary group associated to the free Zakharov--Kuznetsov equation. As a by--product, we deduce maximal estimates which allow us to prove local well-posedness for the generalized Zakharov--Kuznetsov equation in the whole subcritical case whenever $d \ge 4, k \ge 4,$ complementing the rece

Yifan Gao, Chien-Sheng Wu, Shafiq Joty, Caiming Xiong

The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions. Existing approaches are limited in their decision making due to struggles in extracting question-related rules and reasoning about them. In this paper, we present a new framework of conversational machine readin

Xin Man, Ernest Chan

Feature selection in machine learning is subject to the intrinsic randomness of the feature selection algorithms (for example, random permutations during MDA). Stability of selected features with respect to such randomness is essential to the human interpretability of a machine learning algorithm. We proposes a rank based stability metric called instability

Felipe Linares, João P. G. Ramos

We prove local well-posedness for the $L^2$ critical generalized Zakharov-Kuznetsov equation in $H^s, \, s \in (3/4,1).$ We also prove that the equation is "almost well-posedness" for initial data $u_0 \in H^s, \, s \in [1,2),$ in the sense that the solution belongs to a certain intersection $C([0,T] : H^s(\mathbb{R}^3)) \cap X^s_T$ and is unique within that

Yutaka Ohira

A new generation mechanism of the magnetic field in an inhomogeneous collisionless plasma with a beam component is proposed. We show that even though the current and charge neutralities are initially satisfied, the current neutrality is eventually violated if there is an inhomogeneity, so that the magnetic field is generated. By conducting ab initio two-dime

Jie Xu

We consider an infinitesimal volume where there are many rigid molecules of the same kind, and discuss the description and classification of the local anisotropy in this volume by tensors. First, we examine the symmetry of a rigid molecule, which is described by a point group in $SO(3)$. For each point group in $SO(3)$, we find the tensors invariant under th

Takeru Matsuda, William E. Strawderman

We investigate estimation of a normal mean matrix under the matrix quadratic loss. Improved estimation under the matrix quadratic loss implies improved estimation of any linear combination of the columns. First, an unbiased estimate of risk is derived and the Efron--Morris estimator is shown to be minimax. Next, a notion of \textit{matrix superharmonicity} f

Ramkumar Harikrishnakumar, Saideep Nannapaneni, Nam H. Nguyen, James E. Steck

Quantum annealing (QA) is a quantum computing algorithm that works on the principle of Adiabatic Quantum Computation (AQC), and it has shown significant computational advantages in solving combinatorial optimization problems such as vehicle routing problems (VRP) when compared to classical algorithms. This paper presents a QA approach for solving a variant V

Kaichao Jin, Hua Zhong, Yongdong Li, Fangwei Ye

Different from the Fermi surface of the type-I Dirac semimetal being a point, that of the type-II Dirac semimetal is a pair of crossing lines because the Dirac cone is tilted with open and hyperbolic isofrequency contours. As an optical analogy, type-II Dirac photonic lattices have been also designed. Here, we report type-II Dirac cones in Lieb-like photonic

Leslie Ching Ow Tiong, Jeongrae Kim, Sang Soo Han, Donghun Kim

The robust and automated determination of crystal symmetry is of utmost importance in material characterization and analysis. Recent studies have shown that deep learning (DL) methods can effectively reveal the correlations between X-ray or electron-beam diffraction patterns and crystal symmetry. Despite their promise, most of these studies have been limited

Yongrui Wang, Alexey Belyanin

Harmonic frequency combs, in which the lasing modes are separated by a period of tens of free spectral ranges from each other, have been recently discovered in quantum cascade lasers (QCLs). There is an ongoing debate how the harmonic combs can be formed and stable under continuous pumping. Here we reproduce the harmonic state of lasing in QCLs by space-time

Sima E. Borujeni, Nam H. Nguyen, Saideep Nannapaneni, Elizabeth C. Behrman

Bayesian Networks (BN) are probabilistic graphical models that are widely used for uncertainty modeling, stochastic prediction and probabilistic inference. A Quantum Bayesian Network (QBN) is a quantum version of the Bayesian network that utilizes the principles of quantum mechanical systems to improve the computational performance of various analyses. In th

Roba Bairakdar, Lu Cao, Melina Mailhot

The concept of univariate Range Value-at-Risk, presented by Cont et al. (2010), is extended in the multidimensional setting. Traditional risk measures are not well suited when dealing with heavy-tail distributions and infinite tail expectations. The multivariate definitions of robust truncated tail expectations are provided to overcome this problem. Robustne

Feilong Zhang

This correspondence proposes a kind of model-free adaptive control (MFAC) on the basis of full-form equivalent-dynamic-linearization model (EDLM) for the multivariable nonlinear system. Compared with the current MFAC, i) this control law does not have denominator, which is stemmed from the norm of the inverse matrix and it inevitably misses the coupling rela

Alfred L. Tiley, Sam P. Vaughan, John P. Stott, Roger L. Davies

We present the KMOS-CLASH (K-CLASH) survey, a K-band Multi-Object Spectrograph (KMOS) survey of the spatially-resolved gas properties and kinematics of 191 (predominantly blue) H$\alpha$-detected galaxies at $0.2 \lesssim z \lesssim 0.6$ in field and cluster environments. K-CLASH targets galaxies in four Cluster Lensing And Supernova survey with Hubble (CLAS

Yan Jiang, Eliza Cohn, Petr Vorobev, Enrique Mallada

With the decrease in system inertia, frequency security becomes an issue for power systems around the world. Energy storage systems (ESS), due to their excellent ramping capabilities, are considered as a natural choice for the improvement of frequency response following major contingencies. In this manuscript, we propose a new strategy for energy storage --

Matías Mendieta, Hamed Tabkhi

Pedestrian path prediction is an essential topic in computer vision and video understanding. Having insight into the movement of pedestrians is crucial for ensuring safe operation in a variety of applications including autonomous vehicles, social robots, and environmental monitoring. Current works in this area utilize complex generative or recurrent methods

Y. Fang, F. Tang, Y. R. Ruan, J. M. Zhang

Synergic effect of electronic correlation and spin-orbit coupling is an emerging topic in topological materials. Central to this rapidly developing area are the prototypes of strongly correlated heavy-fermion systems. Recently, some Ce-based compounds are proposed to host intriguing topological nature, among which the electronic properties of CeSb are still

Benjamin Bruce

We establish Fourier extension estimates for compact subsets of the hyperbolic hyperboloid in three dimensions via polynomial partitioning.

Sihwan Kim, Taejang Park

Scene text detection based on deep neural networks have progressed substantially over the past years. However, previous state-of-the-art methods may still fall short when dealing with challenging public benchmarks because the performances of algorithm are determined by the robust features extraction and components in network architecture. To address this iss

Jiaxuan Li, Yingcai Zheng, Xinding Fang

The moment tensors of a large portion of deep earthquakes show apparent non-double-couple (non-DC) components. Previously, the observed apparent non-DC values in deep earthquakes have been attributed to different mechanisms such as complex source processes or complicated source medium structures. In this paper, we focused on evaluating the second mechanism.

Hadrien Salat, Markus Schläpfer, Zbigniew Smoreda, Stefania Rubrichi

A reliable and affordable access to electricity has become one of the basic needs for humans and is, as such, at the top of the development agenda. It contributes to socio-economic development by transforming the whole spectrum of people's lives - food, education, health care; it spurs new economic opportunities and thus improves livelihoods. Using a compreh

Sisira Suresh, Orad Reshef, M. Zahirul Alam, Jeremy Upham

Optical materials with vanishing dielectric permittivity, known as epsilon-near-zero (ENZ) materials, have been shown to possess enhanced nonlinear optical responses in their ENZ region. These strong nonlinear optical properties have been firmly established in homogeneous materials; however, it is as of yet unclear whether metamaterials with effective optica

Jeremy P. Scott, Locke D. Spencer, Rosalind Hopwood, Ivan Valtchanov

The SPIRE FTS Spectral Feature Finder (FF), developed within the Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) instrument team, is an automated spectral feature fitting routine that attempts to find significant features in SPIRE FTS spectra. The $^3$P$_1$ - $^3$P$_0$ and $^3$P$_2$ - $^3$P$_1$ neutral carbon f

Chris S. Benson, N. Hladczuk, Locke D. Spencer, A. Robb

The ESA Herschel Spectral and Photometric Imaging Receiver (SPIRE) Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF) project is an automated spectral feature fitting routine developed within the SPIRE instrument team to extract all prominent spectral features from all publicly available SPIRE FTS observations. We present the extension of the

Jeremy P. Scott, Natalia Hladczuk, Locke D. Spencer, Ivan Valtchanov

The Herschel SPIRE FTS Spectral Feature Finder (FF) detects significant spectral features within SPIRE spectra and employs two routines, and external references, to estimate source radial velocity. The first routine is based on the identification of rotational CO emission, the second cross-correlates detected features with a line template containing most of

R. Hopwood, I. Valtchanov, Locke D. Spencer, J. P. Scott

We provide a detailed description of the Herschel-SPIRE Fourier Transform Spectrometer (FTS) Spectral Feature Finder (FF). The FF is an automated process designed to extract significant spectral features from SPIRE FTS data products. Optimising the number of features found in SPIRE-FTS spectra is challenging. The wide SPIRE-FTS frequency range (447-1568 GHz)

Kunal Sharma, M. Cerezo, Lukasz Cincio, Patrick J. Coles

Several architectures have been proposed for quantum neural networks (QNNs), with the goal of efficiently performing machine learning tasks on quantum data. Rigorous scaling results are urgently needed for specific QNN constructions to understand which, if any, will be trainable at a large scale. Here, we analyze the gradient scaling (and hence the trainabil

Prakash Belkale

We give a construction which produces irreducible complex rigid local systems on $\Bbb{P}_{\Bbb{C}}^1-\{p_1,\dots,p_s\}$ via quantum Schubert calculus and strange duality. These local systems are unitary and arise from a study of vertices in the polytopes controlling the multiplicative eigenvalue problem for the special unitary groups $\operatorname{SU}(n)$

Chengyue Wang, Qi Gao, Biao Wang

Compressing complex flows into a tangle of vortex filaments is the basic implication of the classical notion of the vortex representation. Various vortex identification criteria have been proposed to extract the vortex filaments from available velocity fields, which is an essential procedure in the practice of the vortex representation. This work focuses on

Celia Escamilla-Rivera, A. Hernández-Almada, Miguel A. García-Aspeitia, V. Motta

In this paper, we study a particular modified gravity Equation of State, the so-called Jaime-Jaber-Escamilla, that emerges from the first gravity modified action principle and can reproduce three cosmological viable $f(R)$ theories: the Starobinsky, Hu-Sawicki, and Exponential models . This EoS is a suitable candidate to reproduce the dynamical dark energy b

Ali Eshragh, Saed Alizamir, Peter Howley, Elizabeth Stojanovski

The novel Corona Virus COVID-19 arrived on Australian shores around 25 January 2020. This paper presents a novel method of dynamically modeling and forecasting the COVID-19 pandemic in Australia with a high degree of accuracy and in a timely manner using limited data; a valuable resource that can be used to guide government decision-making on societal restri

Vladimir Belavin, Abay Zhakenov

AGT allows one to compute conformal blocks of d = 2 CFT for a large class of chiral CFT algebras. This is related to the existence of a certain orthogonal basis in the module of the (extended) chiral algebra. The elements of the basis are eigenvectors of a certain integrable model, labeled in general by N-tuples of Young diagrams. In particular, it was found

Ioannis Sfyrakis, Thomas Gross

Remote attestation schemes have been utilized for assuring the integrity of a network node to a remote verifier. In recent years, a number of remote attestation schemes have been proposed for various contexts such as cloud computing, Internet of Things (IoTs) and critical network infrastructures. These attestation schemes provide a different perspective in t

Samuel C. Fletcher

There are two classes of topologies most often placed on the space of Lorentz metrics on a fixed manifold. As I interpret a complaint of R. Geroch [Relativity, 259 (1970); Gen. Rel. Grav., 2, 61 (1971)], however, neither of these standard classes correctly captures a notion of global spacetime similarity. In particular, Geroch presents examples to illustrate

Bin Han, Ran Lu

Generalizing wavelets by adding desired redundancy and flexibility,framelets are of interest and importance in many applications such as image processing and numerical algorithms. Several key properties of framelets are high vanishing moments for sparse multiscale representation, fast framelet transforms for numerical efficiency, and redundancy for robustnes

Guanhua Liu, Mathav Murugan

We prove that the parabolic Harnack inequality implies the existence of jump kernel for symmetric pure jump process. This allows us to remove a technical assumption on the jumping measure in the recent characterization of the parabolic Harnack inequality for pure jump processes by Chen, Kumagai and Wang. The key ingredients of our proof are the L\'evy system

Masanobu Kaneko, Masato Kuwata

An elliptic curve may be immersed in ${\mathbf{P}}^{N-1}$ as a degree $N$ curve using level $N$ structure. In the case where $N$ is odd, there are well known classical results dating back to Bianchi and Klein. In this paper we study the case of even $N$ in some detail. In particular, over the complex number field, we define an immersion using suitably chosen

Florian Aigner, Ilse Fischer, Matjaž Konvalinka, Philippe Nadeau

We study the Schur polynomial expansion of a family of symmetric polynomials related to the refined enumeration of alternating sign matrices with respect to their inversion number, complementary inversion number and the position of the unique $1$ in the top row. We prove that the expansion can be expressed as a sum over totally symmetric plane partitions and

Ioannis Sfyrakis, Thomas Gross

Current cloud and network infrastructures do not employ privacy-preserving methods to protect their assets. Anonymous credential schemes are a cryptographic building block that enables the certification of data structures and prove properties over their representations without disclosing the innards of their data structures in zero-knowledge. The GRaph Signa

Massimo Marchiori

Background: Without proven effect treatments and vaccines, Social Distancing is the key protection factor against COVID-19. Social distancing alone should have been enough to protect again the virus, yet things have gone very differently, with a big mismatch between theory and practice. What are the reasons? A big problem is that there is no actual social di

Thomas Creutzig, Matthew Rupert

We construct families of commutative (super) algebra objects in the category of weight modules for the unrolled restricted quantum group $\overline{U}_q^H(\mfg)$ of a simple Lie algebra $\mfg$ at roots of unity, and study their categories of local modules. We determine their simple modules and derive conditions for these categories being finite, non-degenera

Yuchuan Gou, Qiancheng Wu, Minghao Li, Bo Gong

In this paper, we propose a novel generative network (SegAttnGAN) that utilizes additional segmentation information for the text-to-image synthesis task. As the segmentation data introduced to the model provides useful guidance on the generator training, the proposed model can generate images with better realism quality and higher quantitative measures compa

Farhad Akhbardeh, Travis Desell, Marcos Zampieri

Maintenance record logbooks are an emerging text type in NLP. They typically consist of free text documents with many domain specific technical terms, abbreviations, as well as non-standard spelling and grammar, which poses difficulties to NLP pipelines trained on standard corpora. Analyzing and annotating such documents is of particular importance in the de

Shashank Sonkar, Andrew E. Waters, Andrew S. Lan, Phillip J. Grimaldi

Knowledge tracing (KT) models, e.g., the deep knowledge tracing (DKT) model, track an individual learner's acquisition of skills over time by examining the learner's performance on questions related to those skills. A practical limitation in most existing KT models is that all questions nested under a particular skill are treated as equivalent observations o

Yan Cao, Guantao Chen, Songling Shan

Let $G$ be a simple graph with maximum degree $\Delta$. A classic result of Vizing shows that $\chi'(G)$, the chromatic index of $G$, is either $\Delta$ or $\Delta+1$. We say $G$ is of \emph{Class 1} if $\chi'(G)=\Delta$, and is of \emph{Class 2} otherwise. A graph $G$ is \emph{$\Delta$-critical} if $\chi'(G)=\Delta+1$ and $\chi'(H)<\Delta+1$ for every prope

Eve Armstrong, Manuela Runge, Jaline Gerardin

We demonstrate the ability of statistical data assimilation to identify the measurements required for accurate state and parameter estimation in an epidemiological model for the novel coronavirus disease COVID-19. Our context is an effort to inform policy regarding social behavior, to mitigate strain on hospital capacity. The model unknowns are taken to be:

Philippe Schucht, Hee Ryung Lee, Mohammed Hachem Mezouar, Ekkehard Hewer

Identification of white matter fiber tracts of the brain is crucial for delineating the tumor border during neurosurgery. A custom-built Mueller polarimeter was used in reflection configuration for the wide-field imaging of thick section of fixed human brain and fresh calf brain. The experimental images of azimuth of the fast optical axis of linear birefring

Haitian Zheng, Kefei Wu, Jong-Hwi Park, Wei Zhu

With the growth of online shopping for fashion products, accurate fashion recommendation has become a critical problem. Meanwhile, social networks provide an open and new data source for personalized fashion analysis. In this work, we study the problem of personalized fashion recommendation from social media data, i.e. recommending new outfits to social medi

Gang Lu, Yuanfeng Jin, Choonkil Park

The main purpose of this paper is to determine the solution of generalized convex set-valued mappings satisfying certain functional equation. Some conclusions of stability of set-valued functional equations are obtained.

Douglas N. Arnold, Kaibo Hu

This paper is concerned with the derivation and properties of differential complexes arising from a variety of problems in differential equations, with applications in continuum mechanics, relativity, and other fields. We present a systematic procedure which, starting from well-understood differential complexes such as the de Rham complex, derives new comple

Douglas A. Torrance, Nick Vannieuwenhoven

The Chow rank of a form is the length of its smallest decomposition into a sum of products of linear forms. For a generic form, this corresponds to finding the smallest secant variety of the Chow variety which fills the ambient space. We determine the Chow rank of generic cubics and quaternary forms by proving nondefectivity of all involved secant varieties.

A. Arefiev, D. Stark, T. Toncian, M. Murakami

One of the paradigm-shifting phenomena triggered in laser-plasma interactions at relativistic intensities is the so-called relativistic transparency. As the electrons become heated by the laser to relativistic energies, the plasma becomes transparent to the laser light even though the plasma density is sufficiently high to reflect the laser pulse in the non-

F. Tuitje, P. Martínez Gil, T. Helk, J. Gautier

From fusion dynamics in stars, to terrestrial lightning events, to new prospects of energy production or novel light sources, hot dense plasmas are of importance for an array of physical phenomena. Due to a plethora of correlations in highly excited matter, direct probing of isolated dynamics remains challenging. Here, the 32.8-nm emission of a high-harmonic

Shuhan Yuan, Xintao Wu

Insider threats, as one type of the most challenging threats in cyberspace, usually cause significant loss to organizations. While the problem of insider threat detection has been studied for a long time in both security and data mining communities, the traditional machine learning based detection approaches, which heavily rely on feature engineering, are ha

Dmitriy Dmitrishin, Andrey Smorodin, Alex Stokolos

Extremal problems for typically real polynomials go back to a paper by W. W. Rogosinski and G. Szeg\H{o}, where a number of problems were posed, which were partially solved by using orthogonal polynomials. Since then, not too many new results on extremal properties of typically real polynomials have been obtained. Fundamental work in this direction is due to

Shaoming Guo, Changkeun Oh

We prove $L^p$ bounds for the Fourier extension operators associated to surfaces in $\mathbb{R}^3$ with negative Gaussian curvatures for every $p>3.25$.

Elisabeth Remm

We study deformation quantization of nonassociative algebras whose associator satisfies some symmetric relations. This study is expanded to a larger class of nonassociative algebras includind Leibniz algebras. We apply also to this class the rule of polarization-depolarization.

Alessandro Lunghi, Stefano Sanvito

We present a first-principles investigation of spin-phonon relaxation in a molecular crystal of Co(II) single-ion magnets. Our study combines electronic structure calculations with machine-learning force fields and unravels the nature of both the Orbach and the Raman relaxation channels in terms of atomistic processes. We find that although both mechanisms a

Mikhail Odit, Kirill Koshelev, Sergey Gladyshev, Konstantin Ladutenko

Electromagnetic response of dielectric resonators with high refractive index is governed by optically induced electric and magnetic Mie resonances facilitating confinement of light with the amplitude enhancement. However, strong subwavelength trapping of light was associated traditionally only with plasmonic or epsilon-near-zero structures which however suff

Thomas Wiegart, Francesco Da Ros, Metodi Plamenov Yankov, Fabian Steiner

Probabilistic shaping for intensity modulation and direct detection (IM/DD) links is discussed and a peak power constraint determined by the limited modulation extinction ratio (ER) of optical modulators is introduced. The input distribution of 4-ary unipolar pulse amplitude modulation (PAM) symbols is optimized for short-reach transmission links without opt

Jonas Béal, Aurélien Latouche

The development of high-throughput sequencing and targeted therapies has led to the emergence of personalized medicine: a patient's molecular profile or the presence of a specific biomarker of drug response will correspond to a treatment recommendation made either by a physician or by a treatment assignment algorithm. The growing number of such algorithms ra

Gavin P. Lamb, Andrew J. Levan, Nial R. Tanvir

Energy injection into the external shock system that generates the afterglow to a gamma-ray burst (GRB) can result in a re-brightening of the emission. Here we investigate the off-axis view of a re-brightened refreshed shock afterglow. We find that the afterglow light-curve, when viewed from outside of the jet opening angle, could be characterised by a slow

Scarlet J. Park, William W. Ja

Factors that mediate ethanol preference in Drosophila melanogaster are not well understood. A major confound has been the use of diverse methods to estimate ethanol consumption. We measured fly consumptive ethanol preference on base diets varying in nutrients, taste, and ethanol concentration. Both sexes showed ethanol preference that was abolished on high n

Marek Karliner, Jonathan L. Rosner

Recently LHCb reported the discovery of four extremely narrow excited $\Omega_b$ baryons decaying into $\Xi_b^0 K^-$. We interpret these baryons as bound states of a $b$-quark and a $P$-wave $ss$-diquark. For such a system there are exactly five possible combinations of spin and orbital angular momentum. We predict two of spin 1/2, two of spin 3/2, and one o

Bing He, Caleb Ziems, Sandeep Soni, Naren Ramakrishnan

The spread of COVID-19 has sparked racism and hate on social media targeted towards Asian communities. However, little is known about how racial hate spreads during a pandemic and the role of counterspeech in mitigating this spread. In this work, we study the evolution and spread of anti-Asian hate speech through the lens of Twitter. We create COVID-HATE, th

Fabian Pokorny, Chi Zhang, Gerard Higgins, Markus Hennrich

Highly excited Rydberg states are usually extremely polarizable and exceedingly sensitive to electric fields. Because of this Rydberg ions confined in electric fields have state-dependent trapping potentials. We engineer a Rydberg state that is insensitive to electric fields by coupling two Rydberg states with static polarizabilities of opposite sign, in thi

Mehul P. Makwana, Richard Wiltshaw, Sébastien Guenneau, Richard V. Craster

We create hybrid topological-photonic localisation of light by introducing concepts from the field of topological matter to that of photonic crystal fiber arrays. S-polarized obliquely propagating electromagnetic waves are guided by hexagonal, and square, lattice topological systems along an array of infinitely conducting fibers. The theory utilises perfectl

Terence Broad, Frederic Fol Leymarie, Mick Grierson

We introduce a new framework for manipulating and interacting with deep generative models that we call network bending. We present a comprehensive set of deterministic transformations that can be inserted as distinct layers into the computational graph of a trained generative neural network and applied during inference. In addition, we present a novel algori

Takanori Fujiwara, Jian Zhao, Francine Chen, Yaoliang Yu

Identifying unique characteristics in a network through comparison with another network is an essential network analysis task. For example, with networks of protein interactions obtained from normal and cancer tissues, we can discover unique types of interactions in cancer tissues. This analysis task could be greatly assisted by contrastive learning, which i

Cristián Bravo, María Óskarsdóttir

In this paper we present a novel algorithm to study the evolution of credit risk across complex multilayer networks. Pagerank-like algorithms allow for the propagation of an influence variable across single networks, and allow quantifying the risk single entities (nodes) are subject to given the connection they have to other nodes in the network. Multilayer

Alexander Yu. Kostinskiy, Andrei Vlasov, Mikhail Fridman

In this supplementary article to Kostinkskiy et al. (2020), we evaluate how it is possible to initiate and synchronize the start of a large number of streamer flashes, which can provide a powerful VHF signal, in the time range of ~1-3 us. As described in Kostinskiy et al. (2020), we will assume streamer flashes occur due to the voluminous network of 'air ele

P. Medvedev, I. Khabibullin, S. Sazonov

The X-ray spectrum of the Galactic microquasar SS 433 contains a rich set of emission lines of highly ionized atoms of heavy elements whose significant Doppler shift leaves no doubt that they are produced in collimated relativistic jets of outflowing material. We have performed a systematic analysis of the high-resolution X-ray spectra obtained by the Chandr

Daqian Sun, Martin T. Wells

We consider the matrix completion problem of recovering a structured low rank matrix with partially observed entries with mixed data types. Vast majority of the solutions have proposed computationally feasible estimators with strong statistical guarantees for the case where the underlying distribution of data in the matrix is continuous. A few recent approac

Julio Michael Stern, Carlos Alberto de Braganca Pereira, Celma de Oliveira Ribeiro, Cibele Dunder

Optimization and Stochastic Processes Applied to Economy and Finance -- is the name of this book translated to English; It has been used at the IME-USP - The Institute of Mathematics and Statistics of the University of Sao Paulo, since 1993. Contents: Ch.1: Linear Programming; Ch.2: Non-Linear Programming; Ch.3: Quadratic Programming; Ch.4: Markowitz Model;

Willow Ahrens, Erik G. Boman

The Variable Block Row (VBR) format is an influential blocked sparse matrix format designed for matrices with shared sparsity structure between adjacent rows and columns. VBR groups adjacent rows and columns, storing the resulting blocks that contain nonzeros in a dense format. This reduces the memory footprint and enables optimizations such as register bloc

Johannes Köhler, Matthias A. Müller, Frank Allgöwer

We present a model predictive control (MPC) framework to solve the constrained nonlinear output regulation problem. The main feature of the proposed framework is that the application does not require the solution to classical regulator (Francis-Byrnes-Isidori) equations or any other offline design procedure. In particular, the proposed formulation simply min

Mohammad K. Ebrahimpour, Sara Schneider, David C. Noelle, Christopher T. Kello

Acoustic analyses of infant vocalizations are valuable for research on speech development as well as applications in sound classification. Previous studies have focused on measures of acoustic features based on theories of speech processing, such spectral and cepstrum-based analyses. More recently, end-to-end models of deep learning have been developed to ta

Manuel Mager, Katharina Kann

In this paper, we present the systems of the University of Stuttgart IMS and the University of Colorado Boulder (IMS-CUBoulder) for SIGMORPHON 2020 Task 2 on unsupervised morphological paradigm completion (Kann et al., 2020). The task consists of generating the morphological paradigms of a set of lemmas, given only the lemmas themselves and unlabeled text. O

Sanjar Shaymatov, Jaroslav Vrba, Daniele Malafarina, Bobomurat Ahmedov

We investigate particle motion in the vicinity of a $4D$ Einstein-Gauss-Bonnet (EGB) black hole immersed in external asymptotically uniform magnetic field. It is well known that magnetic fields can strongly affect charged particle motion in the black hole vicinity due to the Lorenz force. We find that the presence of the Gauss-Bonnet (GB) coupling gives rise

Petar Radanliev, David De Roure, Max Van Kleek

What makes cyber risks arising from connected systems challenging during the management of a pandemic? Assuming that a variety of cyber-physical systems are already operational-collecting, analyzing, and acting on data autonomously-what risks might arise in their application to pandemic management? We already have these systems operational, collecting, and a

Frank Robinson, Joel Tanner, Sarbani Basu

This paper presents the results of a set of radiative hydrodynamic (RHD) simulations of convection in the near-surface regions of a rapidly rotating star. The simulations use microphysics consistent with stellar models, and include the effects of realistic convection and radiative transfer. We find that the overall effect of rotation is to reduce the strengt

Mohit Srinivasan, Cesar Santoyo, Samuel Coogan

In this paper, a method to achieve smooth transitions between sequential reachability tasks for a continuous time mobile robotic system is presented. Control barrier functions provide formal guarantees of forward invariance of safe sets and finite-time reachability and are able to enforce task execution. Barrier functions used in quadratic programs result in

B. Benson, W. D. Pan, A. Prasad, G. A. Gary

With recent advances in the field of machine learning, the use of deep neural networks for time series forecasting has become more prevalent. The quasi-periodic nature of the solar cycle makes it a good candidate for applying time series forecasting methods. We employ a combination of WaveNet and LSTM neural networks to forecast the sunspot number using the

Omar Amer, Walter O. Krawec, Bing Wang

As quantum key distribution becomes increasingly practical, questions of how to effectively employ it in large-scale networks and over large distances becomes increasingly important. To that end, in this work, we model the performance of the E91 entanglement based QKD protocol when operating in a network consisting of both quantum repeaters and trusted nodes

K. H. Leung, I. Majewska, H. Bekker, C. -H. Lee

Optical trapping of molecules with long coherence times is crucial for many protocols in quantum information and metrology. However, the factors that limit the lifetimes of the trapped molecules remain elusive and require improved understanding of the underlying molecular structure. Here we show that measurements of vibronic line strengths in weakly and deep

Anna Keselman, Leon Balents, Oleg A. Starykh

We study the transverse dynamical susceptibility of an antiferromagnetic spin$-1/2$ chain in presence of a longitudinal Zeeman field. In the low magnetization regime in the gapless phase, we show that the marginally irrelevant backscattering interaction between the spinons creates a non-zero gap between two branches of excitations at small momentum. We furth

Marzieh Fadaee, Christof Monz

Recent works have shown that Neural Machine Translation (NMT) models achieve impressive performance, however, questions about understanding the behavior of these models remain unanswered. We investigate the unexpected volatility of NMT models where the input is semantically and syntactically correct. We discover that with trivial modifications of source sent

Serdar Charyyev, Tonghe Wang, Yang Lei, Beth Ghavidel

Purpose: Dual-energy CT (DECT) has been shown to derive stopping power ratio (SPR) map with higher accuracy than conventional single energy CT (SECT) by obtaining the energy dependence of photon interactions. However, DECT is not as widely implemented as SECT in proton radiation therapy simulation. This work presents a learning-based method to synthetize DEC

Yunseong Cho, Jinseok Choi, Brian L. Evans

In this work, we present a solution for coordinated beamforming and power allocation when base stations employ a massive number of antennas equipped with low-resolution analog-to-digital and digital-to-analog converters. We address total power minimization problems of the coarsely quantized uplink (UL) and downlink (DL) communication systems with target sign

Monia Capanna, Jean C. Nakasato, Marcone C. Pereira, Julio D. Rossi

In this paper we consider the homogenization problem for a nonlocal equation that involve different smooth kernels. We assume that the spacial domain is divided into a sequence of two subdomains $A_n \cup B_n$ and we have three different smooth kernels, one that controls the jumps from $A_n$ to $A_n$, a second one that controls the jumps from $B_n$ to $B_n$

Oscar Pasarin, Arkady A. Tseytlin

We discuss possible application of classical double copy procedure to construction of a generalisation of the Schwarzschild metric starting from an $\alpha'$-corrected open string analogue of Coulomb solution. The latter is approximated by a point-like charge solution of the Born-Infeld action, which represents the open string effective action for an abelian

Davide Viviano, Jelena Bradic

One of the major concerns of targeting interventions on individuals in social welfare programs is discrimination: individualized treatments may induce disparities across sensitive attributes such as age, gender, or race. This paper addresses the question of the design of fair and efficient treatment allocation rules. We adopt the non-maleficence perspective

Ye Hu, Mingzhe Chen, Walid Saad, H. Vincent Poor

In this paper, the design of an optimal trajectory for an energy-constrained drone operating in dynamic network environments is studied. In the considered model, a drone base station (DBS) is dispatched to provide uplink connectivity to ground users whose demand is dynamic and unpredictable. In this case, the DBS's trajectory must be adaptively adjusted to s

Ya-Fen Hsu, Jung-Jung Su

Huang's experiment [Phys. Rev. Lett. $\bf 109$, 156802 (2012)] found, in the quantum Hall bilayer of the Corbino geometry, the interlayer tunneling currents at two edges are coupled to each other and one of two tunneling currents is referred to as the compensating current of the other. Our another work[arXiv:2006.15329] has explained this exotic coupling phe

Dongdong She, Rahul Krishna, Lu Yan, Suman Jana

Fuzzing is a widely used technique for detecting software bugs and vulnerabilities. Most popular fuzzers generate new inputs using an evolutionary search to maximize code coverage. Essentially, these fuzzers start with a set of seed inputs, mutate them to generate new inputs, and identify the promising inputs using an evolutionary fitness function for furthe

Francesca A. Pearce, Scott T. Kay, David J. Barnes, Yannick M. Bahe

The abundance and distribution of metals in galaxy clusters contains valuable information about their chemical history and evolution. By looking at how metallicity evolves with redshift, it is possible to constrain the different metal production channels. We use the C-EAGLE clusters, a sample of 30 high resolution ($m_{gas} \simeq 1.8\times 10^{6}$ M$_{\odot

Ioannis Gallos, Evangelos Galaris, Constantinos Siettos

We construct embedded functional connectivity networks (FCN) from benchmark resting-state functional magnetic resonance imaging (rsfMRI) data acquired from patients with schizophrenia and healthy controls based on linear and nonlinear manifold learning algorithms, namely, Multidimensional Scaling (MDS), Isometric Feature Mapping (ISOMAP) and Diffusion Maps.

Luigi Delle Rose, Carlo Marzo, Luca Marzola

We put forward the framework of simplified leptoquark models: simple extensions of the Standard Model that serve as benchmarks to test the interactions of leptons with new colored degrees of freedom considered, for instance, in leptoquark or grand unification models. As a first application of the scheme, we analyze the power of precision lepton observables b

Qidong He, Scott A. Taylor

To each link $L$ in $S^3$ we associate a collection of certain labelled directed trees, called width trees. We interpret some classical and new topological link invariants in terms of these width trees and show how the geometric structure of the width trees can bound the values of these invariants from below. We also show that each width tree is associated w