January 2019 arXiv papers — page 16

Mathieu Huot, Sam Staton

We argue that notions in quantum theory should have universal properties in the sense of category theory. We consider the completely positive trace preserving (CPTP) maps, the basic notion of quantum channel. Physically, quantum channels are derived from pure quantum theory by allowing discarding. We phrase this in category theoretic terms by showing that th

Robert Furber

From every pair of adjoint functors it is possible to produce a (possibly trivial) equivalence of categories by restricting to the subcategories where the unit and counit are isomorphisms. If we do this for the adjunction between effect algebras and abstract convex sets, we get the surprising result that the equivalent subcategories consist of reflexive orde

Samantha K. Fairchild

We compute higher moments of the Siegel--Veech transform over quotients of $SL(2,\mathbb{R})$ by the Hecke triangle groups. After fixing a normalization of the Haar measure on $SL(2,\mathbb{R})$ we use geometric results and linear algebra to create explicit integration formulas which give information about densities of $k$-tuples of vectors in discrete subse

Andrew Fagan, Ross Duncan

We present a system of equations between Clifford circuits, all derivable in the ZX-calculus, and formalised as rewrite rules in the Quantomatic proof assistant. By combining these rules with some non-trivial simplification procedures defined in the Quantomatic tactic language, we demonstrate the use of Quantomatic as a circuit optimisation tool. We prove th

Dongqi Han, Kenji Doya, Jun Tani

Recurrent neural networks (RNNs) for reinforcement learning (RL) have shown distinct advantages, e.g., solving memory-dependent tasks and meta-learning. However, little effort has been spent on improving RNN architectures and on understanding the underlying neural mechanisms for performance gain. In this paper, we propose a novel, multiple-timescale, stochas

Hao Ren, Jianlin Su, Hong Lu

Image classification is a challenging problem which aims to identify the category of object in the image. In recent years, deep Convolutional Neural Networks (CNNs) have been applied to handle this task, and impressive improvement has been achieved. However, some research showed the output of CNNs can be easily altered by adding relatively small perturbation

Jinyun Yan, Birjodh Tiwana, Souvik Ghosh, Haishan Liu

Organic updates (from a member's network) and sponsored updates (or ads, from advertisers) together form the newsfeed on LinkedIn. The newsfeed, the default homepage for members, attracts them to engage, brings them value and helps LinkedIn grow. Engagement and Revenue on feed are two critical, yet often conflicting objectives. Hence, it is important to desi

Hassan Alkhayuon, Peter Ashwin, Laura C Jackson, Courtney Quinn

The Atlantic Meridional Overturning Circulation (AMOC) transports substantial amounts of heat into the North Atlantic sector, and hence is of very high importance in regional climate projections. The AMOC has been observed to show multi-stability across a range of models of different complexity. The simplest models find a bifurcation associated with the AMOC

Allal Ghanmi

In this paper, we are concerned with the S-polyregularity the regular dot product of slice regular functions. We prove that the product of a slice regular function and right quaternionic polynomial function is a S-polyregular function and we determinate its exact order. The general case of the product of any two slice regular functions is also discussed. In

Guangnan Zhou, Alejandra V. Cuervo Covian, Kwang Hong Lee, Chuan Seng Tan

Ge-on-Si structures in-situ doped with phosphorus or arsenic via metal organic chemical vapor deposition (MOCVD) were investigated. Surface roughness, strain, threading dislocation desnity, Si-Ge interdiffusion, dopant diffusion, and photoluminescence were characterized to study the impacts of defect annealing and Si substrate offcut effects on the Ge film q

Hongjie Dong, Doyoon Kim

In this paper, we establish $L_p$ estimates and solvability for time fractional divergence form parabolic equations in the whole space when leading coefficients are merely measurable in one spatial variable and locally have small mean oscillations with respect to the other variables. The corresponding results for equations on a half space are also derived.

Yanhao Wang, Yuchen Li, Kian-Lee Tan

Massive volumes of data continuously generated on social platforms have become an important information source for users. A primary method to obtain fresh and valuable information from social streams is \emph{social search}. Although there have been extensive studies on social search, existing methods only focus on the \emph{relevance} of query results but i

Thomas Alexander, Henning O. Back, Walter Bonivento, Mark Boulay

In response to the growing need for low-radioactivity argon, community experts and interested parties came together for a 2-day workshop to discuss the worldwide low-radioactivity argon needs and the challenges associated with its production and characterization. Several topics were covered: experimental needs and requirements for low-radioactivity argon, th

Jae-Woo Lee

We present a multiple stellar population (MSP) study of the globular cluster (GC) NGC~6752. We show that our new photometric CN index accurately traces the CN and the nitrogen abundances in cool giants, finding the discrete double red giant branch (RGB) and asymptotic giant branch (AGB) sequences with number ratios between the CN-weak and the CN-strong popul

Sookyung Kim, Jungmin M. Lee, Jiwoo Lee, Jihoon Seo

Polluting fine dusts in South Korea which are mainly consisted of biomass burning and fugitive dust blown from dust belt is significant problem these days. Predicting concentrations of fine dust particles in Seoul is challenging because they are product of complicate chemical reactions among gaseous pollutants and also influenced by dynamical interactions be

Guangrui, Xia

Group IV semiconductor alloys and heterostructures such as SiGe, GeSn, Ge/Si and SiGe:C have been widely used and under extensive research for applications in major microelectronic and photonic devices. In the growth and processing of these materials, nanometer scale interdiffusion happens that are generally undesirable for device performance. With higher Ge

E. S. Bozin, W. G. Yin, R. J. Koch, M. Abeykoon

Fundamental electronic principles underlying all transition metal compounds are the symmetry and filling of the $d$-electron orbitals and the influence of this filling on structural configurations and responses. Here we use a sensitive local structural technique, x-ray atomic pair distribution function analysis, to reveal the presence of fluctuating local-st

Jiawen Li, Xinwu Cao

The large-scale magnetic field threading an accretion disk plays an important role in launching jets/outflows. The field may probably be advected inwards by the plasma in the accretion disk from the ambient environment (interstellar medium or a companion star). It has been suggested that the external field can be efficiently dragged inwards in a thin disk wi

Yessenia Olguin-Trejo, Omar Perez-Figueroa, Ricardo Perez-Martinez, Saul Ramos-Sanchez

Additional Abelian gauge interactions are generic to string compactifications. In heterotic string models, gauge coupling unification of such forces and other gauge interactions is natural due to their common origin. In this letter we study systematically the 1-loop running of the coupling constants in effective vacua emerging from Z8 heterotic orbifold comp

J. Sanchez-Bermudez, A. Alberdi, R. Schödel, W. Brandner

Context. Colliding winds in massive binaries are able to accelerate particles up to relativistic speeds as the result of the interaction between the winds of the different stellar components. HD 167971 exhibits this phenomenology which makes it a strong radio source. Aims. We aim at characterizing the morphology of the radio emission and its dependence on th

Guangcong Wang, Jianhuang Lai, Zhenyu Xie, Xiaohua Xie

Modeling the underlying person structure for person re-identification (re-ID) is difficult due to diverse deformable poses, changeable camera views and imperfect person detectors. How to exploit underlying person structure information without extra annotations to improve the performance of person re-ID remains largely unexplored. To address this problem, we

Eneet Kaur, Saikat Guha, Mark M. Wilde

We consider discrete-modulation protocols for continuous-variable quantum key distribution (CV-QKD) that employ a modulation constellation consisting of a finite number of coherent states and that use a homodyne or a heterodyne-detection receiver. We establish a security proof for collective attacks in the asymptotic regime, and we provide a formula for an a

Di Xu, Manjing Fang, Xia Hong, Junbin Gao

A general framework of least squares support vector machine with low rank kernels, referred to as LR-LSSVM, is introduced in this paper. The special structure of low rank kernels with a controlled model size brings sparsity as well as computational efficiency to the proposed model. Meanwhile, a two-step optimization algorithm with three different criteria is

Wei Jiang, Adam Bowers, Dan Lin

Social networks, instant messages and file sharing systems are common communication means among friends, families, coworkers, etc. Due to concerns of personal privacy, identify thefts, data misuse, freedom of speech and government surveillance, online social or communication networks have provided various options for a user to guard or control his or her per

Stanislav Boldyrev, Nuno F. Loureiro

In a weakly collisional, low-electron-beta plasma, large-scale Alfv\'en turbulence transforms into inertial kinetic-Alfv\'en turbulence at scales smaller than the ion microscale (gyroscale or inertial scale). We propose that at such kinetic scales, the nonlinear dynamics tend to organize turbulent eddies into thin current sheets, consistent with the existenc

Xiaojin Ding, Yulong Zou, Xiaoshu Chen, Xiaojun Wang

We study the physical-layer security of a multiple source-destination (SD) pairs coexisting wireless network in the face of an eavesdropper, where an eavesdropper intends to wiretap the signal transmitted by the SD pairs. In order to protect the wireless transmission against eavesdropping, we propose a cooperation framework relying on two stages. Specificall

Shenyu Liu, Mohamed Ali Belabbas

We propose a novel method for motion planning and illustrate its implementation on several canonical examples. The core novel idea underlying the method is to define a metric for which a path of minimal length is an admissible path, that is path that respects the various constraints imposed by the environment and the physics of the system on its dynamics. To

Konstantin E. Dorfman, Shahaf Asban, Lyuzhou Ye, Daeheum Cho

Homodyne X-ray diffraction signals produced by classical light and classical detectors are given by the modulus square of the charge density in momentum space $\left|\sigma(\mathbf{q})\right|^{2}$, missing its phase which is required in order to invert the signal to real space. We show that quantum detection of the radiation field yields a linear diffraction

Bin Gao, Tong Chen, David W. Tam, Chien-Lung Huang

A quantum spin liquid (QSL) is a state of matter where unpaired electrons' spins in a solid are quantum entangled, but do not show magnetic order in the zero-temperature limit. Because such a state may be important to the microscopic origin of high-transition temperature superconductivity and useful for quantum computation, the experimental realization of QS

Ramiz Aktar, Anuj Nandi, Santabrata Das

We study the global accretion-ejection solutions around a rotating black hole considering three widely accepted pseudo-Kerr potentials that satisfactorily mimic the space-time geometry of rotating black holes. We find that all the pseudo potentials provide standing shock solutions for large range of flow parameters. We identify the effective region of the sh

Xing Gu

In the integral cohomology ring of the classifying space of the projective linear group $PGL_n$ (over $\mathbb{C}$), we find a collection of $p$-torsions $y_{p,k}$ of degree $2(p^{k+1}+1)$ for any odd prime divisor $p$ of $n$, and $k\geq 0$. If in addition, $p^2\nmid n$, there are $p$-torsion classes $\rho_{p,k}$ of degree $p^{k+1}+1$ in the Chow ring of the

Nicolas Garcia Trillos, Ryan Murray

This paper investigates the use of methods from partial differential equations and the Calculus of variations to study learning problems that are regularized using graph Laplacians. Graph Laplacians are a powerful, flexible method for capturing local and global geometry in many classes of learning problems, and the techniques developed in this paper help to

Shikun Zhang, Kun Liu, Daoyi Dong, Xiaoxue Feng

Studied in this article is non-Markovian open quantum systems parametrized by Hamiltonian H, coupling operator L, and memory kernel function {\gamma}, which is a proper candidate for describing the dynamics of various solid-state quantum information processing devices. We look into the subspace stabilization problem of the system from the perspective of dyna

Mauricio Bustamante, Markus Ahlers

The sources and production mechanisms of high-energy astrophysical neutrinos are largely unknown. A promising opportunity for progress lies in the study of neutrino flavor composition, i.e., the proportion of each flavor in the flux of neutrinos, which reflects the physical conditions at the sources. To seize it, we introduce a Bayesian method that infers th

Zhixiong Chen, Qiuyan Wang

Let $q=p^r$ be a power of an odd prime $p$. We study binary sequences $\sigma=(\sigma_0,\sigma_1,\ldots)$ with entries in $\{0,1\}$ defined by using the quadratic character $\chi$ of the finite field $\mathbb{F}_q$: $$ \sigma_n=\left\{ \begin{array}{ll} 0,& \mathrm{if}\quad n= 0,\\ (1-\chi(\xi_n))/2,&\mathrm{if}\quad 1\leq n< q, \end{array} \right. $$ for th

Mark Lewko

Given $A \subset F_{p}^2$ a sufficiently small set in the plane over a prime residue field, we prove that there are at most $O_\epsilon (|A|^{\frac{99}{41}+\epsilon})$ rectangles with corners in $A$. The exponent $\frac{99}{41} = 2.413\ldots$ improves slightly on the exponent of $\frac{17}{7} = 2.428\ldots$ due to Rudnev and Shkredov. Using this estimate we

Cameron Ruggles, Nate Veldt, David F. Gleich

Many clustering applications in machine learning and data mining rely on solving metric-constrained optimization problems. These problems are characterized by $O(n^3)$ constraints that enforce triangle inequalities on distance variables associated with $n$ objects in a large dataset. Despite its usefulness, metric-constrained optimization is challenging in p

A. M. Mukhamedzhanov, A. S. Kadyrov

Within a few-body formalism, we develop a general theory of surrogate nuclear and atomic reactions with the excitation of a resonance in the intermediate binary subsystem leading to three charged particles in the final state. The Coulomb interactions between the spectator and the resonance in the intermediate state and between the three particles in the fina

Nicolas Garcia Trillos, Zach Kaplan, Daniel Sanz-Alonso

The aim of this paper is to provide new theoretical and computational understanding on two loss regularizations employed in deep learning, known as local entropy and heat regularization. For both regularized losses we introduce variational characterizations that naturally suggest a two-step scheme for their optimization, based on the iterative shift of a pro

Sunil K. Chebolu, Keir Lockridge

Which groups can be the group of units in a ring? This open question, posed by L\'{a}szl\'{o} Fuchs in 1960, has been studied by the authors and others with a variety of restrictions on either the class of groups or the class of rings under consideration. In the present work, we investigate Fuchs' problem for the class of $p$-groups. Ditor provided a solutio

Luca Oneto, Michele Donini, Massimiliano Pontil

We tackle the problem of algorithmic fairness, where the goal is to avoid the unfairly influence of sensitive information, in the general context of regression with possible continuous sensitive attributes. We extend the framework of fair empirical risk minimization to this general scenario, covering in this way the whole standard supervised learning setting

Zhanfeng Wang, Yumi Kwon, Yuan-chin Ivan Chang

Modern computing and communication technologies can make data collection procedures very efficient. However, our ability to analyze large data sets and/or to extract information out from them is hard-pressed to keep up with our capacities for data collection. Among these huge data sets, some of them are not collected for any particular research purpose. For

Meng Tian, Yong-Gang Huang, Sha-Sha Wen, Hong Yang

Photon Green function (GF) is the vital and most decisive factor in the field of quantum light-matter interaction. It is divergent with two equal space arguments in arbitrary-shaped lossy structure and should be regularized. We introduce a finite element method for calculating the regularized GF. It is expressed by the averaged radiation electric field over

Sorour Mohajerani, Parvaneh Saeedi

Cloud detection in satellite images is an important first-step in many remote sensing applications. This problem is more challenging when only a limited number of spectral bands are available. To address this problem, a deep learning-based algorithm is proposed in this paper. This algorithm consists of a Fully Convolutional Network (FCN) that is trained by m

Puoya Tabaghi, Maarten de Hoop, Ivan Dokmanić

We study the learnability of a class of compact operators known as Schatten--von Neumann operators. These operators between infinite-dimensional function spaces play a central role in a variety of applications in learning theory and inverse problems. We address the question of sample complexity of learning Schatten-von Neumann operators and provide an upper

ATLAS Collaboration

The ratio of the cross sections for inclusive isolated-photon production in $pp$ collisions at centre-of-mass energies of 13 and 8 TeV is measured using the ATLAS detector at the LHC. The integrated luminosities of the 13 TeV and 8 TeV datasets are 3.2 fb$^{-1}$ and 20.2 fb$^{-1}$, respectively. The ratio is measured as a function of the photon transverse en

Jin Chao, Ahmad Al Badawi, Balagopal Unnikrishnan, Jie Lin

Convolutional neural networks (CNNs) have enabled significant performance leaps in medical image classification tasks. However, translating neural network models for clinical applications remains challenging due to data privacy issues. Fully Homomorphic Encryption (FHE) has the potential to address this challenge as it enables the use of CNNs on encrypted im

Rukayat Ayomide Erinfolami, Aravind Prakash

Recovering class inheritance from C++ binaries has several security benefits including problems such as decompilation and program hardening. Thanks to the optimization guidelines prescribed by the C++ standard, commercial C++ binaries tend to be optimized. While state-of-the-art class inheritance inference solutions are effective in dealing with unoptimized

Xinyang Deng, Wen Jiang

Probability theory and Dempster-Shafer theory are two germane theories to represent and handle uncertain information. Recent study suggested a transformation to obtain the negation of a probability distribution based on the maximum entropy. Correspondingly, determining the negation of a belief structure, however, is still an open issue in Dempster-Shafer the

Tianwen Luo, Tao Tao, Liqun Zhang

We show the existence of H\"{o}lder continuous periodic weak solutions of the 2d Boussinesq equation with diffusive temperature which satisfy the prescribed kinetic energy. More precisely, for any smooth $e(t):[0,1]\rightarrow R_+$ and $\varepsilon\in (0, \frac{1}{10})$, there exist $v\in C^{\frac{1}{10}-\varepsilon}([0,1]\times {\rm T}^2), \theta\in C_t^{1,

Wei-Kuo Chen, Wai-Kit Lam

We present an elementary approach to the order of fluctuations for the free energy in the Sherrington-Kirkpatrick mean field spin glass model at and near the critical temperature. It is proved that at the critical temperature the variance of the free energy is of $O((\log N)^2).$ In addition, we show that if one approaches the critical temperature from the l

Amit Ghosh

In this paper we revisited Hawking radiation in the light of the original calculations of Hawking and Wald and found that some additional insights can be gained. We review a "derivation" of the field theory Hilbert space from the space of solutions, followed by the calculation of Bogoliubov coefficients in a collapsed spacetime from first principles. We show

Wei Ma, Zhen Qian

Recent transportation network studies on uncertainty and reliability call for modeling the probabilistic O-D demand and probabilistic network flow. Making the best use of day-to-day traffic data collected over many years, this paper develops a novel theoretical framework for estimating the mean and variance/covariance matrix of O-D demand considering the day

Ming-Xun Deng, Hou-Jian Duan, Wei Luo, W. Y. Deng

We study the positive longitudinal magnetoconductivity (LMC) and planar Hall effect as emergent effects of the chiral anomaly in Weyl semimetals, following a recent-developed theory by integrating the Landau quantization with Boltzmann equation. It is found that, in the weak magnetic field regime, the LMC and planar Hall conductivity (PHC) obey $\cos^{6}\the

Zhiliang Guo, Wenbin Shen

In this study, we formulated a triaxial three-layered anelastic Earth rotation theory con-sidering various core mantle couplings, including the pressure and gravitational couplings acting on the inner core by the outer core and mantle, the viscoelectromagnetic couplings between the outer core and mantle, and between the outer and inner cores. With this formu

Sergey S. Pershoguba, Leonid I. Glazman

We find the charge and heat currents caused by a temperature difference applied to a superconducting point contact or to a quantum point contact between a superconducting and normal conductors. The results are formulated in terms of the properties of the electron scattering matrix of the quantum point contact in its normal state, and are valid at any transmi

Venkateswara Rao Kagita, Arun K Pujari, Vineet Padmanabhan, Vikas Kumar

We consider the problem of committee selection from a fixed set of candidates where each candidate has multiple quantifiable attributes. To select the best possible committee, instead of voting for a candidate, a voter is allowed to approve the preferred attributes of a given candidate. Though attribute based preference is addressed in several contexts, comm

Zeying Wang

In this paper we prove that if there is a regular Paley type partial difference set in an Abelian group $G$ of order $v$, where $v=p_1^{2k_1}p_2^{2k_2}\cdots p_n^{2k_n}$, $n\ge 2$, $p_1$, $p_2$, $\cdots$, $p_n$ are distinct odd prime numbers, then for any $1 \le i \le n$, $p_i$ is congruent to 3 modulo 4 whenever $k_i$ is odd. These new necessary conditions

Davino Mauro Junior, Luis Melo, Harvey Lu, Marcelo d'Amorim

Internet of Things (IoT) devices are becoming increasingly important. These devices are often resource-limited, hindering rigorous enforcement of security policies. Assessing the vulnerability of IoT devices is an important problem, but analyzing their firmware is difficult for a variety of reasons, including requiring the purchase of devices. This paper fin

Hongjing Zhang, Sugato Basu, Ian Davidson

The area of constrained clustering has been extensively explored by researchers and used by practitioners. Constrained clustering formulations exist for popular algorithms such as k-means, mixture models, and spectral clustering but have several limitations. A fundamental strength of deep learning is its flexibility, and here we explore a deep learning frame

David H. Brookes, Hahnbeom Park, Jennifer Listgarten

We present a new method for design problems wherein the goal is to maximize or specify the value of one or more properties of interest. For example, in protein design, one may wish to find the protein sequence that maximizes fluorescence. We assume access to one or more, potentially black box, stochastic "oracle" predictive functions, each of which maps from

Fan-Yun Sun, Yen-Yu Chang, Yueh-Hua Wu, Shou-De Lin

Human behaviors are regularized by a variety of norms or regulations, either to maintain orders or to enhance social welfare. If artificially intelligent (AI) agents make decisions on behalf of human beings, we would hope they can also follow established regulations while interacting with humans or other AI agents. However, it is possible that an AI agent ca

Hang Liu, Jia-Tao Sun, Sheng Meng

The coupling of monochromatic light fields and solids introduces nonequilibrium Floquet states, offering opportunities to create and explore new topological phenomena. Using combined first-principles and Floquet analysis we show that one can freely engineer Floquet-Dirac fermions (FDFs) in graphene by tuning the frequency and intensity of linearly polarized

Oded Zilberberg, Alessandro Romito

We study the detection of electrons undergoing coherent transfer via adiabatic passage (CTAP) in a triple quantum-dot system with a quantum point-contact sensing the change of the middle dot. In the ideal scenario, the protocol amounts to perfect change transfer between the external dots with vanishing occupation of the central dot at all times, rendering th

Carl R. Shapiro, Dennice F. Gayme, Charles Meneveau

The actuator disk model (ADM) continues to be a popular wind turbine representation in large eddy simulations (LES) of large wind farms. Computational restrictions typically limit the number of grid points across the rotor of each actuator disk and require spatial filtering to smoothly distribute the applied force distribution on discrete grid points. At typ

Bokun Wang, Ian Davidson

Fair clustering under the disparate impact doctrine requires that population of each protected group should be approximately equal in every cluster. Previous work investigated a difficult-to-scale pre-processing step for $k$-center and $k$-median style algorithms for the special case of this problem when the number of protected groups is two. In this work, w

Phokion G. Kolaitis, Lucian Popa, Kun Qian

In several different applications, including data transformation and entity resolution, rules are used to capture aspects of knowledge about the application at hand. Often, a large set of such rules is generated automatically or semi-automatically, and the challenge is to refine the encapsulated knowledge by selecting a subset of rules based on the expected

Shyam Sundar, Said Salem-Sugui, Edmund Lovell, Alexander Vanstone

A series of high quality BaFe$_{2-x}$Ni$_x$As$_2$ pnictide superconductors were studied using magnetic relaxation and isothermal magnetic measurements in order to study the second magnetization peak (SMP) and critical current behaviour in Ni-doped 122 family. The temperature dependence of the magnetic relaxation rate suggests a pinning crossover, whereas, it

Jingxin Wu

Thesis Statement: Cost-effective switching and spectrum utilization efficiency have become critical design considerations in optical networks. This dissertation provides in-depth exploration of these important aspects, and proposes effective techniques for low-cost switching architectures and resource allocation algorithms to facilitate the adoption of optic

Loc H. Nguyen, Qitong Li, Michael V. Klibanov

A new numerical method to solve an inverse source problem for the Helmholtz equation in inhomogenous media is proposed. This method reduces the original inverse problem to a boundary value problem for a coupled system of elliptic PDEs, in which the unknown source function is not involved. The Dirichlet boundary condition is given on the entire boundary of th

J. J. Condon, A. M. Matthews, J. J. Broderick

We identified 15,658 NVSS radio sources among the 55,288 2MASX galaxies brighter than $k_\mathrm{20fe} = 12.25$ at $\lambda = 2.16\,\mu\mathrm{m}$ and covering the $\Omega =7.016$ sr of sky defined by J2000 $\delta > -40^\circ$ and $\vert b \vert > 20^\circ$. The complete sample of 15,043 galaxies with 1.4 GHz flux densities $S \geq 2.45 \mathrm{~mJy}$ conta

Diptarama Hendrian, Takuya Takagi, Shunsuke Inenaga

The suffix trees are fundamental data structures for various kinds of string processing. The suffix tree of a string $T$ of length $n$ has $O(n)$ nodes and edges, and the string label of each edge is encoded by a pair of positions in $T$. Thus, even after the tree is built, the input text $T$ needs to be kept stored and random access to $T$ is still needed.

Ritika Dusad, Franziska K. K. Kirschner, Jesse C. Hoke, Benjamin Roberts

Magnetic monopoles are hypothetical elementary particles exhibiting quantized magnetic charge $m_0=\pm(h/\mu_0e)$ and quantized magnetic flux $\Phi_0=\pm h/e$. A classic proposal for detecting such magnetic charges is to measure the quantized jump in magnetic flux $\Phi$ threading the loop of a superconducting quantum interference device (SQUID) when a monop

Wael Mahboub, Mark Spivakovsky

Let $R$ be a two-dimensional regular local ring. In this paper, we prove that there is a bijection between the set of all valuations of $Quot(R)$ centered at $R$ and valuations of $k(x,y)$ centered at $k[x,y]_{(x,y)}$, where $k$ is the residue field of $R$ and $x$ and $y$ are independent variables. Moreover, we give a new proof, for the fact that the set of

Andreas Debrouwere

Let $E$ be a locally convex Hausdorff space satisfying the convex compact property and let $(T_x)_{x \in \mathbb{R}^d}$ be a locally equicontinuous $C_0$-group of linear continuous operators on $E$. In this article, we show that if $E$ is quasinormable, then the space of smooth vectors in $E$ associated to $(T_x)_{x \in \mathbb{R}^d}$ is also quasinormable.

Joshua L Padgett, Qin Sheng

The numerical solution of a highly nonlinear two-dimensional degenerate stochastic Kawarada equation is investigated. A semi-discretized approximation in space is comprised on arbitrary nonuniform grids. Exponential splitting strategies are then applied to advance solutions of the semi-discretized scheme over adaptive grids in time. It is shown that key quen

Tobias Kluth, Bangti Jin

Magnetic particle imaging (MPI) is a medical imaging modality of recent origin, and it exploits the nonlinear magnetization phenomenon to recover the spatially dependent concentration of the nanoparticles. Currently, image reconstruction in MPI is frequently carried out by standard Tikhonov regularization with nonnegativity constraint, which is then minimize

Kaarthik Sundar, Harsha Nagarajan, Sidhant Misra, Mowen Lu

This article develops a strengthened convex quadratic convex (QC) relaxation of the AC Optimal Power Flow (AC-OPF) problem and presents an optimization-based bound-tightening (OBBT) algorithm to compute tight, feasible bounds on the voltage magnitude variables for each bus and the phase angle difference variables for each branch in the network. Theoretical p

Daniel Kasprowski, Christoph Winges

We adapt Grayson&#39;s model of higher algebraic $K$-theory using binary acyclic complexes to the setting of stable $\infty$-categories. As an application, we prove that the $K$-theory of stable $\infty$-categories preserves infinite products.

Kesav Kaza, Rahul Meshram, Varun Mehta, S. N. Merchant

This work studies a generalized class of restless multi-armed bandits with hidden states and allow cumulative feedback, as opposed to the conventional instantaneous feedback. We call them lazy restless bandits (LRB) as the events of decision-making are sparser than events of state transition. Hence, feedback after each decision event is the cumulative effect

Konstantin Usevich, Philippe Dreesen, Mariya Ishteva

Decoupling multivariate polynomials is useful for obtaining an insight into the workings of a nonlinear mapping, performing parameter reduction, or approximating nonlinear functions. Several different tensor-based approaches have been proposed independently for this task, involving different tensor representations of the functions, and ultimately leading to

M. Bertola, J. Harnad, B. Runov

Multicurrent correlators associated to KP $\tau$-functions of hypergeometric type are used as generating functions for weighted Hurwitz numbers. These are expressed as formal Taylor series and used to compute generic, simple, rational and quantum weighted single Hurwitz numbers.

Kevin A. Cremin, Jingdi Zhang, Christopher C. Homes, Genda D. Gu

Quantum materials are amenable to non-equilibrium manipulation with light, enabling modification and control of macroscopic properties. Light-based augmentation of superconductivity is particularly intriguing. Copper-oxide superconductors exhibit complex interplay between spin order, charge order and superconductivity, offering the prospect of enhanced coher

Felix Roy, Giulio Biroli, Guy Bunin, Chiara Cammarota

Dynamical mean field theory (DMFT) is a tool that allows to analyze the stochastic dynamics of $N$ interacting degrees of freedom in terms of a self-consistent $1$-body problem. In this work, focusing on models of ecosystems, we present the derivation of DMFT through the dynamical cavity method, and we develop a method for solving it numerically. Our numeric

Junping Wang, Xiu Ye

The goal of this article is to clarify some misunderstandings and inappropriate claims made in [6] regarding the relation between the weak Galerkin (WG) finite element method and the hybridizable discontinuous Galerkin (HDG). In this paper, the authors offered their understandings and interpretations on the weak Galerkin finite element method by describing t

Yanchao Yang, Alex Wong, Stefano Soatto

We present a deep learning system to infer the posterior distribution of a dense depth map associated with an image, by exploiting sparse range measurements, for instance from a lidar. While the lidar may provide a depth value for a small percentage of the pixels, we exploit regularities reflected in the training set to complete the map so as to have a proba

Román Aranda

In 2018, M. Chu and S. Tillmann gave a lower bound for the trisection genus of a closed 4-manifold in terms of the Euler characteristic of $M$ and the rank of its fundamental group. We show that given a group $G$, there exist a 4-manifold $M$ with fundamental group $G$ with trisection genus achieving Chu-Tillmann's lower bound.

P. Marziani, E. Bon, N. Bon, A. del Olmo

Quasars accreting matter at very high rates (known as extreme Population A [xA] or super-Eddington accreting massive black holes) provide a new class of distance indicators covering cosmic epochs from the present-day Universe up to less than 1 Gyr from the Big Bang. The very high accretion rate makes it possible that massive black holes hosted in xA quasars

Yinlam Chow, Ofir Nachum, Aleksandra Faust, Edgar Duenez-Guzman

We study continuous action reinforcement learning problems in which it is crucial that the agent interacts with the environment only through safe policies, i.e.,~policies that do not take the agent to undesirable situations. We formulate these problems as constrained Markov decision processes (CMDPs) and present safe policy optimization algorithms that are b

Julia Harz, Kalliopi Petraki

It has been recently demonstrated that the 125 GeV Higgs boson can mediate a long-range force between TeV-scale particles, that can impact considerably their annihilation due to the Sommerfeld effect, and hence the density of thermal relic dark matter. In the presence of long-range interactions, the formation and decay of particle-antiparticle bound states c

Runfan Zhang, Branislav Hredzak

The proposed distributed dynamic clustering algorithm enables to group agents based on their pre-selected feature states. The clusters are determined by comparing the distance of the agents' current feature states with average estimates of the states in all clusters. The algorithm also provides average estimates of pre-selected auxiliary states that can be u

Jindan Xu, Wei Xu, Fengkui Gong, Hua Zhang

Low-resolution digital-to-analog converter (DAC) has shown great potential in facilitating cost- and power-efficient implementation of massive multiple-input multiple-output (MIMO) systems. We investigate the performance of a massive MIMO downlink network with low-resolution DACs using regularized zero-forcing (RZF) precoding. It serves multiple receivers eq

Matus Rybak, G. Calistro Rivera, J. A. Hodge, Ian Smail

We present 0.15-arcsec (1 kpc) resolution ALMA observations of the [CII] 157.74 um line and rest-frame 160-um continuum emission in two z~3 dusty, star-forming galaxies - ALESS 49.1 and ALESS 57.1, combined with resolved CO(3-2) observations. In both sources, the [CII] surface brightness distribution is dominated by a compact core $\leq$1 kpc in radius, a fa

Mauricio Toro

Various formal languages have been proposed in the literature for the individual-based modelling of ecological systems. These languages differ in their treatment of time and space. Each modelling language offers a distinct view and techniques for analyzing systems. Most of the languages are based on process calculi or P systems. In this article, we present a

Ryan A. Rossi, Nesreen K. Ahmed, Aldo Carranza, David Arbour

Many real-world applications give rise to large heterogeneous networks where nodes and edges can be of any arbitrary type (e.g., user, web page, location). Special cases of such heterogeneous graphs include homogeneous graphs, bipartite, k-partite, signed, labeled graphs, among many others. In this work, we generalize the notion of network motifs to heteroge

Gérard Ben Arous, Jing Wang

We study the large deviation estimates for the short time asymptotic behavior of a strongly degenerate diffusion process. Assuming a nilpotent structure of the Lie algebra generated by the driving vector fields, we obtain a graded large deviation principle and prove the existence of those "very rare events". In particular the first grade coincides with the c

Ben Usman, Nick Dufour, Kate Saenko, Chris Bregler

In this work we propose a model that can manipulate individual visual attributes of objects in a real scene using examples of how respective attribute manipulations affect the output of a simulation. As an example, we train our model to manipulate the expression of a human face using nonphotorealistic 3D renders of a face with varied expression. Our model ma

Jung-yeon Baek, Georges Kaddoum, Sahil Garg, Kuljeet Kaur

The powerful paradigm of Fog computing is currently receiving major interest, as it provides the possibility to integrate virtualized servers into networks and brings cloud service closer to end devices. To support this distributed intelligent platform, Software-Defined Network (SDN) has emerged as a viable network technology in the Fog computing environment

J. -R. Soh, F. de Juan, M. G. Vergniory, N. B. M. Schröter

Weyl semimetals exhibit exceptional quantum electronic transport due to the presence of topologically-protected band crossings called Weyl nodes. The nodes come in pairs with opposite chirality, but their number and location in momentum space is otherwise material specific. Following the initial discoveries there is now a need for better material realization

Irmak Aykin, Ezhan Karasan

Heterogeneous networks (HetNets) are proposed in order to meet the increasing demand for next generation cellular wireless networks, but they also increase the energy consumption of the base stations. In this paper, an activity management algorithm for improving the energy efficiency of HetNets is proposed. A smart sleep strategy is employed for the operator