April 2019 arXiv papers — page 42

Fernando L. Metz, Isaac Pérez Castillo

Due to their conceptual and mathematical simplicity, Erdös-Rényi or classical random graphs remain as a fundamental paradigm to model complex interacting systems in several areas. Although condensation phenomena have been widely considered in complex network theory, the condensation of degrees has hitherto eluded a careful study. Here we show that the degree

Yusuke Sawada

Product systems have been originally introduced to classify E$_0$-semigroups on type I factors by Arveson. We develop the classification theory of E$_0$-semigroups on a general von Neumann algebra and the dilation theory of CP$_0$-semigroups in terms of W$^*$-bimodules. For this, we provide a notion of product system of W$^*$-bimodules. This is a W$^*$-bimod

Driss Takir, Karen R. Stockstill-Cahill, Charles A. Hibbitts, Yusuke Nakauchi

We measured 3-micron reflectance spectra of 21 meteorites that represent all carbonaceous chondrite types available in terrestrial meteorite collections. The measurements were conducted at the Laboratory for Spectroscopy under Planetary Environmental Conditions (LabSPEC) at the Johns Hopkins University Applied Physics Laboratory (JHU APL) under vacuum and th

Claudio Carmeli, Gianni Cassinelli, Alessandro Toigo

We describe a particular class of pairs of quantum observables which are extremal in the convex set of all pairs of compatible quantum observables. The pairs in this class are constructed as uniformly noisy versions of two mutually unbiased bases (MUB) with possibly different noise intensities affecting each basis. We show that not all pairs of MUB can be us

Yoshihisa Miyanishi, Grigori Rozenblum

We consider the double layer potential (Neumann-Poincaré) operator appearing in 3-dimensional elasticity. We show that the recent result about the polynomial compactness of this operator for the case of a homogeneous media follows without additional calculations from previous considerations by Agranovich et.al., based upon pseudodifferential operators. Furth

Haozhou Wang, James Henderson, Paola Merlo

Distributed representations of words which map each word to a continuous vector have proven useful in capturing important linguistic information not only in a single language but also across different languages. Current unsupervised adversarial approaches show that it is possible to build a mapping matrix that align two sets of monolingual word embeddings to

Subhash Lakshminarayana, Jabir Shabbir Karachiwala, Teo Zhan Teng, Rui Tan

This paper studies the performance and resilience of a linear cyber-physical control system (CPCS) with attack detection and reactive attack mitigation in the context of power grids. It addresses the problem of deriving an optimal sequence of false data injection attacks that maximizes the state estimation error of the power system. The results provide basic

Jeremiah W. Murphy, Quintin Mabanta, Joshua C. Dolence

There are now $\sim$20 multi-dimensional core-collapse supernova (CCSN) simulations that explode. However, these simulations have explosion energies that are a few times $10^{50}$ erg, not $10^{51}$ erg. In this manuscript, we compare the inferred explosion energies of these simulations and observations of 38 SN~IIP. Assuming a log-normal distribution, the m

Razieh Mehri, Volker Haarslev, Hamidreza Chinaei

Web Ontology Language (OWL) reasoners are used to infer new logical relations from ontologies. While inferring new facts, these reasoners can be further optimized, e.g., by properly ordering disjuncts in disjunction expressions of ontologies for satisfiability testing of concepts. Different expansion-ordering heuristics have been developed for this purpose.

Chenhan Yuan, Yi-Chin Huang

The author-specific word usage is a vital feature to let readers perceive the writing style of the author. In this work, a personalized sentence generation method based on generative adversarial networks (GANs) is proposed to cope with this issue. The frequently used function word and content word are incorporated not only as the input features but also as t

Aiad El Gourari, Allal Ghanmi, Khalil Zine

We consider the $1$- and $2$-d bicomplex analogs of the classical Fourier--Wigner transform. Their basic properties, including Moyal's identity and characterization of their ranges giving rise to new bicomplex--polyanalytic functional spaces are discussed. Particular case of special window is also considered. An orthogonal basis for the space of bicomple

Takashi Horiyama, Jun Kawahara, Shin-ichi Minato, Yu Nakahata

Unigraphs are graphs uniquely determined by their own degree sequence up to isomorphism. There are many subclasses of unigraphs such as threshold graphs, split matrogenic graphs, matroidal graphs, and matrogenic graphs. Unigraphs and these subclasses are well studied in the literature. Nevertheless, there are few results on superclasses of unigraphs. In this

Mingfei Sun, Yiqing Mou, Hongwen Xie, Meng Xia

Equipping social and service robots with the ability to perceive human emotional intensities during an interaction is in increasing demand. Most of existing work focuses on determining which emotion(s) participants are expressing from facial expressions but largely overlooks the emotional intensities spontaneously revealed by other social cues, especially bo

Azza Allouch, Anis Koubaa, Mohamed Khalgui, Tarek Abbes

In the last few years, Unmanned Aerial Vehicles (UAVs) are making a revolution as an emerging technology with many different applications in the military, civilian, and commercial fields. The advent of autonomous drones has initiated serious challenges, including how to maintain their safe operation during their missions. The safe operation of UAVs remains a

A. M. Bykov, A. E. Petrov, A. M. Krassilchtchikov, K. P. Levenfish

We consider acceleration of leptons up to GeV-TeV energies in the bow shock wind nebula of PSR J0437-4715 and their subsequent diffusion through the interstellar magnetic fields. The leptons accelerated at the pulsar wind termination surface are injected into re-acceleration in colliding shock flows. Modelled spectra of synchrotron emission from the accelera

Tatiana Podladchikova, Astrid M. Veronig, Karin Dissauer, Manuela Temmer

EUV waves are large-scale disturbances in the solar corona initiated by coronal mass ejections. However, solar EUV images show only the wave fronts projections along the line-of-sight of the spacecraft. We perform 3D reconstructions of EUV wave front heights using multi-point observations from STEREO-A and STEREO-B, and study their evolution to properly esti

Weiqiang He, Si Li, Yifan Li

In this note we explore the variation of Hodge structures associated to the orbifold Landau-Ginzburg B-model whose superpotential has two variables. We extend the Getzler-Gauss-Manin connection to Hochschild chains twisted by group action. As an application, we provide explicit computations for the Getzler-Gauss-Manin connection on the universal (noncommutat

Jacek Chmieliński, Moshe Goldberg

Let $S$ be a seminorm on an infinite-dimensional real or complex vector space $X$. Our purpose in this note is to study the continuity and discontinuity properties of $S$ with respect to certain norm-topologies on $X$.

Ario Santoso, Michael Felderer

Predictive analysis in business process monitoring aims at forecasting the future information of a running business process. The prediction is typically made based on the model extracted from historical process execution logs (event logs). In practice, different business domains might require different kinds of predictions. Hence, it is important to have a m

Xuelong Li, Aihong Yuan, Xiaoqiang Lu

Using a natural language sentence to describe the content of an image is a challenging but very important task. It is challenging because a description must not only capture objects contained in the image and the relationships among them, but also be relevant and grammatically correct. In this paper a multi-modal embedding model based on gated recurrent unit

Raanju Ragavendar Sundararajan, Vladas Pipiras, Mohsen Pourahmadi

Stationary subspace analysis (SSA) searches for linear combinations of the components of nonstationary vector time series that are stationary. These linear combinations and their number defne an associated stationary subspace and its dimension. SSA is studied here for zero mean nonstationary covariance processes. We characterize stationary subspaces and thei

L. Selliez, C. Briois, N. Carrasco, L. Thirkell

In the Solar System, extra-terrestrial organic molecules have been found on cometary primitive objects, on Titan and Enceladus icy moons and on Mars. Identification could be achieved for simple organic species by remote sensing based on spectroscopic methods. However in situ mass spectrometry is a key technology to determine the nature of more complex organi

Andrew Schopieray

Here we constructively classify quadratic $d$-numbers: algebraic integers in quadratic number fields generating Galois-invariant ideals. We prove the subset thereof maximal among their Galois conjugates in absolute value is discrete in $\mathbb{R}$. Our classification provides a characterization of those real quadratic fields containing a unit of norm -1 whi

Xiao Chen, Thomas Navidi, Stefano Ermon, Ram Rajagopal

Distributed devices such as mobile phones can produce and store large amounts of data that can enhance machine learning models; however, this data may contain private information specific to the data owner that prevents the release of the data. We wish to reduce the correlation between user-specific private information and data while maintaining the useful i

T. Yu. Magakian, T. A. Movsessian, H. R. Andreasyan, M. H. Gevorgyan

Young double star V1318 Cyg, which is associated with a small isolated star-forming region around HAeBe star BD+40o4124, has very unusual photometric and spectral behavior. We present results of photometric and spectroscopic observations in the optical range. We carried out BVRI CCD photometric observations of V1318 Cyg from 2015 Sept. to 2017 July. For the

Hehe Fan, Linchao Zhu, Yi Yang

Predicting future frames in videos has become a promising direction of research for both computer vision and robot learning communities. The core of this problem involves moving object capture and future motion prediction. While object capture specifies which objects are moving in videos, motion prediction describes their future dynamics. Motivated by this a

QianRu Wei, DaZheng Feng, WeiXing Zheng

Most of the classical approaches to straight line detection only deal with a binary edge image and need to use 2D interpolation operation. This paper proposes a new transform method figuratively named as funnel transform which can efficiently and rapidly detect straight lines. The funnel transform consists of three 1D Fourier transforms and one nonlinear var

Seung Hee Yang, Minhwa Chung

Self-imitating feedback is an effective and learner-friendly method for non-native learners in Computer-Assisted Pronunciation Training. Acoustic characteristics in native utterances are extracted and transplanted onto learner's own speech input, and given back to the learner as a corrective feedback. Previous works focused on speech conversion using pro

Branislav Kveton, Saied Mahdian, S. Muthukrishnan, Zheng Wen

A popular approach to selling online advertising is by a waterfall, where a publisher makes sequential price offers to ad networks for an inventory, and chooses the winner in that order. The publisher picks the order and prices to maximize her revenue. A traditional solution is to learn the demand model and then subsequently solve the optimization problem fo

Masanori Nagao, Akira Miura, Ryo Matsumoto, Yuki Maruyama

PrOBiS2 single crystals were successfully grown using a KCl flux. The obtained crystals had a plate-like shape with a typical size of 0.5-1.0 mm and well-developed ab-plane. The Pr valence of the grown crystals, as determined by an X-ray absorption fine structure spectroscopy analysis, was almost trivalent. The PrOBiS2 single crystals did not exhibit superco

Liwei Chen, Jeffery D. McNeal

Solution operators for the equation $\bar \partial u=f$ are constructed on general product domains in $\mathbb{C}^n$. When the factors are one-dimensional, the operator is a simple integral operator: it involves specific derivatives of $f$ integrated against iterated Cauchy kernels. For higher dimensional factors, the solution is constructed by solving sub-$

Xiaofeng Zhou, Ali Sadeghian, Daisy Zhe Wang

Multiple web-scale Knowledge Bases, e.g., Freebase, YAGO, NELL, have been constructed using semi-supervised or unsupervised information extraction techniques and many of them, despite their large sizes, are continuously growing. Much research effort has been put into mining inference rules from knowledge bases. To address the task of rule mining over evolvin

Jinming Wen, Wei Yu

The orthogonal matching pursuit (OMP) algorithm is a commonly used algorithm for recovering $K$-sparse signals $\x\in \mathbb{R}^{n}$ from linear model $\y=\A\x$, where $\A\in \mathbb{R}^{m\times n}$ is a sensing matrix. A fundamental question in the performance analysis of OMP is the characterization of the probability that it can exactly recover $\x$ for r

Salar Fattahi, Nikolai Matni, Somayeh Sojoudi

This paper addresses the problem of identifying sparse linear time-invariant (LTI) systems from a single sample trajectory generated by the system dynamics. We introduce a Lasso-like estimator for the parameters of the system, taking into account their sparse nature. Assuming that the system is stable, or that it is equipped with an initial stabilizing contr

Jinming Wen, Xiao-Wen Chang, Jian Weng

The Korkine-Zolotareff (KZ) reduction is a widely used lattice reduction strategy in communications and cryptography. The Hermite constant, which is a vital constant of lattice, has many applications, such as bounding the length of the shortest nonzero lattice vector and orthogonality defect of lattices. The KZ constant can be used in quantifying some useful

L. H. C. Borges, F. A. Barone

This paper is dedicated to the study of interactions between external sources for the electromagnetic field in a model which exhibits Lorentz symmetry breaking. We investigate such interactions in the CPT-even photon sector of the Standard Model Extension (SME), where the Lorentz symmetry breaking is caused by a background tensor $K_{(F)αβστ}$. Since the bac

Pavel E. Ryabov, Artemiy A. Shadrin

The article is devoted to the results of a phase topology research on a generalized mathematical model, which covers such two problems as dynamics of two point vortices enclosed in a harmonic trap in a Bose-Einstein condensate and dynamics of two point vortices bounded by a circular region in an ideal fluid. New bifurcation diagrams are obtained and three-in

Fabrice Baudoin, Qi Feng, Cheng Ouyang

We study the density of the signature of fractional Brownian motions with parameter $H>1/4$. In particular, we prove existence, smoothness, global Gaussian upper bounds and Varadhan's type asymptotics for this density. A key result is that the estimates on the density we obtain are controlled by the Carnot-Carathéodory distance of the group.

Stefan Höche, Johannes Krause, Frank Siegert

We propose a novel technique for the combination of multi-jet merged simulations in the five-flavor scheme with calculations for the production of b-quark associated final states in the four-flavor scheme. We show the equivalence of our algorithm to the FONLL method at the fixed-order and logarithmic accuracy inherent to the matrix-element and parton-shower

Benjamin Johnson, Aron Laszka, Jens Grossklags, Tyler Moore

Cryptocurrency exchanges are frequently targeted and compromised by cyber-attacks, which may lead to significant losses for the depositors and closure of the affected exchanges. These risks threaten the viability of the entire public blockchain ecosystem since exchanges serve as major gateways for participation in public blockchain technologies. In this pape

Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal

Question Answering (QA) naturally reduces to an entailment problem, namely, verifying whether some text entails the answer to a question. However, for multi-hop QA tasks, which require reasoning with multiple sentences, it remains unclear how best to utilize entailment models pre-trained on large scale datasets such as SNLI, which are based on sentence pairs

Qian Lin, Xianming Sun, Chao Zhou

In the presence of ambiguity on the driving force of market randomness, we consider the dynamic portfolio choice without any predetermined investment horizon. The investment criteria is formulated as a robust forward performance process, reflecting an investor's dynamic preference. We show that the market risk premium and the utility risk premium jointly

Ting Wu, Theodore S. Rappaport, Michael E. Knox, Davood Shahrjerdi

A programmable ultra-wideband sliding correlator-based channel sounder with high temporal and spatial resolution is designed in standard 65 nm CMOS. The baseband chip can be configured either as a baseband transmitter to generate a pseudorandom spread spectrum signal with flexible sequence lengths, or as a baseband receiver with sliding correlator having an

Mohamad Kazem Shirani Faradonbeh, Ambuj Tewari, George Michailidis

In decision making problems for continuous state and action spaces, linear dynamical models are widely employed. Specifically, policies for stochastic linear systems subject to quadratic cost functions capture a large number of applications in reinforcement learning. Selected randomized policies have been studied in the literature recently that address the t

Matias D. Cattaneo, Michael Jansson

This paper highlights a tension between semiparametric efficiency and bootstrap consistency in the context of a canonical semiparametric estimation problem, namely the problem of estimating the average density. It is shown that although simple plug-in estimators suffer from bias problems preventing them from achieving semiparametric efficiency under minimal

Zewei Xiong, Meng-Ru Wu, Yong-Zhong Qian

A protoneutron star produced in a core-collapse supernova (CCSN) drives a wind by its intense neutrino emission. We implement active-sterile neutrino oscillations in a steady-state model of this neutrino-driven wind to study their effects on the dynamics and nucleosynthesis of the wind in a self-consistent manner. Using vacuum mixing parameters indicated by

Robert Marsland, Wenping Cui, Joshua Goldford, Pankaj Mehta

Natural microbial communities contain hundreds to thousands of interacting species. For this reason, computational simulations are playing an increasingly important role in microbial ecology. In this manuscript, we present a new open-source, freely available Python package called Community Simulator for simulating microbial population dynamics in a reproduci

Buser Say, Scott Sanner, Sylvie Thiébaux

Optimal planning with respect to learned neural network (NN) models in continuous action and state spaces using mixed-integer linear programming (MILP) is a challenging task for branch-and-bound solvers due to the poor linear relaxation of the underlying MILP model. For a given set of features, potential heuristics provide an efficient framework for computin

Sean McCurdy

In this paper, we obtain \textit{quantitative} estimates on the fine structure of the singular set of the mutual boundary $\partial \Omega^{\pm}$ for pairs of complementary domains, $\Omega^+, \Omega^- \subset \mathbb{R}^n$ which arise in a class of two-sided free boundary problems for harmonic measure. These estimates give new insight into the structure of

Natasha E. Batalha, Mark S. Marley, Nikole K. Lewis, Jonathan J. Fortney

Here we present the first open-source radiative transfer model for computing the reflected light of exoplanets at any phase geometry, called PICASO: Planetary Intensity Code for Atmospheric Scattering Observations. This code, written in Python, has heritage from a decades old, well-known Fortran model used for several studies of planetary objects within the

Z. Guguchia, J. Verezhak, D. Gawryluk, S. S. Tsirkin

Magnetic topological phases of quantum matter are an emerging frontier in physics and material science. Along these lines, several kagome magnets have appeared as the most promising platforms. However, the magnetic nature of these materials in the presence of topological state remains an unsolved issue. Here, we explore magnetic correlations in the kagome ma

Anatoly Meshkov, Vladimir Sokolov

A complete classification of isotropic vector equations of the geometric type that possess higher symmetries is proposed. New examples of integrable multi-component systems of the geometric type and their auto-Backlund transformations are found.

Geunho Song, Junchen Rong, Sang-Jin Sin

We discuss the stability of the topological invariant of the strongly interacting Weyl semi-metal at finite temperature. We find that if the interactions and temperature of the system are controlled by the holography, the topology is stable even in the case the Fermi surface become fuzzy. We give an argument to show that although the self energy changes the

Jason G. Miles, Nicholas A. Battista

Jellyfish have been called one of the most energy-efficient animals in the world due to the ease in which they move through their fluid environment, by product of their morphological, muscular, and material properties. We investigated jellyfish locomotion by conducting \textit{in silico} comparative studies and explored swimming performance across different

Reza Mohammadi, Matthew Pratola, Maurits Kaptein

Decision trees are flexible models that are well suited for many statistical regression problems. In a Bayesian framework for regression trees, Markov Chain Monte Carlo (MCMC) search algorithms are required to generate samples of tree models according to their posterior probabilities. The critical component of such an MCMC algorithm is to construct good Metr

Julia Bernatska

The paper develops the result of second Thomae theorem in hyperelliptic case. The main formula, called general Thomae formula, provides expressions for values at zero of the lowest non-vanishing derivatives of theta functions with singular characteristics of arbitrary multiplicity in terms of branch points and period matrix. We call these values derivative t

Qinyuan Ye, Liyuan Liu, Maosen Zhang, Xiang Ren

In recent years there is a surge of interest in applying distant supervision (DS) to automatically generate training data for relation extraction (RE). In this paper, we study the problem what limits the performance of DS-trained neural models, conduct thorough analyses, and identify a factor that can influence the performance greatly, shifted label distribu

Mariya A. Lizunova, Samuel Kuypers, Bernet Meijer, Ana Silva

We present a mathematically simple procedure for explaining and visualizing the dynamics of quantized transport in topological insulators. The procedure serves to illustrate and clarify the dynamics of topological transport in general, but for the sake of concreteness, it is phrased here in terms of electron transport in a charge-ordered chain, which may be

Mikhail Kapranov, Vadim Schechtman

We relate shuffle algebras, as defined by Nichols, Feigin-Odesskii and Rosso, to perverse sheaves on symmetric products of the complex line (i.e., on the spaces of monic polynomials stratified by multiplicities of roots). More precisely, we construct an equivalence between: (i) Braided Hopf algebras of a certain type. (ii) Factorizable collections of pervers

Marjan Ghazvininejad, Omer Levy, Yinhan Liu, Luke Zettlemoyer

Most machine translation systems generate text autoregressively from left to right. We, instead, use a masked language modeling objective to train a model to predict any subset of the target words, conditioned on both the input text and a partially masked target translation. This approach allows for efficient iterative decoding, where we first predict all of

Marco Maceda, Daniel Martínez-Carbajal

We construct a noncommutative Kähler manifold based on a non-linear perturbations of Moyal integrable deformations of $D=4$ self-dual gravity. The deformed Kähler manifold preserves all the properties of the commutative one, and we obtain the associated noncommutative Kähler potential using the Moyal deformed gravity approach. We apply this construction to t

Nicolas Behr, Jean Krivine

We extend the notion of compositional associative rewriting as recently studied in the rule algebra framework literature to the setting of rewriting rules with conditions. Our methodology is category-theoretical in nature, where the definition of rule composition operations encodes the non-deterministic sequential concurrent application of rules in Double-Pu

Zhaolun Liu, Yuqing Chen, Gerard Schuster

We recast the forward pass of a multilayered convolutional neural network (CNN) as the solution to the problem of sparse least squares migration (LSM). The CNN filters and feature maps are shown to be analogous, but not equivalent, to the migration Green's functions and the quasi-reflectivity distribution, respectively. This provides a physical interpretatio

Ruotian Luo, Ning Zhang, Bohyung Han, Linjie Yang

We present a novel problem setting in zero-shot learning, zero-shot object recognition and detection in the context. Contrary to the traditional zero-shot learning methods, which simply infers unseen categories by transferring knowledge from the objects belonging to semantically similar seen categories, we aim to understand the identity of the novel objects

Suraka Bhattacharjee, Ranjan Chaudhury

Expressions for generalized charge stiffness constant at zero temperature are derived corresponding to low dimensional hole doped quantum antiferromagnets, describable by the t-J-like models, with a view to understanding fermionic pairing possibilities and charge couplings in the itinerant antiferromagnetic systems. A detailed comparison between spin and cha

Arun John, Anish Murthy

In this paper, based on the Quantum-behaved Particle Swarm Optimization algorithm, we evolve the algorithm to optimize a multiobjective optimization problem, namely the Cobb Douglas Habitability function which is based on CES production functions in Economics. We also propose some changes to the Quantum-behaved Particle Swarm Optimization algorithm to mitiga

Emil Aas Stoltenberg, Nils Lid Hjort

This paper is devoted to the multivariate estimation of a vector of Poisson means. A novel loss function that penalises bad estimates of each of the parameters and the sum (or equivalently the mean) of the parameters is introduced. Under this loss function, a class of minimax estimators that uniformly dominate the maximum likelihood estimator is derived. Cru

Kushal Kafle, Robik Shrestha, Christopher Kanan

Language grounded image understanding tasks have often been proposed as a method for evaluating progress in artificial intelligence. Ideally, these tasks should test a plethora of capabilities that integrate computer vision, reasoning, and natural language understanding. However, rather than behaving as visual Turing tests, recent studies have demonstrated s

Zhihui Wang, Nicholas C. Rubin, Jason M. Dominy, Eleanor G. Rieffel

The Quantum Alternating Operator Ansatz (QAOA) is a promising gate-model meta-heuristic for combinatorial optimization. Applying the algorithm to problems with constraints presents an implementation challenge for near-term quantum resources. This work explores strategies for enforcing hard constraints by using $XY$-Hamiltonians as mixing operators (mixers).

Clara Murgui, Ana Peñuelas, Martin Jung, Antonio Pich

We perform a general model-independent analysis of $b \to c τ\barν_τ$ transitions, including measurements of $\mathcal{R}_D$, $\mathcal{R}_{D^*}$, their $q^2$ differential distributions, the recently measured longitudinal $D^*$ polarization $F_L^{D^*}$, and constraints from the $B_c \to τ\barν_τ$ lifetime, each of which has significant impact on the fit. A g

Indranil Biswas, Krishna Hanumanthu, D. S. Nagaraj

We study the following question: Given a vector bundle on a projective variety $X$ such that the restriction of $E$ to every closed curve $C \,\subset\, X$ is ample, under what conditions $E$ is ample? We first consider the case of an abelian variety $X$. If $E$ is a line bundle on $X$, then we answer the question in the affirmative. When $E$ is of higher ra

Andrew Aberdein

Monsters lurk within mathematical as well as literary haunts. I propose to trace some pathways between these two monstrous habitats. I start from Jeffrey Jerome Cohen's influential account of monster culture and explore how well mathematical monsters fit each of his seven theses. The mathematical monsters I discuss are drawn primarily from three distinct but

Zhiyuan Huang, Mansur Arief, Henry Lam, Ding Zhao

Safety evaluation of self-driving technologies has been extensively studied. One recent approach uses Monte Carlo based evaluation to estimate the occurrence probabilities of safety-critical events as safety measures. These Monte Carlo samples are generated from stochastic input models constructed based on real-world data. In this paper, we propose an approa

Enrique Artal Bartolo, Jose I. Cogolludo-Agustin, Jorge Martín-Morales

The purpose of this paper is to exhibit infinite families of conjugate projective curves in a number field whose complement have the same abelian fundamental group, but are non-homeomorphic. In particular, for any $d>3$ we find Zariski tuples parametrized by the $d$-roots of unity up to complex conjugation. As a consequence, for any divisor $m$ of $d$, $m\ne

Giacomo Cacciapaglia, Haiying Cai, Aldo Deandrea, Ashwani Kushwaha

We consider a realisation of composite Higgs models in the context of $SU(6)/ SO(6)$ symmetry, which features a custodial bi-triplet, two Higgs doublets and dark matter candidates. This model can arise from an underlying gauge-fermion theory. The general vacuum structure is explored using the top partial compositeness to generate a special vacuum characteris

Paula Calderón-Castillo, Neil M. Nagar, Sukyoung Yi, Yu-Yen Chang

Extragalactic surveys provide significant statistical data for the study of crucial galaxy parameters used to constrain galaxy evolution, e.g. stellar mass (M$_*$) and star formation rate (SFR), under different environmental conditions. These quantities are derived using manual or automatic methods for galaxy detection and flux measurement in imaging data at

Cynthia Keeler, Alankrita Priya

We calculate the contributions to the one-loop determinant for transverse traceless gravitons in an $n+3$-dimensional Schwarzschild black hole background in the large dimension limit, due to the $SO(n+2)$-type tensor and vector fluctuations, using the quasinormal mode method. Accordingly we find the quasinormal modes for these fluctuations as a function of a

Samantha Dahlberg, Stephanie van Willigenburg

In 1995 Stanley introduced a generalization of the chromatic polynomial of a graph $G$, called the chromatic symmetric function, $X_G$, which was generalized to noncommuting variables, $Y_G$, by Gebhard-Sagan in 2001. Recently there has been a renaissance in the study of $X_G$, in particular in classifying when $X_G$ is a positive linear combination of eleme

Francesco Torsello

The choice of gauge in numerical relativity is crucial in avoiding coordinate and curvature singularities. In addition, the gauge can affect the well-posedness of the system. In this work, we consider the mean gauges, established with respect to the geometric mean metric $h = g \, (g^{-1}f)^{1/2}$ in bimetric relativity. We consider three gauge conditions wi

Hongwan Liu, Gregory W. Ridgway, Tracy R. Slatyer

We present a new public Python package, DarkHistory, for computing the effects of dark matter annihilation and decay on the temperature and ionization history of the early universe. DarkHistory simultaneously solves for the evolution of the free electron fraction and gas temperature, and for the cooling of annihilation/decay products and the secondary partic

Sarah Habib, E. A. Huerta

We introduce a method to quantify the initial eccentricity, gravitational wave frequency, and mean anomaly of numerical relativity simulations that describe non-spinning black holes on moderately eccentric orbits. We demonstrate that this method provides a robust characterization of eccentric binary black hole mergers with mass-ratios $q\leq10$ and eccentric

Jared Kaplan, Sandipan Kundu

Causality constrains the gravitational interactions of massive higher spin particles in both AdS and flat spacetime. We explore the extent to which these constraints apply to composite particles, explaining why they do not rule out macroscopic objects or hydrogen atoms. However, we find that they do apply to glueballs and mesons in confining large $N$ gauge

Thomas W. -S. Holoien, Patrick J. Vallely, Katie Auchettl, K. Z. Stanek

We present the discovery and early evolution of ASASSN-19bt, a tidal disruption event (TDE) discovered by the All-Sky Automated Survey for Supernovae (ASAS-SN) at a distance of $d\simeq115$ Mpc and the first TDE to be detected by TESS. As the TDE is located in the TESS Continuous Viewing Zone, our dataset includes 30-minute cadence observations starting on 2

Cyril Elouard, Mordecai Waegell, Benjamin Huard, Andrew N. Jordan

Recently highly-efficient quantum engines were devised by exploiting the stochastic energy changes induced by quantum measurement. Here we show that such an engine can be based on an interaction-free measurement, in which the meter seemingly does not interact with the measured object. We use a modified version of the Elitzur-Vaidman bomb tester, an interfero

Vir B. Bulchandani, Christoph Karrasch, Joel E. Moore

Metals in one spatial dimension are described at the lowest energy scales by the Luttinger liquid theory. It is well understood that this free theory, and even interacting integrable models, can support ballistic transport of conserved quantities including energy. In contrast, realistic one-dimensional metals, even without disorder, contain integrability-bre

Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, Richard Socher

Even as pre-trained language encoders such as BERT are shared across many tasks, the output layers of question answering, text classification, and regression models are significantly different. Span decoders are frequently used for question answering, fixed-class, classification layers for text classification, and similarity-scoring layers for regression tas

P. A. D. Gonçalves, Thomas Christensen, Nicholas Rivera, Antti-Pekka Jauho

Plasmon-emitter interactions are of paramount importance in modern nanoplasmonics and are generally maximal at short emitter-surface separations. However, when the separation falls below 10-20 nm, the classical theory progressively deteriorates due to its neglect of quantum mechanical effects such as nonlocality, electronic spill-out, and Landau damping. Her

Lei Wu, Peng Zhou

We study log D-modules on smooth log pairs and construct a comparison theorem of log de Rham complexes. The proof uses Sabbah's generalized b-functions. As applications, we deduce a log index theorem and a Riemann-Roch type formula for perverse sheaves on smooth quasi-projective varieties. The log index theorem naturally generalizes the Dubson-Kashiwara inde

Minoru Eto, Yu Hamada, Masafumi Kurachi, Muneto Nitta

We show that a topological Nambu monopole exists as a regular solution for a large range of parameters in two Higgs doublet models, contrary to the standard model admitting only non-topological Nambu monopoles. We analyze a Higgs potential with a global $U(1)$ symmetry and a discrete symmetry $\mathbb{Z}_2$. The monopole is attached by two topological $Z$ st

Eduardo Castelló Ferrer, Thomas Hardjono, Alex 'Sandy' Pentland, Marco Dorigo

The importance of swarm robotics systems in both academic research and real-world applications is steadily increasing. However, to reach widespread adoption, new models that ensure the secure cooperation of large groups of robots need to be developed. This work introduces a novel method to encapsulate cooperative robotic missions in an authenticated data str

Zhize Li

We analyze stochastic gradient algorithms for optimizing nonconvex problems. In particular, our goal is to find local minima (second-order stationary points) instead of just finding first-order stationary points which may be some bad unstable saddle points. We show that a simple perturbed version of stochastic recursive gradient descent algorithm (called SSR

Atanu Nandy

Exact method of analytical solution of flat, non-dispersive eigenstates in a class of quasi-one dimensional structures is reported within the tight-binding framework. The states are localized over certain sublattice sites. One such finite size cluster of atomic sites is decoupled from the rest of the system by the special non-permissible vertex having zero a

Alexander Vishik

In this article we introduce the local versions of the Voevodsky category of motives with Z/p-coefficients over a field k, parameterized by finitely-generated extensions of k. We introduce the, so-called, flexible fields, passage to which is conservative on motives. We demonstrate that, over flexible fields, the constructed local motivic categories are much

Wei-Lin Hsiao, Isay Katsman, Chao-Yuan Wu, Devi Parikh

Given an outfit, what small changes would most improve its fashionability? This question presents an intriguing new vision challenge. We introduce Fashion++, an approach that proposes minimal adjustments to a full-body clothing outfit that will have maximal impact on its fashionability. Our model consists of a deep image generation neural network that learns

Loïc Marsot

We study the effect of the polarization of light beams on the time delay measured in Gravitational Wave experiments. To this end, we consider the Mathisson-Papapetrou-Dixon equations in a gravitational wave background, with two of the possible spin supplementary conditions: by Frenkel-Pirani, or by Tulczyjew. In the first case, photons follow a null geodesic

Colin Rylands, Natan Andrei

Driven by breakthroughs in experimental and theoretical techniques, the study of non-equilibrium quantum physics is a rapidly expanding field with many exciting new developments. Amongst the manifold ways the topic can be investigated, one dimensional system provide a particularly fine platform. The trifecta of strongly correlated physics, powerful theoretic

Se Young Park, Karin M. Rabe, Jeffrey B. Neaton

Charge-order-driven ferroelectrics are an emerging class of functional materials, distinct from conventional ferroelectrics, where electron-dominated switching can occur at high frequency. Despite their promise, only a few systems exhibiting this behavior have been experimentally realized thus far, motivating the need for new materials. Here, we use density

Yasin Yousif Al-Aboosi, Radhi Sehen Issa, Ali khalid Jassim

In many applications, Image de-noising and improvement represent essential processes in presence of colored noise such that in underwater. Power spectral density of the noise is changeable within a definite frequency range, and autocorrelation noise function is does not like delta function. So, noise in underwater is characterized as colored noise. In this p

Jinxiang Song, Bile Peng, Christian Häger, Henk Wymeersch

Data-driven optimization of transmitters and receivers can reveal new modulation and detection schemes and enable physical-layer communication over unknown channels. Previous work has shown that practical implementations of this approach require a feedback signal from the receiver to the transmitter. In this paper, we study the impact of quantized feedback i

Heather Mattie, Patrick Reidy, Patrik Bachtiger, Emily Lindemer

It is not clear how to target patients who are most likely to benefit from digital care management programs ex-ante, a shortcoming of current risk score based approaches. This study focuses on defining impactability by identifying those patients most likely to benefit from technology enabled care management, delivered through a digital health platform, inclu