November 2019 arXiv papers — page 35

A. Kadja, F. Benamira, L. Guechi

The problem of a Dirac particle moving in a deformed Hulthen potential is solved in the framework of the path integral formalism. With the help of the Biedenharn transformation, the construction of a closed form for the Green's function of the second-order Dirac equation is done by using a proper approximation to the centrifugal term and the Green's

Li Wang, Duchao Liu

By a stronger compact boundary embedding theorem in Musielak-Orlicz-Sobolev space developed in the paper, variational method is employed to deal with the nonlinear elliptic equation with the nonlinear Neumann boundary condition in the framework of Musielak-Orlicz-Sobolev space.

A Kadja, F Benamira, L Guechi

An exact path integral treatment of a particle in a deformed radial Rosen-Morse potential is presented. For this problem with the Dirichlet boundary conditions, the Green's function is constructed in a closed form by adding to V_{q}(r) a δ-function perturbation and making its strength infinitely repulsive. A transcendental equation for the energy levels

Aurelia Dymek

We characterize proximality of multidimensional $\mathscr{B}$-free systems in the case of number fields and lattices in $\mathbb{Z}^m$, $m\geq2$.

Juliano S. Assine, Alan Godoy, Eduardo Valle

Despite recent advances in architectures for mobile devices, deep learning computational requirements remains prohibitive for most embedded devices. To address that issue, we envision sharing the computational costs of inference between local devices and the cloud, taking advantage of the compression performed by the first layers of the networks to reduce co

Davinder Singh, Naman Jain, Pranjali Jain, Pratik Kayal

India loses 35% of the annual crop yield due to plant diseases. Early detection of plant diseases remains difficult due to the lack of lab infrastructure and expertise. In this paper, we explore the possibility of computer vision approaches for scalable and early plant disease detection. The lack of availability of sufficiently large-scale non-lab data set r

Yansong Gao, Yeonjae Kim, Bao Gia Doan, Zhi Zhang

This work corroborates a run-time Trojan detection method exploiting STRong Intentional Perturbation of inputs, is a multi-domain Trojan detection defence across Vision, Text and Audio domains---thus termed as STRIP-ViTA. Specifically, STRIP-ViTA is the first confirmed Trojan detection method that is demonstratively independent of both the task domain and mo

Margaret Trautner, Sai Ravela

Neural dynamical systems are dynamical systems that are described at least in part by neural networks. The class of continuous-time neural dynamical systems must, however, be numerically integrated for simulation and learning. Here, we present a compact neural circuit for two common numerical integrators: the explicit fixed-step Runge-Kutta method of any ord

Benyuan Zhao, Peichao Zhang, Yizhi Cheng

Considering the potential of thermostatically controlled loads (TCLs) to provide flexibility in demand response or load control, a semi-Markov model (SMM) for the ON/OFF controlled TCL is developed in this paper. This model makes full use of the adjustment flexibility of TCLs when the control period is long and maintains the diversity of switch state in the

Yibo Yang, Jianlong Wu, Hongyang Li, Xia Li

The correspondence between residual networks and dynamical systems motivates researchers to unravel the physics of ResNets with well-developed tools in numeral methods of ODE systems. The Runge-Kutta-Fehlberg method is an adaptive time stepping that renders a good trade-off between the stability and efficiency. Can we also have an adaptive time stepping for

Leandro Lichtenfelz, Gerard Misiolek, Stephen C. Preston

We study the Riemannian geometry of 3D axisymmetric ideal fluids. We prove that the $L^2$ exponential map on the group of volume-preserving diffeomorphisms of a $3$-manifold is Fredholm along axisymmetric flows with sufficiently small swirl. Along the way, we define the notions of axisymmetric and swirl-free diffeomorphisms of any manifold with suitable symm

He-Feng Yin, Xiao-Jun Wu, Josef Kittler, Zhen-Hua Feng

Sparse-representation-based classification (SRC) has been widely studied and developed for various practical signal classification applications. However, the performance of a SRC-based method is degraded when both the training and test data are corrupted. To counteract this problem, we propose an approach that learns Representation with Block-Diagonal Struct

Aaditya Kharel, Zhifu Xie, Huiqing Zhu, Michelle McCullum

This paper investigates a dynamical predator-prey interaction model that incorporates: (a) hunting cooperation among predators; (b) Allee effect in prey. We show all possible boundary and interior solutions. In order to analyze the stability of the solution, we make use of the Jacobian matrix and the resultant characteristic polynomial. Particularly, the sig

Pawel Dlotko, Wanling Qiu, Simon Rudkin

Firm financials are well established as return predictors, being the inspiration for a large set of anomalies in the asset pricing literature. Employing topological data analysis we revisit the question of association between seven of the most commonly studied financial ratios and stock returns. Specifically the TDA Ball Mapper algorithm is applied to visual

João Paulo Lima de Oliveira, Alexandre J. Santana, Simão N. Stelmastchuk

The purpose of this paper is to describe explicitly the solution for linear control systems on Lie groups. In case of linear control systems with inner derivations, the solution is given basically by the product of the exponential of the associated invariant system and the exponential of the associated invariant drift field. We present the solutions in low d

Jianguo Chen, Philip S. Yu

As one type of efficient unsupervised learning methods, clustering algorithms have been widely used in data mining and knowledge discovery with noticeable advantages. However, clustering algorithms based on density peak have limited clustering effect on data with varying density distribution (VDD), equilibrium distribution (ED), and multiple domain-density m

Mikil Foss

The paper provides two versions of nonlocal Poincaré-type inequalities for integral operators with a convolution-type structure and functions satisfying a zero-Dirichlet like condition. The inequalities extend existing results to a large class of nonhomogeneous kernels with supports that can vary discontinuously and need not contain a common set throughout t

Wei-An Lin, Yogesh Balaji, Pouya Samangouei, Rama Chellappa

Inferring the latent variable generating a given test sample is a challenging problem in Generative Adversarial Networks (GANs). In this paper, we propose InvGAN - a novel framework for solving the inference problem in GANs, which involves training an encoder network capable of inverting a pre-trained generator network without access to any training data. Un

Sam Kriegman, Amir Mohammadi Nasab, Dylan Shah, Hannah Steele

The manual design of soft robots and their controllers is notoriously challenging, but it could be augmented---or, in some cases, entirely replaced---by automated design tools. Machine learning algorithms can automatically propose, test, and refine designs in simulation, and the most promising ones can then be manufactured in reality (sim2real). However, it

Alin Bostan, Jordan Tirrell, Bruce W. Westbury, Yi Zhang

We study two families of sequences, listed in the On-Line Encyclopedia of Integer Sequences (OEIS), which are associated to invariant theory of Lie algebras. For the first family, we prove combinatorially that the sequences A059710 and A108307 are related by a binomial transform. Based on this, we present two independent proofs of a recurrence equation for A

Ghouthi Boukli Hacene, François Leduc-Primeau, Amal Ben Soussia, Vincent Gripon

Because deep neural networks (DNNs) rely on a large number of parameters and computations, their implementation in energy-constrained systems is challenging. In this paper, we investigate the solution of reducing the supply voltage of the memories used in the system, which results in bit-cell faults. We explore the robustness of state-of-the-art DNN architec

N. Poonthottathil, F. Krennrich, J. Eisch, A. Weinstein

Cold electronics is a key technology in many areas of science and technology including space exploration programs and particle physics. A major experiment with a very large number of analog and digital electronics signal processing channels to be operated at cryogenic temperatures is the next-generation neutrino experiment, the Deep Underground Neutrino Expe

Christoforos Somarakis, Yaser Ghaedsharaf, Nader Motee

We quantify the value-at-risk of inter-vehicle collision and detachment for a class of platoons, which are governed by second-order dynamics in presence of communication time-delay and exogenous stochastic noise. Closed-form expressions for the risk measures are obtained as functions of Laplacian eigen-spectrum as well as their fine explicit approximations u

Lirui Wang, Yu Xiang, Dieter Fox

In robot manipulation, planning the motion of a robot manipulator to grasp an object is a fundamental problem. A manipulation planner needs to generate a trajectory of the manipulator arm to avoid obstacles in the environment and plan an end-effector pose for grasping. While trajectory planning and grasp planning are often tackled separately, how to efficien

Linh Tran, Van Vu

A community of $n$ individuals splits into two camps, Red and Blue. The individuals are connected by a social network, which influences their colors. Everyday, each person changes his/her color according to the majority among his/her neighbors. Red (Blue) wins if everyone in the community becomes Red (Blue) at some point. We study this process when the under

Chao Zhang, Xiang Zhao, Anzhong Wang, Bin Wang

We study gravitational waves emitted by a binary system of non-spinning bodies in a quasi-circular inspiral within the framework of Einstein-aether theory. In particular, we compute explicitly and analytically the expressions for the time-domain and frequency-domain waveforms, gravitational wave polarizations, and response functions for both ground- and spac

Sanson T. S. Poon, Richard P. Nelson, Seth A. Jacobson, Alessandro Morbidelli

NASA's Kepler mission discovered $\sim700$ planets in multi-planet systems containing 3 or more transiting bodies, many of which are super-Earths and mini-Neptunes in compact configurations. Using $N$-body simulations, we examine the in situ, final stage assembly of multi-planet systems via the collisional accretion of protoplanets. Our initial conditions ar

Savannah R. Benbrook, Caitlin A. Chapin, Ruochen Lu, Yansong Yang

This paper is the first report of the high-temperature characteristics of a laterally vibrating piezoelectric lithium niobate (LiNbO$_{3}$) MEMS resonator array up to 500{\deg}C in air. After a high-temperature burn-in treatment, device quality factor (Q) is enhanced to 508 and the resonance shifts to a lower frequency and remains stable up to 500{\deg}C. Du

Bianca Giovanardi, Santiago Serebrinsky, Raul Radovitzky

The propagation of cracks driven by a pressurized fluid emerges in several areas of engineering, including structural, geotechnical, and petroleum engineering. We present a robust numerical framework to simulate fluid-driven fracture propagation that addresses the challenges emerging in the simulation of this complex coupled nonlinear hydro-mechanical respon

Rachel C. Kurchin, Jeremy R. Poindexter, Ville Vähänissi, Hele Savin

Defect-assisted recombination processes are critical to understand, as they frequently limit photovoltaic (PV) device performance. However, the physical parameters governing these processes can be extremely challenging to measure, requiring specialized techniques and sample preparation. And yet the fact that they limit performance as measured by current-volt

Max Reinhold Jahnke

Inspired by the work of Chevalley and Eilenberg on the de Rham cohomology on compact Lie groups, we prove that, under certain algebraic and topological conditions, the cohomology associated to left-invariant elliptic, and even hypocomplex, involutive structures on compact Lie groups can be computed by using only Lie algebras, thus reducing the analytical pro

A. Duzgun, C. Nisoli, C. J. O. Reichhardt, C. Reichhardt

Using continuum based simulations we show that a rich variety of skyrmion liquid crystal states can be realized in the presence of a periodic obstacle array. As a function of the number of skyrmions per obstacle we find hexagonal, square, dimer, trimer and quadrimer ordering, where the $n$-mer structures are a realization of a molecular crystal state of skyr

Amanda Bouman, Paul Nadan, Matthew Anderson, Daniel Pastor

Aircraft that can launch ballistically and convert to autonomous, free flying drones have applications in many areas such as emergency response, defense, and space exploration, where they can gather critical situational data using onboard sensors. This paper presents a ballistically launched, autonomously stabilizing multirotor prototype (SQUID, Streamlined

Rizwanur Khan, Djordje Milićević, Hieu T. Ngo

We show that for at least $\frac{5}{13}$ of the primitive Dirichlet characters $\chi$ of large prime modulus, the central value $L(\frac{1}{2},\chi)$ does not vanish, improving on the previous best known result of $\frac{3}{8}$.

CMS Collaboration

A search for lepton flavour violating decays of a neutral non-standard-model Higgs boson in the $\mu\tau$ and e$\tau$ decay modes is presented. The search is based on proton-proton collisions at a center of mass energy $\sqrt{s} =$ 13 TeV collected with the CMS detector in 2016, corresponding to an integrated luminosity of 35.9 fb$^{-1}$. The $\tau$ leptons

Justyna M. Sokół, Marzena A. Kubiak, Maciej Bzowski, Eberhard Möbius

The interstellar neutral (ISN) gas enters the heliosphere and is detected at a few au from the Sun, as demonstrated by Ulysses and the nterstellar Boundary Explorer (IBEX) missions. Ulysses observed ISN gas from different vantage points in a polar orbit from 1994 to 2007, while IBEX has been observing in an Earth orbit in a fixed direction relative to the Su

Zahra Sadre Momtaz, Stefano Servino, Valeria Demontis, Valentina Zannier

We report results on the control of barrier transparency in InAs/InP nanowire quantum dots via the electrostatic control of the device electron states. Recent works demonstrated that barrier transparency in this class of devices displays a general trend just depending on the total orbital energy of the trapped electrons. We show that a qualitatively differen

Ariadne Nogueira, Jean Carlos Nakasato

In this work we use reiterated homogenization and unfolding operator approach to study the asymptotic behavior of the solutions of the $p$-Laplacian equation with Neumann boundary conditions set in a rough thin domain with concentrated terms on the boundary. We study weak, resonant and high roughness, respectively. In the three cases, we deduce the effective

Marek Karliner, Jonathan L. Rosner

We comment on the results of the recent search by the LHCb collaboration for the doubly charmed baryon $\Xi_{cc}^+$.

Sahil Singla, Soheil Feizi

In deep neural networks, the spectral norm of the Jacobian of a layer bounds the factor by which the norm of a signal changes during forward/backward propagation. Spectral norm regularizations have been shown to improve generalization, robustness and optimization of deep learning methods. Existing methods to compute the spectral norm of convolution layers ei

Marat Pliev, Martin R. Weber

We consider $C$-compact orthogonally additive operators in vector lattices. After providing some examples of $C$-compact orthogonally additive operators on a vector lattice with values in a Banach space we show that the set of those operators is a projection band in the Dedekind complete vector lattice of all regular orthogonally additive operators. In secon

Lei Chen, Attila Moor, Alexander Kreplin, Agnes Kospal

The Herbig Ae star HD 169142 is known to have a gaseous disk with a large inner hole, and also a photometrically variable inner dust component in the sub-au region. Following up our previous analysis, we further studied the temporal evolution of inner dust around HD 169142, which may provide information on the evolution from late-stage protoplanetary disks t

Shubham Tripathi, David A. Kessler, Herbert Levine

Characterization of the differences between biological and random networks can reveal the design principles that enable the robust realization of crucial biological functions including the establishment of different cell types. Previous studies, focusing on identifying topological features that are present in biological networks but not in random networks, h

Jisan Mahmud, Rajat Vikram Singh, Peri Akiva, Spondon Kundu

The rapid development of inexpensive commodity depth sensors has made keypoint detection and matching in the depth image modality an important problem in computer vision. Despite great improvements in recent RGB local feature learning methods, adapting them directly in the depth modality leads to unsatisfactory performance. Most of these methods do not expli

Mohammadhosein Hasanbeig, Natasha Yogananda Jeppu, Alessandro Abate, Tom Melham

This paper proposes DeepSynth, a method for effective training of deep Reinforcement Learning (RL) agents when the reward is sparse and non-Markovian, but at the same time progress towards the reward requires achieving an unknown sequence of high-level objectives. Our method employs a novel algorithm for synthesis of compact automata to uncover this sequenti

Anirudha Menon, Tom Pardini, Rajiv R. P. Singh

We study an effective spin model derived perturbatively from random transverse-field Ising model on the pyrochlore lattice. The model consists of spin-configurations on the pyrochlore lattice, restricted to the spin-ice subspace, with spins interacting with random Ising exchange couplings as well as ring exchanges along the hexagons of the lattice. This mode

Samuel G. Finlayson, Matthew B. A. McDermott, Alex V. Pickering, Scott L. Lipnick

Modeling the relationship between chemical structure and molecular activity is a key goal in drug development. Many benchmark tasks have been proposed for molecular property prediction, but these tasks are generally aimed at specific, isolated biomedical properties. In this work, we propose a new cross-modal small molecule retrieval task, designed to force a

Julio C. S. Araujo, Pedro S. M. Arraes

Let $D$ be an orientation of a simple graph. Given $u,v\in V(D)$, a directed shortest $(u,v)$-path is a $(u,v)$-geodesic. $S \subseteq V(D)$ is convex if, for every $u,v \in S$, the vertices in each $(u,v)$-geodesic and in each $(v,u)$-geodesic are in $S$. For each $S \subseteq V(D)$ the (convex) hull of $S$, denoted by $[S]$, is the smallest convex set cont

Tian Li, Fu Li, Charles Altuzarra, Anton Classen

Two-photon absorption (TPA) fluorescence of biomarkers has been decisive in advancing the fields of biosensing and deep-tissue in vivo imaging of live specimens. However, due to the extremely small TPA cross section and the quadratic dependence on the input photon flux, extremely high peak-intensity pulsed lasers are imperative, which can result in significa

Jonas Gaël Roch, Dmitry Miserev, Guillaume Froehlicher, Nadine Leisgang

Evidence is presented for a first-order magnetic phase transition in a gated two-dimensional semiconductor, monolayer-MoS$_2$. The phase boundary separates a spin-polarised (ferromagnetic) phase at low electron density and a paramagnetic phase at high electron density. Abrupt changes in the optical response signal an abrupt change in the magnetism. The magne

Sara Algeri, Jelle Aalbers, Knut Dundas Morå, Jan Conrad

Particle physics experiments use likelihood ratio tests extensively to compare hypotheses and to construct confidence intervals. Often, the null distribution of the likelihood ratio test statistic is approximated by a $\chi^2$ distribution, following a theorem due to Wilks. However, many circumstances relevant to modern experiments can cause this theorem to

Robert Schneider, James A. Sellers, Ian Wagner

In recent work, M. Schneider and the first author studied a curious class of integer partitions called "sequentially congruent" partitions: the $m$th part is congruent to the $(m+1)$th part modulo $m$, with the smallest part congruent to zero modulo the number of parts. Let $p_{\mathcal S}(n)$ be the number of sequentially congruent partitions of $n,$ and le

Vyachesval Grines, Elena Gurevich, Olga Pochinka, Dmitrii Malyshev

We consider a class $G(S^n)$ of orientation preserving Morse-Smale diffeomorphisms of the sphere $S^{n}$ of dimension $n>3$ in assumption that invariant manifolds of different saddle periodic points have no intersection. We put in a correspondence for every diffeomorphism $f\in G(S^n)$ a colored graph $\Gamma_f$ enriched by an automorphism $P_f$. Then we def

Raul Laasner, Xiaochen Du, Aditya Tanikanti, Connor Clayton

The discovery of new materials as well as the determination of a vast set of materials properties for science and technology is a fast growing field of research, with contributions from many groups worldwide. Materials data from individual research groups is traditionally disseminated by means of loosely interconnected, peer-reviewed publications. MatD3 is a

Amit Pande, Kai Ni, Venkataramani Kini

Recent advancements in deep neural networks for graph-structured data have led to state-of-the-art performance on recommender system benchmarks. In this work, we present a Graph Convolutional Network (GCN) algorithm SWAG (Sample Weight and AGgregate), which combines efficient random walks and graph convolutions on weighted graphs to generate embeddings for n

P. Swaczyna, D. J. McComas, E. J. Zirnstein, J. Heerikhuisen

Interstellar neutral atoms provide a remote diagnostic of plasma in the outer heliosheath and the very local interstellar medium via charge exchange collisions that convert ions into atoms and vice versa. So far, most studies of interstellar atoms assumed that daughter hydrogen atoms directly inherit the kinetic properties of parent protons. This assumption

Vyom Raval, Kevin P. Nguyen, Albert Montillo

Head motion during functional Magnetic Resonance Imaging acquisition can significantly contaminate the neural signal and introduce spurious, distance-dependent changes in signal correlations. This can heavily confound studies of development, aging, and disease. Previous approaches to suppress head motion artifacts have involved sequential regression of nuisa

Benedikt Dorschner, Ke Yu, Gianmarco Mengaldo, Tim Colonius

We propose a mesh refinement technique for solving elliptic difference equations on unbounded domains based on the fast lattice Green's function (FLGF) method. The FLGF method exploits the regularity of the Cartesian mesh and uses the fast multipole method in conjunction with fast Fourier transforms to yield linear complexity and decrease time-to-solution. W

Kush Mohan Mittal, Olivier Giraud, Denis Ullmo

Semiclassical Mechanics allows for a description of quantum systems which preserves their phase information, while using only the system's classical dynamics as an input. Over the time an identification has been developed between stationary phase approximation and semiclassical mechanics. Although it is true that in most of the cases in semiclassical mechani

Sicheng Zhao, Guangzhi Wang, Shanghang Zhang, Yang Gu

Deep neural networks suffer from performance decay when there is domain shift between the labeled source domain and unlabeled target domain, which motivates the research on domain adaptation (DA). Conventional DA methods usually assume that the labeled data is sampled from a single source distribution. However, in practice, labeled data may be collected from

Juan-José Giraldo, Mauricio A. Álvarez

A recent novel extension of multi-output Gaussian processes handles heterogeneous outputs assuming that each output has its own likelihood function. It uses a vector-valued Gaussian process prior to jointly model all likelihoods' parameters as latent functions drawn from a Gaussian process with a linear model of coregionalisation covariance. By means of an i

S. López Pérez, D. Manreza Paret, G. Quintero Angulo, A. Pérez Martínez

Compact objects have an intrinsic anisotropy due to the presence of strong magnetic fields that cause considerable modifications on the equations of state (EoS). In this work, we study the impact of this anisotropy in the size and shape of magnetized strange quark stars using an axially symmetric metric in spherical coordinates, the gamma-metric. The results

Christopher T. Hill

We consider multi-Higgs-doublet models which, for symmetry reasons, have a universal Higgs-Yukawa (HY) coupling, $g$. This is identified with the top quark $g=g_t\approx 1$. The models are concordant with the quasi-infrared fixed point, and the top quark mass is correctly predicted with a compositeness scale (Landau pole) at $M_{planck}$, with sensitivity to

Jamie I. McDonald, Luís B. Ventura

We discuss spectral distortions, time delays and refraction of light in an axion or axion-plasma background. This involves solving the full set of geodesic equations associated to the system of Hamiltonian optics, allowing us to self-consistently take into account the evolution of the momentum, frequency and position of photons. We support our arguments with

Alexandre Arbey, Jean-François Coupechoux

Observations of gravitational waves provide new opportunities to study our Universe. In particular, mergers of stellar black holes are the main targets of the current gravitational wave experiments. In order to make accurate predictions, it is however necessary to simulate the mergers in numerical general relativity, which requires high performance computing

Gregor Kälin, Gustav Mogull, Alexander Ochirov, Bram Verbeek

Using a careful choice of infrared (IR) subtraction scheme, we demonstrate the cancellation of all terms with transcendental weights 0,1,2 from the finite part of the full-color two-loop four-gluon $\mathcal{N}=2$ supersymmetric QCD amplitude, with $N_f$ massless supersymmetric quarks. This generalizes the previously observed cancellation of weight-2 terms i

Jacopo Pantaleoni

In this manuscript, we introduce a novel technique for sampling and integrating direct illumination in the presence of many lights. Unlike previous work, the presented technique importance samples the product distribution of radiance and visibility while using bounded memory footprint and very low sampling overhead. This is achieved by learning a compact app

W. Li, J. C. Pober, N. Barry, B. J. Hazelton

The compact configuration of Phase II of the Murchison Widefield Array (MWA) consists of both a redundant subarray and pseudo-random baselines, offering unique opportunities to perform sky-model and redundant interferometric calibration. The highly redundant hexagonal cores give improved power spectrum sensitivity. In this paper, we present the analysis of n

Sergio Firpo, Antonio F. Galvao, Thomas Parker

We propose a method to conduct uniform inference for the (optimal) value function, that is, the function that results from optimizing an objective function marginally over one of its arguments. Marginal optimization is not Hadamard differentiable (that is, compactly differentiable) as a map between the spaces of objective and value functions, which is proble

Joshua Davies, Florian Herren, Matthias Steinhauser

We compute four-loop corrections to the Higgs boson gluon vertex, including finite top quark mass effects. Analytic results are presented which serve as a building block for the next-to-next-to-next-to-leading order corrections to Higgs boson production at the Large Hadron Collider at CERN.

Benjamin Basso, Gwenaël Ferrando, Vladimir Kazakov, De-liang Zhong

We present the TBA equations and the Y-system for the exact spectrum of general multi-magnon local operators in the $D$-dimensional anisotropic version of the bi-scalar fishnet CFT. The mixing matrix of such operators is given in terms of fishnet planar graphs of multi-wheel and multi-spiral type. These graphs probe the two main building blocks of the TBA ap

Dominika Wylezalek, Anthony M. Flores, Nadia L. Zakamska, Jenny E. Greene

The prevalence of outflow and feedback signatures in active galactic nuclei (AGN) is a major unresolved question which large integral field unit (IFU) surveys now allow to address. In this paper, we present a kinematic analysis of the ionised gas in 2778 galaxies at z $\sim$ 0.05 observed by SDSS-IV MaNGA. Specifically, we measure the kinematics of the [OIII

Nimisha Kumari, Mike J Irwin, Bethan L James

The global Schmidt law of star formation provides a power-law relation between the surface densities of star-formation rate (SFR) and gas, and successfully explains plausible scenarios of galaxy formation and evolution. However, star formation being a multi-scale process, requires spatially-resolved analysis for a better understanding of the physics of star

Jonathan Kozaczuk, Michael J. Ramsey-Musolf, Jessie Shelton

Light new physics weakly coupled to the Higgs can induce a strong first-order electroweak phase transition (EWPT). Here, we argue that scenarios in which the EWPT is driven first-order by a light scalar with mass between $\sim 10$ GeV - $m_h/2$ and small mixing with the Higgs will be conclusively probed by the high-luminosity LHC and future Higgs factories.

Christiaan P. Korthals Altes, Hiromichi Nishimura, Robert D. Pisarski, Vladimir V. Skokov

We compute the term $\sim g^3$ in the free energy for a $SU(N)$ gauge theory with nonzero holonomy at nonzero temperature. If the holonomy is generated kinematically by the introduction of gauge invariant sources coupled to Polyakov loops, the contribution of charged (off-diagonal) gluons to the free energy at order $g^3$, ${\cal F}^{\left( 3\rm{:c.g.} \righ

Jakub Mielczarek, Tomasz Trześniewski

The purpose of this letter is to explore the relation between gauge fields, which are at the base of our understanding of fundamental interactions, and the quantum entanglement. To this end, we investigate the case of ${\rm SU}(2)$ gauge fields. It is first argued that holonomies of the ${\rm SU}(2)$ gauge fields are naturally associated with maximally entan

Ning Bao, Aidan Chatwin-Davies, Jason Pollack, Grant N. Remmen

We study the effects of gravitationally-driven decoherence on tunneling processes associated with false vacuum decays, such as the Coleman--De~Luccia instanton. We compute the thermal graviton-induced decoherence rate for a wave function describing a perfect fluid of nonzero energy density in a finite region. When the effective cosmological constant is posit

Marcela Carena, Zhen Liu, Yikun Wang

This work investigates a simple, representative extension of the Standard Model with a real scalar singlet and spontaneous $Z_2$ breaking, which allows for a strongly first-order phase transition, as required by electroweak baryogenesis. We perform analytical and numerical calculations that systematically include one-loop thermal effects, Coleman-Weinberg co

Ho Lun Tang, V. O. Shkolnikov, George S. Barron, Harper R. Grimsley

Quantum simulation, one of the most promising applications of a quantum computer, is currently being explored intensely using the variational quantum eigensolver. The feasibility and performance of this algorithm depend critically on the form of the wavefunction ansatz. Recently in Nat. Commun. 10, 3007 (2019), an algorithm termed ADAPT-VQE was introduced to

Prasenjit Saha

In 2019 the International System of units (SI) conceptually re-invented itself. This was necessary because quantum-electronic devices had become so precise that the old SI could no longer calibrate them. The new system defines values of fundamental constants (including $c,h,k,e$ but not $G$) and allows units to be realized from the defined constants through

Daniel Egana-Ugrinovic, Samuel Homiller, Patrick Meade

The KOTO experiment recently presented a significant excess of events in their search for the rare SM process $K_L \to \pi^0\nu\bar{\nu}$, well above both Standard Model signal and background predictions. We show that this excess may be due to weakly-coupled scalars that are produced from Kaon decays and escape KOTO undetected. We study two concrete realizat

J. A. Aguilar-Saavedra, J. Alonso-Gonzalez, L. Merlo, J. M. No

Extensions of the Standard Model that include vector-like quarks commonly also include additional particles that may mediate new production or decay modes. Using as example the minimal linear $\sigma$ model, that reduces to the minimal $SO(5)/SO(4)$ composite Higgs model in a specific limit, we consider the phenomenology of vector-like quarks when a scalar s

Bowen Cheng, Maxwell D. Collins, Yukun Zhu, Ting Liu

In this work, we introduce Panoptic-DeepLab, a simple, strong, and fast system for panoptic segmentation, aiming to establish a solid baseline for bottom-up methods that can achieve comparable performance of two-stage methods while yielding fast inference speed. In particular, Panoptic-DeepLab adopts the dual-ASPP and dual-decoder structures specific to sema

Niloofar Bayat, Kunal Mahajan, Sam Denton, Vishal Misra

Despite society's strong dependence on electricity, power outages remain prevalent. Standard methods for directly measuring power availability are complex, often inaccurate, and are prone to attack. This paper explores an alternative approach to identifying power outages through intelligent monitoring of IP address availability. In finding these outages, we

Jie Xu

We introduce an iterative method to prove the existence and uniqueness of the complex-valued nonlinear elliptic PDE of the form $ -\Delta u + F(u) = f $ with Dirichlet or Neumann boundary conditions on a precompact domain $ \Omega \subset \mathbb{R}^{n}$, where $ F : \mathbb{C} \rightarrow \mathbb{C} $ is Lipschitz. The same method gives a solution to $ - \D

Sen Tian, Clifford M. Hurvich, Jeffrey S. Simonoff

Least squares (LS)-based subset selection methods are popular in linear regression modeling. Best subset selection (BS) is known to be NP-hard and has a computational cost that grows exponentially with the number of predictors. Recently, Bertsimas (2016) formulated BS as a mixed integer optimization (MIO) problem and largely reduced the computation overhead

Johann Bellmann, Bjarne Schülke

For $k,n\in \mathbb{N}$, the Kneser graph $K(n,k)$ is the graph with vertex set $V=[n]^{(k)}$ and edge set $E=\{\{x,y\} \in V^{(2)}: x\cap y=\emptyset\}$. Chen proved that for $n\geq 3k$, Kneser graphs are Hamiltonian. Similarly as for graphs with Hajnal's and Szemerédi's result about a minimum degree condition for clique factors and the Pósa-Seymour

C. Casentini, F. Verrecchia, M. Tavani, A. Ursi

We focus on two repeating fast radio bursts (FRBs) recently detected by the CHIME/FRB experiment in 2018--2019 (Source 1: 180916.J0158+65, and Source 2: 181030.J1054+73). These sources have low excess dispersion measures (DMs) ($ < 100 \rm \, pc \, cm^{-3}$ and $ < 20 \rm \, pc \, cm^{-3}$, respectively), implying relatively small maximal distances. They wer

Amit Kumar Sikder, Leonardo Babun, Z. Berkay Celik, Abbas Acar

In a smart home system, multiple users have access to multiple devices, typically through a dedicated app installed on a mobile device. Traditional access control mechanisms consider one unique trusted user that controls the access to the devices. However, multi-user multi-device smart home settings pose fundamentally different challenges to traditional sing

D. R. Matus Carillo, M. Fellhauer, A. G. Alarcon Jara, C. A. Aravena

The aim of this work is to find a progenitor for Canes Venatici I (CVn I), under the assumption that it is a dark matter free object that is undergoing tidal disruption. With a simple point mass integrator, we searched for an orbit for this galaxy using its current position, position angle, and radial velocity in the sky as constraints. The orbit that gives

Dan Li, Dariush Fooladivanda, Sonia Martinez

This paper studies a data-driven predictive control for a class of control-affine systems which is subject to uncertainty. With the accessibility to finite sample measurements of the uncertain variables, we aim to find controls which are feasible and provide superior performance guarantees with high probability. This results into the formulation of a stochas

Edwin Simpson, Yang Gao, Iryna Gurevych

For many NLP applications, such as question answering and summarisation, the goal is to select the best solution from a large space of candidates to meet a particular user's needs. To address the lack of user-specific training data, we propose an interactive text ranking approach that actively selects pairs of candidates, from which the user selects the best

Jon Vadillo, Roberto Santana

Adversarial examples are inputs intentionally perturbed with the aim of forcing a machine learning model to produce a wrong prediction, while the changes are not easily detectable by a human. Although this topic has been intensively studied in the image domain, classification tasks in the audio domain have received less attention. In this paper we address th

Alberto Padovan, Samuel E. Otto, Clarence W. Rowley

We propose a framework that elucidates the input-output characteristics of flows with complex dynamics arising from nonlinear interactions between different time scales. More specifically, we consider a periodically time-varying base flow, and perform a frequency-domain analysis of periodic perturbations about this base flow; the response of these perturbati

Nozomi Ito

In this paper, we discuss the representation-theoretical Miyawaki lift for unitary groups in terms of the endoscopic classification. We give an explicit determination of Miyawaki lifts for U(1) and U(3) with respect to Hermitian Maass lifts, namely Ikeda lifts for U(4).

Daniel Roth, Marc Erich Latoschik

User embodiment is important for many virtual reality (VR) applications, for example, in the context of social interaction, therapy, training, or entertainment. However, there is no validated instrument to empirically measure the perception of embodiment, necessary to reliably evaluate this important quality of user experience (UX). To assess components of v

Zhangxiaowen Gong, Houxiang Ji, Christopher Fletcher, Christopher Hughes

Our community has greatly improved the efficiency of deep learning applications, including by exploiting sparsity in inputs. Most of that work, though, is for inference, where weight sparsity is known statically, and/or for specialized hardware. We propose a scheme to leverage dynamic sparsity during training. In particular, we exploit zeros introduced by th

James M. Stevenson, Leif D. Jacobson, Yutong Zhao, Chuanjie Wu

We have developed a neural network potential energy function for use in drug discovery, with chemical element support extended from 41% to 94% of druglike molecules based on ChEMBL. We expand on the work of Smith et al., with their highly accurate network for the elements H, C, N, O, creating a network for H, C, N, O, S, F, Cl, P. We focus particularly on th

Jiri Mazurek, Konrad Kułakowski

We examine satisfaction of the condition of order preservation (COP) with respect to different levels of inconsistency for randomly generated multiplicative pairwise comparison matrices (MPCMs) of the order n = {3,4,...,9}, where a priority vector is derived both by the eigenvalue method (EV) and the geometric mean (GM) method. Our results suggest the GM met

Yang Cai, Argyris Oikonomou, Grigoris Velegkas, Mingfei Zhao

We consider the black-box reduction from multi-dimensional revenue maximization to virtual welfare maximization. Cai et al. show a polynomial-time approximation-preserving reduction, however, the mechanism produced by their reduction is only approximately Bayesian incentive compatible ($\varepsilon$-BIC). We provide two new polynomial time transformations th