June 2020 arXiv papers — page 38

Yiwen Sun, Kun Fu, Zheng Wang, Changshui Zhang

Recently, deep learning have achieved promising results in Estimated Time of Arrival (ETA), which is considered as predicting the travel time from the origin to the destination along a given path. One of the key techniques is to use embedding vectors to represent the elements of road network, such as the links (road segments). However, the embedding suffers

Yossi Arjevani, Yair Carmon, John C. Duchi, Dylan J. Foster

We design an algorithm which finds an $ε$-approximate stationary point (with $\|\nabla F(x)\|\le ε$) using $O(ε^{-3})$ stochastic gradient and Hessian-vector products, matching guarantees that were previously available only under a stronger assumption of access to multiple queries with the same random seed. We prove a lower bound which establishes that this

Yatao Bian, Joachim M. Buhmann, Andreas Krause

Continuous submodular functions are a category of generally non-convex/non-concave functions with a wide spectrum of applications. The celebrated property of this class of functions - continuous submodularity - enables both exact minimization and approximate maximization in poly. time. Continuous submodularity is obtained by generalizing the notion of submod

Xin Luna Dong, Xiang He, Andrey Kan, Xian Li

Can one build a knowledge graph (KG) for all products in the world? Knowledge graphs have firmly established themselves as valuable sources of information for search and question answering, and it is natural to wonder if a KG can contain information about products offered at online retail sites. There have been several successful examples of generic KGs, but

Shahin Tasoujian, Jaecheol Lee, Karolos Grigoriadis, Matthew Franchek

This paper investigates the design of a robust output-feedback linear parameter-varying (LPV) gain-scheduled controller for the speed regulation of a surface permanent magnet synchronous motor (SPMSM). Motor dynamics is defined in the $α- β$ stationary reference frame and a parameter-varying model formulation is provided to describe the SPMSM nonlinear dynam

Louis Merlin, Jean-Marc Schlenker

Let $λ_-$ and $λ_+$ be two bounded measured laminations on the hyperbolic disk $\mathbb H^2$, which "strongly fill" (definition below). We consider the left earthquakes along $λ_-$ and $λ_+$, considered as maps from the universal Teichmüller space $\mathcal T$ to itself, and we prove that the composition of those left earthquakes has a fixed point. T

Chelhwon Kim, Andrew Port, Mitesh Patel

Learning a mapping between two unrelated domains-such as image and audio, without any supervision is a challenging task. In this work, we propose a distance-preserving generative adversarial model to translate images of human faces into an audio domain. The audio domain is defined by a collection of musical note sounds recorded by 10 different instrument fam

Q. Guan, T. M. Bersano, S. Mossman, P. Engels

Double-well systems loaded with one, two, or many quantum particles give rise to intriguing dynamics, ranging from Josephson oscillation to self-trapping. This work presents theoretical and experimental results for two distinct double-well systems, both created using dilute rubidium Bose-Einstein condensates with particular emphasis placed on the role of int

Qingdong Yang, Weijin Chen, Yuntian Chen, Wei Liu

Polarization independent Mie scattering of building blocks is foundational for constructions of optical systems with robust functionalities. Conventional studies for such polarization independence are generally restricted to special states of either linear or circular polarizations, widely neglecting elliptically-polarized states that are generically present

Kuniyuki Asuma, Kotaro Niinuma, Kazuhiro Takefuji, Takahiro Aoki

Waseda University Nasu telescope array is a spatial fast Fourier transform (FFT) interferometer consisting of eight linearly aligned antennas with 20 m spherical dishes. This type of interferometer was developed to survey transient radio sources with an angular resolution as high as that of a 160 m dish with a field of view as wide as that of a 20 m dish. We

Alina Kononov, André Schleife

We present a first-principles study of pre-equilibrium stopping power and projectile charge capture in thin aluminum sheets irradiated by 6 - 60 keV protons. Our time-dependent density functional theory calculations reveal enhanced stopping power compared to bulk aluminum, particularly near the entrance layers. We propose the additional excitation channel of

Yao Cheng, Chang Xu, Zhen Hai, Yingjiu Li

Strong passwords are fundamental to the security of password-based user authentication systems. In recent years, much effort has been made to evaluate password strength or to generate strong passwords. Unfortunately, the usability or memorability of the strong passwords has been largely neglected. In this paper, we aim to bridge the gap between strong passwo

Thinh T. Doan

Motivated by broad applications in reinforcement learning and federated learning, we study local stochastic approximation over a network of agents, where their goal is to find the root of an operator composed of the local operators at the agents. Our focus is to characterize the finite-time performance of this method when the data at each agent are generated

Jiarui Cai, Yizhou Wang, Haotian Zhang, Hung-Min Hsu

Multiple object tracking (MOT) is a crucial task in computer vision society. However, most tracking-by-detection MOT methods, with available detected bounding boxes, cannot effectively handle static, slow-moving and fast-moving camera scenarios simultaneously due to ego-motion and frequent occlusion. In this work, we propose a novel tracking framework, calle

Jishnu Ray

Let $\mathbf{B}(V)$ be the admissible unitary $GL_2(\mathbb{Q}_p)$-representation associated to two dimensional crystalline Galois representation $V$ by $p$-adic Langlands constructed by Breuil. Berger and Breuil conjectured an explicit description of the locally analytic vectors $\mathbf{B}(V)_{\mathrm{la}}$ of $\mathbf{B}(V)$ which is now proved by Liu. Em

Nike Dattani, Giovanni LiManni, David Feller, Jacek Koput

We show that we can predict the first ionization energy of the carbon atom to within 0.872 cm$^{-1}$ of the experimental value. This is an improvement of more than a factor of 6.5 over the preceding best prediction in [Phys. Rev. A 81, 022503], and opens the door to achieving sub-cm$^{-1}$ accuracy for ab-initio predictions in larger elements of the periodic

Jinyi Yang, Feige Wang, Xiaohui Fan, Joseph F. Hennawi

We report the discovery of a luminous quasar, J1007+2115 at $z=7.515$ ("Pōniuā'ena"), from our wide-field reionization-era quasar survey. J1007+2115 is the second quasar now known at $z>7.5$, deep into the reionization epoch. The quasar is powered by a $(1.5\pm0.2)\times10^9$ $M_{\odot}$ supermassive black hole (SMBH), based on its broad MgII emi

Amey Bhangale, Diptarka Chakraborty, Rajendra Kumar

The problem of finding longest common subsequence (LCS) is one of the fundamental problems in computer science, which finds application in fields such as computational biology, text processing, information retrieval, data compression etc. It is well known that (decision version of) the problem of finding the length of a LCS of an arbitrary number of input se

Turgut Yilmaz, Xiao Tong, Zhongwei Dai, Jerzy T. Sadowski

Dispersionless flat bands are proposed to be a fundamental ingredient to achieve the various sought after quantum states of matter including high-temperature superconductivity1-4 and fractional quantum Hall effect5-6. Materials with such peculiar electronic states, however, are very rare and often exhibit very complex band structures. Here, we report on the

Björn Birnir, Luiza Angheluta, John Kaminsky, Xi Che

We propose a minimal spectral theory for boundary layer turbulence that captures very well the profile of the mean square velocity fluctuations in the stream-wise direction, and gives a quantitative prediction of the Townsend-Perry constants. The phenomenological model is based on connecting the statistics in the streamwise direction with the energy spectrum

Xiuting Zou, Shaofu Xu, Anyi Deng, Rui Wang

Parallel processing technology has been a primary tool for achieving high-speed, high-accuracy, and broadband processing for many years across modern information systems and data processing such as optical and radar, synthetic aperture radar imaging, digital beam forming, and digital filtering systems. However, hardware deviations in a parallel processing sy

Caleb Eckhardt, Kit Fieldhouse, Daniel Gent, Elizabeth Gillaspy

We initiate the program of extending to higher-rank graphs ($k$-graphs) the geometric classification of directed graph $C^*$-algebras, as completed in the 2016 paper of Eilers, Restorff, Ruiz, and Sorensen [ERRS16]. To be precise, we identify four "moves," or modifications, one can perform on a $k$-graph $Λ$, which leave invariant the Morita equivale

Takayuki Suzuki, Hiromichi Nakazato

A method to suppress noise, which is one of the major obstacles to obtain an optimal solution in quantum annealers, is proposed. We generalize the conventionally used Hamiltonian, i.e., the transverse field Hamiltonian, by introducing an ancillary system, which leads to cancellation of the effect of noise on the system under consideration for some typical ca

Yang Wang, Zhi Zhao, Zheng-Jian Bai

In this paper, we consider the inverse eigenvalue problem for the positive doubly stochastic matrices, which aims to construct a positive doubly stochastic matrix from the prescribed realizable spectral data. By using the real Schur decomposition, the inverse problem is written as a nonlinear matrix equation on a matrix product manifold. We propose monotone

Diego Chialva, Alexis-Michel Mugabushaka

We present DINGO (Data INtegration for Grants Ontology), an ontology that provides a machine readable extensible framework to model data for semantically-enabled applications relative to projects, funding, actors, and, notably, funding policies in the research landscape. DINGO is designed to yield high modeling power and elasticity to cope with the huge vari

Innfarn Yoo, Xiyang Luo, Yilin Wang, Feng Yang

Graphics Interchange Format (GIF) is a widely used image file format. Due to the limited number of palette colors, GIF encoding often introduces color banding artifacts. Traditionally, dithering is applied to reduce color banding, but introducing dotted-pattern artifacts. To reduce artifacts and provide a better and more efficient GIF encoding, we introduce

T. Yamaga, S. Ajimura, H. Asano, G. Beer

We have performed an exclusive measurement of the $K^{-}+\! ~^{3}{\rm He} \to Λpn$ reaction at an incident kaon momentum of $1\ {\rm GeV}/c$.In the $Λp$ invariant mass spectrum, a clear peak was observed below the mass threshold of $\bar{K}\!+\!N\!+\!N$, as a signal of the kaonic nuclear bound state, $\bar{K}NN$.The binding energy, decay width, and $S$-wave

Deanna Easley, Tyrus Berry

We develop a new approach for estimating the expected values of nonlinear functions applied to multivariate random variables with arbitrary distributions. Rather than assuming a particular distribution, we assume that we are only given the first four moments of the distribution. The goal is to summarize the distribution using a small number of quadrature nod

Peter Plavchan, Gautam Vasisht, Chas Beichman, Heather Cegla

EarthFinder is a NASA Astrophysics Probe mission concept selected for study as input to the 2020 Astrophysics National Academies Decadal Survey. The EarthFinder concept is based on a dramatic shift in our understanding of how PRV measurements should be made. We propose a new paradigm which brings the high precision, high cadence domain of transit photometry

Lichin Chen, Yu Tsao, Ji-Tian Sheu

In countries that enabled patients to choose their own providers, a common problem is that the patients did not make rational decisions, and hence, fail to use healthcare resources efficiently. This might cause problems such as overwhelming tertiary facilities with mild condition patients, thus limiting their capacity of treating acute and critical patients.

Johann Lueder, Sergei Manzhos

We present novel non-parametric representation math for local pseudopotentials (PP) based on Gaussian Process Regression (GPR). Local pseudopotentials are needed for materials simulations using Orbital-Free Density Functional Theory (OF-DFT) to reduce computational cost and to allow kinetic energy functional (KEF) application only to the valence density. Mor

Kazuma Hashimoto, Raffaella Buschiazzo, James Bradbury, Teresa Marshall

This paper presents a high-quality multilingual dataset for the documentation domain to advance research on localization of structured text. Unlike widely-used datasets for translation of plain text, we collect XML-structured parallel text segments from the online documentation for an enterprise software platform. These Web pages have been professionally tra

Hema Yoganarasimhan, Ebrahim Barzegary, Abhishek Pani

Free trial promotions, where users are given a limited time to try the product for free, are a commonly used customer acquisition strategy in the Software as a Service (SaaS) industry. We examine how trial length affect users' responsiveness, and seek to quantify the gains from personalizing the length of the free trial promotions. Our data come from a l

Dezhou Shen

In recent years, driven by the Asian film industry, such as China and India, the global box office has maintained a steady growth trend. Previous studies have rarely used long-term, full-sample film data in analysis, lack of research on actors' social networks. Existing film box office prediction algorithms only use film meta-data, lack of using social n

Vaibhav Katewa, Rajasekhar Anguluri, Fabio Pasqualetti

We study a security problem for interconnected systems, where each subsystem aims to detect local attacks using local measurements and information exchanged with neighboring subsystems. The subsystems also wish to maintain the privacy of their states and, therefore, use privacy mechanisms that share limited or noisy information with other subsystems. We quan

Edward Witten

Recently, it has been found that JT gravity, which is a two-dimensional theory with bulk action $ -\frac{1}{2}\int {\mathrm d}^2x \sqrt gϕ(R+2)$, is dual to a matrix model, that is, a random ensemble of quantum systems rather than a specific quantum mechanical system. In this article, we argue that a deformation of JT gravity with bulk action $ -\frac{1}{2}\

Stuart Eiffert, Nathan D. Wallace, He Kong, Navid Pirmarzdashti

Achieving long term autonomy of robots operating in dynamic environments such as farms remains a significant challenge. Arguably, the most demanding factors to achieve this are the on-board resource constraints such as energy, planning in the presence of moving individuals such as livestock and people, and handling unknown and undulating terrain. These consi

Dezhou Shen

With the rapid development of social network applications, social network has become an important medium for people to interact. For the minimum distance computation of all pairs in networks, Alon N[4] proposed an algorithm with matrix multiplication, combining with distance product association law and block matrix multiplication, all pairs shortest path len

Chao Zhang, Zhiyuan Ren, Jingwen Wu, Di Li

We studied the filament structures and dense cores in OMC-2,3 region in Orion A North molecular cloud using the high-resolution N2H+ (1-0) spectral cube observed with the Atacama Large Millimeter/Submillimeter Array (ALMA). The filament network over a total length of 2 pc is found to contain 170 intersections and 128 candidate dense cores. The dense cores ar

Brandon Cui, Yinlam Chow, Mohammad Ghavamzadeh

A major challenge in modern reinforcement learning (RL) is efficient control of dynamical systems from high-dimensional sensory observations. Learning controllable embedding (LCE) is a promising approach that addresses this challenge by embedding the observations into a lower-dimensional latent space, estimating the latent dynamics, and utilizing it to perfo

T. Spina, B. M. Tennis, J. Lee, D. N. Seidman

Nb$_3$Sn is a promising advanced material under development for superconducting radiofrequency (SRF) cavities. Past efforts have been focused primarily on small development-scale cavities, but large, often multi-celled cavities, are needed for particle accelerator applications. In this work, we report on successful Nb$_3$Sn coatings on Nb in a 1 m-long 9-cel

Yvonne R. Stürz, Edward L. Zhu, Ugo Rosolia, Karl H. Johansson

This paper presents a distributed learning model predictive control (DLMPC) scheme for distributed linear time invariant systems with coupled dynamics and state constraints. The proposed solution method is based on an online distributed optimization scheme with nearest-neighbor communication. If the control task is iterative and data from previous feasible i

Yi Tian, Jian Qian, Suvrit Sra

We study minimax optimal reinforcement learning in episodic factored Markov decision processes (FMDPs), which are MDPs with conditionally independent transition components. Assuming the factorization is known, we propose two model-based algorithms. The first one achieves minimax optimal regret guarantees for a rich class of factored structures, while the sec

Terufumi Yamaguchi, Nozomi Akashi, Sumito Tsunegi, Hitoshi Kubota

The role of the feedback effect on physical reservoir computing is studied theoretically by solving the vortex-core dynamics in a nanostructured ferromagnet. Although the spin-transfer torque due to the feedback current makes the vortex dynamics complex, it is clarified that the feedback effect does not always contribute to the enhancement of the memory func

Derek W. Robinson

Let $Ω$ be a domain in $\Ri^d$ with boundary $Γ$${\!,}$ $d_Γ$ the Euclidean distance to the boundary and $H=-\divv(C\,\nabla)$ an elliptic operator with $C=(\,c_{kl}\,)>0$ where $c_{kl}=c_{lk}$ are real, bounded, Lipschitz functions. We assume that $C\sim c\,d_Γ^{\,δ}$ as $d_Γ\to0$ in the sense of asymptotic analysis where $c$ is a strictly positive, bounded

Pushkal Agarwal, Miriam Redi, Nishanth Sastry, Edward Wood

Wikipedia is a major source of information providing a large variety of content online, trusted by readers from around the world. Readers go to Wikipedia to get reliable information about different subjects, one of the most popular being living people, and especially politicians. While a lot is known about the general usage and information consumption on Wik

Gavin Ball, Goncalo Oliveira

This article investigates a set of partial differential equations, the DT-instanton equations, whose solutions can be regarded as a generalization of the notion of Hermitian-Yang-Mills connections. These equations owe their name to the hope that they may be useful in extending the DT-invariant to the case of symplectic 6-manifolds. In this article, we give t

Farhad Mirkarimi, Mahtab Mirmohseni, Masoumeh Nasiri-Kenari

Most diffusion based molecular channels suffer from low information capacity due to the structure of the diffusion environment. To address this issue, this paper studies the capacity of the diffusion based molecular communication by exploiting both time and concentration level of the released molecules for information transfer. The transmitter releases molec

Yann Beilliard, François Paquette, Frédéric Brousseau, Serge Ecoffey

This study demonstrates multilevel switching at 1.5 K of Al2O3/TiO2-x resistive memory devices fabricated with CMOS-compatible processes and materials. The I-V characteristics exhibit a negative differential resistance (NDR) effect due to a Joule-heating-induced metal-insulator transition of the Ti4O7 conductive filament. Carrier transport analysis of all mu

Tom Broadhurst, Jose M. Diego, George F. Smoot

Gravitational lensing allows the detection of binary black holes (BBH) at cosmological distances with chirp masses that appear to be enhanced by $1+z$ in the range $1<z<4$, in good agreement with the reported BBH masses. We propose this effect also accounts for the puzzling &#34;mass gap&#34; events (MG) newly reported by LIGO/Virgo, as distant, lensed NSBH

Tong Zhou

This paper investigates regularity, controllability and observability for a networked dynamic system (NDS) with its subsystems being described in a descriptor form and system matrices of each subsystem being represented by a generalized linear fractional transformation (GLFT) of its parameters. Except a well-posedness condition, no any other constraints are

S. Ali Hassani Gangaraj, Boyuan Jin, Christos Argyropoulos, Francesco Monticone

Unidirectional wave propagation in nonreciprocal structures enables exciting opportunities to control and enhance wave-matter interactions in extreme ways. Within this context, here we investigate the possibility of using terminated unidirectional plasmonic waveguides to enhance typically weak nonlinear effects by orders of magnitude. We theoretically demons

Ricardo Grande, Kristin M. Kurianski, Gigliola Staffilani

This work is dedicated to putting on a solid analytic ground the theory of local well-posedness for the two dimensional Dysthe equation. This equation can be derived from the incompressible Navier-Stokes equation after performing an asymptotic expansion of a wavetrain modulation to the fourth order. Recently, this equation has been used to numerically study

Armand Comas-Massagué, Chi Zhang, Zlatan Feric, Octavia Camps

Missing data poses significant challenges while learning representations of video sequences. We present Disentangled Imputed Video autoEncoder (DIVE), a deep generative model that imputes and predicts future video frames in the presence of missing data. Specifically, DIVE introduces a missingness latent variable, disentangles the hidden video representations

Siqian Zhao, Chunpai Wang, Shaghayegh Sahebi

Students acquire knowledge as they interact with a variety of learning materials, such as video lectures, problems, and discussions. Modeling student knowledge at each point during their learning period and understanding the contribution of each learning material to student knowledge are essential for detecting students&#39; knowledge gaps and recommending l

Ben Adcock, Simone Brugiapaglia, Matthew King-Roskamp

The sparsity in levels model recently inspired a new generation of effective acquisition and reconstruction modalities for compressive imaging. Moreover, it naturally arises in various areas of signal processing such as parallel acquisition, radar, and the sparse corruptions problem. Reconstruction strategies for sparse in levels signals usually rely on a su

Hans Höngesberg

Alternating sign trapezoids have recently been introduced as a generalisation of alternating sign triangles. Fischer established a threefold refined enumeration of alternating sign trapezoids and provided three statistics on column strict shifted plane partitions with the same joint distribution. In this paper, we are able to add a new pair of statistics to

Bruna Pascual-Dias, Pratishruti Saha, David London

A number of years ago, low-energy constraints on scalar diquarks, particles that couple to two quarks, were examined. It was found that the two most weakly-constrained diquarks are $D^u$ and $D^d$, colour antitriplets that couple to $u_{R}^{i} u_{R}^{j}$ and $d_{R}^{i} d_{R}^{j}$, respectively. These diquarks have not been observed at the LHC. In this paper,

Xi Zhang

A planetary atmosphere is the outer gas layer of a planet. Besides its scientific significance among the first and most accessible planetary layers observed from space, it is closely connected with planetary formation and evolution, surface and interior processes, and habitability of planets. Current theories of the planetary atmosphere were primarily obtain

Simon Roburin, Yann de Mont-Marin, Andrei Bursuc, Renaud Marlet

Normalization Layers (NLs) are widely used in modern deep-learning architectures. Despite their apparent simplicity, their effect on optimization is not yet fully understood. This paper introduces a spherical framework to study the optimization of neural networks with NLs from a geometric perspective. Concretely, the radial invariance of groups of parameters

Tianyi Liu, Sen He, Sunzhou Huang, Danny Tsang

With the growing popularity of cloud gaming and cloud virtual reality (VR), interactive 3D applications have become a major type of workloads for the cloud. However, despite their growing importance, there is limited public research on how to design cloud systems to efficiently support these applications, due to the lack of an open and reliable research infr

Gunter Fuchs, Corey Bacal Switzer

We prove various iteration theorems for forcing classes related to subproper and subcomplete forcing, introduced by Jensen. In the first part, we use revised countable support iterations, and show that 1) the class of subproper, ${}^ωω$-bounding forcing notions, 2) the class of subproper, $T$-preserving forcing notions (where $T$ is a fixed Souslin tree) and

Ziv Ran

We study vector bundles on curves with rational tails and their smoothings and give a sufficient condition for the general fibre to be balanced.

Theodoros Stouraitis, Lei Yan, João Moura, Michael Gienger

The transition from free motion to contact is a challenging problem in robotics, in part due to its hybrid nature. Additionally, disregarding the effects of impacts at the motion planning level often results in intractable impulsive contact forces. In this paper, we introduce an impact-aware multi-mode trajectory optimization (TO) method that combines hybrid

Giuseppe Colucci, Francesco Giacosa

In this work we present an algorithm to perform algorithmic differentiation in the context of quantum computing. We present two versions of the algorithm, one which is fully quantum and one which employees a classical step (hybrid approach). Since the implementation of elementary functions is already possible on quantum computers, the scheme that we propose

Ding Wang, Brian Yueshuai He, Jingqin Gao, Joseph Y. J. Chow

The COVID-19 pandemic has affected travel behaviors and transportation system operations, and cities are grappling with what policies can be effective for a phased reopening shaped by social distancing. A baseline model was previously developed and calibrated for pre-COVID conditions as MATSim-NYC. A new COVID model is calibrated that represents travel behav

Sheila Sundaram

We investigate the homology representation of the symmetric group on rank-selected subposets of subword order. We show that the homology module for words of bounded length, over an alphabet of size $n,$ decomposes into a sum of tensor powers of the $S_n$-irreducible $S_{(n-1,1)}$ indexed by the partition $(n-1,1),$ recovering, as a special case, a theorem of

Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue

The heterogeneity in recently published knowledge graph embedding models&#39; implementations, training, and evaluation has made fair and thorough comparisons difficult. In order to assess the reproducibility of previously published results, we re-implemented and evaluated 21 interaction models in the PyKEEN software package. Here, we outline which results c

Amir Navidfar, Osman Bulut, Tugba Baytak, Hikmet Iskender

Carbon-nanofillers are known for improving the desired properties of polymers. The dispersion quality of nanofillers in the matrix is vital for the fabrication of high-performance nanocomposites. An effective approach for improving dispersion states of multi-walled carbon nanotubes (MWCNT) and graphene nanoplatelets (GNPs) was employed via hybrid inclusion o

Maurício Hippert, João Guilherme Prado Barbon, David Dobrigkeit Chinellato, Matthew Luzum

The connection between initial-state geometry and anisotropic flow can be quantified through a well-established mapping between $p_T$-integrated flow harmonics and cumulants of the initial transverse energy distribution. In this paper we successfully extend this mapping to also include $p_T$-differential flow. In doing so, we find that subleading principal c

Lian-Bao Jia, Tong Li

The long-standing Galactic center gamma-ray excess could be explained by GeV dark matter (DM) annihilation, while the DM interpretation seems in tension with recent joint limits from different astronomical scale observations, such as dwarf spheroidal galaxies, the Milky Way halo and galaxy groups/clusters. Motivated by $^8$Be and $^4$He anomalous transitions

Muhammad Ajmal Azad, Junaid Arshad, Ali Akmal, Farhan Riaz

Today&#39;s smartphones are equipped with a large number of powerful value-added sensors and features such as a low power Bluetooth sensor, powerful embedded sensors such as the digital compass, accelerometer, GPS sensors, Wi-Fi capabilities, microphone, humidity sensors, health tracking sensors, and a camera, etc. These value-added sensors have revolutioniz

Bo Li, Yezhen Wang, Tong Che, Shanghang Zhang

Domain adaptation (DA) is a technique that transfers predictive models trained on a labeled source domain to an unlabeled target domain, with the core difficulty of resolving distributional shift between domains. Currently, most popular DA algorithms are based on distributional matching (DM). However in practice, realistic domain shifts (RDS) may violate the

Jeremy Hahn, Asaf Horev, Inbar Klang, Dylan Wilson

In this paper, we study genuine equivariant factorization homology and its interaction with equivariant Thom spectra, which we construct using the language of parametrized higher category theory. We describe the genuine equivariant factorization homology of Thom spectra, and use this description to compute several examples of interest. A key ingredient for o

Melvyn B. Nathanson

A classical theorem of Kempner states that the sum of the reciprocals of positive integers with missing decimal digits converges. This result is extended to much larger families of &#34;missing digits&#34; sets of positive integers with both convergent and divergent harmonic series.

Damian C. Swift, Andrea L. Kritcher, James A. Hawreliak, James Gaffney

Time-resolved radiography can be used to obtain absolute shock Hugoniot states by simultaneously measuring at least two mechanical parameters of the shock, and this technique is particularly suitable for one-dimensional converging shocks where a single experiment probes a range of pressures as the converging shock strengthens. However, at sufficiently high p

Gilad Gour

We introduce an axiomatic approach for channel divergences and channel relative entropies that is based on three information-theoretic axioms of monotonicity under superchannels (i.e. generalized data processing inequality), additivity under tensor products, and normalization, similar to the approach given recently for the state domain. We show that these ax

Soran Jahangiri, Juan Miguel Arrazola, Nicolás Quesada, Alain Delgado

The excitation of vibrational modes in molecules affects the outcome of chemical reactions, for example by providing molecules with sufficient energy to overcome activation barriers. In this work, we introduce a quantum algorithm for simulating molecular vibrational excitations during vibronic transitions. We discuss how a special-purpose quantum computer ca

D. Condado, J. I. Castro-Alatorre, E. Sadurní

In this article we formulate and solve the problem of molecular beam diffraction when each molecule consists of two interacting bodies. Then, using our results, we present the diffraction patterns for various molecular sizes employing the harmonic oscillator as interaction model between the two atoms. Lastly, we analyze the corrections produced by the intern

Joo-Von Kim, Jeroen Mulkers

An implementation of a lattice-based approach for computing the topological skyrmion charge is provided for the open source micromagnetics code MuMax3. Its accuracy with respect to an existing method based on finite difference derivatives is compared for three different test cases. The lattice-based approach is found to be more robust for finite-temperature

Christian Grussler, Tobias Damm, Rodolphe Sepulchre

This paper considers balanced truncation of discrete-time Hankel $k$-positive systems, characterized by Hankel matrices whose minors up to order $k$ are nonnegative. Our main result shows that if the truncated system has order $k$ or less, then it is Hankel totally positive ($\infty$-positive), meaning that it is a sum of first order lags. This result can be

Alisa Liu, Alexander Fang, Gaëtan Hadjeres, Prem Seetharaman

Deep learning has rapidly become the state-of-the-art approach for music generation. However, training a deep model typically requires a large training set, which is often not available for specific musical styles. In this paper, we present augmentative generation (Aug-Gen), a method of dataset augmentation for any music generation system trained on a resour

Masoud Badiei Khuzani, Yinyu Ye, Sandy Napel, Lei Xing

We develop and analyze a projected particle Langevin optimization method to learn the distribution in the Schönberg integral representation of the radial basis functions from training samples. More specifically, we characterize a distributionally robust optimization method with respect to the Wasserstein distance to optimize the distribution in the Schönberg

Alexander Fang, Alisa Liu, Prem Seetharaman, Bryan Pardo

Deep generative systems that learn probabilistic models from a corpus of existing music do not explicitly encode knowledge of a musical style, compared to traditional rule-based systems. Thus, it can be difficult to determine whether deep models generate stylistically correct output without expert evaluation, but this is expensive and time-consuming. Therefo

Andrea Pascucci, Antonello Pesce

We derive the forward and backward filtering equations for a class of degenerate partially observable diffusions, satisfying the weak Hörmander condition. Our approach is based on the Hölder theory for degenerate SPDEs that allows to pursue the direct approaches proposed by N. V. Krylov and A. Zatezalo, and A. Yu. Veretennikov, avoiding the use of general re

Daniel Kabat, Gilad Lifschytz, Phuc Nguyen, Debajyoti Sarkar

We compute modular Hamiltonians for excited states obtained by perturbing the vacuum with a unitary operator. We use operator methods and work to first order in the strength of the perturbation. For the most part we divide space in half and focus on perturbations generated by integrating a local operator $J$ over a null plane. Local operators with weight $n

Rameswar Panda, Michele Merler, Mayoore Jaiswal, Hui Wu

Neural Architecture Search (NAS) is an open and challenging problem in machine learning. While NAS offers great promise, the prohibitive computational demand of most of the existing NAS methods makes it difficult to directly search the architectures on large-scale tasks. The typical way of conducting large scale NAS is to search for an architectural building

Sunsoo Kim, Vaishnav Tadiparthi, Raktim Bhattacharya

Accurate state estimation using low-cost MEMS (Micro Electro- Mechanical Systems) sensors present on Commercial-off-the-shelf (COTS) drones is a challenging problem. Most UAV systems use a combination of a gyroscope, an accelerometer, and a magnetometer to obtain measurements and estimate attitude. Under this paradigm of sensor fusion, the Extended Kalman Fi

Soumik Adhikary

We propose a new training algorithm for supervised quantum classifiers. Here, we have harnessed the property of quantum entanglement to build a model that can simultaneously manipulate multiple training samples along with their labels. Subsequently a Bell-inequality based cost function is constructed, that can encode errors from multiple samples, simultaneou

Sven Bachmann, Wojciech De Roeck, Martin Fraas, Markus Lange

In general, linear response theory expresses the relation between a driving and a physical system&#39;s response only to first order in perturbation theory. In the context of charge transport, this is the linear relation between current and electromotive force expressed in Ohm&#39;s law. We show here that, in the case of the quantum Hall effect, all higher o

Arijit Sehanobish, Hector H. Corzo, Onur Kara, David van Dijk

Attempts to apply Neural Networks (NN) to a wide range of research problems have been ubiquitous and plentiful in recent literature. Particularly, the use of deep NNs for understanding complex physical and chemical phenomena has opened a new niche of science where the analysis tools from Machine Learning (ML) are combined with the computational concepts of t

Ben Wormleighton

We study invariants coming from certain optimisation problems for nef divisors on surfaces. These optimisation problems arise in work of the author and collaborators tying obstructions to embeddings between symplectic 4-manifolds to questions of positivity for (possibly singular) algebraic surfaces. We develop the general framework for these invariants and p

Lewis Bowen, Ben Hayes, Yuqing, Lin

The classical Multiplicative Ergodic Theorem (MET) of Oseledets is generalized here to cocycles taking values in a semi-finite von Neumann algebra. This allows for a continuous Lyapunov distribution.

Gerhard Kirsten, Valeria Simoncini

We are interested in numerically approximating the solution ${\bf U}(t)$ of the large dimensional semilinear matrix differential equation $\dot{\bf U}(t) = { \bf A}{\bf U}(t) + {\bf U}(t){ \bf B} + {\cal F}({\bf U},t)$, with appropriate starting and boundary conditions, and $ t \in [0, T_f]$. In the framework of the Proper Orthogonal Decomposition (POD) meth

Markus Hiekkamäki, Robert Fickler

Two-photon interference is a fundamental quantum optics effect with numerous applications in quantum information science. Here, we study two-photon interference in multiple transverse-spatial modes along a single beam-path. Besides implementing the analogue of the Hong-Ou-Mandel interference using a two-dimensional spatial-mode splitter, we extend the scheme

Antardipan Pal, Yong Zhang, Dennis D. Yau

There is an extremely high demand for a high speed, low power, low leakage, and low noise Static Random-Access Memory (SRAM) for high performance cache memories. The energy efficiency of SRAM is of paramount importance in both high performance and ultralow-power portable, battery operated electronic systems. In this article the factors affecting the over-all

Andrew J. Groszek, Paolo Comaron, Nikolaos P. Proukakis, Thomas P. Billam

We study the phase ordering dynamics of a uniform Bose gas in two dimensions following a quench into the ordered phase. We explore the crossover between dissipative and conservative evolution by performing numerical simulations within the classical field methodology. Regardless of the dissipation strength, we find clear evidence for universal scaling, with d

John R. Klauder

Classical phase-space variables are normally chosen to promote to quantum operators in order to quantize a given classical system. While classical variables can exploit coordinate transformations to address the same problem, only one set of quantum operators to address the same problem can give the correct analysis. Such a choice leads to the need to find th

Jingang Xiong, Lei Zhang

We study the asymptotic behavior of local solutions to the Yamabe equation near an isolated singularity, when the metric is not conformally flat. We prove that, in dimension $6$, any solution is asymptotically close to a Fowler solution, which is an extension of the same result for lower dimensions by F.C. Marques in 2008.

Alan E. Robinson

XENON1T recently reported an excess of low-energy electron recoil events that may be attributable to either new physics or to the radioactive decay of tritium. It is likely that hydrogen is not be effectively removed by the hot zirconium getters deployed in the detector. Cosmogenic activation of the xenon underground is found to be insufficient to describe t