March 2020 arXiv papers — page 66

Guang Chao Wang, Kenny Gross, Akshay Subramaniam

Deploying big-data Machine Learning (ML) services in a cloud environment presents a challenge to the cloud vendor with respect to the cloud container configuration sizing for any given customer use case. OracleLabs has developed an automated framework that uses nested-loop Monte Carlo simulation to autonomously scale any size customer ML use cases across the

Khawar Islam, Akhter Raza

Data mining is the process in which we extract the different patterns and useful Information from large dataset. According to London police, crimes are immediately increases from beginning of 2017 in different borough of London. No useful information is available for prevent crime on future basis. We forecasts crime rates in London borough by extracting larg

Parag Mali, Puneeth Kukkadapu, Mahshad Mahdavi, Richard Zanibbi

We introduce the Scanning Single Shot Detector (ScanSSD) for locating math formulas offset from text and embedded in textlines. ScanSSD uses only visual features for detection: no formatting or typesetting information such as layout, font, or character labels are employed. Given a 600 dpi document page image, a Single Shot Detector (SSD) locates formulas at

Haiyang Xu, Yun Wang, Kun Han, Baochang Ma

Abstractive text summarization is a challenging task, and one need to design a mechanism to effectively extract salient information from the source text and then generate a summary. A parsing process of the source text contains critical syntactic or semantic structures, which is useful to generate more accurate summary. However, modeling a parsing tree for t

Pourya Shamsolmoali, Masoumeh Zareapoor, Huiyu Zhou, Jie Yang

Human pose estimation has an important impact on a wide range of applications from human-computer interface to surveillance and content-based video retrieval. For human pose estimation, joint obstructions and overlapping upon human bodies result in departed pose estimation. To address these problems, by integrating priors of the structure of human bodies, we

Farahnaz Akrami, Mohammed Samiul Saeef, Qingheng Zhang, Wei Hu

In the active research area of employing embedding models for knowledge graph completion, particularly for the task of link prediction, most prior studies used two benchmark datasets FB15k and WN18 in evaluating such models. Most triples in these and other datasets in such studies belong to reverse and duplicate relations which exhibit high data redundancy d

Hongjie Dong, Doyoon Kim

We give a unified approach to weighted mixed-norm estimates and solvability for both the usual and time fractional parabolic equations in nondivergence form when coefficients are merely measurable in the time variable. In the spatial variables, the leading coefficients locally have small mean oscillations. Our results extend the previous result in [6] for un

Donghao Zhang, Siqi Liu, Shikha Chaganti, Eli Gibson

With the injection of contrast material into blood vessels, multi-phase contrasted CT images can enhance the visibility of vessel networks in the human body. Reconstructing the 3D geometric morphology of liver vessels from the contrasted CT images can enable multiple liver preoperative surgical planning applications. Automatic reconstruction of liver vessel

Amit Seta, Paul J. Bushby, Anvar Shukurov, Toby S. Wood

The presence of magnetic fields in many astrophysical objects is due to dynamo action, whereby a part of the kinetic energy is converted into magnetic energy. A turbulent dynamo that produces magnetic field structures on the same scale as the turbulent flow is known as the fluctuation dynamo. We use numerical simulations to explore the nonlinear, statistical

Shivali Goel, Homayoon Beigi

The majority of existing speech emotion recognition models are trained and evaluated on a single corpus and a single language setting. These systems do not perform as well when applied in a cross-corpus and cross-language scenario. This paper presents results for speech emotion recognition for 4 languages in both single corpus and cross corpus setting. Addit

Sara Venkatesh

We study the reduced symplectic cohomology of disk subbundles in negative symplectic line bundles. We show that this cohomology theory "sees" the spectrum of a quantum action on quantum cohomology. Precisely, quantum cohomology decomposes into generalized eigenspaces of the action of the first Chern class by quantum cup product. The reduced symplecti

Mike Guidry, Yang Sun, Lian-Ao Wu, Cheng-Li Wu

We review application of the SU(4) model of strongly-correlated electrons to cuprate and iron-based superconductors. A minimal self-consistent generalization of BCS theory to incorporate antiferromagnetism on an equal footing with pairing and strong Coulomb repulsion is found to account systematically for the major features of high-temperature superconductiv

Simon Zhang, Mengbai Xiao, Hao Wang

The computation of Vietoris-Rips persistence barcodes is both execution-intensive and memory-intensive. In this paper, we study its computational structure and identify several unique mathematical properties and algorithmic opportunities with connections to the GPU. Mathematically and empirically, we look into the properties of apparent pairs, which are inde

Wei Wang, Shiwen Zhang

We consider the discrete Schr\"odinger operator $H=-\Delta+V$ on a cube $M\subset \mathbb{Z}^d$, with periodic or Dirichlet (simple) boundary conditions. We use a hidden landscape function $u$, defined as the solution of an inhomogeneous boundary problem with uniform right-hand side for $H$, to predict the location of the localized eigenfunctions of $H$. Exp

Robert Scherer

We prove a conjectured asymptotic formula of Kuperberg from the representation theory of the Lie algebra $G_2$. Given a non-negative sequence $(a_n)_{n\geq 1}$, the identity $B(x)=A(xB(x))$ for generating functions $A(x)=1+\sum_{n\geq 1} a_n x^n$ and $B(x)=1+\sum_{n\geq 1} b_n x^n$ determines the number $b_n$ of rooted planar trees with $n$ vertices such tha

Ramesh Kumar Sah, Hassan Ghasemzadeh

Machine learning is used for inference and decision making in wearable sensor systems. However, recent studies have found that machine learning algorithms are easily fooled by the addition of adversarial perturbations to their inputs. What is more interesting is that adversarial examples generated for one machine learning system is also effective against oth

Jorge Oliveira, Margarida Carvalho, Diogo Marcelo Nogueira, Miguel Coimbra

Physiological signals, such as the electrocardiogram and the phonocardiogram are very often corrupted by noisy sources. Usually, artificial intelligent algorithms analyze the signal regardless of its quality. On the other hand, physicians use a completely orthogonal strategy. They do not assess the entire recording, instead they search for a segment where th

Masoud Arash, Hamed Mirghasemi, Ivan Stupia, Luc Vandendorpe

In the next generation of wireless systems, Massive MIMO offers high angular resolution for localization. By virtue of large number of antennas, the Angle of Arrival (AoA) of User Terminals (UTs) can be estimated with high accuracy. According to Dense Multipath Component (DMC) channel model, local scatters around UTs can create different multipath signals fo

Sarah M. Hooper, Jared A. Dunnmon, Matthew P. Lungren, Sanjiv Sam Gambhir

Automated medical image classification with convolutional neural networks (CNNs) has great potential to impact healthcare, particularly in resource-constrained healthcare systems where fewer trained radiologists are available. However, little is known about how well a trained CNN can perform on images with the increased noise levels, different acquisition pr

Matthew Abate, Maxence Dutreix, Samuel Coogan

The vector field of a mixed-monotone system is decomposable via a decomposition function into increasing (cooperative) and decreasing (competitive) components, and this decomposition allows for, e.g., efficient computation of reachable sets and forward invariant sets. A main challenge in this approach, however, is identifying an appropriate decomposition fun

Chiara Marletto, Vlatko Vedral

We propose a general argument to show that if a physical system can mediate locally the generation of entanglement between two quantum systems, then it itself must be non-classical. Remarkably, we do not assume any classical or quantum formalism to describe the mediating physical system: our result follows from general information-theoretic principles, drawn

Dong Zhang, Luis D. Couto, Sebastien Benjamin, Wente Zeng

This manuscript presents an algorithm for individual Lithium-ion (Li-ion) battery cell state of charge (SOC) estimation when multiple cells are connected in parallel, using only terminal voltage and total current measurements. For battery packs consisting of thousands of cells, it is desirable to estimate individual SOCs by only monitoring the total current

Siddharth Agarwal, Ankit Vora, Gaurav Pandey, Wayne Williams

This paper presents a challenging multi-agent seasonal dataset collected by a fleet of Ford autonomous vehicles at different days and times during 2017-18. The vehicles traversed an average route of 66 km in Michigan that included a mix of driving scenarios such as the Detroit Airport, freeways, city-centers, university campus and suburban neighbourhoods, et

L. E. Czelusniak, V. P. Mapelli, M. S. Guzella, L. Cabezas-Gómez

The pseudopotential method is one of the most popular extensions of the lattice Boltzmann method (LBM) for phase change and multiphase flow simulation. One attractive feature of the original proposed method consists on its simplicity of adding a force dependent on a nearest-neighbor potential function, which became known as the Shan-Chen interaction force. S

Lane P. Hughston, Leandro Sánchez-Betancourt

In the information-based pricing framework of Brody, Hughston and Macrina, the market filtration $\{ \mathcal F_t\}_{t\geq 0}$ is generated by an information process $\{ \xi_t\}_{t\geq0}$ defined in such a way that at some fixed time $T$ an $\mathcal F_T$-measurable random variable $X_T$ is "revealed". A cash flow $H_T$ is taken to depend on the market facto

Robin Delabays, Laurent Pagnier, Melvyn Tyloo

A wide variety of natural and human-made systems consist of a large set of dynamical units coupled into a complex structure. Breakdown of such systems can have a dramatic impact, as in the case of neurons in the brain or lines in an electric grid, to name but a few. Preventing such catastrophic events requires in particular to be able to detect and locate th

Daniel Rutter, Balt C. van Rees

We extend the definition of alpha space as introduced in [1] to two spacetime dimensions. We discuss how this can be used to find conformal block decompositions of known functions and how to easily recover several lightcone bootstrap results. In the second part of the paper we establish a connection between alpha space and the Lorentzian inversion formula of

Tapajit Dey, Bogdan Vasilescu, Audris Mockus

Background: Bots help automate many of the tasks performed by software developers and are widely used to commit code in various social coding platforms. At present, it is not clear what types of activities these bots perform and understanding it may help design better bots, and find application areas which might benefit from bot adoption. Aim: We aim to cate

Han Lin Shang

The Hurst exponent is the simplest numerical summary of self-similar long-range dependent stochastic processes. We consider the estimation of Hurst exponent in long-range dependent curve time series. Our estimation method begins by constructing an estimate of the long-run covariance function, which we use, via dynamic functional principal component analysis,

Thomas Doehrman, Sunder Sethuraman, Shankar C. Venkataramani

We consider the scaling behavior of the range and $p$-multiple range, that is the number of points visited and the number of points visited exactly $p\geq 1$ times, of simple random walk on ${\mathbb Z}^d$, for dimensions $d\geq 2$, up to time of exit from a domain $D_N$ of the form $D_N = ND$ where $D\subset {\mathbb R}^d$, as $N\uparrow\infty$. Recent pape

Jianan Yao, Gabriel Ryan, Justin Wong, Suman Jana

Verifying real-world programs often requires inferring loop invariants with nonlinear constraints. This is especially true in programs that perform many numerical operations, such as control systems for avionics or industrial plants. Recently, data-driven methods for loop invariant inference have shown promise, especially on linear invariants. However, apply

Julien Gaboriaud, Luc Vinet

Two descriptions of the dual $-1$ Hahn algebra are presented and shown to be related under Howe duality. The dual pair involved is formed by the Lie algebra $\mathfrak{o}(4)$ and the Lie superalgebra $\mathfrak{osp}(1|2)$.

Freddy Cachazo, Nick Early

In this note we present a formula for the Cachazo-Early-Guevara-Mizera (CEGM) generalized biadjoint amplitudes for all $k$ and $n$ on what we call the minimal kinematics. We prove that on the minimal kinematics, the scattering equations on the configuration space of $n$ points on $\mathbb{CP}^{k-1}$ has a unique solution, and that this solution is in the ima

Guido D'Amico, Leonardo Senatore, Pierre Zhang

We apply the Effective Field Theory of Large-Scale Structure to analyze the $w$CDM cosmological model. By using the full shape of the power spectrum and the BAO post-reconstruction measurements from BOSS, the Supernovae from Pantheon, and a prior from BBN, we set the competitive CMB-independent limit $w=-1.046_{-0.052}^{+0.055}$ at $68\%$ C.L.. After adding

Shounak Chattopadhyay, Antik Chakraborty, David B. Dunson

There is a rich literature on Bayesian methods for density estimation, which characterize the unknown density as a mixture of kernels. Such methods have advantages in terms of providing uncertainty quantification in estimation, while being adaptive to a rich variety of densities. However, relative to frequentist locally adaptive kernel methods, Bayesian appr

Raquel Aoki, Martin Ester

Methods for causal inference from observational data are an alternative for scenarios where collecting counterfactual data or realizing a randomized experiment is not possible. Adopting a stacking approach, our proposed method ParKCA combines the results of several causal inference methods to learn new causes in applications with some known causes and many p

V. Deckert, T. Deckert-Gaudig, D. Cialla, J. Popp

From the famous 1918 H1N1 influenza to the present COVID-19 pandemic, the need for improved virial detection techniques is all too apparent. The aim of the present paper is to show that identification of individual virus particles in clinical sample materials quickly and reliably is near at hand. First of all, our team has developed techniques for identifica

Javier Aramayona, Nicholas G. Vlamis

We survey recent developments on mapping class groups of surfaces of infinite topological type.

Edemir Ferreira, Matheus Brito, Remis Balaniuk, Mário S. Alvim

In this work we present BrazilDAM, a novel public dataset based on Sentinel-2 and Landsat-8 satellite images covering all tailings dams cataloged by the Brazilian National Mining Agency (ANM). The dataset was built using georeferenced images from 769 dams, recorded between 2016 and 2019. The time series were processed in order to produce cloud free images. T

Yuxiao Wu, Aviad Frydman, Arnab Roy

We describe an alternating current method to measure the Nernst effect in superconducting thin films at low temperatures. The Nernst effect is an important tool in the understanding superconducting fluctuations and, in particular, vortex motion near critical points. However, in most materials, the Nernst signal in a typical experimental setup rarely exceeds

Soroush Bateni, Zhendong Wang, Yuankun Zhu, Yang Hu

Cutting-edge embedded system applications, such as self-driving cars and unmanned drone software, are reliant on integrated CPU/GPU platforms for their DNNs-driven workload, such as perception and other highly parallel components. In this work, we set out to explore the hidden performance implication of GPU memory management methods of integrated CPU/GPU arc

Debsoumya Chakraborti, Da Qi Chen

Generalized Tur\'an problems have been a central topic of study in extremal combinatorics throughout the last few decades. One such problem, maximizing the number of cliques of a fixed order in a graph with fixed number of vertices and bounded maximum degree, was recently completely resolved by Chase. Kirsch and Radcliffe raised a natural variant of this pro

Ilgiz Murzakhanov, Andreas Venzke, George S. Misyris, Spyros Chatzivasileiadis

This paper introduces a framework to capture previously intractable optimization constraints and transform them to a mixed-integer linear program, through the use of neural networks. We encode the feasible space of optimization problems characterized by both tractable and intractable constraints, e.g. differential equations, to a neural network. Leveraging a

Tiancong Zhu, Alexander J. Bishop, Tong Zhou, Menglin Zhu

The intrinsic magnetic topological insulators MnBi$_2$X$_4$ (X = Se, Te) are promising candidates in realizing various novel topological states related to symmetry breaking by magnetic order. Although much progress had been made in MnBi$_2$Te$_4$, the study of MnBi$_2$Se$_4$ has been lacking due to the difficulty of material synthesis of the desired trigonal

Yassir Jedra, Alexandre Proutiere

We present a new finite-time analysis of the estimation error of the Ordinary Least Squares (OLS) estimator for stable linear time-invariant systems. We characterize the number of observed samples (the length of the observed trajectory) sufficient for the OLS estimator to be $(\varepsilon,δ)$-PAC, i.e., to yield an estimation error less than $\varepsilon$ wi

Yichun Shi, Anil K. Jain

In recent years, significant progress has been made in face recognition, which can be partially attributed to the availability of large-scale labeled face datasets. However, since the faces in these datasets usually contain limited degree and types of variation, the resulting trained models generalize poorly to more realistic unconstrained face datasets. Whi

Jose R. Alonso, Roger Barlow, Janet M. Conrad, Loyd Hoyt Waites

Authors describe technical advances that will allow the IsoDAR cyclotron -- being developed for neutrino physics research -- to produce medical isotopes more efficiently than existing cyclotrons can.

Stefano Vidussi

Let $G$ be a finitely presented group that can be written as an extension \[ 1 \longrightarrow K \longrightarrow G \longrightarrow F_2 \longrightarrow 1 \] where $K$ is either the finitely generated free group $F_n$, $n > 2$ or the fundamental group of a closed surface of genus $g > 1$. We prove that if the image of the monodromy map $ρ\colon F_2 \to \operat

Marco Bonetti, Ugofilippo Basellini

We describe Epilocal, a simple R program designed to automatically download the most recent data on reported infected SARS-CoV-2 cases for all Italian provinces and regions, and to provide a simple descriptive analysis. For each province the cumulative number of reported infected cases is available each day. In addition, the current numbers of hospitalized p

A. O. Murzin, B. V. Stroganov, C. Günnemann, S. B. Hammouda

Halide perovskites are a promising optical gain media with high tunability and simple solution synthesis. In this study, two gain regimes, namely amplified spontaneous emission and random lasing, are demonstrated in same MAPbBr$_3$ halide perovskite single crystal. For this, photoluminescence is measured at a temperature of 4 K with pulsed femtosecond pumpin

G. Venkat, C. D. W. Cox, A. Sola, V. Basso

The spin Seebeck effect (SSE) has generated interest in the thermoelectric and magnetic communities for potential high efficiency energy harvesting applications, and spintronic communities as a source of pure spin current. To understand the underlying mechanisms requires characterisation of potential materials across a range of temperatures, however, for thi

Colin B. Hansen, Vishwesh Nath, Diego A. Mesa, Yuankai Huo

In semi-supervised learning, information from unlabeled examples is used to improve the model learned from labeled examples. In some learning problems, partial label information can be inferred from otherwise unlabeled examples and used to further improve the model. In particular, partial label information exists when subsets of training examples are known t

Olaf Kaczmarek, Frithjof Karsch, Anirban Lahiri, Lukas Mazur

We present a lattice QCD based determination of the chiral phase transition temperature in QCD with two massless (up and down) and one strange quark having its physical mass. We propose and calculate two novel estimators for the chiral transition temperature for several values of the light quark masses, corresponding to Goldstone pion masses in the range of

Antoine Allard, Fabrice Valentino, Cécile Sykes, Timo Betz

Many biological functions rely on the reshaping of cell membranes, in particular into nanotubes, which are covered in vivo by dynamic actin networks. Nanotubes are subject to thermal fluctuations, but the effect of these on cell functions is unknown. Here, we form nanotubes from liposomes using an optically trapped bead adhering to the liposome membrane. Fro

Germán Kruszewski, Tomas Mikolov

An explanatory model for the emergence of evolvable units must display emerging structures that (1) preserve themselves in time (2) self-reproduce and (3) tolerate a certain amount of variation when reproducing. To tackle this challenge, here we introduce Combinatory Chemistry, an Algorithmic Artificial Chemistry based on a minimalistic computational paradig

Walter Cedric Simo Tao Lee

In this paper, we address the problem of approximating solutions of ill-posed problems using mollification. We quickly review existing mollification regularization methods and provide two new approximate solutions to a general ill-posed equation $T(f) =g$ where $T$ can be nonlinear. The regularized solutions we define extend the work of Bonnefond and Marécha

Gabor Vattay

During the COVID-19 outbreak, it is essential to monitor the effectiveness of measures taken by governments on the course of the epidemic. Here we show that there is already a sufficient amount of data collected in Italy to predict the outcome of the process. We show that using the proper metric, the data from Hubei Province and Italy has striking similarity

Simon Hadush, Yaecob Girmay, Abiot Sinamo, Gebrekirstos Hagos

Breast cancer is prevalent in Ethiopia that accounts 34% among women cancer patients. The diagnosis technique in Ethiopia is manual which was proven to be tedious, subjective, and challenging. Deep learning techniques are revolutionizing the field of medical image analysis and hence in this study, we proposed Convolutional Neural Networks (CNNs) for breast m

Alexander Pütz

We study finite dimensional approximations to degenerate versions of affine flag varieties using quiver Grassmannians for cyclic quivers. We prove that they admit cellular decompositions parametrized by affine Dellac configurations, and that their irreducible components are normal Cohen-Macaulay varieties with rational singularities.

Chao Yan, Ziqi Zhang, Steve Nyemba, Bradley A. Malin

Sharing electronic health records (EHRs) on a large scale may lead to privacy intrusions. Recent research has shown that risks may be mitigated by simulating EHRs through generative adversarial network (GAN) frameworks. Yet the methods developed to date are limited because they 1) focus on generating data of a single type (e.g., diagnosis codes), neglecting

Linhui Shen

We study the dual ${\rm G}^\ast$ of a standard semisimple Poisson-Lie group ${\rm G}$ from a perspective of cluster theory. We show that the coordinate ring $\mathcal{O}({\rm G}^\ast)$ can be naturally embedded into a cluster Poisson algebra with a Weyl group action. We prove that $\mathcal{O}({\rm G}^\ast)$ admits a natural basis which has positive integer

Ben Lambert, Aki Vehtari

Markov chain Monte Carlo (MCMC) has transformed Bayesian model inference over the past three decades: mainly because of this, Bayesian inference is now a workhorse of applied scientists. Under general conditions, MCMC sampling converges asymptotically to the posterior distribution, but this provides no guarantees about its performance in finite time. The pre

Abhinav Prakash, Rui Tuo, Yu Ding

This work proposes a nonparametric method to compare the underlying mean functions given two noisy datasets. The motivation for the work stems from an application of comparing wind turbine power curves. Comparing wind turbine data presents new problems, namely the need to identify the regions of difference in the input space and to quantify the extent of dif

Zarko Sakotic, Alex Krasnok, Norbert Cselyuszka, Nikolina Jankovic

Embedded eigenstates are nonradiative modes of an open structure with momentum compatible with radiation, yet characterized by unboundedly large Q-factors. Traditionally, these states originate from total destructive interference of radiation from two or more non-orthogonal modes in periodic structures. In this work, we demonstrate a novel class of embedded

Lawrence G. Phillips, David B. Grimes, Yihan Jessie Li

We present an approach to domain adaptation, addressing the case where data from the source domain is abundant, labelled data from the target domain is limited or non-existent, and a small amount of paired source-target data is available. The method is designed for developing deep learning models that detect the presence of medical conditions based on data f

Matthew Heydeman, Christian B. Jepsen, Ziming Ji, Amos Yarom

We study renormalization group flow in a non-local version of quantum electrodynamics (QED). We determine the regime in which the theory flows to a local theory in the infrared and study a possible UV completion of four-dimensional QED. In addition, we find that there exist non-local conformal theories with a one-dimensional conformal manifold and non-local

Avner Karasik

We introduce a novel Skyrme-like conserved current in the effective theory of pions and vector mesons based on the idea of hidden local symmetry. The associated charge is equivalent to the skyrmion charge for any smooth configuration. In addition, there exist singular configurations that can be identified as N_f=1 baryons charged under the new symmetry. Unde

Shrey Desai, Greg Durrett

Pre-trained Transformers are now ubiquitous in natural language processing, but despite their high end-task performance, little is known empirically about whether they are calibrated. Specifically, do these models' posterior probabilities provide an accurate empirical measure of how likely the model is to be correct on a given example? We focus on BERT and R

Michèle Levi, Andrew J. McLeod, Matthew von Hippel

We compute the N$^3$LO gravitational quadratic-in-spin interactions at $G^4$ in the post-Newtonian (PN) expansion via the effective field theory (EFT) of gravitating spinning objects for the first time. This result contributes at the $5$PN order for maximally-spinning compact objects, adding the spinning case to the static sector at this PN accuracy. This se

Sagnik Chakraborty, Dariusz Chruściński, Gniewomir Sarbicki, Frederik vom Ende

We address the problem of existence of completely positive trace preserving (CPTP) maps between two sets of density matrices. We refine the result of Alberti and Uhlmann and derive a necessary and sufficient condition for the existence of a unital channel between two pairs of qubit states which ultimately boils down to three simple inequalities.

Hanieh Keneshlou, Fabio Tanturri

We show that $\mathcal{M}_{g,n}$, the moduli space of smooth curves of genus $g$ together with $n$ marked points, is unirational for $g=12$ and $2 \leq n\leq 4$ and for $g=13$ and $1 \leq n \leq 3$, by constructing suitable dominant families of projective curves in $\mathbb{P}^1 \times \mathbb{P}^2$ and $\mathbb{P}^3$ respectively. We also exhibit several ne

Olcay Plevne, Özgecan Önal Taş, Selçuk Bilir, George M. Seabroke

This study presents the multi-wavelength investigation of the absolute magnitudes and colours of the red clump (RC) stars selected from APOGEE and GALAH DR2 combined catalogue which is complemented with {\it Gaia} DR2 astrometric data and multi-wavelength photometric data of {\it GALEX} GR6/7, SDSS DR7, {\it Gaia} DR2, 2MASS and {\it WISE} sky surveys. The a

Radu Ioan Bot, Michael Sedlmayer, Phan Tu Vuong

We introduce a relaxed inertial forward-backward-forward (RIFBF) splitting algorithm for approaching the set of zeros of the sum of a maximally monotone operator and a single-valued monotone and Lipschitz continuous operator. This work aims to extend Tseng's forward-backward-forward method by both using inertial effects as well as relaxation parameters.

E. M. Ait Ben Hassi, S. E. Chorfi, L. Maniar, O. Oukdach

In this paper, we study an inverse problem for linear parabolic system with variable diffusion coefficients subject to dynamic boundary conditions. We prove a global Lipschitz stability for the inverse problem involving a simultaneous recovery of two source terms from a single measurement and interior observations, based on a recent Carleman estimate for suc

Vipin Chandra Dubey, Ambuj Kumar Mishra, Umesh Kumar Sharma

In this paper, we have examined the R$\acute{e}$nyi holographic dark energy (RHDE) model in the framework of an isotropic and spatially homogeneous flat FLRW (Friedmann- Lema$\hat i$tre-Robertson-Walker) Universe by considering different values of parameter $\delta$, where the infrared cut-off is taken care by the Hubble horizon. We examined the RHDE model t

Ioannis Katsantonis, Sotiris Droulias, Costas M. Soukoulis, Eleftherios N. Economou

We investigate the influence of chirality on the PT-symmetric and PT-broken phase of PT-symmetric chiral systems. Starting from the point that transverse magnetic (TM) and transverse electric (TE) waves have different exceptional points, we show that with circularly polarized waves (which are linear combinations of TM and TE waves) mixed PT-symmetric phases

Edwin Herrera, Victor Barrena, Isabel Guillamon, Jose Augusto Galvis

Moir\'e patterns can lead to fundamentally new electronic behavior when formed between two atomic lattices slightly shifted with respect to each other. A solid is however not just characterized by the atomic lattice, but also by charge or magnetic excitations that do not need to be commensurate to the lattice. This raises the question if one can obtain a moi

Chenming Wu, Yong-Jin Liu, Charlie C. L. Wang

Multi-directional 3D printing has the capability of decreasing or eliminating the need for support structures. Recent work proposed a beam-guided search algorithm to find an optimized sequence of plane-clipping, which gives volume decomposition of a given 3D model. Different printing directions are employed in different regions to fabricate a model with trem

Dan Li, Sonia Martínez

This paper considers a sensor attack and fault detection problem for linear cyber-physical systems, which are subject to system noise that can obey an unknown light-tailed distribution. We propose a new threshold-based detection mechanism that employs the Wasserstein metric, and which guarantees system performance with high confidence employing a finite numb

Vassilis-Dionyssis Moustakas

We propose a unified approach to prove general formulas for the joint distribution of an Eulerian and a Mahonian statistic over a set of colored permutations by specializing Poirier's colored quasisymmetric functions. We apply this method to derive formulas for Euler-Mahonian distributions on colored permutations, derangements and involutions. A number of kn

Naresh Sharma, Govind Kumar, Vivek Garg, Rakesh G. Mote

Thin film optical elements exhibiting translational invariance, and thus robustness to optical misalignment, are crucial for rapid development of compact and integrated optical devices. In this letter, we experimentally demonstrate a beam-shaping element that generates an annular beam by spatially filtering the fundamental Gaussian mode of a laser beam. The

Petr Chvosta, Dominik Lips, Viktor Holubec, Artem Ryabov

We derive an exact expression for the probability density of work done on a particle that diffuses in a parabolic potential with a stiffness varying by an arbitrary piecewise constant protocol. Based on this result, the work distribution for time-continuous protocols of the stiffness can be determined up to any degree of accuracy. This is achieved by replaci

Lorenzo Pastori, Simone Barbarino, Jan Carl Budich

Motivated by recent experimental progress in the study of quantum systems far from equilibrium, we investigate the relation between several dynamical signatures of topology in the coherent time-evolution after a quantum quench. Specifically, we study the conditions for the appearance of entanglement spectrum crossings, dynamical quantum phase transitions, an

Yuri D. van Nieuwkerk, Fabian H. L. Essler

We consider a model of two tunnel-coupled one-dimensional Bose gases with hard-wall boundary conditions. Bosonizing the model and retaining only the most relevant interactions leads to a decoupled theory consisting of a quantum sine-Gordon model and a free boson, describing respectively the antisymmetric and symmetric combinations of the phase fields. We go

Ilyas Noor Bhatti, Imtiaz Noor Bhatti, Rabindra Nath Mahato, M. A. H. Ahsan

Structural, magnetic and dielectric properties have been studied for Yb$_2$CoMnO$_6$. Nano-crystalline sample of Yb$_2$CoMnO$_6$ synthesized by sol-gel method and structural analysis shows that the sample crystallizes in monoclinic crystal structure with \textit{P2$_1$/n} phase group. To understand the charge state of Co, Mn and Yb we have performed the XPS

Wei-Han Hsiao

We consider the time-reversal odd dynamics of the bilayer graphene at low energies in the quantum Hall regime. A generating functional for the effective action that captures the electromagnetic response to all orders in momentum and frequency is presented and evaluated to the third order in the space-time gradient $\mathcal O(\partial^3)$. In addition, we ca

Samir Choudhuri, Abhik Ghosh, Nirupam Roy, Somnath Bharadwaj

Measurements of the Galactic synchrotron emission is relevant for the 21-cm studies from the Epoch of Reionization. The study of the synchrotron emission is also useful to quantify the fluctuations in the magnetic field and the cosmic ray electron density of the turbulent interstellar medium (ISM) of our Galaxy. Here, we present the all-sky angular power spe

Waleed Abdallah, Shehu AbdusSalam, Azar Ahmadov, Amine Ahriche

We report on the status of efforts to improve the reinterpretation of searches and measurements at the LHC in terms of models for new physics, in the context of the LHC Reinterpretation Forum. We detail current experimental offerings in direct searches for new particles, measurements, technical implementations and Open Data, and provide a set of recommendati

Cheng-Wei Chiang, Giovanna Cottin, Yong Du, Kaori Fuyuto

We study discovery prospects for a real triplet extension of the Standard Model scalar sector at the Large Hadron Collider (LHC) and a possible future 100 TeV $pp$ collider. We focus on the scenario in which the neutral triplet scalar is stable and contributes to the dark matter relic density. When produced in $pp$ collisions, the charged triplet scalar deca

Amir Siraj, Abraham Loeb

Water plumes erupting from the `tiger stripe' features on the south pole of Enceladus are thought to connect to a global subsurface ocean. Proposed origins for the initial stress necessary to form the `tiger stripes' include a giant impact, which would require true polar wander to explain the location of the plumes if the impact did not occur at the South Po

Nikita Blinov, Gustavo Marques-Tavares

Standard cosmology predicts that prior to matter-radiation equality about 41% of the energy density was in free-streaming neutrinos. In many beyond Standard Model scenarios, however, the amount and free-streaming nature of this component is modified. For example, this occurs in models with new neutrino self-interactions or an additional dark sector with inte

Przemyslaw Bienias, Michael J. Gullans, Marcin Kalinowski, Alexander N. Craddock

Ultracold systems offer an unprecedented level of control of interactions between atoms. An important challenge is to achieve a similar level of control of the interactions between photons. Towards this goal, we propose a realization of a novel Lennard-Jones-like potential between photons coupled to the Rydberg states via electromagnetically induced transpar

Julien Baglio, Sally Dawson, Samuel Homiller, Samuel D. Lane

The production of $W^{\pm}H$, $ZH$, $W^+W^-$, and $W^\pm Z$ pairs probes non-Standard-Model interactions of quarks, gauge bosons, and the Higgs boson. New effects can be parameterized in terms of an effective field theory (EFT) where the Lagrangian is expanded in terms of higher-dimension operators suppressed by increasing powers of a high scale $\Lambda$. W

Huiyu Wang, Yukun Zhu, Bradley Green, Hartwig Adam

Convolution exploits locality for efficiency at a cost of missing long range context. Self-attention has been adopted to augment CNNs with non-local interactions. Recent works prove it possible to stack self-attention layers to obtain a fully attentional network by restricting the attention to a local region. In this paper, we attempt to remove this constrai

Jesper Grodal, Anssi Lahtinen

We show that the mod $\ell$ cohomology of any finite group of Lie type in characteristic $p$ different from $\ell$ admits the structure of a module over the mod $\ell$ cohomology of the free loop space of the classifying space $BG$ of the corresponding compact Lie group $G$, via ring and module structures constructed from string topology, a la Chas-Sullivan.

Pok Man Tam, Tongtong Liu, Inti Sodemann, Liang Fu

Two-dimensional multi-valley electronic systems in which the dispersion of individual pockets has low symmetry give rise to quantum Hall ferroelectric and nematic states in the presence of strong quantising magnetic fields. We investigate local signatures of these states arising near impurities that can be probed via Scanning Tunnelling Microscopy (STM) spec

Jessie T. Zhang, Yichao Yu, William B. Cairncross, Kenneth Wang

We demonstrate the formation of a single NaCs molecule in an optical tweezer by magnetoassociation through an s-wave Feshbach resonance at 864.11(5)G. Starting from single atoms cooled to their motional ground states, we achieve conversion efficiencies of 47(1)%, and measure a molecular lifetime of 4.7(7)ms. By construction, the single molecules are predomin

Takuhiro Kaneko, Tatsuya Harada

Generative adversarial networks (GANs) have gained considerable attention owing to their ability to reproduce images. However, they can recreate training images faithfully despite image degradation in the form of blur, noise, and compression, generating similarly degraded images. To solve this problem, the recently proposed noise robust GAN (NR-GAN) provides

Yunzhong Hou, Liang Zheng, Stephen Gould

Color and structure are the two pillars that construct an image. Usually, the structure is well expressed through a rich spectrum of colors, allowing objects in an image to be recognized by neural networks. However, under extreme limitations of color space, the structure tends to vanish, and thus a neural network might fail to understand the image. Intereste

Xinshuo Weng, Ye Yuan, Kris Kitani

Multi-object tracking (MOT) and trajectory prediction are two critical components in modern 3D perception systems that require accurate modeling of multi-agent interaction. We hypothesize that it is beneficial to unify both tasks under one framework in order to learn a shared feature representation of agent interaction. Furthermore, instead of performing tra