March 2020 arXiv papers — page 2

Suresh Thapa, Sydney R. Provence, Devin Jessup, Jason Lapano

Hybrid oxide molecular beam epitaxy (hMBE), a thin-film deposition technique in which transition metal cations are delivered using a metal-organic precursor, has emerged as the state-of-the-art approach to the synthesis of electronic-grade complex oxide films with a stoichiometric growth window. However, numerous questions remain regarding the chemical mecha

Michael Leventhal, Allahsera Tapo, Sarah Luger, Marcos Zampieri

We present novel methods for assessing the quality of human-translated aligned texts for learning machine translation models of under-resourced languages. Malian university students translated French texts, producing either written or oral translations to Bambara. Our results suggest that similar quality can be obtained from either written or spoken translat

Gyula M. Szabó

The epidemic curve and the final extent of the COVID-19 pandemic are usually predicted from the rate of early exponential raising using the SIR model. These predictions implicitly assume a full social mixing, which is not plausible generally. Here I am showing a counterexample to the these predictions, based on random propagation of an epidemic in Barab\'asi

Rosemary F. G. Wyse, Maxwell Moe, Kaitlin M. Kratter

Blue straggler stars (BSS) have been identified in star clusters and in field populations in our own Milky Way galaxy and in its satellite galaxies. They manifest as stars bluer and more luminous than the dominant old population, and usually have a spatial distribution that follows the old population. Their progenitors are likely to have been close binaries.

Ye-Sheen Lim, Denise Gorse

In this paper we propose a deep recurrent architecture for the probabilistic modelling of high-frequency market prices, important for the risk management of automated trading systems. Our proposed architecture incorporates probabilistic mixture models into deep recurrent neural networks. The resulting deep mixture models simultaneously address several practi

Susarla Raghuram, Anil Bhardwaj

Alice ultraviolet spectrometer onboard Rosetta space mission observed several spectroscopic emissions emanated from volatile species of comet 67P/Churyumov-Gerasimenko (hear after 67P/C-G) during its entire escorting phase. We have developed a photochemical model for comet 67P/C-G to study the atomic hydrogen (HI 1216, 1025, & 973 Ang), oxygen (OI 1152, 1304

Akshay Krishna, R. N. Bhatt

We study the one-dimensional nearest neighbor tight binding model of electrons with independently distributed random hopping and no on-site potential (i.e. off-diagonal disorder with particle-hole symmetry, leading to sub-lattice symmetry, for each realization). For non-singular distributions of the hopping, it is known that the model exhibits a universal, s

S. Kanas, V. S. Masih

We find an unifying approach to the analytic representation of the domain bounded by a generalized Pascal snail. Special cases as Pascal snail, Both leminiscate, conchoid of the Sluze and a disc are included. The behavior of functions related to generalized Pascal snail are demonstrated.

Michael Hendriksen, Nils Kapust

The concept of $k$-compatibility measures how many phylogenetic trees it would take to display all splits in a given set. A set of trees that display every single possible split is termed a \textit{universal tree set}. In this note, we find $A(n)$, the minimal size of a universal tree set for $n$ taxa. By normalising the $k$-compatibility using $A(n)$, one c

Marco Valentino, Mokanarangan Thayaparan, André Freitas

This paper presents a novel framework for reconstructing multi-hop explanations in science Question Answering (QA). While existing approaches for multi-hop reasoning build explanations considering each question in isolation, we propose a method to leverage explanatory patterns emerging in a corpus of scientific explanations. Specifically, the framework ranks

Bardia Doosti, Shujon Naha, Majid Mirbagheri, David Crandall

Hand-object pose estimation (HOPE) aims to jointly detect the poses of both a hand and of a held object. In this paper, we propose a lightweight model called HOPE-Net which jointly estimates hand and object pose in 2D and 3D in real-time. Our network uses a cascade of two adaptive graph convolutional neural networks, one to estimate 2D coordinates of the han

A. H. Bentbib, M. El Ghomari, K. Jbilou

The numerical computation of matrix functions such as $f(A)V$, where $A$ is an $n\times n$ large and sparse square matrix, $V$ is an $n \times p$ block with $p\ll n$ and $f$ is a nonlinear matrix function, arises in various applications such as network analysis ($f(t)=exp(t)$ or $f(t)=t^3)$, machine learning $(f(t)=log(t))$, theory of quantum chromodynamics

Larissa Albantakis, Francesco Massari, Maggie Beheler-Amass, Giulio Tononi

In science, macro level descriptions of the causal interactions within complex, dynamical systems are typically deemed convenient, but ultimately reducible to a complete causal account of the underlying micro constituents. Yet, such a reductionist perspective is hard to square with several issues related to autonomy and agency: (1) agents require (causal) bo

Carolina Arruda Moreira

In this work we study the synchronization of Kuramoto oscillators driven by external forces in complex modular networks. The motivation is the neuronal dynamics that takes place during information processing in the neural cortex. The neuron organization is modular, with clusters associated to different functions and brain structures, and need to constantly r

Kashif Zia, Umar Farooq

Motivated by the rapid spread of COVID-19 all across the globe, we have performed simulations of a system dynamic epidemic spread model in different possible situations. The simulation, not only captures the model dynamic of the spread of the virus, but also, takes care of population and mobility data. The model is calibrated based on epidemic data and event

Scott Viteri, Simon DeDeo

Mathematical proofs are both paradigms of certainty and some of the most explicitly-justified arguments that we have in the cultural record. Their very explicitness, however, leads to a paradox, because the probability of error grows exponentially as the argument expands. When a mathematician encounters a proof, how does she come to believe it? Here we show

Claudia V. S. Magaño, Graham Smith

We construct eternal mean curvature flows of tori in perturbations of the standard unit sphere $\Bbb{S}^3$. This has applications to the study of the Morse homologies of area functionals over the space of embedded tori in $\Bbb{S}^3$.

Congzheng Song, Ananth Raghunathan

Embeddings are functions that map raw input data to low-dimensional vector representations, while preserving important semantic information about the inputs. Pre-training embeddings on a large amount of unlabeled data and fine-tuning them for downstream tasks is now a de facto standard in achieving state of the art learning in many domains. We demonstrate th

Andrea Di Lorenzo, Damiano Fulghesu, Angelo Vistoli

We compute the integral Chow ring of the stack of smooth, non-hyperelliptic curves of genus three. We obtain this result by computing the integral Chow ring of the stack of smooth plane quartics, by means of equivariant intersection theory.

C. Malacaria, P. Jenke, O. J. Roberts, C. A. Wilson-Hodge

We review more than 10 years of continuous monitoring of accreting X-ray pulsars with the all-sky Gamma-ray Burst Monitor (GBM) aboard the Fermi Gamma-ray Space Telescope. Our work includes data from the start of GBM operations in August 2008, through to November 2019. Pulsations from 39 accreting pulsars are observed over an energy range of $10-50\,$keV by

Elena Zotova, Rodrigo Agerri, Manuel Nuñez, German Rigau

Stance detection aims to determine the attitude of a given text with respect to a specific topic or claim. While stance detection has been fairly well researched in the last years, most the work has been focused on English. This is mainly due to the relative lack of annotated data in other languages. The TW-10 Referendum Dataset released at IberEval 2018 is

Uri Shaham, Tom Zahavy, Cesar Caraballo, Shiwani Mahajan

We propose a novel reinforcement learning-based approach for adaptive and iterative feature selection. Given a masked vector of input features, a reinforcement learning agent iteratively selects certain features to be unmasked, and uses them to predict an outcome when it is sufficiently confident. The algorithm makes use of a novel environment setting, corre

Jiapeng Zhu, Yujun Shen, Deli Zhao, Bolei Zhou

Recent work has shown that a variety of semantics emerge in the latent space of Generative Adversarial Networks (GANs) when being trained to synthesize images. However, it is difficult to use these learned semantics for real image editing. A common practice of feeding a real image to a trained GAN generator is to invert it back to a latent code. However, exi

João P. Abrantes, Arnaldo J. Abrantes, Frans A. Oliehoek

Evolution gave rise to human and animal intelligence here on Earth. We argue that the path to developing artificial human-like-intelligence will pass through mimicking the evolutionary process in a nature-like simulation. In Nature, there are two processes driving the development of the brain: evolution and learning. Evolution acts slowly, across generations

Ladislav Kristoufek

Bitcoin being a safe haven asset is one of the traditional stories in the cryptocurrency community. However, during its existence and relevant presence, i.e. approximately since 2013, there has been no severe situation on the financial markets globally to prove or disprove this story until the COVID-19 pandemics. We study the quantile correlations of Bitcoin

Gianmaria DelMonte, Elia Onofri, Giorgio Scorzelli, Alberto Paoluzzi

The object of this paper is to transform a set of local chain complexes to a single global complex using an equivalence relation of congruence of cells, solving topologically the numerical inaccuracies of floating-point arithmetics. While computing the space arrangement generated by a collection of cellular complexes, one may start from independently and eff

Nicolas Libedinsky, Geordie Williamson

We refine an idea of Deodhar, whose goal is a counting formula for Kazhdan-Lusztig polynomials. This is a consequence of a simple observation that one can use the solution of Soergel's conjecture to make ambiguities involved in defining certain morphisms between Soergel bimodules in characteristic zero (double leaves) disappear.

Cesar Manchein, Eduardo L. Brugnago, Rafael M. da Silva, Carlos F. O. Mendes

In this work we analyse the growth of the cumulative number of confirmed infected cases by the COVID-19 until March 27th, 2020, from countries of Asia, Europe, North and South America. Our results show (i) that power-law growth is observed for all countries; (ii) by using the distance correlation, that the power-law curves between countries are statistically

Cui-Ying Song, Tong Liu, Yun-Feng Wei

Gamma-ray bursts (GRBs) might be powered by a black hole (BH) hyperaccretion systems via the Blandford-Znajek (BZ) mechanism or neutrino annihilation from neutrino-dominated accretion flows (NDAFs). Magnetic coupling (MC) between the inner disc and BH can transfer angular momentum and energy from the fast-rotating BH to the disc. The neutrino luminosity and

Philip Ndikum

This research paper explores the performance of Machine Learning (ML) algorithms and techniques that can be used for financial asset price forecasting. The prediction and forecasting of asset prices and returns remains one of the most challenging and exciting problems for quantitative finance and practitioners alike. The massive increase in data generated an

Xi Sisi Shen

We study the behavior of the K\"ahler-Ricci flow on compact manifolds developing finite-time singularities, in particular, when the flow contracts exceptional divisors or collapses the Fano fibers of a holomorphic fiber bundle. We present a technique using holomorphic vector fields to prove estimates related to the work of Song-Weinkove and Fu-Zhang.

Zhou Fan, Yi Sun, Tianhao Wang, Yihong Wu

We study the non-convex optimization landscape for maximum likelihood estimation in the discrete orbit recovery model with Gaussian noise. This model is motivated by applications in molecular microscopy and image processing, where each measurement of an unknown object is subject to an independent random rotation from a rotational group. Equivalently, it is a

Ye-Sheen Lim, Denise Gorse

In this paper we propose a deep recurrent model based on the order flow for the stationary modelling of the high-frequency directional prices movements. The order flow is the microsecond stream of orders arriving at the exchange, driving the formation of prices seen on the price chart of a stock or currency. To test the stationarity of our proposed model we

Guillermo F. Quinteiro, Christian T. Schmiegelow, Ferdinand Schmidt-Kaler

Neglecting the electric field component along the light's propagation direction is a common practice, known as paraxial approximation. However, experimental evidence and theory on the head-on excitation of atoms by Laguerre-Gaussian beams reveal that the full vector character of the light field has to be taken into account. Optical vortices are a large famil

Javier Rubio

I review the Higgs-Dilaton model: a scale-invariant extension of the Standard Model and gravity able to support inflation and dark energy with just an additional degree of freedom on top of the Standard Model content. Potential extensions of the simplest realization on the basis of transverse diffeomorphisms are also discussed.

Halgurd S. Maghdid, Aras T. Asaad, Kayhan Zrar Ghafoor, Ali Safaa Sadiq

COVID-19 (also known as 2019 Novel Coronavirus) first emerged in Wuhan, China and spread across the globe with unprecedented effect and has now become the greatest crisis of the modern era. The COVID-19 has proved much more pervasive demands for diagnosis that has driven researchers to develop more intelligent, highly responsive and efficient detection metho

Alexander Zderic, Ann-Marie Madigan

Axisymmetric disks of high eccentricity, low mass bodies on near-Keplerian orbits are unstable to an out-of-plane buckling. This "inclination instability" exponentially grows the orbital inclinations, raises perihelia distances and clusters in argument of perihelion. Here we examine the instability in a massive primordial scattered disk including the orbit-a

Xiao Lei Zhang, Anish Agarwal

The study of unsupervised learning can be generally divided into two categories: imitation learning and reinforcement learning. In imitation learning the machine learns by mimicking the behavior of an expert system whereas in reinforcement learning the machine learns via direct environment feedback. Traditional deep reinforcement learning takes a significant

Zhi-Qiang You, Xing-Jiang Zhu, Gregory Ashton, Eric Thrane

Gravitational-wave astronomy provides a unique new way to study the expansion history of the Universe. In this work, we investigate the impact future gravitational-wave observatories will have on cosmology. Third-generation observatories like the Einstein Telescope and Cosmic Explorer will be sensitive to essentially all of the binary black hole coalescence

Rose McCarty

We prove that every bipartite graph of sufficiently large average degree has either a $K_{t,t}$-subgraph or an induced subgraph of average degree at least $t$ and girth at least $6$. We conjecture that "$6$" can be replaced by "$k$", which strengthens a conjecture of Thomassen. In support of this conjecture, we show that it holds for regular graphs.

Christian Krüger, Tanja Kojić, Luis Meier, Sebastian Möller

This paper describes the development and validation of a continuous pictographic scale for self-reported assessment of affective states in virtual environments. The developed tool, called Morph A Mood (MAM), consists of a 3D character whose facial expression can be adjusted with simple controller gestures according to the perceived affective state to capture

Rodrigo Agerri, Iñaki San Vicente, Jon Ander Campos, Ander Barrena

Word embeddings and pre-trained language models allow to build rich representations of text and have enabled improvements across most NLP tasks. Unfortunately they are very expensive to train, and many small companies and research groups tend to use models that have been pre-trained and made available by third parties, rather than building their own. This is

Camille L. Latune, Ilya Sinayskiy, Francesco Petruccione

The performances of quantum thermometry in thermal equilibrium together with the output power of certain class of quantum engines share a common characteristic: both are determined by the heat capacity of the probe or working medium. After noticing that the heat capacity of spin ensembles can be significantly modified by collective coupling with a thermal ba

Brendan O'Connor, Paz Beniamini, Chryssa Kouveliotou

Observational follow-up of well localized short gamma-ray bursts (SGRBs) has left $20-30\%$ of the population without a coincident host galaxy association to deep optical and NIR limits ($\gtrsim 26$ mag). These SGRBs have been classified as observationally hostless due to their lack of strong host associations. It has been argued that these hostless SGRBs c

David Andriot, Niccolò Cribiori, David Erkinger

We consider the swampland distance and de Sitter conjectures, of respective order one parameters $\lambda$ and $c$. Inspired by the recent Trans-Planckian Censorship conjecture (TCC), we propose a generalization of the distance conjecture, which bounds $\lambda$ to be a half of the TCC bound for $c$, i.e. $\lambda \geq \frac{1}{2}\sqrt{\frac{2}{3}}$ in 4d. I

Yaron Kedem

We revisit the quantum phase transition from a paraelectric state to a ferroelectric one and in particular the widespread distinction between a longitudinal modes to transverse one. In contrast to transitions at finite temperature, for a quantum phase transition breaking a discrete symmetry the splitting between the modes is irrelevant. We show that an aniso

Gourab Ray, Yinon Spinka

We consider the unique measure of maximal entropy for proper 3-colorings of $\mathbb{Z}^2$, or equivalently, the so-called zero-slope Gibbs measure. Our main result is that this measure is Bernoulli, or equivalently, that it can be expressed as the image of a translation-equivariant function of independent and identically distributed random variables placed

Peng Ru, Zhong-Bo Kang, Enke Wang, Hongxi Xing

We present the first global extraction of the jet transport coefficient ($\hat q$) for cold nuclear matter within the framework of higher-twist expansion. The analysis takes into account the world data on transverse momentum broadening in semi-inclusive $e$-A deep inelastic scattering (DIS) and in Drell-Yan dilepton and heavy quarkonium production in $p$-A c

Aram W. Harrow

We introduce hybrid classical-quantum algorithms for problems involving a large classical data set X and a space of models Y such that a quantum computer has superposition access to Y but not X. These algorithms use data reduction techniques to construct a weighted subset of X called a coreset that yields approximately the same loss for each model. The cores

B. P. Gompertz, R. Cutter, D. Steeghs, D. K. Galloway

We report the results of optical follow-up observations of 29 gravitational-wave triggers during the first half of the LIGO-Virgo Collaboration (LVC) O3 run with the Gravitational-wave Optical Transient Observer (GOTO) in its prototype 4-telescope configuration (GOTO-4). While no viable electromagnetic counterpart candidate was identified, we estimate our 3D

Hui Zhang, Jinfeng Liao, Enke Wang, Qian Wang

Exploring the nature of exotic multiquark candidates such as the $X(3872)$ plays a pivotal role in understanding quantum chromodynamics (QCD). Despite significant efforts, consensus on their internal structures is still lacking. As a prime example, it remains a pressing open question to decipher the $X(3872)$ state between two popular exotic configurations:

Ryan A. Jackson, Garreth Martin, Sugata Kaviraj, Clotilde Laigle

Galaxy merger histories correlate strongly with stellar mass, largely regardless of morphology. Thus, at fixed stellar mass, spheroids and discs share similar assembly histories, both in terms of the frequency of mergers and the distribution of their mass ratios. Since mergers are the principal drivers of disc-to-spheroid morphological transformation, and th

Guillermo Torres, Claud H. Sandberg Lacy, Francis C. Fekel, Matthew W. Muterspaugh

We report extensive differential V-band photometry and high-resolution spectroscopy for the 1.14 day, detached, double-lined eclipsing binary BT Vul (F0+F7). Our radial-velocity monitoring and light curve analysis lead to absolute masses and radii of M1 = 1.5439 +/- 0.0098 MSun and R1 = 1.536 +/- 0.018 RSun for the primary, and M2 = 1.2196 +/- 0.0080 MSun an

Forrest W. Glines, Brian W. O'Shea, G. Mark Voit

In cool-core galaxy clusters with central cooling times much shorter than a Hubble time, condensation of the ambient central gas is regulated by a heating mechanism, probably an active galactic nucleus (AGN). Previous analytical work has suggested that certain radial distributions of heat input may result in convergence to a quasi-steady global state that do

Hila Glanz, Hagai B. Perets

The dynamical evolution of triple stellar systems could induce the formation of compact binaries and binary mergers. Common envelope (CE) evolution, which plays a major role in the evolution of compact binary systems, can similarly play a key role in the evolution of triples. Here we use hydrodynamical simulations coupled with few-body dynamics to provide th

J. Dexter, A. Jiménez-Rosales, S. M. Ressler, A. Tchekhovskoy

The Galactic center black hole candidate Sgr A* is the best target for studies of low-luminosity accretion physics, including with near-infrared and submillimeter wavelength long baseline interferometry experiments. Here we compare images and spectra generated from a parameter survey of general relativistic MHD simulations to a set of radio to near-infrared

Michael Hanke, Andreas Koch, Zdenek Prudil, Eva K. Grebel

We present chemodynamical links between the present-day Milky Way halo field star population and Galactic globular clusters (GCs) using a dataset that combines information from the $\rm{\it Gaia}$ space mission and the Sloan Digital Sky Survey (SDSS-IV, DR14). Moreover, we incorporated a sample of halo giant stars with a distinct chemical signature (strong C

Mattias Blennow, Monojit Ghosh, Tommy Ohlsson, Arsenii Titov

We review and investigate lepton flavor models, stemming from discrete non-Abelian flavor symmetries, described by one or two free model parameters. First, we confront eleven one- and seven two-parameter models with current results on leptonic mixing angles from global fits to neutrino oscillation data. We find that five of the one- and five of the two-param

Charles J. Law, Dan Milisavljevic, Daniel J. Patnaude, Paul P. Plucinsky

We present a three-dimensional kinematic reconstruction of the optically-emitting, oxygen-rich ejecta of supernova remnant N132D in the Large Magellanic Cloud. Data were obtained with the 6.5 m Magellan telescope in combination with the IMACS+GISMO instrument and survey [O III] $\lambda\lambda$4959,5007 line emission in a ${\sim}$3$^{\prime}~\times$ 3$^{\pri

Nathan Seiberg, Shu-Heng Shao

We extend our exploration of nonstandard continuum quantum field theories in 2+1 dimensions to 3+1 dimensions. These theories exhibit exotic global symmetries, a peculiar spectrum of charged states, unusual gauge symmetries, and surprising dualities. Many of the systems we study have a known lattice construction. In particular, one of them is a known gapless

Dylan Keating, Kevin B. Stevenson, Nicolas B. Cowan, Emily Rauscher

We present \textit{Spitzer} full-orbit thermal phase curves of the hot Jupiter Qatar-1b, a planet with the same equilibrium temperature---and intermediate surface gravity and orbital period---as the well-studied planets HD 209458b and WASP-43b. We measure secondary eclipse of $0.21 \pm 0.02 \%$ at $3.6~\mu$m and $0.30 \pm 0.02 \%$ at $4.5~\mu$m, correspondin

Laura Lopez-Honorez, Olga Mena, Sergio Palomares-Ruiz, Pablo Villanueva-Domingo

The observation of space-time variations in fundamental constants would provide strong evidence for the existence of new light degrees of freedom in the theory of Nature. Robustly constraining such scenarios requires exploiting observations that span different scales and probe the state of the Universe at different epochs. In the context of cosmology, both t

Zac Johnston

In low-mass X-ray binaries, the accretion of stellar material onto a neutron star can fuel unstable thermonuclear flashes known as Type I X-ray bursts. Simulating these events using computational models can provide valuable information about the nature of the accreting system. One-dimensional (1D) astrophysics codes with large nuclear reaction networks are t

Joshua W. Foster, Yonatan Kahn, Oscar Macias, Zhiquan Sun

Axion dark matter (DM) may convert to radio-frequency electromagnetic radiation in the strong magnetic fields around neutron stars. The radio signature of such a process would be an ultra-narrow spectral peak at a frequency determined by the mass of the axion particle. We analyze data we collected from the Robert C. Byrd Green Bank Telescope in the L-band an

Clément L. Canonne, Gautam Kamath, Thomas Steinke

A key tool for building differentially private systems is adding Gaussian noise to the output of a function evaluated on a sensitive dataset. Unfortunately, using a continuous distribution presents several practical challenges. First and foremost, finite computers cannot exactly represent samples from continuous distributions, and previous work has demonstra

Samuel Albanie, Jaime Thewmore, Robert McCraith, Joao F. Henriques

Peer review forms the backbone of modern scientific manuscript evaluation. But after two hundred and eighty-nine years of egalitarian service to the scientific community, does this protocol remain fit for purpose in 2020? In this work, we answer this question in the negative (strong reject, high confidence) and propose instead State-Of-the-Art Review (SOAR),

Mariko Isogawa, Ye Yuan, Matthew O'Toole, Kris Kitani

We describe a method for 3D human pose estimation from transient images (i.e., a 3D spatio-temporal histogram of photons) acquired by an optical non-line-of-sight (NLOS) imaging system. Our method can perceive 3D human pose by `looking around corners' through the use of light indirectly reflected by the environment. We bring together a diverse set of technol

Therese Biedl, Milap Sheth

In this paper, we study how to draw Halin-graphs, i.e., planar graphs that consist of a tree $T$ and a cycle among the leaves of that tree. Based on tree-drawing algorithms and the pathwidth $ pw(T) $, a well-known graph parameter, we find poly-line drawings of height at most $6pw(T)+3\in O(\log n)$. We also give an algorithm for straight-line drawings, and

Alex Berke, Michiel Bakker, Praneeth Vepakomma, Kent Larson

Governments and researchers around the world are implementing digital contact tracing solutions to stem the spread of infectious disease, namely COVID-19. Many of these solutions threaten individual rights and privacy. Our goal is to break past the false dichotomy of effective versus privacy-preserving contact tracing. We offer an alternative approach to ass

Zongjian Fan, Ryan Bunk, Guangying Wang, Jerry M. Woodall

Novel ohmic contacts to n-ZnSe are demonstrated using single crystal Al films deposited on epitaxially grown ZnSe (100) by molecular beam epitaxy (MBE). Electron Backscatter Diffraction (EBSD) confirmed the single crystalline structure of the Al films. The (110)-oriented Al layer was rotated rotated 45$^\circ$ relative to substrate to match the ZnSe (100) la

Lauren Doyle, Gavin Ramsay, J. Gerard Doyle

Superflares on solar-type stars has been a rapidly developing field ever since the launch of $\it Kepler$. Over the years, there have been several studies investigating the statistics of these explosive events. In this study, we present a statistical analysis of stellar flares on solar-type stars made using photometric data in 2-min cadence from $\it TESS$ o

Chiara Toldo

Recent years have witnessed lots of progress in the computation of supersymmetric partition functions of SCFTs on curved manifolds via localization. The twisted partition function on product manifolds of the form $S^1 \times \Sigma_g$, where $\Sigma_g$ is a two-dimensional Riemann surface, is of particular relevance due to its role in the microstate counting

Morgan Facchin, Graham D. Bruce, Kishan Dholakia

Laser speckle is generated by the multiple interference of light through a disordered medium. Here we study the premise that the speckle pattern retains information about the polarisation state of the incident field. We analytically verify that a linear relation exists between the Stokes vector of the light and the resulting speckle pattern. As a result, the

Anne S. Wannenwetsch, Stefan Roth

Encoder-decoder networks have found widespread use in various dense prediction tasks. However, the strong reduction of spatial resolution in the encoder leads to a loss of location information as well as boundary artifacts. To address this, image-adaptive post-processing methods have shown beneficial by leveraging the high-resolution input image(s) as guidan

Joseph R. Masiero, Patrice Smith, Lean D. Teodoro, A. K. Mainzer

Thermal infrared measurements of near-Earth objects provide critical data for constraining their physical properties such as size. The NEOWISE mission has been conducting an all-sky infrared survey to gather such data and improve our understanding of this population. While automated routines are employed to identify the majority of moving objects detected by

Mark Girard, Debbie Leung, Jeremy Levick, Chi-Kwong Li

In the theory of quantum information, the mixed-unitary quantum channels, for any positive integer dimension $n$, are those linear maps that can be expressed as a convex combination of conjugations by $n\times n$ complex unitary matrices. We consider the mixed-unitary rank of any such channel, which is the minimum number of distinct unitary conjugations requ

Christian Gérard, Michał Wrochna

We report on the well-posedness of the Feynman problem for the Klein-Gordon equation on asymptotically Minkowski spacetimes. The main result is the invertibility of the Klein-Gordon operator with Feynman conditions at infinite times. Furthermore, the inverse is shown to coincide with the Duistermaat-H\"ormander Feynman parametrix modulo smoothing terms.

Surafel M. Lakew, Matteo Negri, Marco Turchi

Recent advents in Neural Machine Translation (NMT) have shown improvements in low-resource language (LRL) translation tasks. In this work, we benchmark NMT between English and five African LRL pairs (Swahili, Amharic, Tigrigna, Oromo, Somali [SATOS]). We collected the available resources on the SATOS languages to evaluate the current state of NMT for LRLs. O

Zhuoqian Yang, Wentao Zhu, Wayne Wu, Chen Qian

We present a lightweight video motion retargeting approach TransMoMo that is capable of transferring motion of a person in a source video realistically to another video of a target person. Without using any paired data for supervision, the proposed method can be trained in an unsupervised manner by exploiting invariance properties of three orthogonal factors

Randy Lemons, Wei Liu, Josef C. Frisch, Alan Fry

The structural versatility of light underpins an outstanding collection of optical phenomena where both geometrical and topological states of light can dictate how matter will respond or display. Light possesses multiple degrees of freedom such as amplitude, and linear, spin angular, and orbital angular momenta, but the ability to adaptively engineer the spa

Wenbo Gao, Laura Graesser, Krzysztof Choromanski, Xingyou Song

We propose a model-free algorithm for learning efficient policies capable of returning table tennis balls by controlling robot joints at a rate of 100Hz. We demonstrate that evolutionary search (ES) methods acting on CNN-based policy architectures for non-visual inputs and convolving across time learn compact controllers leading to smooth motions. Furthermor

Tim D. Hewson, Fatima M. Pillosu

Computer-generated forecasts divide the earth's surface into gridboxes, each now ~25% of the size of London, and predict one value per gridbox. If weather varies markedly within a gridbox forecasts for specific sites inevitably fail. A completely new statistical post-processing method, using ensemble forecasts as input, anticipates two gridbox-weather-depend

R. C. Malone, A. S. Crowell, L. C. Cumberbatch, B. A. Fallin

New measurements of the neutron-neutron quasifree scattering cross section in neutron-deuteron breakup at an incident neutron energy of 10.0 MeV are reported. The experiment setup was optimized to evaluate the technique for determining the integrated beam-target luminosity in neutron-neutron coincidence cross-section measurements in neutron-deuteron breakup.

Muhammad Farooq, Abdul Hafeez

In the last few months, the novel COVID19 pandemic has spread all over the world. Due to its easy transmission, developing techniques to accurately and easily identify the presence of COVID19 and distinguish it from other forms of flu and pneumonia is crucial. Recent research has shown that the chest Xrays of patients suffering from COVID19 depicts certain a

Anurag Anshu, David Gosset, Karen Morenz

We consider a computational problem where the goal is to approximate the maximum eigenvalue of a two-local Hamiltonian that describes Heisenberg interactions between qubits located at the vertices of a graph. Previous work has shed light on this problem's approximability by product states. For any instance of this problem the maximum energy attained by a pro

Anirudh Vemula, J. Andrew Bagnell

Trajectory optimization is an important tool for control and planning of complex, underactuated robots, and has shown impressive results in real world robotic tasks. However, in applications where the cost function to be optimized is non-smooth, modern trajectory optimization methods have extremely slow convergence. In this work, we present TRON, an iterativ

Eleftherios Triantafyllidis, Christopher McGreavy, Jiacheng Gu, Zhibin Li

Research in multi-modal interfaces aims to provide solutions to immersion and increase overall human performance. A promising direction is combining auditory, visual and haptic interaction between the user and the simulated environment. However, no extensive comparisons exist to show how combining audiovisuohaptic interfaces affects human perception reflecte

Giuseppe C. Calafiore, Carlo Novara, Corrado Possieri

The purpose of this work is to give a contribution to the understanding of the COVID-19 contagion in Italy. To this end, we developed a modified Susceptible-Infected-Recovered (SIR) model for the contagion, and we used official data of the pandemic up to March 30th, 2020 for identifying the parameters of this model. The non standard part of our approach resi

Dmitry B. Uskov, Paul M. Alsing

We suggest a dynamical vector model of entanglement in a three qubit system based on isomorphism between $su(4)$ and $so(6)$ Lie algebras. Generalizing Pl\"ucker-type description of three-qubit local invariants we introduce three pairs of real-valued $3D$ vector (denoted here as $A_{R,I}$ , $B_{R,I}$ and $C_{R,I}$). Magnitudes of these vectors determine two-

Helvi Witek, Leonardo Gualtieri, Paolo Pani

Scalar Gauss-Bonnet gravity is the only theory with quadratic curvature corrections to general relativity whose field equations are of second differential order. This theory allows for nonperturbative dynamical corrections and is therefore one of the most compelling case studies for beyond-general relativity effects in the strong-curvature regime. However, h

S. M. Fosson, V. Cerone, D. Regruto

The problem of sparse linear regression is relevant in the context of linear system identification from large datasets. When data are collected from real-world experiments, measurements are always affected by perturbations or low-precision representations. However, the problem of sparse linear regression from fully-perturbed data is scarcely studied in the l

Tim Richardt, Matthias Heinrich, Markus Gräfe, Alexander Szameit

We report on the uncanny resemblance of the global distribution of all experimentally known atomic spectral lines to the Planckian spectral distribution associated with black body radiation at a temperature of $T\approx9000\,\mathrm{K}$. This value coincides with the critical temperature of equilibrium between the respective densities of radiation and matter

Kazunori Ando, Hyeonbae Kang, Yoshihisa Miyanishi, Mihai Putinar

This is a survey of accumulated spectral analysis observations spanning more than a century, referring to the double layer potential integral equation, also known as Neumann-Poincar\'e operator. The very notion of spectral analysis has evolved along this path. Indeed, the quest for solving this specific singular integral equation, originally aimed at elucida

Asmelash Teka Hadgu, Adam Beaudoin, Abel Aregawi

Machine translation (MT) systems are now able to provide very accurate results for high resource language pairs. However, for many low resource languages, MT is still under active research. In this paper, we develop and share a dataset to automatically evaluate the quality of MT systems for Amharic. We compare two commercially available MT systems that suppo

Blake C. Stacey

The Bohr--Einstein debate is one of the more remarkable protracted intellectual exchanges in the history of physics. Its influence has been lasting: One of the few clear patterns in a 2013 survey about quantum foundations was that the physicists who believed Bohr to be correct were apt to say that Einstein had been wrong. The exchanges began when Bohr and Ei

Paul Bryan, Mohammad N. Ivaki, Julian Scheuer

We employ curvature flows without global terms to seek strictly convex, spacelike solutions of a broad class of elliptic prescribed curvature equations in the simply connected Riemannian spaceforms and the Lorentzian de Sitter space, where the prescribed function may depend on the position and the normal vector. In particular, in the Euclidean space we solve

Mahmoud M. Asmar, Wang-Kong Tse

We present a theory for the Ruderman-Kittel-Kasuya-Yosida (RKKY) interaction mediated by a two-dimensional (2D) electron system subjected to periodic driving. This is demonstrated for a heterostructure consisting of two ferromagnets laterally sandwiching the 2D metallic spacer. Our calculations reveal new non-analytic features in the spin susceptibility. For

Petra Tomanová, Vladimír Holý

Arrivals in queueing systems are typically assumed to be independent and exponentially distributed. Our analysis of an online bookshop, however, shows that there is an autocorrelation structure present. First, we adjust the inter-arrival times for diurnal and seasonal patterns. Second, we model adjusted inter-arrival times by the generalized autoregressive s

Mihail Bazhba, Jose Blanchet, Chang-Han Rhee, Bert Zwart

We prove a sample path large deviation principle (LDP) with sub-linear speed for unbounded functionals of certain Markov chains induced by the Lindley recursion. The LDP holds in the Skorokhod space $\mathbb{D}[0,T]$ equipped with the $M_1'$ topology. Our technique hinges on a suitable decomposition of the Markov chain in terms of regeneration cycles. Each r

Evelyn Herberg, Michael Hinze

We consider a parabolic optimal control problem with an initial measure control. The cost functional consists of a tracking term corresponding to the observation of the state at final time. Instead of a regularization term in the cost functional, we follow an approach by E. Casas and K. Kunisch and consider a bound on the measure norm of the initial control.