March 2020 arXiv papers — page 9

William Broniec, Sungeun An, Spencer Rugaber, Ashok K. Goel

COVID-19 continues to spread across the country and around the world. Current strategies for managing the spread of COVID-19 include social distancing. We present VERA, an interactive AI tool, that first enables users to specify conceptual models of the impact of social distancing on the spread of COVID-19. Then, VERA automatically spawns agent-based simulat

Rui Hu, Yuanxiong Guo, Yanmin Gong

Federated learning is a machine learning setting where a set of edge devices collaboratively train a model under the orchestration of a central server without sharing their local data. At each communication round of federated learning, edge devices perform multiple steps of stochastic gradient descent with their local data and then upload the computation res

Davide Modolo, Bing Shuai, Rahul Rama Varior, Joseph Tighe

Every crowd counting researcher has likely observed their model output wrong positive predictions on image regions not containing any person. But how often do these mistakes happen? Are our models negatively affected by this? In this paper we analyze this problem in depth. In order to understand its magnitude, we present an extensive analysis on five of the

Rami Luisto

Too little mathematics has been written in prose. Thus we prove here, via a fantasy novellette, that a locally L-bilipschitz mapping $f \colon X \to Y$ between uniformly Ahlfors $q$-regular, complete and locally compact path-metric spaces $X$ and $Y$ is an $L$-bilipschitz map when $Y$ is simply connected. The motivation for such a result arises from studying

Yiqin Zhao, Tian Guo

We propose an efficient lighting estimation pipeline that is suitable to run on modern mobile devices, with comparable resource complexities to state-of-the-art mobile deep learning models. Our pipeline, PointAR, takes a single RGB-D image captured from the mobile camera and a 2D location in that image, and estimates 2nd order spherical harmonics coefficient

Alejandro Ayala, Marco Alberto Ayala Torres, Eleazar Cuautle, Isabel Dominguez

We compute the Lambda and anti-Lambda global polarization in semi-central heavy-ion collisions modeling the source as consisting of a high-density core and a less dense corona. We show that when more Lambdas than anti-Lambdas are produced in the corona, and this is combined with a smaller number of Lambdas coming from the core, as compared to those coming fr

Zbynek Urban, Francesco Bajardi, Salvatore Capozziello

The Noether-Bessel-Hagen theorem can be considered a natural extension of Noether Theorem to search for symmetries. Here, we develop the approach for dynamical systems introducing the basic foundations of the method. Specifically, we establish the Noether-Bessel-Hagen analysis of mechanical systems where external forces are present. In the second part of the

Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen

This two-part review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this second part, we reflect on a selection of exemplary studies. It is increasingly important to articulate what the role of automation and computation has been in the scientific process and how that has or has not accelerated discover

Connor W. Coley, Natalie S. Eyke, Klavs F. Jensen

This two-part review examines how automation has contributed to different aspects of discovery in the chemical sciences. In this first part, we describe a classification for discoveries of physical matter (molecules, materials, devices), processes, and models and how they are unified as search problems. We then introduce a set of questions and considerations

Tamara Kohler, Stephen Piddock, Johannes Bausch, Toby Cubitt

Recent work has characterised rigorously what it means for one quantum system to simulate another, and demonstrated the existence of universal Hamiltonians -- simple spin lattice Hamiltonians that can replicate the entire physics of any other quantum many body system. Previous universality results have required proofs involving complicated `chains' of pertur

Andrzej Jarynowski, Monika Wojta-Kempa, Vitaly Belik

We study the perception of COVID-2019 epidemic in Polish society using quantitative analysis of its digital footprints on the Internet (on Twitter, Google, YouTube, Wikipedia and electronic media represented by Event Registry) from January 2020 to 12.03.2020 (before and after official introduction to Poland on 04.03.2020). To this end we utilize data mining,

Dominik Bendle, Janko Boehm, Yue Ren, Benjamin Schröter

In this article, we present a massively parallel framework for computing tropicalizations of algebraic varieties which can make use of finite symmetries. We compute the tropical Grassmannian TGr$_0(3,8)$, and show that it refines the $15$-dimensional skeleton of the Dressian Dr$(3,8)$ with the exception of $23$ special cones for which we construct explicit o

Sanne J. van den Boom, Jian Zhang, Fred van Keulen, Alejandro M. Aragón

During design optimization, a smooth description of the geometry is important, especially for problems that are sensitive to the way interfaces are resolved, e.g., wave propagation or fluid-structure interaction. A levelset description of the boundary, when combined with an enriched finite element formulation, offers a smoother description of the design than

Eric Müller, Christian Mauch, Philipp Spilger, Oliver Julien Breitwieser

BrainScaleS-2 is a mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing. To augment its flexibility, the analog neural network core is accompanied by an embedded SIMD microprocessor. The BrainScaleS Operating System (BrainScaleS OS) is a software stack designed for the

Eric Müller, Sebastian Schmitt, Christian Mauch, Sebastian Billaudelle

BrainScaleS-1 is a wafer-scale mixed-signal accelerated neuromorphic system targeted for research in the fields of computational neuroscience and beyond-von-Neumann computing. The BrainScaleS Operating System (BrainScaleS OS) is a software stack giving users the possibility to emulate networks described in the high-level network description language PyNN wit

Sanaz Panahandeh, Siyu Li, Laurent Marichal, Rafael Leite Rubim

Previous self-assembly experiments on a model icosahedral plant virus have shown that, under physiological conditions, capsid proteins initially bind to the genome through an en masse mechanism and form nucleoprotein complexes in a disordered state, which raises the questions as to how virions are assembled into a highly ordered structure in the host cell. U

J. E. Amaro

We present a simple analytical model to describe the fast increase of deaths produced by the corona virus (COVID-19) infections. The 'D' (deaths) model comes from a simplified version of the SIR (susceptible-infected-recovered) model known as SI model. It assumes that there is no recovery. In that case the dynamical equations can be solved analytically and t

Fan Yao, Adnan Siraj Rakin, Deliang Fan

Security of machine learning is increasingly becoming a major concern due to the ubiquitous deployment of deep learning in many security-sensitive domains. Many prior studies have shown external attacks such as adversarial examples that tamper with the integrity of DNNs using maliciously crafted inputs. However, the security implication of internal threats (

Jendrik Brachter, Pascal Schweitzer

In comparison to graphs, combinatorial methods for the isomorphism problem of finite groups are less developed than algebraic ones. To be able to investigate the descriptive complexity of finite groups and the group isomorphism problem, we define the Weisfeiler-Leman algorithm for groups. In fact we define three versions of the algorithm. In contrast to grap

Patrick Barnes, Zachary Johnson, Aaron Pierce, Bibhushan Shakya

A hidden sector that kinetically mixes with the Minimal Supersymmetric Standard Model provides simple and well-motivated dark matter candidates that possess many of the properties of a traditional weakly interacting massive particle (WIMP). These supersymmetric constructions can also provide a natural explanation for why the dark matter is at the weak scale

Manchen Wang, Joseph Tighe, Davide Modolo

We propose a novel top-down approach that tackles the problem of multi-person human pose estimation and tracking in videos. In contrast to existing top-down approaches, our method is not limited by the performance of its person detector and can predict the poses of person instances not localized. It achieves this capability by propagating known person locati

Vivek Khatana, Murti V. Salapaka

This article reports an algorithm for multi-agent distributed optimization problems with a common decision variable, local linear equality and inequality constraints and set constraints with convergence rate guarantees. \textcolor{black}{The algorithm accrues all the benefits of the Alternating Direction Method of Multipliers (ADMM) approach}. It also overco

Karl Kurzer, Christoph Hörtnagl, J. Marius Zöllner

Monte Carlo Tree Search (MCTS) has proven to be capable of solving challenging tasks in domains such as Go, chess and Atari. Previous research has developed parallel versions of MCTS, exploiting today's multiprocessing architectures. These studies focused on versions of MCTS for the discrete case. Our work builds upon existing parallelization strategies and

Musajan Kadir, Alim Ablet, Sayipjamal Dulat, Tie-Jiun Hou

By applying the Error PDF Updating Method, we analyze the impact of the absolute and normalized single differential cross-sections for top-quark pair production data from the ATLAS and CMS experiments at the Large Hadron Collider, at a centre-of-mass energy of $\sqrt{s}= 8$ TeV, on the CT14HERA2 PDFs. We find that the top quark pair single differential distr

Kaivalya Bakshi, Evangelos A. Theodorou, Piyush Grover

Control of continuous time dynamics with multiplicative noise is a classic topic in stochastic optimal control. This work addresses the problem of designing infinite horizon optimal controls with stability guarantees for \textit{a single agent or large population systems} of identical, non-cooperative and non-networked agents, with multi-dimensional and nonl

David Loeffler

We construct examples of p-adic L-functions over universal deformation spaces for GL(2). We formulate a conjecture predicting that the natural parameter spaces for p-adic L-functions are not the usual eigenvarieties (parametrising nearly-ordinary families of automorphic representations), but other, larger spaces depending on a choice of a parabolic subgroup,

Jim Samuel

Conjunct with the universal acceleration in information growth, financial services have been immersed in an evolution of information dynamics. It is not just the dramatic increase in volumes of data, but the speed, the complexity and the unpredictability of big-data phenomena that have compounded the challenges faced by researchers and practitioners in finan

Erik Sjöqvist

The geometric phase (GP) acquired by a neutron passing through a uniform magnetic field elucidates a subtle interplay between its spatial and spin degrees of freedom. In the standard setup using thermal neutrons, the kinetic energy is much larger than the typical Zeeman split. This causes the spin to undergo nearly perfect precession around the axis of the m

Carl Leake, David Arnas, Daniele Mortari

This study introduces a new "Non-Dimensional" star identification algorithm to reliably identify the stars observed by a wide field-of-view star tracker when the focal length and optical axis offset values are known with poor accuracy. This algorithm is particularly suited to complement nominal lost-in-space algorithms, which may identify stars incorrectly w

Davide Torlo

Model order reduction (MOR) techniques have always struggled in compressing information for advection dominated problems. Their linear nature does not allow to accelerate the slow decay of the Kolmogorov $N$--width of these problems. In the last years, new nonlinear algorithms obtained smaller reduced spaces. In these works only the offline phase of these al

Olmo Francesconi, Marco Panero, David Preti

We compute the running coupling of non-Abelian gauge theories in the Schr\"odinger-functional scheme, by means of non-equilibrium Monte Carlo simulations on the lattice.

Qiyuan Fu, Sean W. Gart, Thomas W. Mitchel, Jin Seob Kim

Snakes can move through almost any terrain. Similarly, snake robots hold the promise as a versatile platform to traverse complex environments like earthquake rubble. Unlike snake locomotion on flat surfaces which is inherently stable, when snakes traverse complex terrain by deforming their body out of plane, it becomes challenging to maintain stability. Here

Fangzhou Xie

Recent proposal of Wasserstein Index Generation model (WIG) has shown a new direction for automatically generating indices. However, it is challenging in practice to fit large datasets for two reasons. First, the Sinkhorn distance is notoriously expensive to compute and suffers from dimensionality severely. Second, it requires to compute a full $N\times N$ m

Mercedes Garcia-Salguero, Jesus Briales, Javier Gonzalez-Jimenez

In this paper we present the first fast optimality certifier for the non-minimal version of the Relative Pose problem for calibrated cameras from epipolar constraints. The proposed certifier is based on Lagrangian duality and relies on a novel closed-form expression for dual points. We also leverage an efficient solver that performs local optimization on the

Michael Braun, Florian Weber, Florian Alt

Affective technology offers exciting opportunities to improve road safety by catering to human emotions. Modern car interiors enable the contactless detection of user states, paving the way for a systematic promotion of safe driver behavior through emotion regulation. We review the current literature regarding the impact of emotions on driver behavior and an

Radouane Gannouji, Yolbeiker Rodríguez Baez

We study gravitational collapse in K-essence model with shift symmetry. For these models, we have the formation of two types of horizons, event and sonic. For the particular case $K(X)=X+\beta X^2$ we found three different regimes. In the weak field regime the scalar field disperses to infinity, in the very strong regime both horizons form at the same time a

Kristina Giesel, Laura Herold, Bao-Fei Li, Parampreet Singh

The aim of this article is to understand the role of dust reference fields, often also called clocks, on cosmological perturbations around a flat FLRW universe. We derive the Mukhanov-Sasaki (MS) equation for the Brown-Kuchar (BK) and Gaussian dust models, which both consider four dust fields as reference fields. The reduced phase space of Dirac observables,

Zekarias T. Kefato, Sarunas Girdzijauskas

Graph representation learning (GRL) is a powerful technique for learning low-dimensional vector representation of high-dimensional and often sparse graphs. Most studies explore the structure and metadata associated with the graph using random walks and employ an unsupervised or semi-supervised learning schemes. Learning in these methods is context-free, resu

José M. Amigó, Roberto Dale, Piergiulio Tempesta

Permutation entropy measures the complexity of deterministic time series via a data symbolic quantization consisting of rank vectors called ordinal patterns or just permutations. The reasons for the increasing popularity of this entropy in time series analysis include that (i) it converges to the Kolmogorov-Sinai entropy of the underlying dynamics in the lim

Jinhong Park, Bernd Rosenow, Yuval Gefen

Low-energy transport in quantum Hall states is carried through edge modes, and is dictated by bulk topological invariants and possibly microscopic Boltzmann kinetics at the edge. Here we show how the presence or breaking of symmetries of the edge Hamiltonian underlie transport properties, specifically d.c. conductance and noise. We demonstrate this through t

Sangwon Jung, Hongjoon Ahn, Sungmin Cha, Taesup Moon

We propose a novel regularization-based continual learning method, dubbed as Adaptive Group Sparsity based Continual Learning (AGS-CL), using two group sparsity-based penalties. Our method selectively employs the two penalties when learning each node based its the importance, which is adaptively updated after learning each new task. By utilizing the proximal

Hamid Abchir, Mohammed Sabak

We construct an infinite family of links which are both almost alternating and quasi-alternating from a given either almost alternating diagram representing a quasi-alternating link, or connected and reduced alternating tangle diagram. To do that we use what we call a dealternator extension which consists in replacing the dealternator by a rational tangle ex

S. D. Odintsov, V. K. Oikonomou, F. P. Fronimos

In this work we introduce a new theoretical framework for Einstein-Gauss-Bonnet theories of gravity, which results to particularly elegant, functionally simple and transparent gravitational equations of motion, slow-roll indices and the corresponding observational indices. The main requirement is that the Einstein-Gauss-Bonnet theory has to be compatible wit

Panagiotis Lolas

We study general singular value shrinkage estimators in high-dimensional regression and classification, when the number of features and the sample size both grow proportionally to infinity. We allow models with general covariance matrices that include a large class of data generating distributions. As far as the implications of our results are concerned, we

Marven F. Pedbost, Trillean Pomalgu, Chris Lintott, Nora Eisner

Since the discovery of the first confirmed exoplanet, observations have revealed a remarkable diversity of worlds. A wide variety of orbital and physical characteristics are detected in the exoplanet population, and much work has been devoted to deciding which of these planets may be suitable for life. Until now, though, little work has been devoted to decid

Amr M. Zaki, Mahmoud I. Khalil, Hazem M. Abbas

Text Summarization is the task of condensing long text into just a handful of sentences. Many approaches have been proposed for this task, some of the very first were building statistical models (Extractive Methods) capable of selecting important words and copying them to the output, however these models lacked the ability to paraphrase sentences, as they si

Marko Vasic, Cameron Chalk, Sarfraz Khurshid, David Soloveichik

Embedding computation in molecular contexts incompatible with traditional electronics is expected to have wide ranging impact in synthetic biology, medicine, nanofabrication and other fields. A key remaining challenge lies in developing programming paradigms for molecular computation that are well-aligned with the underlying chemical hardware and do not atte

Dayun Yan, Qihui Wang, Manish Adhikari, Alisa Malyavko

For years, extensive efforts have been made to discover effective, non-invasive anti-cancer therapies. Cold atmospheric plasma (CAP), is a near room temperature ionized gas composed of reactive species, charged particles, neutral particles, and electrons. CAP also has several physical factors including thermal radiation, ultraviolet (UV) radiation, and elect

Zachary Hamaker, Oliver Pechenik, Anna Weigandt

The geometric naturality of Schubert polynomials and their combinatorial pipe dream representations was established by Knutson and Miller (2005) via antidiagonal Gr\"obner degeneration of matrix Schubert varieties. We consider instead diagonal Gr\"obner degenerations. In this dual setting, Knutson, Miller, and Yong (2009) obtained alternative combinatorics f

M. R. Kennedy, R. P. Breton, C. J. Clark, V. S. Dhillon

We present an optical, X-ray, and $\gamma$-ray study of 1SXPS J042749.2-670434, an eclipsing X-ray binary which has an associated $\gamma$-ray counterpart, 4FGL J0427.8-6704. This association has led to the source being classified as a transitional millisecond pulsar (tMSP) in an accreting state. We analyse 10.5 years of Fermi LAT data, and detect a $\gamma$

Mark W. Phillips, Pascal Tremblin, Isabelle Baraffe, Gilles Chabrier

We present a new set of solar metallicity atmosphere and evolutionary models for very cool brown dwarfs and self-luminous giant exoplanets, which we term ATMO 2020. Atmosphere models are generated with our state-of-the-art 1D radiative-convective equilibrium code ATMO, and are used as surface boundary conditions to calculate the interior structure and evolut

Georgios K. Karananas

I will discuss spontaneous conformal symmetry breaking in the strongly $\gamma$-deformed limit of the $\mathcal N=4$ supersymmetric Yang-Mills theory known as~\emph{Fishnet Conformal Field Theory}.

Vukosi Marivate, Tshephisho Sefara, Vongani Chabalala, Keamogetswe Makhaya

The recent advances in Natural Language Processing have only been a boon for well represented languages, negating research in lesser known global languages. This is in part due to the availability of curated data and research resources. One of the current challenges concerning low-resourced languages are clear guidelines on the collection, curation and prepa

Michalis Skotiniotis, Andreas Winter

Godwin's law, i.e. the empirical observation that as an online discussion grows in time, the probability of a comparison with Nazis or Hitler quickly approaches unity, is one of the best-documented facts of the internet. Anticipating the quantum internet, here we show under reasonable model assumptions a polynomial quantum speedup of Godwin's law. Concretely

Rankeya Datta, Takumi Murayama

An excellent ring of prime characteristic for which the Frobenius map is pure is also Frobenius split in many commonly occurring situations in positive characteristic commutative algebra and algebraic geometry. However, using a fundamental construction from rigid geometry, we show that excellent $F$-pure rings of prime characteristic are not Frobenius split

Marco Benini, Marco Perin, Alexander Schenkel, Lukas Woike

This paper develops a concept of 2-categorical algebraic quantum field theories (2AQFTs) that assign locally presentable linear categories to spacetimes. It is proven that ordinary AQFTs embed as a coreflective full 2-subcategory into the 2-category of 2AQFTs. Examples of 2AQFTs that do not come from ordinary AQFTs via this embedding are constructed by a loc

F. N. Díaz, J. Hoefken, A. M. Gago

A number of different effects of the violation of the Equivalence Principle (VEP), taken as sub-leading mechanism of neutrino flavor oscillation, are examined within the framework of the DUNE experiment. We study the possibility of obtaining a misleading neutrino oscillation parameter region caused by our unawareness of VEP. Additionally, we evaluate the imp

Laura K. Rogers, Siyi Xu, Amy Bonsor, Simon Hodgkin

The inwards scattering of planetesimals towards white dwarfs is expected to be a stochastic process with variability on human time-scales. The planetesimals tidally disrupt at the Roche radius, producing dusty debris detectable as excess infrared emission. When sufficiently close to the white dwarf, this debris sublimates and accretes on to the white dwarf a

R. Nanni, R. Gilli, C. Vignali, M. Mignoli

We present the X-ray source catalog for the 479 ks Chandra exposure of the SDSS J1030+0524 field, that is centered on a region that shows the best evidence to date of an overdensity around a z > 6 quasar, and also includes a galaxy overdensity around a Compton-thick Fanaroff-Riley type II radio galaxy at z = 1.7. Using wavdetect for initial source detection

Yue Yu, Steven A. Kivelson

We analyze the zero temperature phase diagrams of the spin S quantum antiferromagnet on square and triangular lattices with competing nearest and next-nearest exchange interactions as well as biquadratic couplings. We approach the problem from the large S limit. Our primary focus is on determining the extent to which the existence and character of any quantu

Jacopo De Nardis, Sarang Gopalakrishnan, Enej Ilievski, Romain Vasseur

Finite-temperature spin transport in the quantum Heisenberg spin chain is known to be superdiffusive, and has been conjectured to lie in the Kardar-Parisi-Zhang (KPZ) universality class. Using a kinetic theory of transport, we compute the KPZ coupling strength for the Heisenberg chain as a function of temperature, directly from microscopics; the results agre

Ilya Belopolski, Kaustuv Manna, Daniel S. Sanchez, Guoqing Chang

Topological matter is known to exhibit unconventional surface states and anomalous transport owing to unusual bulk electronic topology. In this study, we use photoemission spectroscopy and quantum transport to elucidate the topology of the room temperature magnet Co$_2$MnGa. We observe sharp bulk Weyl fermion line dispersions indicative of nontrivial topolog

K. Fahrion, M. Lyubenova, M. Hilker, G. van de Ven

Globular cluster (GC) systems of massive galaxies often show a bimodal colour distribution. This has been interpreted as a metallicity bimodality, created by a two-stage galaxy formation where the red, metal-rich GCs were formed in the parent halo and the blue metal-poor GCs were accreted. This interpretation, however, crucially depends on the assumption tha

Byungmin Kang, Wonjun Lee, Gil Young Cho

We construct new many-body invariants for 2d Chern and 3d chiral hinge insulators, which are characterized by quantized pumping of dipole and quadrupole moments. The invariants that we devise are written entirely in terms of many-body ground state wavefunctions on a torus geometry with a set of unitary operators. We provide a number of supporting evidences f

K. Fahrion, M. Lyubenova, M. Hilker, G. van de Ven

Globular clusters (GCs) are found ubiquitously in massive galaxies and due to their old ages, they are regarded as fossil records of galaxy evolution. Spectroscopic studies of GC systems are often limited to the outskirts of galaxies, where GCs stand out against the galaxy background and serve as bright tracers of galaxy assembly. In this work, we use the ca

Livia Ferro, Tomasz Lukowski, Robert Moerman

The momentum amplituhedron is a positive geometry encoding tree-level scattering amplitudes in $\mathcal{N}=4$ super Yang-Mills directly in spinor-helicity space. In this paper we classify all boundaries of the momentum amplituhedron $\mathcal{M}_{n,k}$ and explain how these boundaries are related to the expected factorization channels, and soft and collinea

Markus Q. Huber

Correlation functions of Yang-Mills theory in the Landau gauge are calculated from their equations of motion. The employed setup is completely parameter free and leads, within errors, to good quantitative agreement with corresponding lattice results for the ghost and gluon propagators as well as the ghost-gluon and three-gluon vertices. Also the four-gluon v

Ya-Hui Zhang, T. Senthil

Recently Chern insulators with Chern number $C=1$ and $C=2$ in zero (or very small) magnetic field have been observed in two moire graphene systems: twisted bilayer graphene and ABC trilayer graphene, both aligned with a hexagonal Boron-Nitride (h-BN) substrate. These Chern insulator states arise due to many body effects in the Chern bands of these systems w

Quentin Marsal, Daniel Varjas, Adolfo G. Grushin

Amorphous solids remain outside of the classification and systematic discovery of new topological materials, partially due to the lack of realistic models that are analytically tractable. Here we introduce the topological Weaire-Thorpe class of models, which are defined on amorphous lattices with fixed coordination number, a realistic feature of covalently b

Jeffrey A. Harvey, Gregory W. Moore

Special conformal field theories can have symmetry groups which are interesting sporadic finite simple groups. Famous examples include the Monster symmetry group of a $c=24$ two-dimensional conformal field theory (CFT) constructed by Frenkel, Lepowsky and Meurman, and the Conway symmetry group of a $c=12$ CFT explored in detail by Duncan and Mack-Crane. The

Jan Carl Budich, Emil J. Bergholtz

We introduce and study a novel class of sensors whose sensitivity grows exponentially with the size of the device. Remarkably, this drastic enhancement does not rely on any fine-tuning, but is found to be a stable phenomenon immune to local perturbations. Specifically, the physical mechanism behind this striking phenomenon is intimately connected to the anom

Félix-Louis Julié, Emanuele Berti

We present the $d+1$ formulation of Einstein-scalar-Gauss-Bonnet (ESGB) theories in dimension $D=d+1$ and for arbitrary (spacelike or timelike) slicings. We first build an action which generalizes those of Gibbons-Hawking-York and Myers to ESGB theories, showing that they can be described by a Dirichlet variational principle. We then generalize the Arnowitt-

Panagiotis Betzios, Olga Papadoulaki

We analyse the connections between the Wheeler DeWitt approach for two dimensional quantum gravity and holography, focusing mainly in the case of Liouville theory coupled to $c=1$ matter. Our motivation is to understand whether some form of averaging is essential for the boundary theory, if we wish to describe the bulk quantum gravity path integral of this t

Samuel J. Witte, Salvador Rosauro-Alcaraz, Samuel D. McDermott, Vivian Poulin

Dark photon dark matter will resonantly convert into visible photons when the dark photon mass is equal to the plasma frequency of the ambient medium. In cosmological contexts, this transition leads to an extremely efficient, albeit short-lived, heating of the surrounding gas. Existing work in this field has been predominantly focused on understanding the im

Aleksandra Kuznetsova, Lee Hartmann, Fabian Heitsch

Building on our previous hydrodynamic study of the angular momenta of cloud cores formed during gravitational collapse of star-forming molecular gas in our previous work, we now examine core properties assuming ideal magnetohydrodynamics (MHD). Using the same sink-patch implementation for the \emph{Athena} MHD code, we characterize the statistical properties

M. R. Lovell

Evidence has continued to accumulate over the last few decades as to the existence and nature of dark matter. Depending on the particle candidate, the dark matter can exhibit one of several cosmologically defined models: hot dark matter, cold dark matter, warm dark matter, self-interacting dark matter, and fuzzy dark matter. In this paper I review the releva

Yuto Ashida, Atac Imamoglu, Jerome Faist, Dieter Jaksch

The light-matter interaction can be utilized to qualitatively alter physical properties of materials. Recent theoretical and experimental studies have explored this possibility of controlling matter by light based on driving many-body systems via strong classical electromagnetic radiation, leading to a time-dependent Hamiltonian for electronic or lattice deg

Arianna S. Long, Asantha Cooray, Jingzhe Ma, Caitlin M. Casey

Recent simulations and observations of massive galaxy cluster evolution predict that the majority of stellar mass build up happens within cluster members by $z=2$, before cluster virialization. Protoclusters rich with dusty, star-forming galaxies (DSFGs) at $z>3$ are the favored candidate progenitors for these massive galaxy clusters at $z\sim0$. We present

Thomas W. -S. Holoien, Katie Auchettl, Michael A. Tucker, Benjamin J. Shappee

We present nearly 500 days of observations of the tidal disruption event ASASSN-18pg, spanning from 54 days before peak light to 441 days after peak light. Our dataset includes X-ray, UV, and optical photometry, optical spectroscopy, radio observations, and the first published spectropolarimetric observations of a TDE. ASASSN-18pg was discovered on 2018 July

Benjamin Gerard, Christian Marois

The continual push to directly image exoplanets at lower masses and closer separations orbiting around bright stars remains limited by both quasi-static and residual adaptive optics (AO) aberration. In previous papers we have proposed a modification of the self-coherent camera (SCC) design to address both of these limitations, called the Fast Atmospheric SCC

Giuseppe Puglisi, Xiran Bai

Deep convolutional neural networks have been a popular tool for image generation and restoration. The performance of these networks is related to the capability of learning realistic features from a large dataset. In this work, we applied the problem of inpainting non-Gaussian signal, in the context of Galactic diffuse emissions at the millimetric and sub-mi

Kevin Slagle, Liang Fu

Transition metal dichalcogenide (TMD) bilayers are a new class of tunable moir\'e systems attracting interest as quantum simulators of strongly-interacting electrons in two dimensions. In particular, recent theory predicts that the correlated insulator observed in WSe$_2$/WS$_2$ at half filling is a charge-transfer insulator similar to cuprates and, upon fur

Yawei Li, Shuhang Gu, Kai Zhang, Luc Van Gool

Network pruning has been the driving force for the acceleration of neural networks and the alleviation of model storage/transmission burden. With the advent of AutoML and neural architecture search (NAS), pruning has become topical with automatic mechanism and searching based architecture optimization. Yet, current automatic designs rely on either reinforcem

Mirjam Cvetic, Jonathan J. Heckman, Thomas B. Rochais, Ethan Torres

Higgs bundles are a central tool used to study a range of intersecting brane systems in string compactifications. Solutions to the internal gauge theory equations of motion for the corresponding worldvolume theories of branes give rise to different low energy effective field theories. This has been heavily used in the study of M-theory on local $G_2$ spaces

Kyle Hayden

This paper studies properly embedded surfaces in the 4-ball that are exotically knotted (i.e., topologically but not smoothly isotopic), and leverages this local phenomenon to study surfaces in larger 4-manifolds. The main results provide a new construction of exotically knotted surfaces, including exotic slice surfaces of all genera in the 4-ball and exotic

Vasileios Balos, Genaro Bierhance, Martin Wolf, Mohsen Sajadi

Rotation of the plane of the polarization of light in the presence of a magnetic-field, known as the Faraday rotation, is a consequence of the electromagnetic nature of light and has been utilized in many optical devices. Current efforts aim to realize the ultrafast Faraday rotation on a sub-picosecond time scale. Thereby, the Faraday medium should allow an

Sven Krippendorf, Marc Syvaeri

Identifying symmetries in data sets is generally difficult, but knowledge about them is crucial for efficient data handling. Here we present a method how neural networks can be used to identify symmetries. We make extensive use of the structure in the embedding layer of the neural network which allows us to identify whether a symmetry is present and to ident

Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He

In this work, we present a new network design paradigm. Our goal is to help advance the understanding of network design and discover design principles that generalize across settings. Instead of focusing on designing individual network instances, we design network design spaces that parametrize populations of networks. The overall process is analogous to cla

Wágner Badilla-Céspedes

In prime characteristic there are important invariants that allow us to measure singularities. For certain cases, it is known that they are rational numbers. In this article, we show this property for Stanley-Reisner rings in several cases.

Pieter Libin, Arno Moonens, Timothy Verstraeten, Fabian Perez-Sanjines

Epidemics of infectious diseases are an important threat to public health and global economies. Yet, the development of prevention strategies remains a challenging process, as epidemics are non-linear and complex processes. For this reason, we investigate a deep reinforcement learning approach to automatically learn prevention strategies in the context of pa

Monireh Mohebbi Moghaddam, Mohammad Hossein Manshaei, Mehdi Naderi Soorki, Walid Saad

Cooperative cloud providers in the form of cloud federations can potentially reduce their energy costs by exploiting electricity price fluctuations across different locations. In this environment, on the one hand, the electricity price has a significant influence on the federations formed, and, thus, on the profit earned by the cloud providers, and on the ot

Fan Qin

Given any quantum cluster algebra arising from a quantum unipotent subgroup of symmetrizable Kac-Moody type, we verify the quantization conjecture in full generality that the quantum cluster monomials are contained in the dual canonical basis after rescaling.

Nicholas Loutrel

Recently, we developed effective fly-by (EFB) waveforms designed to model the burst of gravitational radiation from highly eccentric binaries. We here present a faster to evaluate frequency domain EFB waveform. The waveform is constructed through the use of asymptotic expansions of hypergeometric functions. Since the waveform is fully analytic, we study the

Tanguy Marchand, Quentin Henry, François Larrouturou, Sylvain Marsat

The mass-type quadrupole moment of inspiralling compact binaries (without spins) is computed at the fourth post-Newtonian (4PN) approximation of general relativity. The multipole moments are defined by matching between the field in the exterior zone of the matter system and the PN field in the near zone, following the multipolar-post-Minkowskian (MPM)-PN for

Chaim Even-Zohar

There is a well-studied correspondence by Jaclyn Anderson between partitions that avoid hooks of length s or t and certain binary strings of length s+t. Using this map, we prove that the total size of a random partition of this kind converges in law to Watson's U^2 distribution, as conjectured by Doron Zeilberger.

Ran Canetti, Ari Trachtenberg, Mayank Varia

Successful containment of the Coronavirus pandemic rests on the ability to quickly and reliably identify those who have been in close proximity to a contagious individual. Existing tools for doing so rely on the collection of exact location information of individuals over lengthy time periods, and combining this information with other personal information. T

Alireza Javaheri, Catarina Brites, Fernando Pereira, Joao Ascenso

Reliable quality assessment of decoded point cloud geometry is essential to evaluate the compression performance of emerging point cloud coding solutions and guarantee some target quality of experience. This paper proposes a novel point cloud geometry quality assessment metric based on a generalization of the Hausdorff distance. To achieve this goal, the so-

Sam Vente, Angelika Kimmig, Alun Preece, Federico Cerutti

Automated negotiation has been used in a variety of distributed settings, such as privacy in the Internet of Things (IoT) devices and power distribution in Smart Grids. The most common protocol under which these agents negotiate is the Alternating Offers Protocol (AOP). Under this protocol, agents cannot express any additional information to each other besid

Sajani Vithana, Karim Banawan, Sennur Ulukus

We investigate the problem of semantic private information retrieval (semantic PIR). In semantic PIR, a user retrieves a message out of $K$ independent messages stored in $N$ replicated and non-colluding databases without revealing the identity of the desired message to any individual database. The messages come with \emph{different semantics}, i.e., the mes

Kyosuke Adachi, Kyogo Kawaguchi

Motivated by the observations of intracellular phase separations and the wetting of cell membranes by protein droplets, we study the nonequilibrium surface wetting by Monte Carlo simulations of a lattice gas model involving particle creation. We find that, even when complete wetting should occur in equilibrium, the fast creation of particles can hinder the s