June 2020 arXiv papers — page 24

Kieran Leschinski, João Alves

The initial mass function (IMF) is an important, yet enigmatic aspect of the star formation process. The two major open questions regarding the IMF are: is the IMF constant regardless of environment? Is the IMF a universal property of star formation? The next generation of extremely large telescopes will allow us to observe further, fainter and more compact

Rohini Ramadas

The moduli space $\overline{\mathcal{M}}_{0,n}$ carries a codimension-$d$ cycle class $κ_{d}$. We consider the subspace $\mathcal{K}^{d}_{n}$ of $A^d(\overline{\mathcal{M}}_{0,n},\mathbb{Q})$ spanned by pullbacks of $κ_d$ via forgetful maps. We find a permutation basis for $\mathcal{K}^{d}_{n}$, and describe its annihilator under the intersection pairing in

R. Kraft, M. -H. Liu, P. B. Selvasundaram, S. -C. Chen

We consider graphene superlattice miniband fermions probed by electronic interferometry in magneto-transport experiments. By decoding the observed Fabry-Pérot interference patterns together with our corresponding quantum transport simulations, we find that the Dirac quasiparticles originating from the superlattice minibands do not undergo conventional cyclot

J. Roquette, S. H. P. Alencar, J. Bouvier, M. G. Guarcello

We present the results of a J, H, and K photometric variability survey of the central 0.78 square degrees of the young OB association Cygnus OB2. We used data observed with the Wide-Field CAMera at the United Kingdom Infrared Telescope in 2007 (spanning 217 days) to investigate the light curves of 5083 low mass candidate members in the association and explor

Farnaz Niroui, Mayuran Saravanapavanantham, Jinchi Han, Jatin J. Patil

Molecules with versatile functionalities and well-defined structures, can serve as building blocks for extreme nanoscale devices. This requires their precise integration into functional heterojunctions, most commonly in the form of metal-molecule-metal architectures. Structural damage and nonuniformities caused by current fabrication techniques, however, lim

A. Catalano, A. Bideaud, O. Bourrion, M. Calvo

We report the design, fabrication and testing of Lumped Element Kinetic Inductance Detectors (LEKID) showing performance in line with the requirements of the next generation space telescopes operating in the spectral range from 80 to 600 GHz. This range is of particular interest for Cosmic Microwave Background (CMB) studies. For this purpose we have designed

A. I. Korolkov, A. V. Shanin, K. S. Kniazeva

A thin two-layered waveguide is considered. The governing equations for this waveguide is a matrix Klein--Gordon equation of dimension~2. A formal solution of this system in the form of a double integral can be obtained by using Fourier transformation. Then, the double integral can be reduced to a single integral with the help of residue integration with res

Clément Luneau, Nicolas Macris

We consider rank-one symmetric tensor estimation when the tensor is corrupted by Gaussian noise and the spike forming the tensor is a structured signal coming from a generalized linear model. The latter is a mathematically tractable model of a non-trivial hidden lower-dimensional latent structure in a signal. We work in a large dimensional regime with fixed

Alex J. Chan, Ahmed M. Alaa, Zhaozhi Qian, Mihaela van der Schaar

Modern neural networks have proven to be powerful function approximators, providing state-of-the-art performance in a multitude of applications. They however fall short in their ability to quantify confidence in their predictions - this is crucial in high-stakes applications that involve critical decision-making. Bayesian neural networks (BNNs) aim at solvin

M. Broz, J. C. Cabanillas Noris, E. Calvo Villar, C. Duarte Galvan

Two modules of the AD detector have been studied with the test beam at the T10 facility at CERN. The AD detector is made of scintillator pads read out by wave-length shifters (WLS)coupled to clean fibres that carry the produced light to photo-multiplier tubes (PMTs). In ALICE the AD is used to trigger and study the physics of diffractive and ultra-peripheral

Jayant Joshi, Luc H. M. Rouppe van der Voort, Jaime de la Cruz Rodríguez

Ellerman Bomb-like brightenings of the hydrogen Balmer line wings in the quiet Sun (QSEBs) are a signature of the fundamental process of magnetic reconnection at the smallest observable scale in the solar lower atmosphere. We analyze high spatial resolution observations (0.1 arcsec) obtained with the Swedish 1-m Solar Telescope to explore signatures of QSEBs

Aleksander Figiel, Anne-Sophie Himmel, André Nichterlein, Rolf Niedermeier

Editing a graph into a disjoint union of clusters is a standard optimization task in graph-based data clustering. Here, complementing classic work where the clusters shall be cliques, we focus on clusters that shall be 2-clubs, that is, subgraphs of diameter two. This naturally leads to the two NP-hard problems 2-Club Cluster Editing (the allowed editing ope

Thomas Germer, Tobias Uelwer, Stefan Conrad, Stefan Harmeling

Alpha matting aims to estimate the translucency of an object in a given image. The resulting alpha matte describes pixel-wise to what amount foreground and background colors contribute to the color of the composite image. While most methods in literature focus on estimating the alpha matte, the process of estimating the foreground colors given the input imag

J. C. Birget

We show that the word problem of the Brin-Higman-Thompson group $n G_{k,1}$ is {\sf coNP}-complete for all $n \ge 2$ and all $k \ge 2$. For this we prove that $n G_{k,1}$ is finitely generated, and that $n G_{k,1}$ contains a subgroup of $2 G_{2,1}$ that can represent bijective circuits. We also show that for all $n \ge 1$ and $k \ge 2$: \ If $\,K = 1 + (k-1

Pol Ribes-Pleguezuelo, Fanny Keller, Matteo Taccola

Small satellite platforms with high performance avionics are becoming more affordable. So far, with a few exceptions, small satellites have been mainly dedicated to earth observation. However, astronomy is a fascinating field with a history of large missions and a future of promising large mission candidates. This prompts many questions; can the recent affor

Abbey Bourdon, David R. Gill, Jeremy Rouse, Lori D. Watson

Let $C$ be a curve defined over a number field $k$. We say a closed point $x\in C$ of degree $d$ is isolated if it does not belong to an infinite family of degree $d$ points parametrized by the projective line or a positive rank abelian subvariety of the curve's Jacobian. Building on work of Bourdon, Ejder, Liu, Odumodu, and Viray, we characterize ellipt

Hagen Echzell, Tobias Friedrich, Pascal Lenzner, Anna Melnichenko

Network Creation Games(NCGs) model the creation of decentralized communication networks like the Internet. In such games strategic agents corresponding to network nodes selfishly decide with whom to connect to optimize some objective function. Past research intensively analyzed models where the agents strive for a central position in the network. This models

Annika Johansson, Börge Göbel, Jürgen Henk, Manuel Bibes

The Edelstein effect provides the purely electrical generation and control of a homogeneous magnetization in primarily nonmagnetic materials with broken inversion symmetry. Usually, only the spin density response to an external electric field is discussed. Here, we report on the electrically induced magnetization containing spin as well as orbital contributi

Andres Cotorruelo, Ilya Kolmanovsky, Daniel R. Ramírez, Daniel Limon

The reduction of constraints to obtain minimal representations of sets is a very common problem in many engineering applications. While well-established methodologies exist for the case of linear constraints, the problem of how to detect redundant non-linear constraints is an open problem. In this paper we present a novel methodology based on Sum of Squares

Kai Guther, Robert J. Anderson, Nick S. Blunt, Nikolay A. Bogdanov

We present NECI, a state-of-the-art implementation of the Full Configuration Interaction Quantum Monte Carlo algorithm, a method based on a stochastic application of the Hamiltonian matrix on a sparse sampling of the wave function. The program utilizes a very powerful parallelization and scales efficiently to more than 24000 CPU cores. In this paper, we desc

Melissa Lee

Let $V$ be a finite-dimensional vector space over a finite field, and suppose $G \leq Γ\mathrm{L}(V)$ is a group with a unique subnormal quasisimple subgroup $E(G)$ that is absolutely irreducible on $V$. A base for $G$ is a set of vectors $B\subseteq V$ with pointwise stabiliser $G_B=1$. If $G$ has a base of size 1, we say that it has a regular orbit on $V$.

B. Boldizsár, T. Kovács, J. Vanyó

The equations of motion of planar elliptic restricted three body problem are transformed to four decoupled Hill&#39;s equations. By using the Floquet theorem analytic solution to the oscillator equations with time dependent periodic coefficients are presented. We show that the new analytic approach is valid for system parameters $0 < e \leq 0.05$ and $0 < μ\

Luisa Arrabito, Konrad Bernlöhr, Johan Bregeon, Matthieu Carrère

COsmic Ray SImulations for KAscade) is a program for detailed simulation of extensive air showers initiated by high energy cosmic ray particles in the atmosphere, and is used today by almost all the major instruments that aim at measuring primary and secondary cosmic rays on the ground. The Cherenkov Telescope Array (CTA), currently under construction, is th

Manfred Jaeger, Giorgio Bacci, Giovanni Bacci, Kim Guldstrand Larsen

Euclidean Markov decision processes are a powerful tool for modeling control problems under uncertainty over continuous domains. Finite state imprecise, Markov decision processes can be used to approximate the behavior of these infinite models. In this paper we address two questions: first, we investigate what kind of approximation guarantees are obtained wh

Geneviève Bélanger, Alexander Pukhov, Carlos Yaguna, Oscar Zapata

Scenarios for multi-component scalar dark matter based on a single $Z_N$ ($N\geq 4$) symmetry are simple and well-motivated. In this paper we investigate, for the first time, the phenomenology of the $Z_5$ model for two-component dark matter. This model, which can be seen as an extension of the well-known singlet scalar model, features two complex scalar fie

Leonid B. Sokolinsky, Irina M. Sokolinskaya

In the development of industrial digital twins, the optimization problem of technological and business processes often arises. In many cases, this problem can be reduced to a large-scale linear programming (LP) problem. The article is devoted to the new method for solving large-scale LP problems. This method is called the &#34;apex-method&#34;. The apex-meth

R. K. Zamanov, V. D. Marchev, K. A. Stoyanov

Using diffuse interstellar bands (DIBs) at 5780 A, 5797 A and 6613 A, visible in the high resolution spectra, and measuring their equivalent widths, we estimate the interstellar extinction toward seven symbiotic stars. We find $E_{B-V}$= $1.28 \pm 0.10$ for AS 289, $E_{B-V}$= $1.55 \pm 0.10$ for BI Cru, $E_{B-V}$= $0.63 \pm 0.10$ for HD330036, $E_{B-V}$= $0.

Michele Curatolo, Paola Nardinocchi, Luciano Teresi

Liquid migration in active soft solids is a very common phenomenon in Nature at different scales: from cells to leaves. It can be caused by mechanical as well as chemical actions. The work focuses on the migration of liquid provoked by remodeling processes in an active impermeable gel sphere. Within this context, we present a consistent mathematical theory c

Dieter Mitsche, Mathew D. Penrose

In the random geometric graph $G(n,r_n)$, $n$ vertices are placed randomly in Euclidean $d$-space and edges are added between any pair of vertices distant at most $r_n$ from each other. We establish strong laws of large numbers (LLNs) for a large class of graph parameters, evaluated for $G(n,r_n)$ in the thermodynamic limit with $nr_n^d =$ const., and also i

V. M. Pereira, C. N. Wu, C. -A. Knight, A. Choa

Relying on the magnetism induced by the proximity effect in heterostructures of topological insulators and magnetic insulators is one of the promising routes to achieve the quantum anomalous Hall effect. Here we investigate heterostructures of Bi$_2$Te$_3$ and Fe$_3$O$_4$. By growing two different types of heterostructures by molecular beam epitaxy, Fe$_3$O$

Jian-Jia Weng, Fady Alajaji, Tamás Linder

We propose an adaptive lossy joint source-channel coding (JSCC) scheme for sending correlated sources over two-terminal discrete-memoryless two-way channels (DM-TWCs). The main idea is to couple the independent operations of the terminals via an adaptive coding mechanism, which can mitigate cross-interference resulting from simultaneous channel transmissions

Jiemin Li, Abhishek Nag, Jonathan Pelliciari, Hannah Robarts

Charge density waves (CDWs) are ubiquitous in under-doped cuprate superconductors. As a modulation of the valence electron density, CDWs in hole-doped cuprates possess both Cu-3d and O-2p orbital character owing to the strong hybridization of these orbitals near the Fermi level. Here, we investigate under-doped Bi$_2$Sr$_{1.4}$La$_{0.6}$CuO$_{6+δ}$ using res

Anatoly Klypin, Vivian Poulin, Francisco Prada, Joel Primack

LCDM cosmological models with Early Dark Energy (EDE) have been proposed to resolve tensions between the Hubble constant H0 = 100h km/s/Mpc measured locally, giving h ~ 0.73, and H0 deduced from Planck cosmic microwave background (CMB) and other early universe measurements plus LCDM, giving h ~ 0.67. EDE models do this by adding a scalar field that temporari

Claudia Backes, Davide Campi, Beata M. Szydlowska, Kevin Synnatschke

Liquid phase exfoliation is a commonly used method to produce 2D nanosheets from a range of layered crystals. However, such nanosheets display broad size and thickness distributions and correlations between area and thickness, issues that limit nanosheet application potential. To understand the factors controlling the exfoliation process, we have liquid-exfo

Mieke Bouwhuis, Keith W. Bannister, Jean-Pierre Macquart, R. M. Shannon

We report the results of the rapid follow-up observations of gamma-ray bursts (GRBs) detected by the Fermi satellite to search for associated fast radio bursts. The observations were conducted with the Australian Square Kilometre Array Pathfinder at frequencies from 1.2-1.4 GHz. A set of 20 bursts, of which four were short GRBs, were followed up with a typic

Marco Pezzella, Krystel El Hage, Michiel J. M. Niesen, Sucheol Shin

The water dynamics, as characterized by the local hydrophobicity (LH), is investigated for tetrameric hemoglobin and dimeric melittin. For the T0 to R0 transition in Hb it is found that LH provides additional molecular-level insight into the Perutz mechanism, i.e., the breaking and formation of salt bridges at the alpha1 / beta2 and alpha2 / beta1 interface

Andrea Skolik, Jarrod R. McClean, Masoud Mohseni, Patrick van der Smagt

With the increased focus on quantum circuit learning for near-term applications on quantum devices, in conjunction with unique challenges presented by cost function landscapes of parametrized quantum circuits, strategies for effective training are becoming increasingly important. In order to ameliorate some of these challenges, we investigate a layerwise lea

Jiajin Li, Anthony Man-Cho So, Wing-Kin Ma

Many contemporary applications in signal processing and machine learning give rise to structured non-convex non-smooth optimization problems that can often be tackled by simple iterative methods quite effectively. One of the keys to understanding such a phenomenon---and, in fact, one of the very difficult conundrums even for experts---lie in the study of &#3

Aleksandr V. Mosenkov, Anton A. Smirnov, Olga K. Sil&#39;chenko, R. Michael Rich

Tilted and warped discs inside tilted dark matter haloes are predicted from numerical and semi-analytical studies. In this paper, we use deep imaging to demonstrate the likely existence of tilted outer structures in real galaxies. We consider two SB0 edge-on galaxies, NGC4469 and NGC4452, which exhibit apparent tilted outer discs with respect to the inner st

Martin Jørgensen, Marc Peter Deisenroth, Hugh Salimbeni

We present a Bayesian non-parametric way of inferring stochastic differential equations for both regression tasks and continuous-time dynamical modelling. The work has high emphasis on the stochastic part of the differential equation, also known as the diffusion, and modelling it by means of Wishart processes. Further, we present a semi-parametric approach t

Marcin Białas, Marcin Michał Mirończuk, Jacek Mańdziuk

This study proposes a novel biologically plausible mechanism for generating low-dimensional spike-based text representation. First, we demonstrate how to transform documents into series of spikes spike trains which are subsequently used as input in the training process of a spiking neural network (SNN). The network is composed of biologically plausible eleme

Manana Kachakhidze, Nino Kachakhidze-Murphy, Badri Kvitia, Giorgi Khazaradze

In the presented paper we will focus on the optimal option of network arrangemnet of the VLF / LF EM radiation before the earthquakes. The paper discusses the new possibility of arrangement of VLF / LF network based on certain physical considerations, which is relatively simplified and completely different from the existing networks. It will increase to the

Fernando Farroni, Luigi Greco, Gioconda Moscariello, Gabriella Zecca

We consider a family of quasilinear second order elliptic differential operators which are not coercive and are defined by functions in Marcinkiewicz spaces. We prove the existence of a solution to the corresponding Dirichlet problem. The associated obstacle problem is also solved. Finally, we show higher integrability of a solution to the Dirichlet problem

Kevissen Sellapillay, Alberto D. Verga

We introduce a model of a quantum walk on a graph in which a particle jumps between neighboring nodes and interacts with independent spins sitting on the edges. Entanglement propagates with the walker. We apply this model to the case of a one dimensional lattice, to investigate its magnetic and entanglement properties. In the continuum limit, we recover a La

Fan Zuo, Jingxing Wang, Jingqin Gao, Kaan Ozbay

The COVID-19 outbreak has dramatically changed travel behavior in affected cities. The C2SMART research team has been investigating the impact of COVID-19 on mobility and sociability. New York City (NYC) and Seattle, two of the cities most affected by COVID-19 in the U.S. were included in our initial study. An all-in-one dashboard with data mining and cloud

Ludwig A. Hothorn, Frank Schaarschmidt

The Armitage test for linear trend in proportions can be modified using the multiple marginal model approach for three regression models with arithmetic, ordinal and logarithmic dose scores simultaneously, to be powerful against a wide range of possible dose response relationships. Moreover, it can be used for particular designs in the generalized linear (mi

D. Barnes, J. A. Davies, R. A. Harrison, J. P. Byrne

We present an analysis of coronal mass ejections (CMEs) observed by the Heliospheric Imagers (HIs) on board NASA&#39;s Solar Terrestrial Relations Observatory (STEREO) spacecraft. Between August 2008 and April 2014 we identify 273 CMEs that are observed simultaneously, by the HIs on both spacecraft. For each CME, we track the observed leading edge, as a func

Sonja Gorjanc, Ema Jurkin

In this paper we define $q$-spherical surfaces as the surfaces that contain the absolute conic of the Euclidean space as a $q-$fold curve. Particular attention is paid to the surfaces with singular points of the highest order. Two classes of such surfaces, with one and two $n-$fold points, are discussed in detail. We study their properties, give their algebr

Yanpeng Qi, Tianping Ying, Xianxin Wu, Zhuoya Dong

Vacancies are prevalent and versatile in solid-state physics and materials science. The role of vacancies in strongly correlated materials, however, remains uncultivated until now. Here, we report the discovery of an unprecedented vacancy state forming an extended buckled-honeycomb-vacancy (BHV) ordering in Ir$_{16}$Sb$_{18}$. Superconductivity emerges by su

Aleksandrs Belovs, Arturo Castellanos, François Le Gall, Guillaume Malod

The classical communication complexity of testing closeness of discrete distributions has recently been studied by Andoni, Malkin and Nosatzki (ICALP&#39;19). In this problem, two players each receive $t$ samples from one distribution over $[n]$, and the goal is to decide whether their two distributions are equal, or are $ε$-far apart in the $l_1$-distance.

T. J. Galvin, M. Huynh, R. P. Norris, X. R. Wang

We develop a new analysis approach towards identifying related radio components and their corresponding infrared host galaxy based on unsupervised machine learning methods. By exploiting PINK, a self-organising map algorithm, we are able to associate radio and infrared sources without the a priori requirement of training labels. We present an example of this

Zihao Yan, Ruizhen Hu, Xingguang Yan, Luanmin Chen

We introduce RPM-Net, a deep learning-based approach which simultaneously infers movable parts and hallucinates their motions from a single, un-segmented, and possibly partial, 3D point cloud shape. RPM-Net is a novel Recurrent Neural Network (RNN), composed of an encoder-decoder pair with interleaved Long Short-Term Memory (LSTM) components, which together

Will Abramson, Nicole E. van Deursen, William J Buchanan

A substantial administrative burden is placed on healthcare professionals as they manage and progress through their careers. Identity verification, pre-employment screening and appraisals: the bureaucracy associated with each of these processes takes precious time out of a healthcare professional&#39;s day. Time that could have been spent focused on patient

Feng Liu, Xiaoxong Zhang, Fang Wan, Xiangyang Ji

We present Domain Contrast (DC), a simple yet effective approach inspired by contrastive learning for training domain adaptive detectors. DC is deduced from the error bound minimization perspective of a transferred model, and is implemented with cross-domain contrast loss which is plug-and-play. By minimizing cross-domain contrast loss, DC guarantees the tra

Ralph Brinks, Annika Hoyer

We analyse the infection-age-dependent SIR model from a numerical point of view. First, we present an algorithm for calculating the solution the infection-age-structured SIR model without demography of the background host. Second, we examine how and under which conditions, the conventional SIR model (without infection-age) serves as a practical approximation

David Kügler, Marc Uecker, Arjan Kuijper, Anirban Mukhopadhyay

Despite recent successes, the advances in Deep Learning have not yet been fully translated to Computer Assisted Intervention (CAI) problems such as pose estimation of surgical instruments. Currently, neural architectures for classification and segmentation tasks are adopted ignoring significant discrepancies between CAI and these tasks. We propose an automat

Leonidas Mouchliadis, Sotiris Psilodimitrakopoulos, George Miltos Maragkakis, Ioanna Demeridou

Degenerate minima in momentum space - valleys - provide an additional degree of freedom that can be used for information transport and storage. Notably, such minima naturally exist in the band structure of transition metal dichalcogenides (TMDs). When these atomically thin crystals interact with intense laser light, the second harmonic generated (SHG) field

Mohammad A. A. K. Jalwana, Naveed Akhtar, Mohammed Bennamoun, Ajmal Mian

Deep learning has demonstrated state-of-the-art performance for a variety of challenging computer vision tasks. On one hand, this has enabled deep visual models to pave the way for a plethora of critical applications like disease prognostics and smart surveillance. On the other, deep learning has also been found vulnerable to adversarial attacks, which calls

D. Yvon, V. Sharyy, M. Follin, J-P Bard

We describe the concept of a new gamma ray scintronic detector targeting a time resolution of the order of 25 ps FWHM, with millimetric volume reconstruction and high detection efficiency. Its design consists of a monolithic large PbWO4 scintillating crystal with an efficient photocathode directly deposited on it. With an index of refraction higher for the p

Tianyu Zhang, Florent Pled, Christophe Desceliers

The aim of this work is to efficiently and robustly solve the statistical inverse problem related to the identification of the elastic properties at both macroscopic and mesoscopic scales of heterogeneous anisotropic materials with a complex microstructure that usually cannot be properly described in terms of their mechanical constituents at microscale. With

Filippo Attivissimo, Nicola Giaquinto, Marco Scarpetta, Maurizio Spadavecchia

Identity documents automatic reading and verification is an appealing technology for nowadays service industry, since this task is still mostly performed manually, leading to waste of economic and time resources. In this paper the prototype of a novel automatic reading system of identity documents is presented. The system has been thought to extract data of

Urs Langenegger

Results on $B \to μ^+ μ^-$ decays with the CMS experiment are reported, using 61 fb$^{-1}$ of data recorded during LHC Run 1 and 2016. With an improved muon identification algorithm and refined unbinned maximum likelihood fitting methods, the decay $B_s^0 \to μ^+ μ^-$ is observed with a significance of 5.6 standard deviations. Its branching fraction is measu

Vincent Mancois, Julien Barré, Chang Chi Kwong, Alain Olivetti

In two dimensions, a system of self-gravitating particles collapses and forms a singularity in finite time below a critical temperature $T_c$. We investigate experimentally a quasi two-dimensional cloud of cold neutral atoms in interaction with two pairs of perpendicular counter-propagating quasi-resonant laser beams, in order to look for a signature of this

Mitchell Cavanagh, Kenji Bekki

Stellar bars are a common morphological feature of spiral galaxies. While it is known that they can form in isolation, or be induced tidally, few studies have explored the production of stellar bars in galaxy merging. We look to investigate bar formation in galaxy merging using methods from deep learning to analyse our N-body simulations. The primary aim is

Kijti Rodtes

In this article, we prove a class of normal dilation matrices affirming the Marcus-de Oliveira conjecture.

Masaaki Takada, Hironori Fujisawa

Machine learning algorithms typically require abundant data under a stationary environment. However, environments are nonstationary in many real-world applications. Critical issues lie in how to effectively adapt models under an ever-changing environment. We propose a method for transferring knowledge from a source domain to a target domain via $\ell_1$ regu

Gianluca Gorni, Gaetano Zampieri

A simple general theorem is used as a tool that generates nonlocal constants of motion for Lagrangian systems. We review some cases where the constants that we find are useful in the study of the systems: the homogeneous potentials of degree~$-2$, the mechanical systems with viscous fluid resistance and the conservative and dissipative Maxwell-Bloch equation

Jonas D. Ziegler, Jonas Zipfel, Barbara Meisinger, Matan Menahem

Two-dimensional hybrid perovskites are currently in the spotlight of condensed matter and nanotechnology research due to their intriguing optoelectronic and vibrational properties with emerging potential for light-harvesting and -emitting applications. While it is known that these natural quantum wells host tightly bound excitons, the mobilities of these fun

Jean-Bernard Chatelain, Kirsten Ralf

With non-controllable auto-regressive shocks, the welfare of Ramsey optimal policy is the solution of a single Riccati equation of a linear quadratic regulator. The existing theory by Hansen and Sargent (2007) refers to an additional Sylvester equation but miss another equation for computing the block matrix weighting the square of non-controllable variables

D. M. Rodkin, Yu. M. Tchuvil&#39;sky

A new convenient method for precise theoretical calculations of quantities of traditional theory of nuclear reactions such as widths of resonances (including sub-threshold), and asymptotic normalization coefficients is proposed. This method may be considered as a step on the road to full theoretical ab initio description of light nuclei spectroscopic data. A

Benjamin Heymann, Michel de Lara, Jean-Philippe Chancelier

We state and prove Kuhn&#39;s equivalence theorem for a new representation of games, the intrinsic form. First, we introduce games in intrinsic form where information is represented by $σ$-fields over a product set. For this purpose, we adapt to games the intrinsic representation that Witsenhausen introduced in control theory. Those intrinsic games do not re

Masahiro Takahashi, Alessandro Moro, Yonghoon Ji, Kazunori Umeda

This paper aims at constructing a light-weight object detector that inputs a depth and a color image from a stereo camera. Specifically, by extending the network architecture of YOLOv3 to 3D in the middle, it is possible to output in the depth direction. In addition, Intersection over Uninon (IoU) in 3D space is introduced to confirm the accuracy of region e

Lei Shi, Qingchen Liu, Jinliang Shao, Yuhua Cheng

In this paper, we study the problem of localizing the sensors&#39; positions in presence of denial-of-service (DoS) attacks. We consider a general attack model, in which the attacker action is only constrained through the frequency and duration of DoS attacks. We propose a distributed iterative localization algorithm with an abandonment strategy based on the

Sandra Keiper

In this paper we study the reconstruction of binary sparse signals from partial random circulant measurements. We show that the reconstruction via the least-squares algorithm is as good as the reconstruction via the usually used program basis pursuit. We further show that we need as many measurements to recover an $s$-sparse signal $x_0\in\mathbb{R}^N$ as we

Binzheng Zhang, Peter A. Delamere, Zhonghua Yao, Bertrand Bonfond

Jupiter&#39;s bright persistent polar aurora and Earth&#39;s dark polar region indicate that the planets&#39; magnetospheric topologies are very different. High-resolution global simulations show that the reconnection rate at the interface between the interplanetary and jovian magnetic fields is too slow to generate a magnetically open, Earth-like polar cap

David R. Baños, Marc Lagunas-Merino, Salvador Ortiz-Latorre

One of the risks derived from selling long term policies that any insurance company has, arises from interest rates. In this paper we consider a general class of stochastic volatility models written in forward variance form. We also deal with stochastic interest rates to obtain the risk-free price for unit-linked life insurance contracts, as well as providin

Taiji Marugame

A global secondary CR invariant is defined as the integral of a pseudo-hermitian invariant which is independent of a choice of pseudo-Einstein contact form. We prove that any global secondary CR invariant on CR five-manifolds is a linear combination of the total $Q&#39;$-curvature, the total $\mathcal{I}&#39;$-curvature, and the integral of a local CR invari

Zhao Ren, Sungkyu Jung, Xingye Qiao

Set classification aims to classify a set of observations as a whole, as opposed to classifying individual observations separately. To formally understand the unfamiliar concept of binary set classification, we first investigate the optimal decision rule under the normal distribution, which utilizes the empirical covariance of the set to be classified. We sh

Ming Ding, David Lopez-Perez, Ruiqi Xue, Athanasios V. Vasilakos

Motivated by the promising benefits of dynamic Time Division Duplex (TDD), in this paper, we use a unified framework to investigate both the technical issues of applying dynamic TDD in homogeneous small cell networks (HomSCNs), and the feasibility of introducing dynamic TDD into heterogeneous networks (HetNets). First, HomSCNs are analyzed, and a small cell

Oksana Banna, Filipp Buryak, Yuliya Mishura

We find the best approximation of the fractional Brownian motion with the Hurst index $H\in (0,1/2)$ by Gaussian martingales of the form $\int _0^ts^γdW_s$, where $W$ is a Wiener process, $γ>0$.

Takumi Saegusa, Shonosuke Sugasawa, Partha Lahiri

The multivariate Fay-Herriot model is quite effective in combining information through correlations among small area survey estimates of related variables or historical survey estimates of the same variable or both. Though the literature on small area estimation is already very rich, construction of second-order efficient confidence intervals from multivaria

Mohamed Marzougue, Yaya Sagna

In this paper, a solution is given to reflected backward doubly stochastic differential equations when the barrier is not necessarily right-continuous, and the noise is driven by two independent Brownian motions and an independent Poisson random measure. The existence and uniqueness of the solution is shown, firstly when the coefficients are stochastic Lipsc

Alexander Kukush, Ivan Senko

A multivariate errors-in-variables (EIV) model with an intercept term, and a polynomial EIV model are considered. Focus is made on a structural homoskedastic case, where vectors of covariates are i.i.d. and measurement errors are i.i.d. as well. The covariates contaminated with errors are normally distributed and the corresponding classical errors are also a

Alexander A. Gushchin

A single jump filtration $({\mathscr{F}}_t)_{t\in \mathbb{R}_+}$ generated by a random variable $γ$ with values in $\overline{\mathbb{R}}_+$ on a probability space $(Ω,{\mathscr{F}},\mathsf{P})$ is defined as follows: a set $A\in {\mathscr{F}}$ belongs to ${\mathscr{F}}_t$ if $A\cap \{γ>t\}$ is either $\varnothing$ or $\{γ>t\}$. A process $M$ is proved to be

Markus Hess

A new multi-factor short rate model is presented which is bounded from below by a real-valued function of time. The mean-reverting short rate process is modeled by a sum of pure-jump Ornstein--Uhlenbeck processes such that the related bond prices possess affine representations. Also the dynamics of the associated instantaneous forward rate is provided and a

Yu Tian, Gabriel Maicas, Leonardo Zorron Cheng Tao Pu, Rajvinder Singh

Anomaly detection methods generally target the learning of a normal image distribution (i.e., inliers showing healthy cases) and during testing, samples relatively far from the learned distribution are classified as anomalies (i.e., outliers showing disease cases). These approaches tend to be sensitive to outliers that lie relatively close to inliers (e.g.,

Sebastian Pokutta

In this overview article we will consider the deliberate restarting of algorithms, a meta technique, in order to improve the algorithm&#39;s performance, e.g., convergence rates or approximation guarantees. One of the major advantages is that restarts are relatively black box, not requiring any (significant) changes to the base algorithm that is restarted or

Riku Anegawa, Masayoshi Aritsugi

Text detection enables us to extract rich information from images. In this paper, we focus on how to generate bounding boxes that are appropriate to grasp text areas on books to help implement automatic text detection. We attempt not to improve a learning-based model by training it with an enough amount of data in the target domain but to leverage it, which

Eric J. Hall, Søren Taverniers, Markos A. Katsoulakis, Daniel M. Tartakovsky

We introduce the concept of a Graph-Informed Neural Network (GINN), a hybrid approach combining deep learning with probabilistic graphical models (PGMs) that acts as a surrogate for physics-based representations of multiscale and multiphysics systems. GINNs address the twin challenges of removing intrinsic computational bottlenecks in physics-based models an

Masahiro Kawasaki, Kazunori Kohri, Takeo Moroi, Kai Murai

We consider the effects of the injections of energetic photon and electron (or positron) on the big-bang nucleosynthesis. We study the photodissociation of light elements in the early Universe paying particular attention to the case that the injection energy is sub-GeV and derive upper bounds on the primordial abundances of the massive decaying particle as a

Tung D. Nguyen, Kathryn E. Kasmarik, Hussein A. Abbass

It is well-known that information loss can occur in the classic and simple Q-learning algorithm. Entropy-based policy search methods were introduced to replace Q-learning and to design algorithms that are more robust against information loss. We conjecture that the reduction in performance during prolonged training sessions of Q-learning is caused by a loss

Francisco Romero, Benjamin Braun, David Cheriton

Main memory database systems aim to provide users with low latency and high throughput access to data. Most data resides in secondary storage, which is limited by the access speed of the technology. For hot content, data resides in DRAM, which has become increasingly expensive as datasets grow in size and access demand. With the emergence of low-latency stor

Cheng Chang, Zhixiong Chen

We identified three most challenging points related to diverse, equitable, and inclusive (DEI) issues. First, the majority of our students entering the College lack the math skills essential to success in Calculus, as basic as College Algebra, some others have a multi-year gap after graduating high school. Almost all but a few STEM students must start from C

Zhen Zhang, Simona Ispas, Walter Kob

Using molecular dynamics simulations we investigate the dependence of the structural and vibrational properties of the surfaces of sodo-silicate glasses on the sodium content as well as the nature of the surface. Two types of glass surfaces are considered: A melt-formed surface (MS) in which a liquid with a free surface has been cooled down into the glass ph

Emilio Angelina, Sebastian Andujar, Oscar Parravicini, Daniel Enriz

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is the strain of coronavirus that causes coronavirus disease 2019 (COVID-19), the respiratory illness responsible for the COVID-19 pandemic. Currently there is no known vaccine or specific antiviral treatment for COVID-19 and so, there is an urgent need for expedite discovery of new therapeutics to

Tristan Buckmaster, Steve Shkoller, Vlad Vicol

We analyze the shock formation process for the 3d non-isentropic Euler equations with the ideal gas law, in which sounds waves interact with entropy waves to produce vorticity. Building on our theory for isentropic flows in [3,4], we give a constructive proof of shock formation from smooth initial data. Specifically, we prove that there exist smooth solution

Jangwon Ju, Daejun Kim, Kyoungmin Kim, Mingyu Kim

A (positive definite and integral) quadratic form is said to be $\textit{prime-universal}$ if it represents all primes. Recently, Doyle and Williams in [2] classified all prime-universal diagonal ternary quadratic forms, and all prime-universal diagonal quaternary quadratic forms under two conjectures proposed by themselves. In this article, we classify all

Gurpriya Kaur Bhatia, Shubham Gupta, Alpana Dubey, Ponnurangam Kumaraguru

Crowdsourcing is a process wherein an individual or an organisation utilizes the talent pool present over the Internet to accomplish their task. The existing crowdsourcing platforms and their reputation computation are centralised and hence prone to various attacks or malicious manipulation of the data by the central entity. A few distributed crowdsourcing p

Tuo Zhao, Han Liu, Kathryn Roeder, John Lafferty

We describe an R package named huge which provides easy-to-use functions for estimating high dimensional undirected graphs from data. This package implements recent results in the literature, including Friedman et al. (2007), Liu et al. (2009, 2012) and Liu et al. (2010). Compared with the existing graph estimation package glasso, the huge package provides e

In S. Jeon, Deokyoung Kang, Suk I. Yoo

In this paper, we solve blind image deconvolution problem that is to remove blurs form a signal degraded image without any knowledge of the blur kernel. Since the problem is ill-posed, an image prior plays a significant role in accurate blind deconvolution. Traditional image prior assumes coefficients in filtered domains are sparse. However, it is assumed he