December 2020 arXiv papers — page 41

J. Baumeister, A. De Cezaro, A. Leitao

We investigate iterated Tikhonov methods coupled with a Kaczmarz strategy for obtaining stable solutions of nonlinear systems of ill-posed operator equations. We show that the proposed method is a convergent regularization method. In the case of noisy data we propose a modification, the so called loping iterated Tikhonov-Kaczmarz method, where a sequence of

Geert R. Hoogeboom, Geert-Jan N. Sint Nicolaas, Andreas Alexander, Olga Kuschel

In spin transport experiments with spin currents propagating through antiferromagnetic (AFM) material, the antiferromagnet is treated as a mainly passive spin conductor not generating nor adding any spin current to the system. The spin current transmissivity of the AFM NiO is affected by magnetic fluctuations, peaking at the N\'eel temperature and decreasing

Vladimir Temlyakov, Tino Ullrich

In this paper we present results on asymptotic characteristics of multivariate function classes in the uniform norm. Our main interest is the approximation of functions with mixed smoothness parameter not larger than $1/2$. Our focus will be on the behavior of the best $m$-term trigonometric approximation as well as the decay of Kolmogorov and entropy number

Daryus Chandra, Angela Sara Cacciapuoti, Marcello Caleffi, Lajos Hanzo

To realize the Quantum Internet, quantum communications require pre-shared entanglement among quantum nodes. However, both the generation and the distribution of the maximally-entangled quantum states are inherently contaminated by quantum decoherence. Conventionally, the quantum decoherence is mitigated by performing the consecutive steps of quantum entangl

Maria Papatsimouli, Lazaros Lazaridis, Konstantinos-Filippos Kollias, Ioannis Skordas

Sign Language is used to facilitate the communication between Deaf and non-Deaf people. It uses signs-words with basic structural elements such as handshape, parts of face, body or space, and the orientation of the fingers-palm. Sign Languages vary from people to people and from country to country and evolve as spoken languages. In the current study, an appl

J. P. Agnelli, A. De Cezaro, A. Leitao, M. Marques Alves

In this paper, we propose a level set regularization approach combined with a split strategy for the simultaneous identification of piecewise constant diffusion and absorption coefficients from a finite set of optical tomography data (Neumann-to-Dirichlet data). This problem is a high nonlinear inverse problem combining together the exponential and mildly il

K. Atazadeh

We consider the imbalance of matter and antimatter by using a gravitational baryogenesis mechanism in the background of Dvali-Gabadadze-Porrati (DGP) brane cosmology. By taking into account a flat Friedmann-Lemaitre-Robertson-Walker (FLRW) metric in the DGP brane model, we find that for a radiation dominated universe, $w = 1/3$, the ratio of baryon number de

Peter Lynch

Several continued fraction expansions for $e$ have been produced by an automated conjecture generator (ACG) called \emph{The Ramanujan Machine}. Some of these were already known, some have recently been proved and some remain unproven. While an ACG can produce interesting putative results, it gives very limited insight into their significance. In this paper,

Karl K. Brustad

The explicit solution to the Dirichlet problem for a class of mean value equations on the real line is derived. It shed some light on the behavior of solutions to general nonlocal elliptic equations.

Alessandro Rudi, Ulysse Marteau-Ferey, Francis Bach

We consider the global minimization of smooth functions based solely on function evaluations. Algorithms that achieve the optimal number of function evaluations for a given precision level typically rely on explicitly constructing an approximation of the function which is then minimized with algorithms that have exponential running-time complexity. In this p

D. Vale, Y. F. Niu, N. Paar

Spin-isospin transitions in nuclei away from the valley of stability are essential for the description of astrophysically relevant weak interaction processes. While they remain mainly beyond the reach of experiment, theoretical modeling provides important insight into their properties. In order to describe the spin-isospin response,vcthe proton-neutron relat

Johan Aronsson, Philip Lu, Daniel Strüber, Thorsten Berger

Conversational Artificial Intelligence (AI) systems have recently sky-rocketed in popularity and are now used in many applications, from car assistants to customer support. The development of conversational AI systems is supported by a large variety of software platforms, all with similar goals, but different focus points and functionalities. A systematic fo

Daniel Schöllhammer, Benjamin Marussig, Thomas-Peter Fries

Shell analysis is a well-established field, but achieving optimal higher-order convergence rates for such simulations is a difficult challenge. We present an isogeometric Kirchhoff-Love shell framework that treats every numerical aspect in a consistent higher-order accurate way. In particular, a single trimmed B-spline surface provides a sufficiently smooth

Chen Qin, Jinming Duan, Kerstin Hammernik, Jo Schlemper

Purpose: To introduce a novel deep learning based approach for fast and high-quality dynamic multi-coil MR reconstruction by learning a complementary time-frequency domain network that exploits spatio-temporal correlations simultaneously from complementary domains. Theory and Methods: Dynamic parallel MR image reconstruction is formulated as a multi-variable

Mariola Kłusek-Gawenda, Wolfgang Schäfer, Antoni Szczurek

We propose a new complete method, based on the Wigner distributions of photons, how to calculate differential distributions of dileptons created via photon-photon fusion in semicentral ($b<2R_A$) $AA$ collisions. The formalism is used to calculate different distributions of invariant mass, dilepton transverse momentum and acoplanarity for different regions o

Gabriela Kováčová, Birgit Rudloff, Igor Cialenco

The aim of this paper is to study the optimal investment problem by using coherent acceptability indices (CAIs) as a tool to measure the portfolio performance. We call this problem the acceptability maximization. First, we study the one-period (static) case, and propose a numerical algorithm that approximates the original problem by a sequence of risk minimi

Sumudu Samarakoon, Mehdi Bennis, Walid Saad, Merouane Debbah

Ultra-reliable communication (URC) is a key enabler for supporting immersive and mission-critical 5G applications. Meeting the strict reliability requirements of these applications is challenging due to the absence of accurate statistical models tailored to URC systems. In this letter, the wireless connectivity over dynamic channels is characterized via stat

Miguel A. N. Araújo, Pedro Ninhos, Pedro Ribeiro

It is shown that the presence of discrete symmetries in Floquet systems connected to metallic reservoirs imprints a definite parity on the charge and heat pumping as a function of the reservoir's chemical potential, $\mu$. In particular, when particle-hole symmetry (PHS) holds, the pumping of charge (heat) is an odd (even) function of $\mu$. Whereas, if only

Basabendu Barman, Amit Dutta Banik, Avik Paul

Recent pulsar timing data reported by the NANOGrav collaboration indicates the existence of a stochastic gravitational wave (GW) background at a frequency $f\sim 10^{-8}~\rm Hz$. We show that a dark sector consisting of a Standard Model (SM) gauge singlet fermion $\chi$ and a singlet scalar $\phi$, both charged under a $Z_4$ symmetry, is capable of generatin

Paul S. Barklem, Anish M. Amarsi, Jon Grumer, Gustav Eklund

Advances in merged-beams instruments have allowed experimental studies of the mutual neutralisation (MN) processes in collisions of both Li$^+$ and Na$^+$ ions with D$^-$ at energies below 1 eV. These experimental results place constraints on theoretical predictions of MN processes of Li$^+$ and Na$^+$ with H$^-$, important for non-LTE modelling of Li and Na

Anna Glazkova, Maksim Glazkov, Timofey Trifonov

The COVID-19 pandemic has had a huge impact on various areas of human life. Hence, the coronavirus pandemic and its consequences are being actively discussed on social media. However, not all social media posts are truthful. Many of them spread fake news that cause panic among readers, misinform people and thus exacerbate the effect of the pandemic. In this

Rafael Granero-Belinchón, Stefano Scrobogna

The motion of the free surface of an incompressible fluid is a very active research area. Most of these works examine the case of an inviscid fluid. However, in several practical applications, there are instances where the viscous damping needs to be considered. In this paper we derive and study a new asymptotic model for the motion of unidirectional viscous

Nofar Carmeli, Nikolaos Tziavelis, Wolfgang Gatterbauer, Benny Kimelfeld

We study the question of when we can provide direct access to the k-th answer to a Conjunctive Query (CQ) according to a specified order over the answers in time logarithmic in the size of the database, following a preprocessing step that constructs a data structure in time quasilinear in database size. Specifically, we embark on the challenge of identifying

ShengNan Zhang, Bo Xie, QuanSheng Wu, Jianpeng Liu

We formulate the chiral decomposition rules that govern the electronic structure of a broad family of twisted $N+M$ multilayer graphene configurations that combine arbitrary stacking order and a mutual twist. We show that at the magic angle in the chiral limit the low-energy bands of such systems are composed of chiral pseudospin doublets which are energetic

Jens Sonntag, Sven Reichardt, Bernd Beschoten, Christoph Stampfer

We explore the tunability of the phonon polarization in suspended uniaxially strained graphene by magneto-phonon resonances. The uniaxial strain lifts the degeneracy of the LO and TO phonons, yielding two cross-linearly polarized phonon modes and a splitting of the Raman G peak. We utilize the strong electron-phonon coupling in graphene and the off-resonant

Rickmoy Samanta, Naomi Oppenheimer

When considering flows in biological membranes, they are usually treated as flat, though more often than not, they are curved surfaces, even extremely curved, as in the case of the endoplasmic reticulum. Here, we study the topological effects of curvature on flows in membranes. Focusing on a system of many point vortical defects, we are able to cast the visc

Zhi Hu, Runhong Zong

In this paper, we will generalize some results in Manin's paper "Three-dimensional hyperbolic geometry as $\infty$-adic Arakelov geometry" to the supergeometric setting. More precisely, viewing $\mathbb{C}^{1|1}$ as the boundary of the hyperbolic superspace $\mathcal{H}^{3|2}$, we reexpress the super-Green functions on the supersphere $\hat{\mathbb{C}}^{1|1}

Kai Chen, Meng Niu, Qingcai Chen

We address the task of automatically scoring the competency of candidates based on textual features, from the automatic speech recognition (ASR) transcriptions in the asynchronous video job interview (AVI). The key challenge is how to construct the dependency relation between questions and answers, and conduct the semantic level interaction for each question

Gianbattista-Piero Nicosia, Jackson Levi Said, Viktor Gakis

Generalised Proca theories of gravity represent an interesting class of vector-tensor theories where only three propagating degrees of freedom are present. In this work, we propose a new teleparallel gravity analog to Proca theories where the generalised Proca framework is extended due to the lower order nature of torsion based gravity. We develop a new acti

Asier Castrillo, Yago Ascasibar, Lluís Galbany, Sebastián F. Sánchez

Constraining the delay-time distribution (DTD) of different supernova (SN) types can shed light on the timescales of galaxy chemical enrichment and feedback processes affecting galaxy dynamics, and SN progenitor properties. Here, we present an approach to recover SN DTDs based on integral field spectroscopy (IFS) of their host galaxies. Using a statistical a

Yao Zhang, Xu Zhang, Jun Wang, Hongru Liang

Developing link prediction models to automatically complete knowledge graphs has recently been the focus of significant research interest. The current methods for the link prediction taskhavetwonaturalproblems:1)the relation distributions in KGs are usually unbalanced, and 2) there are many unseen relations that occur in practical situations. These two probl

M. Markova, P. von Neumann-Cosel, A. C. Larsen, S. Bassauer

The validity of the Brink-Axel hypothesis, which is especially important for numerous astrophysical calculations, is addressed for 116,120,124Sn below the neutron separation energy by means of three independent experimental methods. The $\gamma$-ray strength functions (GSFs) extracted from primary $\gamma$-decay spectra following charged-particle reactions w

Ana Foles, Luis Fialho, Manuel Collares-Pereira, Pedro Horta

The variability of the solar resource is mainly caused by cloud passing, causing rapid power fluctuations on the output of photovoltaic (PV) systems. The fluctuations can negatively impact the electric grid, and smoothing techniques can be used as attempts to correct it. However, the integration of a PV+VRFB to deal with the extreme power ramps at a building

Atsuhira Nagano, Hironori Shiga

We study a family of lattice polarized $K3$ surfaces which is an extension of the family of Kummer surfaces derived from principally polarized Abelian surfaces. Our family has two special properties. First, it is coming from a resolution of a simple $K3$ singularity. Second, it has a natural parametrization by Hermitian modular forms of four complex variable

Tony Johansson

Given a symmetric $n\times n$ matrix $P$ with $0 \le P(u, v)\le 1$, we define a random graph $G_{n, P}$ on $[n]$ by independently including any edge $\{u, v\}$ with probability $P(u, v)$. For $k\ge 1$ let $\mathcal{A}_k$ be the property of containing $\lfloor k/2 \rfloor$ Hamilton cycles, and one perfect matching if $k$ is odd, all edge-disjoint. With an eig

Shanaka Ramesh Gunasekara, HNTK Kaldera, Maheshi B. Dissanayake

Deep learning algorithms have accounted for the rapid acceleration of research in artificial intelligence in medical image analysis, interpretation, and segmentation with many potential applications across various sub disciplines in medicine. However, only limited number of research which investigates these application scenarios, are deployed into the clinic

Stefanos Tsimenidis

Deep neural networks have triggered a revolution in artificial intelligence, having been applied with great results in medical imaging, semi-autonomous vehicles, ecommerce, genetics research, speech recognition, particle physics, experimental art, economic forecasting, environmental science, industrial manufacturing, and a wide variety of applications in nea

Judith Wewerka, Manfred Reichert

Robotic Process Automation (RPA) is the automation of rule-based routine processes to increase efficiency and to reduce costs. Due to the utmost importance of process automation in industry, RPA attracts increasing attention in the scientific field as well. This paper presents the state-of-the-art in the RPA field by means of a Systematic Literature Review (

Justin R. Crepp, Stanimir O. Letchev, Sam J. Potier, Joshua H. Follansbee

Strong turbulence conditions create amplitude aberrations through the effects of near-field diffraction. When integrated over long optical path lengths, amplitude aberrations (seen as scintillation) can nullify local areas in the recorded image of a coherent beam, complicating the wavefront reconstruction process. To estimate phase aberrations experienced by

G. T. Adamashvili

Using the generalized perturbation reduction method the scalar nonlinear Schr\"odinger equation is transformed to the coupled nonlinear Schr\"odinger equations for auxiliary functions. A solution in the form of a two-component vector nonlinear pulse is obtained. The components of the pulse oscillate with the sum and difference of the frequencies and wave num

Jun Suzuki

In this paper, we study the quantum-state estimation problem in the framework of optimal design of experiments. We first find the optimal designs about arbitrary qubit models for popular optimality criteria such as A-, D-, and E-optimal designs. We also give the one-parameter family of optimality criteria which includes these criteria. We then extend a class

Dongho Chae, Peter Constantin

We prove a blow up criterion in terms of the Hessian of the pressure of smooth solutions $u\in C([0, T); W^{2,q} (\mathbb R^3))$, $q>3$ of the incompressible Euler equations. We show that a blow up at $t=T$ happens only if $$\int_0 ^T \int_0 ^t \left\{\int_0 ^s \|D^2 p (\tau)\|_{L^\infty} d\tau \exp \left( \int_{s} ^t \int_0 ^{\s} \|D^2 p (\tau)\|_{L^\infty}

Jan Dereziński, Oskar Grocholski

The Bessel operator, that is, the Schr\"odinger operator on the half-line with a potential proportional to $1/x^2$, is analyzed in the momentum representation. Many features of this analysis are parallel to the approach \`a la K. Wilson to Quantum Field Theory: one needs to impose a cutoff, add counterterms, study the renormalization group flow with its fixe

P. Hickson, J. Hellemeier, R. Yang

Adaptive optics (AO) is a key technology for ground-based optical and infrared astronomy, providing high angular resolution and sensitivity. AO systems employing laser guide stars (LGS) can achieve high sky coverage, but their performance is limited by LGS return flux. We examine the potential of two new approaches that might produce high-intensity atmospher

Marco Dusel, Simon Betzold, Tristan. H. Harder, Monika Emmerling

Interacting bosonic particles in artificial lattices have proven to be a powerful tool for the investigation of exotic phases of matter as well as phenomena resulting from non-trivial topology. Exciton-polaritons, bosonic quasi-particles of light and matter, have shown to combine the on-chip benefits of optical systems with strong interactions, inherited for

Pierre Baldi, Lukas Blecher, Anja Butter, Julian Collado

QCD-jets at the LHC are described by simple physics principles. We show how super-resolution generative networks can learn the underlying structures and use them to improve the resolution of jet images. We test this approach on massless QCD-jets and on fat top-jets and find that the network reproduces their main features even without training on pure samples

Ze-Feng Gao, Xingwei Sun, Lan Gao, Junfeng Li

Long Short Term Memory(LSTM) models are the building blocks of many state-of-the-art natural language processing(NLP) and speech enhancement(SE) algorithms. However, there are a large number of parameters in an LSTM model. This usually consumes a large number of resources to train the LSTM model. Also, LSTM models suffer from computational inefficiency in th

Meng Xu, J. T. Stockburger, J. Ankerhold

Quantum heat transfer through a generic superconducting set-up consisting of a tunable transmon qubit placed between resonators that are termined by thermal reservoirs is explored. Two types of architectures are considered, a sequential and a beam splitter setting. Applying the numerical exact hierarchical equation of motion (HEOM) approach, steady state pro

J. Cayssol, J. -N. Fuchs

This paper provides a pedagogical introduction to recent developments in geometrical and topological band theory following the discovery of graphene and topological insulators. Amusingly, many of these developments have a connection to contributions in high-energy physics by Dirac. The review starts by a presentation of the Dirac magnetic monopole, goes on w

J. Adassuriya, S. Ganesh, J. L. Gutierrez, G. Handler

We report the analysis of high temporal resolution ground and space based photometric observations of SZ Lyncis, a binary star one of whose components is a high amplitude $\delta$ Scuti. UBVR photometric observations were obtained from Mt. Abu Infrared Observatory and Fairborn Observatory; archival observations from the WASP project were also included. Furth

Jianzhou Zhao, Yilin Wang, Xiaolong Feng, Shengyuan A. Yang

The interplay between structural phase and electronic correlations has been an intriguing topic of research. An prominent example is the pressure-induced uncollapsed to collapsed tetragonal phase transition observed in CaFe$_2$As$_2$, which is accompanied with the emergence of superconductivity in the collapsed phase. Recently, a very similar structural phas

Weitong Hua, Jiaxin Guo, Yue Wang, Rong Xiong

Object 6D pose estimation is an important research topic in the field of computer vision due to its wide application requirements and the challenges brought by complexity and changes in the real-world. We think fully exploring the characteristics of spatial relationship between points will help to improve the pose estimation performance, especially in the sc

Michael Lindner, Lucas Lincoln, Fenja Drauschke, Julia Monika Koulen

NetworkDynamics.jl is an easy-to-use and computationally efficient package for working with heterogeneous dynamical systems on complex networks, written in Julia, a high-level, high-performance, dynamic programming language. By combining state of the art solver algorithms from DifferentialEquations.jl with efficient data structures, NetworkDynamics.jl achiev

Chao-Hong Tan, Xiaoyu Yang, Zi'ou Zheng, Tianda Li

Task-oriented conversational modeling with unstructured knowledge access, as track 1 of the 9th Dialogue System Technology Challenges (DSTC 9), requests to build a system to generate response given dialogue history and knowledge access. This challenge can be separated into three subtasks, (1) knowledge-seeking turn detection, (2) knowledge selection, and (3)

Nacira Abbas, Kholoud Alghamdi, Mortaza Alinam, Francesca Alloatti

One of the grand challenges discussed during the Dagstuhl Seminar "Knowledge Graphs: New Directions for Knowledge Representation on the Semantic Web" and described in its report is that of a: "Public FAIR Knowledge Graph of Everything: We increasingly see the creation of knowledge graphs that capture information about the entirety of a class of entities. [..

Antonio Martin Arroyo, Aranzazu de Juan Fernandez

This paper considers the Split-Then-Combine (STC) approach (Arroyo and de Juan, 2014) to combine forecasts inside the simplex space, the sample space of positive weights adding up to one. As it turns out, the simplicial statistic given by the center of the simplex compares favorably against the fixed-weight, average forecast. Besides, we also develop a Combi

S. Vignesh Raja, A. Govindarajan, A. Mahalingam, M. Lakshmanan

A comb spectrum generating device based on Bragg grating superstructures with gain and loss is suggested in this paper. It includes a comprehensive analysis of the device formulation, generation and manipulation of the comb spectrum with a number of degrees of freedom such as duty cycle, sampling period and gain-loss parameter. For applications such as RF tr

Valentin Gabeff, Tomas Teijeiro, Marina Zapater, Leila Cammoun

While Deep Learning (DL) is often considered the state-of-the art for Artificial Intelligence-based medical decision support, it remains sparsely implemented in clinical practice and poorly trusted by clinicians due to insufficient interpretability of neural network models. We have tackled this issue by developing interpretable DL models in the context of on

Kazumasa Ohno, Xi Zhang, Ryo Tazaki, Satoshi Okuzumi

The largest moon of Neptune, Triton, possess a cold and hazy atmosphere. Since the discovery of near-surface haze layer during the Voyager fly in 1989, the haze formation mechanism has not been investigated in detail. Here, we provide the first haze microphysical model on Triton. Our model solves the evolution of both size and porosity distributions of haze

Victor Fadin

This paper contains my recollection of the creation and development of the so-called BFKL approach and my ideas about the ways of its further development.

Nicoletta Sanna, Elena Pancino, Giuseppe Altavilla, Silvia Marinoni

We describe the preliminary results of a ground-based observing campaign aimed at building a grid of approximately 200 spectro-photometric standard stars (SPSS), with an internal $\simeq 1$\% accuracy (and sub-percent precision), tied to CALSPEC Vega and Sirius systems within $\simeq 1$\%, for the absolute flux calibration of data gathered by {\it Gaia}, the

Fenglei Tian, Yiju Wang

Let $G$ be a connected simple graph of order $n$. Let $\rho_1(G)\geq \rho_2(G)\geq \cdots \geq \rho_{n-1}(G)> \rho_n(G)=0$ be the eigenvalues of the normalized Laplacian matrix $\mathcal{L}(G)$ of $G$. Denote by $m(\rho_i)$ the multiplicity of the normalized Laplacian eigenvalue $\rho_i$. Let $\nu(G)$ be the independence number of $G$. In this paper, we give

Zhi-Qiang Li, Shou-Fu Tian, Jin-Jie Yang

In this work, we employ the $\bar{\partial}$ steepest descent method in order to study the Cauchy problem of the cgNLS equations with initial conditions in weighted Sobolev space $H^{1,1}(\mathbb{R})=\{f\in L^{2}(\mathbb{R}): f',xf\in L^{2}(\mathbb{R})\}$. The large time asymptotic behavior of the solution $u(x,t)$ and $v(x,t)$ are derived in a fixed space-t

Aaron Chan, Erik Darpö, Osamu Iyama, René Marczinzik

We study periodicity and twisted periodicity of the trivial extension algebra $T(A)$ of a finite-dimensional algebra $A$. Our main results show that (twisted) periodicity of $T(A)$ is equivalent to $A$ being (twisted) fractionally Calabi-Yau of finite global dimension. We also extend this result to a large class of self-injective orbit algebras. As a signifi

Ming Ding, Zhiqi Chen, Jifu Li

In this paper, we introduce the notion of F-manifold color algebras and study their properties which extend some results for F-manifold algebras.

Timo Schick, Hinrich Schütze

Providing pretrained language models with simple task descriptions in natural language enables them to solve some tasks in a fully unsupervised fashion. Moreover, when combined with regular learning from examples, this idea yields impressive few-shot results for a wide range of text classification tasks. It is also a promising direction to improve data effic

Denis Constales, Rolf Sören Kraußhar

In this paper we consider generalized Hardy spaces in the octonionic setting associated to arbitrary Lipschitz domains where the unit normal field exists almost everywhere. First we discuss some basic properties and explain structural differences to the associative Clifford analysis setting. The non-associativity requires special attention in the definition

Y. Gong, A. Belloche, F. J. Du, K. M. Menten

The Serpens filament, a prominent elongated structure in a relatively nearby molecular cloud, is believed to be at an early evolutionary stage, so studying its physical and chemical properties can shed light on filament formation and early evolution. The main goal is to address the physical and chemical properties as well as the dynamical state of the Serpen

Héctor Estellés, Sascha Husa, Marta Colleoni, David Keitel

In this work we present an extension of the time domain phenomenological model IMRPhenomT for gravitational wave signals from binary black hole coalescences to include subdominant harmonics, specifically the $(l=2, m=\pm 1)$, $(l=3, m=\pm 3)$, $(l=4, m=\pm 4)$ and $(l=5, m=\pm 5)$ spherical harmonics. We also improve our model for the dominant $(l=2, m=\pm 2

Fernando Mateo, Jordi Munoz-Mari, Valero Laparra, Jochem Verrelst

Gaussian Processes (GPs) has experienced tremendous success in geoscience in general and for bio-geophysical parameter retrieval in the last years. GPs constitute a solid Bayesian framework to formulate many function approximation problems consistently. This paper reviews the main theoretical GP developments in the field. We review new algorithms that respec

Jiaqi Xu, Yuanwei Liu

The reconfigurable intelligent surface (RIS) is one of the promising technology contributing to the next generation smart radio environment. The application scenarios include massive connectivity support, signal enhancement, and security protection. One crucial difficulty of analyzing the RIS-assisted networks is that the channel performance is sensitive to

Anis M. Haddouche, Dominique Fourdrinier, Fatiha Mezoued

In this paper, we consider the problem of estimating the $p\times p$ scale matrix $\Sigma$ of a multivariate linear regression model $Y=X\,\beta + \mathcal{E}\,$ when the distribution of the observed matrix $Y$ belongs to a large class of elliptically symmetric distributions. After deriving the canonical form $(Z^T U^T)^T$ of this model, any estimator $\hat{

Peter Horsch, Andrzej M. Oleś, Adolfo Avella

We explore the competiton of doped holes and defects that leads to the loss of orbital order in vanadate perovskites. In compounds such as La$_{1-{\sf x}}$Ca$_{\,\sf x}$VO$_3$ spin and orbital order result from super-exchange interactions described by an extended three-orbital degenerate Hubbard-Hund model for the vanadium $t_{2g}$ electrons. Long-range Coul

Bhuvana G. R., Radhika D., V. K. Agrawal, Samir Mandal

We present the first results of extragalactic black hole X-ray binaries LMC X-1 and LMC X-3 using all the archival and legacy observations by AstroSat during the period of $2016-2020$. Broadband energy spectra ($0.5-20$ keV) of both sources obtained from the SXT and LAXPC on-board AstroSat are characterized by strong thermal disc blackbody component ($kT_{in

Marko Znidaric

Reply to a comment by T. Rakovszky, F. Pollmann, and C. W von Keyserlingk [arXiv:2010.07969].

Lorenzo Caprini, Umberto Marini Bettolo Marconi

Recently, it has been discovered that systems of Active Brownian particles (APB) at high density organise their velocities into coherent domains showing large spatial structures in the velocity field. Such a collective behavior occurs spontaneously, i.e. is not caused by any specific interparticle force favoring the alignment of the velocities. This phenomen

Claus Thorn Ekstrøm, Andreas Kryger Jensen

Many popular sports involve matches between two teams or players where each team have the possibility of scoring points throughout the match. While the overall match winner and result is interesting, it conveys little information about the underlying scoring trends throughout the match. Modeling approaches that accommodate a finer granularity of the score di

ALF Collaboration, F. F. Assaad, M. Bercx, F. Goth

The Algorithms for Lattice Fermions package provides a general code for the finite-temperature and projective auxiliary-field quantum Monte Carlo algorithm. The code is engineered to be able to simulate any model that can be written in terms of sums of single-body operators, of squares of single-body operators and single-body operators coupled to a bosonic f

Micha Sharir, Noam Solomon

Let $L$ be a set of $n$ lines in $R^3$ that is contained, when represented as points in the four-dimensional Pl\"ucker space of lines in $R^3$, in an irreducible variety $T$ of constant degree which is \emph{non-degenerate} with respect to $L$ (see below). We show: \medskip \noindent{\bf (1)} If $T$ is two-dimensional, the number of $r$-rich points (points i

Zbigniew Błaszczyk, José Carrasquel, Arturo Espinosa Baro

The sectional category of a subgroup inclusion $H \hookrightarrow G$ can be defined as the sectional category of the corresponding map between Eilenberg--MacLane spaces. We extend a characterization of topological complexity of aspherical spaces given by Farber, Grant, Lupton and Oprea to the context of sectional category of subgroup inclusions and investiga

Tahira Iqbal, Arslan Shaukat, Usman Akram, Zartasha Mustansar

Pneumothorax, a life threatening disease, needs to be diagnosed immediately and efficiently. The prognosis in this case is not only time consuming but also prone to human errors. So an automatic way of accurate diagnosis using chest X-rays is the utmost requirement. To-date, most of the available medical images datasets have class-imbalance issue. The main t

César M. Silva

We obtain characterizations of nonuniform dichotomies, defined by general growth rates, based on admissibility conditions. Additionally, we use the obtained characterizations to derive robustness results for the considered dichotomies. As particular cases, we recover several results in the literature concerning nonuniform exponential dichotomies and nonunifo

Katharina A. Lutz, Mark Allen, Caroline Bot, Miriam Cortés-Contreras

With some telescopes standing still, now more than ever simple access to archival data is vital for astronomers and they need to know how to go about it. Within European Virtual Observatory (VO) projects, such as AIDA (2008-2010), ICE (2010-2012), CoSADIE (2013-2015), ASTERICS (2015-2018) and ESCAPE (since 2019), we have been offering Virtual Observatory sch

Andreas Bauswein, Gang Guo, Jr-Hua Lien, Yen-Hsun Lin

We estimate the long-lasting gravitational wave (GW) emission of compact dark objects following a binary neutron-star (NS) merger. We consider compact dark objects, which initially reside in the centers of NSs and which may consist of self-interacting dark matter (DM). By approximating the compact dark objects as test particles, we model the merging of NS bi

K. A. Lutz, J. Dempsey, Y. G. Grange, M. Kettenis

With SKA precursor and pathfinder operations in full swing, radio and (sub-)mm astronomy is entering the era of super big data. The big questions is how to make (sub-)mm and radio data available to the astronomical community, preferably using FAIR (findable, accessible, interoperable and re-useable; Wilkinson et al. 2016) principles. There are already a lot

Mizuka Komatsu, Takaharu Yaguchi

In this study, we propose a method for extracting the hidden algebraic structures of model parameters that are uniquely determined by observed time-series data and unidentifiable state-space models, explicitly and exhaustively. State-space models are often constructed based on the domain, for example, physical or biological. Such models include parameters th

Silvan Mertes, Tobias Huber, Katharina Weitz, Alexander Heimerl

With the ongoing rise of machine learning, the need for methods for explaining decisions made by artificial intelligence systems is becoming a more and more important topic. Especially for image classification tasks, many state-of-the-art tools to explain such classifiers rely on visual highlighting of important areas of the input data. Contrary, counterfact

Zhi-Hui Guo, J. A. Oller

The newly observed hidden-charm tetraquark state $Z_{cs}(3985)$, together with $Z_c(3900)$ and $X(4020)$, are studied in the combined theoretical framework of the effective range expansion, compositeness relation and the decay width saturation. The elastic effective-range-expansion approach leads to sensible results for the scattering lengths, effective rang

Rijk Mercuur, Virginia Dignum, Catholijn M. Jonker

Our routines play an important role in a wide range of social challenges such as climate change, disease outbreaks and coordinating staff and patients in a hospital. To use agent-based simulations (ABS) to understand the role of routines in social challenges we need an agent framework that integrates routines. This paper provides the domain-independent Socia

John M. Mackay, Alessandro Sisto

We study relations between maps between relatively hyperbolic groups/spaces and quasisymmetric embeddings between their boundaries. More specifically, we establish a correspondence between (not necessarily coarsely surjective) quasi-isometric embeddings between relatively hyperbolic groups/spaces that coarsely respect peripherals, and quasisymmetric embeddin

M. Martínez-Chicharro, V. Grinberg, J. M. Torrejón, N. Schulz

We present an analysis of the first observation of the iconic High Mass X-ray Binary \so with the \chandra High Energy Transmission Gratings during an X-ray eclipse. The goal of the observation was to study the structure/physical conditions in the clumpy stellar wind through high resolution spectroscopy. We find that: a) emission line brightness from K shell

Ljupco Kocarev, Jasna Koteska

This paper addresses ontology and ethics of an AI agent called digital me. We define digital me as autonomous, decision-making, and learning agent, representing an individual and having practically immortal own life. It is assumed that digital me is equipped with the big-five personality model, ensuring that it provides a model of some aspects of a strong AI

Tung Yu Marco Chan

We seek to take a different approach in deriving the optimal search policy for the repeated consumer search model found in Fishman and Rob (1995) with the main motivation of dropping the assumption of prior knowledge of the price distribution $F(p)$ in each period. We will do this by incorporating the famous multi-armed bandit problem (MAB). We start by modi

Ming Zhang, Shuqiao Zhang, Haitan Xu, Hankai Zhang

With the ability to directly obtain the Wigner function and density matrix of photon states, quantum tomography (QT) has had a significant impact on quantum optics, quantum computing and quantum information. By an appropriate sequence of measurements on the evolution of each degreeof freedom (DOF), the full quantum state of the observed photonic system can b

Jia Li, Tomas Yu, Da-Cheng Juan, Arjun Gopalan

Recent studies have indicated that Graph Convolutional Networks (GCNs) act as a \emph{low pass} filter in spectral domain and encode smoothed node representations. In this paper, we consider their opposite, namely Graph Deconvolutional Networks (GDNs) that reconstruct graph signals from smoothed node representations. We motivate the design of Graph Deconvolu

Daniel Schuster, Gero J. Kolhof

Conformance checking techniques aim to collate observed process behavior with normative/modeled process models. The majority of existing approaches focuses on completed process executions, i.e., offline conformance checking. Recently, novel approaches have been designed to monitor ongoing processes, i.e., online conformance checking. Such techniques detect d

Shaofang Hong, Chaoxi Zhu

Let ${\mathbb F}_q$ be the finite field with $q=p^k$ elements with $p$ being a prime and $k$ be a positive integer. For any $y, z\in\mathbb{F}_q$, let $N_s(z)$ and $T_s(y)$ denote the numbers of zeros of $x_1^{3}+\cdots+x_s^3=z$ and $x_1^3+\cdots+x_{s-1}^3+yx_s^3=0$, respectively. Gauss proved that if $q=p, p\equiv1\pmod3$ and $y$ is non-cubic, then $T_3(y)=

Yubei Xiao, Ke Gong, Pan Zhou, Guolin Zheng

Low-resource automatic speech recognition (ASR) is challenging, as the low-resource target language data cannot well train an ASR model. To solve this issue, meta-learning formulates ASR for each source language into many small ASR tasks and meta-learns a model initialization on all tasks from different source languages to access fast adaptation on unseen ta

Yipeng Liu, Qi Yang, Yiling Xu, Le Yang

Full-reference (FR) point cloud quality assessment (PCQA) has achieved impressive progress in recent years. However, in many cases, obtaining the reference point clouds is difficult, so no-reference (NR) metrics have become a research hotspot. Few researches about NR-PCQA are carried out due to the lack of a large-scale PCQA dataset. In this paper, we first

Liang He, Su Yi

We investigate the finite temperature spin density wave (SDW) and charge density wave (CDW) transition of two-component lattice spinor Bose gases in optical lattices in the Mott-insulator limit. At the temperature scale around half of the on-site interaction energy, we find a new critical regime emerges and features, in particular, a new bicritical line and