December 2020 arXiv papers — page 142

Jonas Sedin, Luca Feltrin, Xingqin Lin

A non-terrestrial network (NTN), a term coined by the 3rd Generation Partnership Project (3GPP), refers to a network utilizing airborne or spaceborne payload for communication. The use of NTN has the potential of facilitating providing connectivity to underserved areas. This has motivated the work in 3GPP on evolving the fifth generation (5G) wireless access

Li-Yi Wei, Arjun V Anand, Shally Kumar, Tarun Beri

Representing complex shapes with simple primitives in high accuracy is important for a variety of applications in computer graphics and geometry processing. Existing solutions may produce suboptimal samples or are complex to implement. We present methods to approximate given shapes with user-tunable number of spheres to balance between accuracy and simplicit

Gia Dvali

$S$-matrix formulation of gravity excludes de Sitter vacua. In particular, this is organic to string theory. The $S$-matrix constraint is enforced by an anomalous quantum break-time proportional to the inverse values of gravitational and/or string couplings. Due to this, de Sitter can satisfy the conditions for a valid vacuum only at the expense of trivializ

Milton Javier Cardenas Mendez, Armando Mauro Vasquez Corro

In this work we define the surfaces spherical type via support function (in short, SS-surfaces). We present a Weierstrass type representation for SS-surfaces with prescribed Gauss map which depends on two holomorphic functions. Also, we use this representation to classify the surfaces of rotation. Moreover, we show that every compact and connected SS-surface

Zaid ALzaid, Xin Yuan, Saptarshi Bhowmik

The Jellyfish network has recently be proposed as an alternate to the fat-tree network as the interconnect for data centers and high performance computing clusters. Jellyfish adopts a random regular graph as its topology and has been showed to be more cost-effective than fat-trees. Effective routing on Jellyfish is challenging. It is known that shortest path

Jing Su, Qingyun Dai, Frank Guerin, Mian Zhou

Visual storytelling is a creative and challenging task, aiming to automatically generate a story-like description for a sequence of images. The descriptions generated by previous visual storytelling approaches lack coherence because they use word-level sequence generation methods and do not adequately consider sentence-level dependencies. To tackle this prob

Siyu Dai, Andreas Hofmann, Brian C. Williams

Many real-world robotic operations that involve high-dimensional humanoid robots require fast-reaction to plan disturbances and probabilistic guarantees over collision risks, whereas most probabilistic motion planning approaches developed for car-like robots can not be directly applied to high-dimensional robots. In this paper, we present probabilistic Cheko

Dimitrios Psaltis, Colm Talbot, Ethan Payne, Ilya Mandel

In General Relativity, the spacetimes of black holes have three fundamental properties: (i) they are the same, to lowest order in spin, as the metrics of stellar objects; (ii) they are independent of mass, when expressed in geometric units; and (iii) they are described by the Kerr metric. In this paper, we quantify the upper bounds on potential black-hole me

Qi Qi, Pak Hay Kwok

This paper details our solution to Traffic4cast 2020. Similar to Traffic4cast 2019, Traffic4cast 2020 challenged its contestants to develop algorithms that can predict the future traffic states of big cities. Our team tackled this challenge on two fronts. We studied the importance of feature and loss function design, and achieved significant improvement to t

Luis Felipe Gutiérrez, Sima Siami-Namini, Neda Tavakoli, Akbar Siami Namin

It is important and informative to compare and contrast major economic crises in order to confront novel and unknown cases such as the COVID-19 pandemic. The 2006 Great Recession and then the 2019 pandemic have a lot to share in terms of unemployment rate, consumption expenditures, and interest rates set by Federal Reserve. In addition to quantitative histor

Alexey Bokhovkin, Vladislav Ishimtsev, Emil Bogomolov, Denis Zorin

Recent advances in 3D semantic scene understanding have shown impressive progress in 3D instance segmentation, enabling object-level reasoning about 3D scenes; however, a finer-grained understanding is required to enable interactions with objects and their functional understanding. Thus, we propose the task of part-based scene understanding of real-world 3D

Nguyen Quynh Lan, Grant J. Mathews, Lara Arielle Phillips, Miguel A. Correa

The core-cusp problem remains as a challenging discrepancy between observations and simulations in the standard $Λ$CDM model for the formation of galaxies. The problem is that $Λ$CDM simulations predict a steep power-law mass density profile at the center of galactic dark matter halos. However, observations of dwarf galaxies in the Local Group reveal a densi

Oscar Claveria

This paper examines the evolution of business and consumer uncertainty amid the coronavirus pandemic in 32 European countries and the European Union (EU).Since uncertainty is not directly observable, we approximate it using the geometric discrepancy indicator of Claveria et al. (2019).This approach allows us quantifying the proportion of disagreement in busi

A. Ryan Kutayiah, Smriti Kumar, Rivi Ratnaweera, Kenny Easwaran

We develop a method based on Markov chains to model fluorescence, absorption, and scattering in nanophotonic systems. We show that the method reproduces Beer-Lambert's Law and Kirchhoff's Law, but also can be used to analyze deviations from these laws when some of their assumptions are violated. We show how to use the method to analyze a luminescent

Simon Ruetz, Karin Schnass

In this paper we derive tail bounds on the norms of random submatrices with non-uniformly distributed supports. We apply these results to sparse approximation and conduct an analysis of the average case performance of thresholding, Orthogonal Matching Pursuit and Basis Pursuit. As an application of these results we characterise sensing dictionaries to improv

Rafael March, David Egya, Christine Maier, Andreas Busch

We present stress-sensitive permeability relationships for two-dimensional fracture networks in the Opalinus Clay from the Mont Terri underground rock laboratory. These relationships may be used as a proxy for fracture network permeability in numerical models that resolve large spatial scales and are used in a variety of GeoEnergy applications involving flow

Ngan Le, Kashu Yamazaki, Dat Truong, Kha Gia Quach

In recent years, deep neural networks have achieved state-of-the-art performance in a variety of recognition and segmentation tasks in medical imaging including brain tumor segmentation. We investigate that segmenting a brain tumor is facing to the imbalanced data problem where the number of pixels belonging to the background class (non tumor pixel) is much

A. Drutskoy

Prompt and nonprompt productions of exotic multiquark states are studied using the $\sim$10.4 fb$^{-1}$ data sample collected by the D0 experiment in Tevatron $p\bar{p}$ collisions at $\sqrt{s}$ = 1.96 TeV. The recent D0 results on the prompt and nonprompt production of the $X(3872)$ and $Z_c^+(3900)$ states and the $P_c$ pentaquarks at the 4450 MeV region a

Martino Marelli, Silvano Molendi, Mariachiara Rossetti, Fabio Gastaldello

Our understanding of the background of the EPIC/pn camera onboard XMM-Newton is incomplete. This affects the study of extended sources and can influence the predictions of the background of future X-ray missions. We provide new results based on the analysis of the largest data set ever used. We focus on the unconcentrated component of the EPIC/pn background

Johannes Bellm, Cody B. Duncan, Stefan Gieseke, Miroslav Myska

Herwig 7 is a general-purpose Monte Carlo generator of particle collisions comprising both hard perturbative as well as soft phenomenological physics. Herwig is therefore capable to describe the entire final state of hadronized particles in a collision event. A spacetime topology of a parton system entering hadronization is fully described and tested for the

N. Rowell, M. Davidson, L. Lindegren, F. van Leeuwen

Context: The unprecedented astrometric precision of the Gaia mission relies on accurate estimates of the locations of sources in the Gaia data stream. This is ultimately performed by point spread function (PSF) fitting, which in turn requires an accurate reconstruction of the PSF. Gaia Early Data Release 3 (EDR3) will, for the first time, use a PSF calibrati

Norbert Bodendorfer, Muxin Han, Fabian Haneder, Hongguang Liu

A coarse graining technique akin to block spin transformations that groups together fiducial cells in a homogeneous and isotropic universe has been recently developed in the context of loop quantum cosmology. The key technical ingredient was an SU(1, 1) group and Lie algebra structure of the physical observables as well as the use of Perelomov coherent state

Gábor Székelyhidi

We show that the cylindrical tangent cone $C\times \mathbf{R}$ for an area-minimizing hypersurface is unique, where $C$ is the Simons cone $C_S= C(S^3\times S^3)$. Previously Simon proved a uniqueness result for cylindrical tangent cones that applies to a large class of cones $C$, however not to the Simons cone. The main new difficulty is that the cylindrica

Mark Pankov, Thomas Vetterlein

Let $H$ be a complex Hilbert space and let ${\mathcal P}(H)$ be the associated projective space (the set of rank-one projections). Suppose that $\dim H\ge 3$. We prove the following Wigner-type theorem: if $H$ is finite-dimensional, then every orthogonality preserving transformation of ${\mathcal P}(H)$ is induced by a unitary or anti-unitary operator. This

Gaia Collaboration, R. L. Smart, L. M. Sarro, J. Rybizki

We produce a clean and well-characterised catalogue of objects within 100\,pc of the Sun from the \G\ Early Data Release 3. We characterise the catalogue through comparisons to the full data release, external catalogues, and simulations. We carry out a first analysis of the science that is possible with this sample to demonstrate its potential and best pract

Melissa Mozifian, Amy Zhang, Joelle Pineau, David Meger

The goal of this work is to address the recent success of domain randomization and data augmentation for the sim2real setting. We explain this success through the lens of causal inference, positioning domain randomization and data augmentation as interventions on the environment which encourage invariance to irrelevant features. Such interventions include vi

Zohre Ranjbar-Mojaveri, Andras Farago

We consider random graphs in which the edges are allowed to be dependent. In our model the edge dependence is quite general, we call it $p$-robust random graph. It means that every edge is present with probability at least $p$, regardless of the presence/absence of other edges. This is more general than independent edges with probability $p$, as we illustrat

Kendra Albert, Maggie Delano, Jonathon Penney, Afsaneh Rigot

This paper critically assesses the adequacy and representativeness of physical domain testing for various adversarial machine learning (ML) attacks against computer vision systems involving human subjects. Many papers that deploy such attacks characterize themselves as "real world." Despite this framing, however, we found the physical or real-world t

Sathwik Bharadwaj, Ashwin Ramasubramaniam, L. R. Ram-Mohan

Accurate determination of carrier transport properties in two-dimensional (2D) materials is critical for designing high-performance nano-electronic devices and quantum information platforms. While first-principles calculations effectively determine the atomistic potentials associated with defects and impurities, they are ineffective for direct modeling of ca

Suhas Lohit, Rushil Anirudh, Pavan Turaga

Motion capture (mocap) and time-of-flight based sensing of human actions are becoming increasingly popular modalities to perform robust activity analysis. Applications range from action recognition to quantifying movement quality for health applications. While marker-less motion capture has made great progress, in critical applications such as healthcare, ma

Claudio Mendoza, Manuel A. Bautista, Jérôme Deprince, Javier A. García

We describe the atomic database of the XSTAR spectral modeling code, summarizing the systematic upgrades carried out in the past twenty years to enable the modeling of K lines from chemical elements with atomic number $Z\leq 30$ and recent extensions to handle high-density plasmas. Such plasma environments are found, for instance, in the inner region of accr

Andrea Oldofredi

It is generally accepted that quantum mechanics entails a revision of the classical propositional calculus as a consequence of its physical content. However, the universal claim according to which a new quantum logic is indispensable in order to model the propositions of every quantum theory is challenged. In the present essay we critically discuss this clai

Robert Paluch, Krzysztof Suchecki, Janusz A. Hołyst

We investigate the problem of locating the source of a self-interacting signal spreading in a complex networks. We use a well-known rumour model as an example of the process with self-interaction. According to this model based on the SIR epidemic dynamics, the infected nodes may interact and discourage each other from gossiping with probability $α$. We compa

Gaia Collaboration, S. A. Klioner, F. Mignard, L. Lindegren

Context. Gaia Early Data Release 3 (Gaia EDR3) provides accurate astrometry for about 1.6 million compact (QSO-like) extragalactic sources, 1.2 million of which have the best-quality five-parameter astrometric solutions. Aims. The proper motions of QSO-like sources are used to reveal a systematic pattern due to the acceleration of the solar system barycentre

David Pfau, Danilo Rezende

We introduce a method for reconstructing an infinitesimal normalizing flow given only an infinitesimal change to a (possibly unnormalized) probability distribution. This reverses the conventional task of normalizing flows -- rather than being given samples from a unknown target distribution and learning a flow that approximates the distribution, we are given

Benjamin Desrousseaux, François Lique, Javier R. Goicoechea, Ernesto Quintas-Sánchez

The detection of CF$^+$ in interstellar clouds potentially allows astronomers to infer the elemental fluorine abundance and the ionization fraction in ultraviolet-illuminated molecular gas. Because local thermodynamic equilibrium (LTE) conditions are hardly fulfilled in the interstellar medium (ISM), the accurate determination of the CF$^+$ abundance require

Rohit K. Patra, Moulinath Banerjee, George Michailidis

Distributed systems serve as a key technological infrastructure for monitoring diverse systems across space and time. Examples of their widespread applications include: precision agriculture, surveillance, ecosystem and physical infrastructure monitoring, animal behavior and tracking, disaster response and recovery to name a few. Such systems comprise of a l

Michael R. Heffels, Joaquin Vanschoren

Aerial imagery can be used for important work on a global scale. Nevertheless, the analysis of this data using neural network architectures lags behind the current state-of-the-art on popular datasets such as PASCAL VOC, CityScapes and Camvid. In this paper we bridge the performance-gap between these popular datasets and aerial imagery data. Little work is d

Robert Paluch, Łukasz G. Gajewski, K. Suchecki, Janusz A. Hołyst

Nowadays it is not uncommon to have to deal with dissemination on multi-layered networks and often finding the source of said propagation can be a crucial task. In this paper we tackle this exact problem with a maximum likelihood approach that we extend to be operational on multi-layered graphs. We test our method for source location estimation on synthetic

Itay Hen

Although stoquastic Hamiltonians are known to be simulable via sign-problem-free quantum Monte Carlo (QMC) techniques, the non-stoquasticity of a Hamiltonian does not necessarily imply the existence of a QMC sign problem. We give a sufficient and necessary condition for the QMC-simulability of Hamiltonians in a fixed basis in terms of geometric phases associ

Hadi Safari-Katesari, S. Yaser Samadi, Samira Zaroudi

Copula models have been widely used to model the dependence between continuous random variables, but modeling count data via copulas has recently become popular in the statistics literature. Spearman's rho is an appropriate and effective tool to measure the degree of dependence between two random variables. In this paper, we derived the population versio

Yudan Liu, Joycer Osorio, Hamid R. Ossareh

This paper presents a computationally efficient solution for constraint management of multi-input and multi-output (MIMO) systems. The solution, referred to as the Decoupled Reference Governor (DRG), maintains the highly-attractive computational features of Scalar Reference Governors (SRG) while having performance comparable to Vector Reference Governors (VR

Sophie Grivaux, Étienne Matheron, Quentin Menet

Given a Polish topology $τ$ on ${\mathcal{B}_{1}(X)}$, the set of all contraction operators on $X=\ell_p$, $1\le p<\infty$ or $X=c_0$, we prove several results related to the following question: does a typical $T\in {\mathcal{B}_{1}(X)}$ in the Baire Category sense has a non-trivial invariant subspace? In other words, is there a dense $G_δ$ set $\mathcal G\s

Esther van den Berg, Katja Markert

Informational bias is bias conveyed through sentences or clauses that provide tangential, speculative or background information that can sway readers&#39; opinions towards entities. By nature, informational bias is context-dependent, but previous work on informational bias detection has not explored the role of context beyond the sentence. In this paper, we

Piotr Deuar, Alex Ferrier, Michał Matuszewski, Giuliano Orso

Methods for modeling large driven dissipative quantum systems are becoming increasingly urgent due to recent experimental progress in a number of photonic platforms. We demonstrate the positive-P method to be ideal for this purpose across a wide range of parameters, focusing on the archetypal driven dissipative Bose-Hubbard model. Notably, these parameters i

Yushi Guan

Recent Automatic Speech Recognition systems have been moving towards end-to-end systems that can be trained together. Numerous techniques that have been proposed recently enabled this trend, including feature extraction with CNNs, context capturing and acoustic feature modeling with RNNs, automatic alignment of input and output sequences using Connectionist

Juraj Krempaský, Laurent Nicolaï, Martin Gmitra, Houke Chen

Ferroelectric GeTe is unveiled to exhibit an intriguing multiple non-trivial topology of the electronic band structure due to the existence of triple-point and type-II Weyl fermions, which goes well beyond the giant Rashba spin splitting controlled by external fields as previously reported. Using spin- and angle-resolved photoemission spectroscopy combined w

Larry R. Nittler, Conel M. O&#39;D. Alexander, Andrea Patzer, Maximilien J. Verdier-Paoletti

We report a NanoSIMS search for presolar grains in the CM chondrites Asuka (A) 12169 and A12236. We found 90 presolar O-rich grains and 25 SiC grains in A12169, giving matrix-normalized abundances of 275 (+55/-50, 1$σ$) ppm or, excluding an unusually large grain, 236 (+37/-34) ppm for O-rich grains and 62 (+15/-12) ppm for SiC grains. For A12236, 18 presolar

Mahbubur Rahman

Learning from the multidimensional data has been an interesting concept in the field of machine learning. However, such learning can be difficult, complex, expensive because of expensive data processing, manipulations as the number of dimension increases. As a result, we have introduced an ordered index-based data organization model as the ordered data set p

Sergey Finashin, Viatcheslav Kharlamov, Oleg Viro

This note is written for a book dedicated to outstanding St-Petersburg mathematicians and timed to the ICM-2022 in St-Petersburg. In accordance with the plan of ICM-organizers, we try to tell about one of the most prominent Rokhlin&#39;s achievements in an accessible form and respecting the allowed volume.

V. S. S. Kandarpa, Alexandre Bousse, Didier Benoit, Dimitris Visvikis

This paper explores convolutional generative networks as an alternative to iterative reconstruction algorithms in medical image reconstruction. The task of medical image reconstruction involves mapping of projection main data collected from the detector to the image domain. This mapping is done typically through iterative reconstruction algorithms which are

Dheeraj Kumar Singh, Yunkyu Bang

We investigate the magnetic excitations in view of the recent reports suggesting that the spin-wave energy may exhibit a significant dependence on the in-plane strain of a thin film of La$_2$CuO$_4$. The nature of dependence, as we find, can be explained naturally within a two-orbital model based on the $d_{x^2-y^2}$ and $d_{3z^2-r^2}$ orbitals. In particula

Thomas Konrad, Amy Rouillard, Michael Kastner, Hermann Uys

Quantum systems can be controlled by other quantum systems in a reversible way, without any information leaking to the outside of the system-controller compound. Such coherent quantum control is deterministic, is less noisy than measurement-based feedback control, and has potential applications in a variety of quantum technologies, including quantum computat

Rico Landman, Sebastiaan Y. Haffert, Vikram M. Radhakrishnan, Christoph U. Keller

Current and future high-contrast imaging instruments require extreme Adaptive Optics (XAO) systems to reach contrasts necessary to directly image exoplanets. Telescope vibrations and the temporal error induced by the latency of the control loop limit the performance of these systems. Optimization of the (predictive) control algorithm is crucial in reducing t

N. K. Timofeyuk, M. J. Dinmore, J. S AL-Khalili

The contribution of a three-nucleon (3N) force, acting between the neutron and proton in the incoming deuteron with a target nucleon, to the deuteron-target potential in the entrance channel of the $A(d,p)B$ reaction has been calculated within the adiabatic distorted wave approximation (ADWA). Four different 3N interaction sets from local chiral effective fi

Rose Nakasi, Aminah Zawedde, Ernest Mwebaze, Jeremy Francis Tusubira

Effectively determining malaria parasitemia is a critical aspect in assisting clinicians to accurately determine the severity of the disease and provide quality treatment. Microscopy applied to thick smear blood smears is the de facto method for malaria parasitemia determination. However, manual quantification of parasitemia is time consuming, laborious and

Simon T. Isele, Marcel P. Schilling, Fabian E. Klein, Sascha Saralajew

Research on localization and perception for Autonomous Driving is mainly focused on camera and LiDAR datasets, rarely on radar data. Manually labeling sparse radar point clouds is challenging. For a dataset generation, we propose the cross sensor Radar Artifact Labeling Framework (RALF). Automatically generated labels for automotive radar data help to cure r

Domingos M. Cardoso, Inês Serôdio Costa, Rui Duarte

The $n$-Queens&#39; graph, $\mathcal{Q}(n)$, is the graph associated to the $n \times n$ chessboard (a generalization of the classical $8 \times 8$ chessboard), with $n^2$ vertices, each one corresponding to a square of the chessboard. Two vertices of $\mathcal{Q}(n)$ are adjacent if and only if they are in the same row, in the same column or in the same dia

Wen Wu, Nan Chen, Conghao Zhou, Mushu Li

In this paper, we investigate a radio access network (RAN) slicing problem for Internet of vehicles (IoV) services with different quality of service (QoS) requirements, in which multiple logically-isolated slices are constructed on a common roadside network infrastructure. A dynamic RAN slicing framework is presented to dynamically allocate radio spectrum an

Rajesh Kumar Gupta, Augniva Ray, Karunava Sil

We compute the partition function of $\mathcal N=2$ supersymmetric mixed dimensional QED on a squashed hemisphere using localization. Mixed dimensional QED is an abelian gauge theory coupled to charged matter fields at the boundary. The partition function is a function of the complex gauge coupling $τ$, the choice of R-symmetry and the squashing deformation.

Paul Manuel Müller, Jobst Heitzig, Jürgen Kurths, Kathy Lüdge

In the past decades human activities caused global Earth system changes, e.g., climate change or biodiversity loss. Simultaneously, these associated impacts have increased environmental awareness within societies across the globe, thereby leading to dynamical feedbacks between the social and natural Earth system. Contemporary modelling attempts of Earth syst

Silas Nyboe Ørting

We report on the results of a small crowdsourcing experiment conducted at a workshop on machine learning for segmentation held at the Danish Bio Imaging network meeting 2020. During the workshop we asked participants to manually segment mitochondria in three 2D patches. The aim of the experiment was to illustrate that manual annotations should not be seen as

Bakir Farhi

This paper presents a new generalization of the Genocchi numbers and the Genocchi theorem. As consequences, we obtain some important families of integer-valued polynomials those are closely related to the Bernoulli polynomials. Denoting by ${(B_n)}_{n \in \mathbb{N}}$ the sequence of the Bernoulli numbers and by ${(B_n(X))}_{n \in \mathbb{N}}$ the sequence o

Sangpyo Kim, Wonkyung Jung, Jaiyoung Park, Jung Ho Ahn

Homomorphic encryption (HE) draws huge attention as it provides a way of privacy-preserving computations on encrypted messages. Number Theoretic Transform (NTT), a specialized form of Discrete Fourier Transform (DFT) in the finite field of integers, is the key algorithm that enables fast computation on encrypted ciphertexts in HE. Prior works have accelerate

Donald R. Sheehy, Siddharth Sheth

Given a persistence diagram with $n$ points, we give an algorithm that produces a sequence of $n$ persistence diagrams converging in bottleneck distance to the input diagram, the $i$th of which has $i$ distinct (weighted) points and is a $2$-approximation to the closest persistence diagram with that many distinct points. For each approximation, we precompute

Yasin Kikabi, Juma Kasozi

In this paper, we introduce a new method of sampling from transition densities of diffusion processes including those unknown in closed forms by solving a partial differential equation satisfied by the quotient of transition densities. We demonstrate the performance of the developed method on processes with known densities and the obtained results are consis

Vaishali Kansal, Mayank Dave

Distributed Denial of Service (DDoS) attacks are serious cyber attacks and mitigating DDoS attacks in cloud is a topic of ongoing research interest which remains a major security challenge. Fog computing is an extension of cloud computing which has been used to secure cloud. Moving Target Defense (MTD) is a newly recognized, proactive security defense that c

Matthew A. Kenworthy, Frans Snik, Christoph U. Keller, David Doelman

ERIS is a diffraction limited thermal infrared imager and spectrograph for the Very Large Telescope UT4. One of the science cases for ERIS is the detection and characterization of circumstellar structures and exoplanets around bright stars that are typically much fainter than the stellar diffraction halo. Enhanced sensitivity is provided through the combinat

Yu. A. Aleshchenko, A. V. Muratov, G. A. Ummarino, S. Richter

Optical spectroscopy was used to study the electrodynamics and hidden transport properties of a BaFe$_{1.91}$Ni$_{0.09}$As$_{2}$ thin superconducting film. We analyzed the normal state data using a Drude-Lorentz model with two Drude components: one narrow ($D_1$) and another broad one ($D_2$). In the superconducting state, two gaps with $2Δ_{0}^{(2)}/k_BT_c=

F. Cavaliere, S. Zlotnik, R. Sevilla, X. Larrayoz

The Inertia Relief (IR) technique is widely used by industry and produces equilibrated loads allowing to analyze unconstrained systems without resorting to the more expensive full dynamic analysis. The main goal of this work is to develop a computational framework for the solution of unconstrained parametric structural problems with IR and the Proper General

Alessio Maiezza

We study the possibility of soft breaking effects of the generalized parity within the minimal Left-Right model. One aim of the paper is to elaborate on the potentiality, the limit, and the predictivity of a restored parity at high scale. While revisiting the issue of strong CP in the Left-Right theories, we motivate the possibility of explicit-parity-breaki

Carlos Badenes-Olmedo, David Chaves-Fraga, MarÍa Poveda-VillalÓn, Ana Iglesias-Molina

In the absence of sufficient medication for COVID patients due to the increased demand, disused drugs have been employed or the doses of those available were modified by hospital pharmacists. Some evidences for the use of alternative drugs can be found in the existing scientific literature that could assist in such decisions. However, exploiting large corpus

D. Fiorentini, D. R. Junior, L. E. Oxman, G. M. Simões

Recently, based on a new procedure to quantize the theory in the continuum, it was argued that Singer&#39;s theorem points towards the existence of a Yang-Mills ensemble. In the new approach, the gauge fields are mapped into an auxiliary field space used to separately fix the gauge on different sectors labeled by center vortices. In this work, we study this

João R. Santos Junior, Gaetano Siciliano

We consider a boundary value problem in a bounded domain involving a degenerate operator of the form $$L(u)=-\textrm{div} (a(x)\nabla u)$$ and a suitable nonlinearity $f$. The function $a$ vanishes on smooth 1-codimensional submanifolds of $Ω$ where it is not allowed to be $C^{2}$. By using weighted Sobolev spaces we are still able to find existence of solut

A. Krawiecki

The $q$-neighbor Ising model is investigated on homogeneous random graphs with a fraction of edges associated randomly with antiferromagnetic exchange integrals and the remaining edges with ferromagnetic ones. It is a nonequilibrium model for the opinion formation in which the agents, represented by two-state spins, change their opinions according to a Metro

Donald R. Sheehy

We show how a filtration of Delaunay complexes can be used to approximate the persistence diagram of the distance to a point set in $R^d$. Whereas the full Delaunay complex can be used to compute this persistence diagram exactly, it may have size $O(n^{\lceil d/2 \rceil})$. In contrast, our construction uses only $O(n)$ simplices. The central idea is to conn

Marco Squarcina, Mauro Tempesta, Lorenzo Veronese, Stefano Calzavara

Related-domain attackers control a sibling domain of their target web application, e.g., as the result of a subdomain takeover. Despite their additional power over traditional web attackers, related-domain attackers received only limited attention by the research community. In this paper we define and quantify for the first time the threats that related-doma

Oleg Kariuk, Dima Karamshuk

In this paper, we focus on the challenge of learning controllable text simplifications in unsupervised settings. While this problem has been previously discussed for supervised learning algorithms, the literature on the analogies in unsupervised methods is scarse. We propose two unsupervised mechanisms for controlling the output complexity of the generated t

Parivesh Choudhary

Gravitational waves were first proposed by Henri Poincaré in 1905 and were subsequently predicted by Albert Einstein in his General Theory of Relativity. In 2015, first Gravitational Waves signals were detected by LIGO of two black holes merging about 1.3 billion light-years away. The discovery opened a new window of astronomy. Currently, four laser interfer

Hajer Bahouri, Galina Perelman

This paper is dedicated to the study of the derivative nonlinear Schrödinger equation on the real line. The local well-posedness of this equation in the Sobolev spaces is well understood since a couple of decades, while the global well-posedness is not completely settled. For the latter issue, the best known results up-to-date concern either Cauchy data in $

M. Riello, F. De Angeli, D. W. Evans, P. Montegriffo

Gaia Early Data Release 3 contains astrometry and photometry results for about 1.8 billion sources based on observations collected by the ESA Gaia satellite during the first 34 months of operations. This paper focuses on the photometric content, describing the input data, the algorithms, the processing, and the validation of the results. Particular attention

Alessandro Sestini, Alexander Kuhnle, Andrew D. Bagdanov

In this paper we introduce DeepCrawl, a fully-playable Roguelike prototype for iOS and Android in which all agents are controlled by policy networks trained using Deep Reinforcement Learning (DRL). Our aim is to understand whether recent advances in DRL can be used to develop convincing behavioral models for non-player characters in videogames. We begin with

Benjamin Maschler, Dominik Braun, Nasser Jazdi, Michael Weyrich

Digital Twins have been described as beneficial in many areas, such as virtual commissioning, fault prediction or reconfiguration planning. Equipping Digital Twins with artificial intelligence functionalities can greatly expand those beneficial applications or open up altogether new areas of application, among them cross-phase industrial transfer learning. I

Sabah Al-Fedaghi

According to some algorithmicists, algorithmics traditionally uses algorithm theory, which stems from mathematics. The growing need for innovative algorithms has caused increasing gaps between theory and practice. Originally, this motivated the development of algorithm engineering, which is viewed as experimental techniques related to software engineering. C

Guillaume Bal, Benjamin Palacios

We consider the modeling of light beams propagating in highly forward-peaked turbulent media by fractional Fokker-Planck equations and their approximations by fractional Fermi pencil-beam models. We obtain an error estimate in a 1-Wasserstein distance for the latter model showing that beam spreading is well captured by the Fermi pencil-beam approximation in

Asier Minondo

The COVID-19 crisis has led to the sharpest collapse in the Spanish trade of goods and services in recent decades. The containment measures adopted to arrest the spread of the virus have caused an especially intense fall of trade in services. Spain&#39;s export specialization in transport equipment, capital and outdoor goods, and services that rely on the mo

M. Guttormsen, Y. Alhassid, W. Ryssens, K. O. Ay

Understanding the evolution of level densities in the crossover from spherical to well-deformed nuclei has been a long-standing problem in nuclear physics. We measure nuclear level densities for a chain of neodymium isotopes $^{142,144-151}$Nd which exhibit such a crossover. These results represent to date the most complete data set of nuclear level densitie

Giuseppe Ughi, Vinayak Abrol, Jared Tanner

We perform a comprehensive study on the performance of derivative free optimization (DFO) algorithms for the generation of targeted black-box adversarial attacks on Deep Neural Network (DNN) classifiers assuming the perturbation energy is bounded by an $\ell_\infty$ constraint and the number of queries to the network is limited. This paper considers four pre

Dong Xie, Chunling Xu, An Min Wang

We investigate the advantage of coherent superposition of two different coded channels in quantum metrology. In a continuous variable system, we show that the Heisenberg limit $1/N$ can be beaten by the coherent superposition without the help of indefinite causal order. And in parameter estimation, we demonstrate that the strategy with the coherent superposi

Reinis Irmejs, Nadav Avidor

The study explores machine learning methods for revealing chemical sensitivity in Helium spin-echo spectroscopy, in order to obtain ultra-sensitive surface analytic technique. We model bi-species co-adsorbed systems and demonstrate that by using deep-learning neural-networks partial surface concentrations are obtainable. An example system of particles with m

Elliot London, Emanuele Virgillito, Andrea D&#39;Amico, Antonio Napoli

Through a physical layer simulation study we highlight that the coherent accumulation of nonlinear interference becomes non-negligible for optical networks operating within high symbol rate transmission scenarios. This initiates a discussion on how to accurately plan and model optical networks, starting from the physical layer.

Chandrima Paul

The quantum entanglement measures for $T{\overline{T}}$ deformed field theory on boundary, deformation coefficient $μ$, with dual bulk geometry with finite radial cutoff $ρ_c$, for entangling region is single or disjoint intervals on the boundary, of length l is expected to give global description of these measures over the complete parameter-regime of $(l,

V. V. Pilipenko, V. I. Kuprikov

An improved model of the multiple Dirac eikonal scattering of proton on nucleons of the target nucleus is considered. In this model, the amplitudes of elastic $p-A$ scattering are found on the basis of the Watson series of multiple scattering by means of the eikonal expansion of the Dirac propagator for the free proton motion between scattering events on nuc

Dong Xie, Chunling Xu, An min Wang

We investigate the parameter estimation in a magnon-cavity-magnon coupled system. PT symmetrical two magnons system can be formed in the gain magnetic materials by the adiabatic elimination of the cavity field mode. We show that the optimal estimation will not appear at the exceptional point due to that the quantum fluctuations are the strongest at the excep

Alina R. Mayorova, Ekaterina A. Vassilieva

Over the past years, major attention has been drawn to the question of identifying Schur-positive sets, i.e. sets of permutations whose associated quasisymmetric function is symmetric and can be written as a non-negative sum of Schur symmetric functions. The set of arc permutations, i.e. the set of permutations $π$ in $S_n$ such that for any $1\leq j \leq n$

Louis Abraham

We study two questions related to competition on the OTC CDS market using data collected as part of the EMIR regulation. First, we study the competition between central counterparties through collateral requirements. We present models that successfully estimate the initial margin requirements. However, our estimations are not precise enough to use them as in

Uri Meir

Distribution testing can be described as follows: $q$ samples are being drawn from some unknown distribution $P$ over a known domain $[n]$. After the sampling process, a decision must be made about whether $P$ holds some property, or is far from it. The most studied problem in the field is arguably uniformity testing, where one needs to distinguish the case

Robert Paluch, Łukasz G. Gajewski, Janusz A. Hołyst, Boleslaw K. Szymanski

As the world becomes more and more interconnected, our everyday objects become part of the Internet of Things, and our lives get more and more mirrored in virtual reality, where every piece of~information, including misinformation, fake news and malware, can spread very fast practically anonymously. To suppress such uncontrolled spread, efficient computer sy

Ersin Gogus, Matthew G. Baring, Chryssa Kouveliotou, Tolga Guver

We present detailed spectral and temporal characteristics of the persistent X-ray emission of SGR J1935+2154 based on our XMM-Newton and Chandra observations taken in the aftermath of its April 2020 burst storm, during which hundreds of energetic X-ray bursts were emitted, including one associated with an extraordinary fast radio burst. We clearly detect the

Giorgio Sonnino, Fernando Mora, Pasquale Nardone

We propose two stochastic models for the Coronavirus pandemic. The statistical properties of the models, in particular the correlation functions and the probability density function, have duly been computed. Our models, which generalises a model previously proposed and published in a specialised journal, take into account the adoption of the lockdown measure