November 2020 arXiv papers — page 49

Konstantinos Kousias, Apostolos Pappas, Ozgu Alay, Antonios Argyriou

Bandwidth forecasting in Mobile Broadband (MBB) networks is a challenging task, particularly when coupled with a degree of mobility. In this work, we introduce HINDSIGHT++, an open-source R-based framework for bandwidth forecasting experimentation in MBB networks with Long Short Term Memory (LSTM) networks. We instrument HINDSIGHT++ following an Automated Ma

Anubhav Guha, Anuradha Annaswamy

Reinforcement learning (RL) algorithms have been successfully used to develop control policies for dynamical systems. For many such systems, these policies are trained in a simulated environment. Due to discrepancies between the simulated model and the true system dynamics, RL trained policies often fail to generalize and adapt appropriately when deployed in

I-Da Chiang, Karin M. Sandstrom, Jérémy Chastenet, Cinthya N. Herrera

We investigate the relationship between the dust-to-metals ratio (D/M) and the local interstellar medium environment at ~2 kpc resolution in five nearby galaxies: IC342, M31, M33, M101, and NGC628. A modified blackbody model with a broken power-law emissivity is used to model the dust emission from 100 to 500 um observed by Herschel. We utilize the metallici

Mansur Zhussupbekov, Wei-Tao Wu, Megan A. Jamiolkowski, Mehrdad Massoudi

Thromboembolic complications remain a central issue in management of patients on mechanical circulatory support. Despite the best practices employed in design and manufacturing of modern ventricular assist devices, complexity and modular nature of these systems often introduces internal steps and crevices in the flow path which can serve as nidus for thrombu

Fabrizio Renzi, Alessandra Silvestri

We introduce a novel way of measuring $H_0$ from a combination of independent geometrical datasets, with no need of calibration nor of the choice of a cosmological model. We build on the {\it distance duality relation} which sets the ratio of the luminosity and angular diameter distance to a fixed scaling in redshift for any metric theory of gravity with sta

Marrick Braam, Floris F. S. van der Tak, Katy L. Chubb, Michiel Min

Context. The characterisation of exoplanet atmospheres has shown a wide diversity in compositions. Hot Jupiters have the appropriate temperatures to host metallic compounds, which should be detectable through transmission spectroscopy. Aims. We aim to detect exotic species in transmission spectra of hot Jupiters, specifically WASP-31b, by testing a variety o

Giovanni Camelio, Tim Dietrich, Stephan Rosswog, Brynmor Haskell

Merging neutron stars are expected to produce hot, metastable remnants in rapid differential rotation, which subsequently cool and evolve into rigidly rotating neutron stars or collapse to black holes. Studying this metastable phase and its further evolution is essential for the prediction and interpretation of the electromagnetic, neutrino, and gravitationa

N. Emil J. Bjerrum-Bohr, Taro V. Brown, Humberto Gomez

We provide a new efficient diagrammatic tool, in the context of the scattering equations, for computation of covariant $D$-dimensional tree-level $n$-point amplitudes with pairs of spinning massive particles using compact exponential numerators. We discuss how this framework allows non-integer spin extensions of recurrence relations for amplitudes developed

Osman Karakuş, Fehmi Ekmekçi

Within the scope of extended matter research, we present new spectral analysis results of an active binary system AR Lac. The low and high resolution spectra of this system were taken during the period 2013-2016. The evaluation of low dispersion spectra together with the B, V, Rc, Ic and WISE photometric data showed that AR Lac has an excess radiation in W2

Eric Bobrow, Junjia Zhang, Yi Li

By connecting Hund's physics with flat band physics, we establish an exact result for studying ferromagnetism in a multiorbital system. We consider a two-layer model consisting of a $p_x$, $p_y$-orbital honeycomb lattice layer and an $f$-orbital triangular lattice layer with sites aligned with the centers of the honeycomb plaquettes. The system features a fl

Mark A. Fardal, Roeland van der Marel, Andres del Pino, Sangmo Tony Sohn

Parallaxes measured by the Gaia mission have huge significance for astronomy, but parallaxes in Gaia DR2 are known to have systematic errors that depend on the source position and other quantities. We use the abundant information in faint Milky Way stars, along with the GOG simulation of the Gaia catalog, to probe the spatial dependence of Gaia DR2 parallax

Michael J. Schlosser, Nian Hong Zhou

In this paper, we study properties of the coefficients appearing in the $q$-series expansion of $\prod_{n\ge 1}[(1-q^n)/(1-q^{pn})]^\delta$, the infinite Borwein product for an arbitrary prime $p$, raised to an arbitrary positive real power $\delta$. We use the Hardy--Ramanujan--Rademacher circle method to give an asymptotic formula for the coefficients. For

John M. Lawson

In a theoretical analysis, we generalise well known asymptotic results to obtain expressions for the rate of transfer of material from the surface of an arbitrary, rigid particle suspended in an open pathline flow at large P\'eclet number, $\textrm{Pe}$. The flow may be steady or periodic in time. We apply this result to numerically evaluate expressions for

Mark W. Stephenson, Ram Rangan

Recent research has shown that dynamic zeros in shader programs of gaming applications can be effectively leveraged with a profile-guided, code-versioning transform. This transform duplicates code, specializes one path assuming certain key program operands, called versioning variables, are zero, and leaves the other path unspecialized. Dynamically, depending

Ankith Mohan, Aiichiro Nakano, Emilio Ferrara

We propose a model-agnostic pipeline to recover graph signals from an expert system by exploiting the content addressable memory property of restricted Boltzmann machine and the representational ability of a neural network. The proposed pipeline requires the deep neural network that is trained on a downward machine learning task with clean data, data which i

Stéphane Perrard, Aliénor Rivière, Wouter Mostert, Luc Deike

We investigate the modes of deformation of an initially spherical bubble immersed in a homogeneous and isotropic turbulent background flow. We perform direct numerical simulations of the two-phase incompressible Navier-Stokes equations, considering a low-density bubble in the high density turbulent flow at various Weber number (the ratio of turbulent and sur

Raphael Gobat, Georgios Magdis, Chiara D'Eugenio, Francesco Valentino

We discuss the evolution of the interstellar medium of quiescent galaxies, currently emerging from recent analyses, with the help of a simple model based on well-established empirical relations such as the stellar mass functions and the main sequence of star formation. This model is meant to describe observed quantities without making specific assumptions on

Paul W. Oxby

The sinc function is often used as the basis for the design of discrete linear-phase FIR filters. However the Fourier transform of the truncated sinc function exhibits ripple in the pass band due to the Gibbs phenomenon. This paper introduces an alternative function based on Chebyshev polynomials whose Fourier transform decreases monotonically in the pass ba

Priya Malpani

In quantum optics, nonclassical properties of various quantum states of radiation field are frequently studied. Some of those states are finite dimensional and referred to as qudits. These states are important because of their potential applications in quantum information processing. Further, nonclassical states are those which do not have any classical coun

Evaldas Vaiciukynas, Paulius Danenas, Vilius Kontrimas, Rimantas Butleris

Amounts of historical data collected increase and business intelligence applicability with automatic forecasting of time series are in high demand. While no single time series modeling method is universal to all types of dynamics, forecasting using an ensemble of several methods is often seen as a compromise. Instead of fixing ensemble diversity and size, we

Sanhan Khasraw

Let $G$ be a finite group. The intersection graph of $G$ is a graph whose vertex set is the set of all proper non-trivial subgroups of $G$ and two distinct vertices $H$ and $K$ are adjacent if and only if $H\cap K \neq \{e\}$, where $e$ is the identity of the group $G$. In this paper, we investigate some properties and exploring some topological indices such

ATLAS Collaboration

A search is performed for the electroweak pair production of charginos and associated production of a chargino and neutralino, each of which decays through an $R$-parity-violating coupling into a lepton and a $W$, $Z$, or Higgs boson. The trilepton invariant-mass spectrum is constructed from events with three or more leptons, targeting chargino decays that i

Björn Baumeier, Onur Çaylak, Carlo Mercuri, Mark Peletier

We prove existence and uniqueness of solutions to the initial-value problem associated with a class of time-dependent Kohn-Sham equations coupled with Newtonian nuclear dynamics. We consider a pure power exchange term within a generalisation of the Local Density Approximation (LDA), identifying a range of exponents for the existence and uniqueness of $H^2$ s

Karim Kassan, Haïfa Farès, D. Christian Glattli, Yves Louët

This study revokes the performance of continuous phase modulation (CPM) able to generate a single-sideband (SSB) spectrum directly. This signal is analyzed in terms of modulation indices, pulse lengths, and pulse widths, all of which affect error probability, bandwidth, SSB property, and receiver complexity. The error probability performance is based on an a

Yordan S. Yordanov, V. Armaos, Crispin H. W. Barnes, David R. M. Arvidsson-Shukur

Molecular simulations with the variational quantum eigensolver (VQE) are a promising application for emerging noisy intermediate-scale quantum computers. Constructing accurate molecular ans\"atze that are easy to optimize and implemented by shallow quantum circuits is crucial for the successful implementation of such simulations. Ans\"atze are, generally, co

Hongki Jung

We prove a sharp $l^{10}(L^{10})$ decoupling for the moment curve in $\mathbb{R}^3$. The proof involves a two-step decoupling combined with new incidence estimates for planks, tubes and plates.

Andreas Schwarz, Ilya Sklyar, Simon Wiesler

We present a training scheme for streaming automatic speech recognition (ASR) based on recurrent neural network transducers (RNN-T) which allows the encoder network to learn to exploit context audio from a stream, using segmented or partially labeled sequences of the stream during training. We show that the use of context audio during training and inference

Alice J. Merryweather, Christoph Schnedermann, Quentin Jacquet, Clare P. Grey

Key to advancing lithium-ion battery technology, and in particular fast charging capabilities, is our ability to follow and understand the dynamic processes occurring in operating materials under realistic conditions, in real time, and on the nano- to meso-scale. Currently, operando imaging of lithium-ion dynamics requires sophisticated synchrotron X-ray or

Lucas R. Hofer, Milan Krstajić, Péter Juhász, Anna L. Marchant

We use a deep neural network to detect and place region-of-interest boxes around ultracold atom clouds in absorption and fluorescence images---with the ability to identify and bound multiple clouds within a single image. The neural network also outputs segmentation masks that identify the size, shape and orientation of each cloud from which we extract the cl

Yago Ferreiros, Karl Landsteiner

We show that geometric torsion does not lead to new chiral dissipationless transport effects. Instead apparent response to torsion can be viewed as a manifestation of the chiral vortical effect.

Olivier Carton

In this paper, we establish a strong link between the ambiguity for finite words of a B\"uchi automaton and the ambiguity for infinite words of the same automaton. This link is based on measure theory. More precisely, we show that such an automaton is unambiguous, in the sense that no finite word labels two runs with the same starting state and the same endi

Ilaria Musella, Marcella Marconi, Roberto Molinaro, Giuliana Fiorentino

Ultra Long Period Cepheids (ULPs) are pulsating variable stars with a period longer than 80d and have been hypothesized to be the extension of the Classical Cepheids (CCs) at higher masses and luminosities. If confirmed as standard candles, their intrinsic luminosities, 1 to 3 mag brighter than typical CCs, would allow to reach the Hubble flow and, in turn,

M. Battaglieri, P. Bisio, M. Bondí, A. Celentano

This paper describes the design and performance of a compact detector, BDX-MINI, that incorporates all features of a concept that optimized the detection of light dark matter produced by electrons in a beam dump. It represents a reduced version of the future BDX experiment expected to run at JLAB. BDX-MINI was exposed to penetrating particles produced by a 2

T. Lizée, B. Vollmer, J. Braine, F. Nehlig

NGC 4654 is a Virgo galaxy seen almost face-on, which undergoes nearly edge-on gas ram pressure stripping and a fly-by gravitational interaction with another massive galaxy, NGC 4639. NGC 4654 shows a strongly compressed gas region near the outer edge of the optical disk, with HI surface densities (HSDR), exceeding the canonical value of 10-15 Msun/pc2. New

Alexey Uvarov, Jacob Biamonte

Variational quantum algorithms rely on gradient based optimization to iteratively minimize a cost function evaluated by measuring output(s) of a quantum processor. A barren plateau is the phenomenon of exponentially vanishing gradients in sufficiently expressive parametrized quantum circuits. It has been established that the onset of a barren plateau regime

Iman Habibi, Effat S Emamian, Osvaldo Simeone, Ali Abdi

Due to structural and functional abnormalities or genetic variations and mutations, there may be dysfunctional molecules within an intracellular signaling network that do not allow the network to correctly regulate its output molecules, such as transcription factors. This disruption in signaling interrupts normal cellular functions and may eventually develop

Paritosh Verma

This work concerns with proving space lower bounds for graph problems in the streaming model. It is known that computing the length of shortest path between two nodes in the streaming model requires $\Omega(n)$ space, where $n$ is the number of nodes in the graph. We study the problem of finding the depth of a given node in a rooted tree in the streaming mod

Tae Jin Park, Manoj Kumar, Shrikanth Narayanan

Identifying the identity of the speaker of short segments in human dialogue has been considered one of the most challenging problems in speech signal processing. Speaker representations of short speech segments tend to be unreliable, resulting in poor fidelity of speaker representations in tasks requiring speaker recognition. In this paper, we propose an unc

H. R. A. Jones, W. E. Martin, G. Anglada-Escudé, R. Errmann

We present the design and testing of a prototype in-plane echelle spectrograph based on an actively controlled fibre-fed double-pass design. This system aims to be small and efficient with the minimum number of optical surfaces - currently a collimator/camera lens, cross-dispersing prism, grating and a reflector to send light to the detector. It is built fro

Richa Kundu, Camila Navarrete, José G. Fernández-Trincado, Dante Minniti

Context. Extratidal stars are stellar bodies that end up outside the tidal radius of a cluster as a result of internal processes or external forces acting upon it. The presence and spatial distribution of these stars can give us insights into the past evolution of a cluster inside our Galaxy. Aims. Previous works suggest that globular clusters, when explored

Chong Huang, Gaojie Chen, Yu Gong

This paper investigates the reinforcement learning for the relay selection in the delay-constrained buffer-aided networks. The buffer-aided relay selection significantly improves the outage performance but often at the price of higher latency. On the other hand, modern communication systems such as the Internet of Things often have strict requirement on the

James Dawber, Nicola Salvati, Timo Schmid, Nikos Tzavidis

M-quantile regression is a general form of quantile-like regression which usually utilises the Huber influence function and corresponding tuning constant. Estimation requires a nuisance scale parameter to ensure the M-quantile estimates are scale invariant, with several scale estimators having previously been proposed. In this paper we assess these scale est

Weina Wang, Qiaomin Xie, Mor Harchol-Balter

Cloud computing today is dominated by multi-server jobs. These are jobs that request multiple servers simultaneously and hold onto all of these servers for the duration of the job. Multi-server jobs add a lot of complexity to the traditional one-job-per-server model: an arrival might not "fit" into the available servers and might have to queue, blocking late

Hugo Tessier, Vincent Gripon, Mathieu Léonardon, Matthieu Arzel

Introduced in the late 1980s for generalization purposes, pruning has now become a staple for compressing deep neural networks. Despite many innovations in recent decades, pruning approaches still face core issues that hinder their performance or scalability. Drawing inspiration from early work in the field, and especially the use of weight decay to achieve

Tabea Glatzel, Jan Nagel

In this paper we consider random walks on Galton-Watson trees with random conductances. On these trees, the distance of the walker to the root satisfies a law of large numbers with limit the effective velocity, or speed of the walk. We study the regularity of the speed as a function of the distribution of conductances, in particular when the distribution of

Amanuel Alambo, Swati Padhee, Tanvi Banerjee, Krishnaprasad Thirunarayan

COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the ano

Emma Shen, Dominic Anstey, Eloy de Lera Acedo, Anastasia Fialkov

We modelled the two major layer of Earth's ionosphere, the F-layer and the D-layer, by a simplified spatial model with temporal variance to study the chromatic ionospheric effects on global 21-cm observations. From the analyses, we found that the magnitude of the ionospheric disruptions due to ionospheric refraction and absorption can be greater than the exp

Theresa Lange, Wilhelm Stannat

Consider the class of Ensemble Square Root filtering algorithms for the numerical approximation of the posterior distribution of nonlinear Markovian signals partially observed with linear observations corrupted with independent measurement noise. We analyze the asymptotic behavior of these algorithms in the large ensemble limit both in discrete and continuou

Atul Pokharel, Robert Soulé, Avi Silberschatz

We present an evaluation of the effectiveness of manual contact tracing compared to bulletin board contact tracing. We show that bulletin board contact tracing gives comparable results in terms of the reproductive number, duration, prevalence and incidence but is less resource intensive, easier to implement and offers a wider range of privacy options. Classi

Rahav Gowtham Venkateswaran, Ursula Kowalsky, Dieter Dinkler

Particle based methods such as the Discrete Element Method and the Lattice Spring Method may be used for describing the behaviour of isotropic linear elastic materials. However, the common bond models employed to describe the interaction between particles restrict the range of Poisson's ratio that can be represented. In this paper, to overcome the restrictio

Karen V. Hovhannisyan, Mathias R. Jørgensen, Gabriel T. Landi, Álvaro M. Alhambra

Precise thermometry for quantum systems is important to the development of new technology, and understanding the ultimate limits to precision presents a fundamental challenge. It is well known that optimal thermometry requires projective measurements of the total energy of the sample. However, this is infeasible in even moderately-sized systems, where realis

D. A. Forsyth, Jason J. Rock

Intrinsic image decomposition is the classical task of mapping image to albedo. The WHDR dataset allows methods to be evaluated by comparing predictions to human judgements ("lighter", "same as", "darker"). The best modern intrinsic image methods learn a map from image to albedo using rendered models and human judgements. This is convenient for practical met

Matthew Shelley, Alessandro Pastore

We investigated the role of a pairing correlation in the chemical composition of the inner crust of a neutron star with the extended Thomas-Fermi method, using the Strutinsky integral correction. We compare our results with the fully self-consistent Hartree-Fock-Bogoliubov approach, showing that the resulting discrepancy, apart from the very low density regi

M Quamer Nasim, Tannistha Maiti, Ayush Srivastava, Tarry Singh

Deep neural networks (DNNs) can learn accurately from large quantities of labeled input data, but often fail to do so when labelled data are scarce. DNNs sometimes fail to generalize ontest data sampled from different input distributions. Unsupervised Deep Domain Adaptation (DDA)techniques have been proven useful when no labels are available, and when distri

Melvyn Weeks, Tobias Gabel Christiansen

Various poverty reduction strategies are being implemented in the pursuit of eliminating extreme poverty. One such strategy is increased access to microcredit in poor areas around the world. Microcredit, typically defined as the supply of small loans to underserved entrepreneurs that originally aimed at displacing expensive local money-lenders, has been both

Yue Hao, Weilin Guan, Edwin A Peraza Hernandez, Jyh-Ming Lien

Designing a robot or structure that can fold itself into a target shape is a process that involves challenges originated from multiple sources. For example, the designer of rigid self-folding robots must consider foldability from geometric and kinematic aspects to avoid self-intersection and undesired deformations. Recent works have shown success in estimati

Tasio Gonzalez-Raya, Rodrigo Asensio-Perea, Ana Martin, Lucas C. Céleri

Digital-analog quantum computation aims to reduce the currently infeasible resource requirements needed for near-term quantum information processing by replacing sequences of one- and two-qubit gates with a unitary transformation generated by the systems' underlying Hamiltonian. Inspired by this paradigm, we consider superconducting architectures and extend

F. Parvin, M. A. Hossain, M. I. Ahmed, K. Akter

We have explored the mechanical, electronic, optical and thermoelectric properties of p-type half-Heusler compound BaAgP for the first time using density functional theory based calculations. The mechanical and dynamical stability of this compound is confirmed by studying the Born stability criteria and phonon dispersion curve, respectively. It is soft, duct

Leonid Mill, David Wolff, Nele Gerrits, Patrick Philipp

Nanoparticles occur in various environments as a consequence of man-made processes, which raises concerns about their impact on the environment and human health. To allow for proper risk assessment, a precise and statistically relevant analysis of particle characteristics (such as e.g. size, shape and composition) is required that would greatly benefit from

Júlio C. Fabris, Oliver F. Piattella, Davi C. Rodrigues

Rastall introduced a stress-energy tensor whose divergence is proportional to the gradient of the Ricci scalar. This proposal leads to a change in the form of the field equations of General Relativity, but it preserves the number of degrees of freedom. Rastall's field equations can be either interpreted as GR with a redefined SET, or it can imply different p

Paolo Braca, Domenico Gaglione, Stefano Marano, Leonardo M. Millefiori

This paper develops an easily-implementable version of Page's CUSUM quickest-detection test, designed to work in certain composite hypothesis scenarios with time-varying data statistics. The decision statistic can be cast in a recursive form and is particularly suited for on-line analysis. By back-testing our approach on publicly-available COVID-19 data we f

Diego Vicencio, Olga Vasilieva, Pedro Gajardo

In this paper, we propose a simplified bidimensional Wolbachia infestation model in a population of Aedes aegypti mosquitoes, preserving the main features associated with the biology of this species that can be found in higher-dimensional models. Namely, our model represents the maternal transmission of the Wolbachia symbiont, expresses the reproductive phen

Haakon Andresen, Robert Glas, H-Thomas Janka

We compare gravitational-wave (GW) signals from eight three-dimensional simulations of core-collapse supernovae, using two different progenitors with zero-age main sequence masses of 9 and 20 solar masses. The collapse of each progenitor was simulated four times, at two different grid resolutions and with two different neutrino transport methods, using the A

Artem Kaznatcheev, Prakash Panangaden

We show that weighted automata over the field of two elements can be exponentially more compact than non-deterministic finite state automata. To show this, we combine ideas from automata theory and communication complexity. However, weighted automata are also efficiently learnable in Angluin's minimal adequate teacher model in a number of queries that is pol

Ricardo Pérez-Marco

We find an explicit general formula for the iterated local monodromy of singularities of the Hadamard product of functions with integrable singularities. The formula implies the invariance by Hadamard product of the class of functions with integrable singularities with recurrent monodromies. In particular, it implies the recurrence of the local monodromy of

Hussein Sibai, Sayan Mitra

We extend the notion of estimation entropy of autonomous dynamical systems proposed by Liberzon and Mitra [1] to nonlinear dynamical systems with uncertain inputs with bounded variation. We call this new notion the {$\epsilon$}-estimation entropy of the system and show that it lower bounds the bit rate needed for state estimation. {$\epsilon$}-estimation ent

Qi-Nan Wang, Wei Chen, Hua-Xing Chen

We have calculated the mass spectra for the $\bar{D}_s^{(*)}D^{(*)}$ molecular states and $sc\bar q\bar c$ tetraquark states with $J^P=0^+, 1^+, 2^+$. The masses of the axial-vector $\bar{D}_sD^{*}$, $\bar{D}_s^{*}D$ molecular states and $\mathbf{1}_{[sc]} \oplus \mathbf{0}_{[\bar q \bar{c}]}$, $\mathbf{0}_{[sc]} \oplus \mathbf{1}_{[\bar q \bar{c}]}$ tetraqu

Neil R. Sheeley

This paper describes a mathematical model for the spread of a virus through an isolated population of a given size. The model uses three, color-coded components, called molecules (red for infected and still contagious; green for infected, but no longer contagious; and blue for uninfected). In retrospect, the model turns out to be a digital analogue for the w

Sevag Abadian, Giovanni Magno, Vy Yam, Béatrice Dagens

Optical isolator remains one of the main missing elements for photonic integrated circuits despite several decades of research. The best solutions up to now are based on transverse magneto-optical effect using either narrow-band resonators or high-gyrotropy magneto-optical materials with difficult integration on usual photonic platforms. We propose in this p

Thai Le, Noseong Park, Dongwon Lee

The Universal Trigger (UniTrigger) is a recently-proposed powerful adversarial textual attack method. Utilizing a learning-based mechanism, UniTrigger generates a fixed phrase that, when added to any benign inputs, can drop the prediction accuracy of a textual neural network (NN) model to near zero on a target class. To defend against this attack that can ca

Lorenzo Panebianco

We investigate some analytical properties of loop group models, showing that a Positive Energy Representation (PER) of a loop group $LG$ can be extended to a PER of $H^{3/2}(S^1,G)$ for any compact, simple and simply connected Lie group $G$. We then explicitly compute the adjoint action of $H^{5/2}(S^1,G)$ on the stress energy tensor and we use these results

A. Y. Potekhin, G. Chabrier

We study the effect of physics input on thermal evolution of neutron stars in soft X-ray transients (SXTs). In particular, we consider different modern models of the sources of deep crustal heating during accretion episodes and the effects brought about by impurities embedded in the crust during its formation. We simulate thermal structure and evolution of e

Chiara Pinto

Recent results on the production of light nuclei, including deuterons, tritons, $^3$He, $^4$He and the corresponding antinuclei in Pb-Pb collisions at $\sqrt{s_{\mathrm{NN}}}$ = 5.02 TeV are presented and compared with theoretical predictions to provide insight into their production mechanisms in heavy-ion collisions. The large variety of measurements perfor

Corey Williams, Adam Schroeder

ROS (Robot Operating System) has become ubiquitous for testing new algorithms, alternative hardware configurations, and prototyping. By performing research with its modular framework, it can streamline sharing new work and integrations. However, it has many features and new terms that can take a considerable amount of time to learn for a new user. This paper

Jiahui Yu, Konstantinos Spiliopoulos

We consider shallow (single hidden layer) neural networks and characterize their performance when trained with stochastic gradient descent as the number of hidden units $N$ and gradient descent steps grow to infinity. In particular, we investigate the effect of different scaling schemes, which lead to different normalizations of the neural network, on the ne

Özgün Çiçek, Yassine Marrakchi, Enoch Boasiako Antwi, Barbara Di Ventura

Deploying off-the-shelf segmentation networks on biomedical data has become common practice, yet if structures of interest in an image sequence are visible only temporarily, existing frame-by-frame methods fail. In this paper, we provide a solution to segmentation of imperfect data through time based on temporal propagation and uncertainty estimation. We int

Pál András Papp, Roger Wattenhofer

We consider financial networks, where banks are connected by contracts such as debts or credit default swaps. We study the clearing problem in these systems: we want to know which banks end up in a default, and what portion of their liabilities can these defaulting banks fulfill. We analyze these networks in a sequential model where banks announce their defa

H. Zhao, M. Schultheis, A. Recio-Blanco, G. Kordopatis

We developed a set of procedures to automatically detect and measure the DIB around 8620 {\AA} (the Gaia DIB) for a wide range of temperatures. The DIB profile is fit with a Gaussian function. Specifically, the DIB feature is extracted from the spectra of late-type stars by subtracting the corresponding synthetic spectra. For early-type stars we applied a sp

P. Wójcik, A. Bertoni, G. Goldoni

We use the $\mathbf{k} \cdot \mathbf{p}$ theory and the envelope function approach to evaluate the Rashba spin-orbit coupling induced in a semiconductor nanowire by a magnetic field at different orientations, taking explicitely into account the prismatic symmetry of typical nano-crystals. We make the case for the strongly spin-orbit-coupled InAs semiconducto

A. Carpio, E. Cebrian

Hypoxy induced angiogenesis processes can be described coupling an integrodifferential kinetic equation of Fokker-Planck type with a diffusion equation for the angiogenic factor. We propose high order positivity preserving schemes to approximate the marginal tip density by combining an asymptotic reduction with weighted essentially non oscillatory and strong

Zhongyang Li, Fei Lu

In the learning of systems of interacting particles or agents, coercivity condition ensures identifiability of the interaction functions, providing the foundation of learning by nonparametric regression. The coercivity condition is equivalent to the strictly positive definiteness of an integral kernel arising in the learning. We show that for a class of inte

R. Mendez Rojano, M. Zhussupbekov, J. F. Antaki

As pump thrombosis is reduced in current-generation ventricular assist devices (VAD), adverse events such as bleeding or stroke remain at unacceptable rates. Thrombosis around the VAD inlet cannula (IC) has been highlighted as a possible source of stroke events. Recent computational fluid dynamics (CFD) studies have attempted to characterize the thrombosis r

Grigorios G. Anagnostopoulos, Alexandros Kalousis

The primary expectation from positioning systems is for them to provide the users with reliable estimates of their position. An additional piece of information that can greatly help the users utilize position estimates is the level of uncertainty that a positioning system assigns to the position estimate it produced. The concept of dynamically estimating the

Nik Cunniffe, Frédéric Hamelin, Abderrahman Iggidr, Alain Rapaport

In this review, we recall the concepts of Identifiability and Observability of dynamical systems, and analyse them in the framework of Mathematical Epidemiology. We show that, even for simple and well known models of the literature, these properties are not always fulfilled. We then consider the problem of practical identifiability and observability, which a

Chenyang Xu

We give a survey of the recent progress on the study of K-stability of Fano varieties by an algebro-geometric approach.

Charanpreet Singh, Vikram Singh, Gyandeep Pradhan, Velaga Srihari

Here, we present a detailed theoretical and experimental study on the pressure induced switching of anomalous Hall effect (AHE) in the triangular antiferromagnetic (AFM) compound Mn$_3$Sn. Our theoretical model suggests pressure driven significant splitting of the in-plane Mn bond lengths $i.e.$ an effective trimerization, which in turn stabilizes a helical

Eunju Cha, Chanseok Lee, Mooseok Jang, Jong Chul Ye

Fourier phase retrieval is a classical problem of restoring a signal only from the measured magnitude of its Fourier transform. Although Fienup-type algorithms, which use prior knowledge in both spatial and Fourier domains, have been widely used in practice, they can often stall in local minima. Modern methods such as PhaseLift and PhaseCut may offer perform

L. Varotto, A. Cenedese, A. Cavallaro

Active Search and Tracking for search and rescue missions or collaborative mobile robotics relies on the actuation of a sensing platform to detect and localize a target. In this paper we focus on visually detecting a radio-emitting target with an aerial robot equipped with a radio receiver and a camera. Visual-based tracking provides high accuracy, but the d

Israa Khaled, Charlotte Langlais, Ammar Falou, Bachar Elhassan

In millimeter-wave communication, digital beamsteering (DBS), only based on the user direction, is a promising angle-domain multi-antenna technique to mitigate the severe path loss and multiuser interference, with low-complexity and partial channel state information (CSI). In this paper, we design a power-domain non-orthogonal multiple access (NOMA) scheme t

Sam Davis, Giuseppe Coccia, Sam Gooch, Julian Mack

WaveNet is a state-of-the-art text-to-speech vocoder that remains challenging to deploy due to its autoregressive loop. In this work we focus on ways to accelerate the original WaveNet architecture directly, as opposed to modifying the architecture, such that the model can be deployed as part of a scalable text-to-speech system. We survey a wide variety of m

Jen-Tsung Hsiang, B. L. Hu

A definition of nonequilibrium free energy $\mathcal{F}_{\textsc{s}}$ is proposed for dynamical Gaussian quantum open systems strongly coupled to a heat bath and a formal derivation is provided by way of the generating functional in terms of the coarse-grained effective action and the influence action. For Gaussian open quantum systems exemplified by the qua

Connie H. Mousatov, Sean A. Hartnoll

The room temperature thermal diffusivity of high T$_c$ materials is dominated by phonons. This allows the scattering of phonons by electrons to be discerned. We argue that the measured strength of this scattering suggests a converse Planckian scattering of electrons by phonons across the room temperature phase diagram of these materials. Consistent with this

Wu Kehe, Chen Zuge, Zhang Xiaoliang, Li Wei

RetinaNet proposed Focal Loss for classification task and improved one-stage detectors greatly. However, there is still a gap between it and two-stage detectors. We analyze the prediction of RetinaNet and find that the misalignment of classification and localization is the main factor. Most of predicted boxes, whose IoU with ground-truth boxes are greater th

Xinyi Xu, Lingjuan Lyu

Federated learning (FL) is an emerging practical framework for effective and scalable machine learning among multiple participants, such as end users, organizations and companies. However, most existing FL or distributed learning frameworks have not well addressed two important issues together: collaborative fairness and adversarial robustness (e.g. free-rid

D. D. Cherkashin, A. S. Gordeev, G. A. Strukov, Y. I. Teplitskaya

Fix a compact $M \subset \mathbb{R}^2$ and $r>0$. A minimizer of the maximal distance functional is a connected set $\Sigma$ of the minimal length, such that \[ max_{y \in M} dist(y,\Sigma) \leq r. \] The problem of finding maximal distance minimizers is connected to the Steiner tree problem. In this paper we consider the case of a convex closed curve $M$, w

Debdas Ghosha, Amit Kumar Debnath, Ram Surat Chauhan, Oscar Castillo

This article proposes a general gH-gradient efficient-direction method and a W-gH-gradient efficient method for the optimization problems with interval-valued functions. The convergence analysis and the step-wise algorithms of both the methods are presented. It is observed that the W-gH-gradient efficient method converges linearly for a strongly convex inter

Konrad Tschernig, Alvaro Jimenez-Galan, Demetrios N. Christodoulides, Misha Ivanov

Topological insulators combine insulating properties in the bulk with scattering-free transport along edges, supporting dissipationless unidirectional energy and information flow even in the presence of defects and disorder. The feasibility of engineering quantum Hamiltonians with photonic tools, combined with the availability of entangled photons, raises th

Michael Wiemeler

We study locally standard $T^k$-manifolds $M$. In particular, we study the case where there is a continuous section to the orbit map $\pi : M \rightarrow M/T$. We give a classification of $T^k$-manifolds satisfying these conditions up to equivariant diffeomorphism.

Doriann Blain, Benjamin Charnay, Bruno Bézard

The atmospheric composition of exoplanets with masses between 2 and 10 M$_\oplus$ is poorly understood. In that regard, the sub-Neptune K2-18b, which is subject to Earth-like stellar irradiation, offers a valuable opportunity for the characterisation of such atmospheres. Previous analyses of its transmission spectrum from the Kepler, Hubble (HST), and Spitze

Raffaella Mulas, Nathan Reff

A complex unit hypergraph is a hypergraph where each vertex-edge incidence is given a complex unit label. We define the adjacency, incidence, Kirchoff Laplacian and normalized Laplacian of a complex unit hypergraph and study each of them. Eigenvalue bounds for the adjacency, Kirchoff Laplacian and normalized Laplacian are also found. Complex unit hypergraphs