December 2020 arXiv papers — page 94

Mohammed Rashid, Mort Naraghi-Pour

We study the problem of downlink channel estimation in multi-user massive multiple input multiple output (MIMO) systems. To this end, we consider a Bayesian compressive sensing approach in which the clustered sparse structure of the channel in the angular domain is employed to reduce the pilot overhead. To capture the clustered structure, we employ a conditi

Azeem Ahmad, Vishesh Dubey, Nikhil Jayakumar, Anowarul Habib

High space-bandwidth product with high spatial phase sensitivity is indispensable for a single-shot quantitative phase microscopy (QPM) system. It opens avenue for widespread applications of QPM in the field of biomedical imaging. Temporally low coherence length light sources are generally implemented to achieve high spatial phase sensitivity in QPM at the c

Ernst Eberlain, Yuri Kabanov, Thorsten Schmidt

We study a Sparre Andersen model in which the business activity of the company is described by a compound renewal process with drift assuming that the capital reserves are invested in a risky asset. The price of the latter is assumed to evolve according to a geometric L\'evy process. We prove that the asymptotic behavior of the ruin probability depends to a

Gabriele Umbriaco

In the last years, the Observatory of Padova (Istituto Nazionale di Astrofisica - Osservatorio Astronomico di Padova) and the University of Padova have been involved massively in projects dedicated to the exoplanets search, both ground, and space-based. The activities concerning my Ph.D. have been exploited both in the framework of the space projects and in

Radim Pánis, Martin Kološ, Zdeněk Stuchlík

Deterministic chaos is phenomenon from nonlinear dynamics and it belongs to greatest advances of twentieth-century science. Chaotic behavior appears apart of mathematical equations also in wide range in observable nature, so as in there originating time series. Chaos in time series resembles stochastic behavior, but apart of randomness it is totally determin

Yuya Jeremy Ong, Yi Zhou, Nathalie Baracaldo, Heiko Ludwig

Federated Learning (FL) is an approach to collaboratively train a model across multiple parties without sharing data between parties or an aggregator. It is used both in the consumer domain to protect personal data as well as in enterprise settings, where dealing with data domicile regulation and the pragmatics of data silos are the main drivers. While gradi

Stefano Markidis, Vyacheslav Olshevsky, Gabor Toth, Yuxi Chen

This paper presents the state of the art of kinetic modeling techniques for simulating plasma kinetic dynamics in magnetospheres. We describe the critical numerical techniques for enabling large-scale kinetic simulations of magnetospheres: parameter scaling, implicit Particle-in-Cell schemes, and fluid-kinetic coupling. We show an application of these techni

Mohammad N. Murshed, M. Monir Uddin

Dynamic Mode Decomposition (DMD) is a data based modeling tool that identifies a matrix to map a quantity at some time instant to the same quantity in future. We design a new version which we call Adaptive Dynamic Mode Decomposition (ADMD) that utilizes time delay coordinates, projection methods and filters as per the nature of the data to create a model for

W. A. Rojas C., J. R. Arenas S

A Black Hole (BH) is a spacetime region with a horizon and where geodesics converge to a singularity. At such a point, the gravitational field equations fail. As an alternative to the problem of the singularity arises the existence of Exotic Compact Objects (ECOs) that prevent the problem of the singularity through a transition phase of matter once it has cr

Christopher Caruvana, Jared Holshouser

In this paper we connect selection principles on a topological space to corresponding selection principles on one of its hyperspaces. We unify techniques and generalize theorems from the known results about selection principles for common hyperspace constructions. This includes results of Lj.D.R. Ko\v{c}inac, Z. Li, and others. We use selection games to gene

Kelvin Kan, James G Nagy, Lars Ruthotto

We demonstrate the ability of hybrid regularization methods to automatically avoid the double descent phenomenon arising in the training of random feature models (RFM). The hallmark feature of the double descent phenomenon is a spike in the regularization gap at the interpolation threshold, i.e. when the number of features in the RFM equals the number of tra

Mohammad Khodaei, Panos Papadimitratos

Vehicular communications disclose rich information about the vehicles and their whereabouts. Pseudonymous authentication secures communication while enhancing user privacy. To enhance location privacy, cryptographic mix-zones were proposed to facilitate vehicles covertly transition to new ephemeral credentials. The resilience to (syntactic and semantic) pseu

Carlos Marín, Jorge poveda

Higher order corrections are obtained for the perihelion precession in binary systems like OJ287, Sagittarius A*-S2 and H1821+643 using both the Schwarzschild metric and the Kerr metric to take into account the spin effect. The corrections are performed considering the third root of the motion equation and developing the expansion in terms of $\epsilon \equi

Adam Subel, Ashesh Chattopadhyay, Yifei Guan, Pedram Hassanzadeh

Developing data-driven subgrid-scale (SGS) models for large eddy simulations (LES) has received substantial attention recently. Despite some success, particularly in a priori (offline) tests, challenges have been identified that include numerical instabilities in a posteriori (online) tests and generalization (i.e., extrapolation) of trained data-driven SGS

Wanli Ma, Alin Achim, Oktay Karakuş

In this paper, we analyse synthetic aperture radar (SAR) images of the sea surface using an inverse problem formulation whereby Radon domain information is enhanced in order to accurately detect ship wakes. This is achieved by promoting linear features in the images. For the inverse problem-solving stage, we propose a penalty function, which combines the dua

Wenhao Yu, C. Karen Liu, Greg Turk

Being able to transfer existing skills to new situations is a key capability when training robots to operate in unpredictable real-world environments. A successful transfer algorithm should not only minimize the number of samples that the robot needs to collect in the new environment, but also prevent the robot from damaging itself or the surrounding environ

Érica Z. Fornaroli, Mykola Khrypchenko, Ednei A. Santulo

Let $X$ be a finite connected poset and $K$ a field. We give a full description of the Lie automorphisms of the incidence algebra $I(X,K)$. In particular, we show that they are in general not proper.

Xinye Chen

Graph neural networks have developed by leaps and bounds in recent years due to the restriction of traditional convolutional filters on non-Euclidean structured data. Spectral graph theory mainly studies fundamental graph properties using algebraic methods to analyze the spectrum of the adjacency matrix or Laplacian matrix of a graph, which lays the foundati

Shaoshi Ling, Yuzong Liu

Recent success in speech representation learning enables a new way to leverage unlabeled data to train speech recognition model. In speech representation learning, a large amount of unlabeled data is used in a self-supervised manner to learn a feature representation. Then a smaller amount of labeled data is used to train a downstream ASR system using the new

Pietro Borrello, Emilio Coppa, Daniele Cono D'Elia

Largely known for attack scenarios, code reuse techniques at a closer look reveal properties that are appealing also for program obfuscation. We explore the popular return-oriented programming paradigm under this light, transforming program functions into ROP chains that coexist seamlessly with the surrounding software stack. We show how to build chains that

Oktay Karakuş, Igor Rizaev, Alin Achim

The analysis of ocean surface is widely performed using synthetic aperture radar (SAR) imagery as it yields information for wide areas under challenging weather conditions, during day or night, etc. Speckle noise constitutes however the main reason for reduced performance in applications such as classification, ship detection, target tracking and so on. This

Siddharth Mysore, Bassel Mabsout, Kate Saenko, Renato Mancuso

We focus on the problem of reliably training Reinforcement Learning (RL) models (agents) for stable low-level control in embedded systems and test our methods on a high-performance, custom-built quadrotor platform. A common but often under-studied problem in developing RL agents for continuous control is that the control policies developed are not always smo

Charles Paulino de Oliveira, Elisangela Martins de Sá, Flávio Vinícius Cruzeiro Martins

This work aims to apply the Facility Location Problem in the Emergency Medical Service (EMS) of Belo Horizonte, Brazil. The objective is to improve two previous optimization models from literature to handle base locations and ambulances allocation/relocation problems. The proposed multi-period models introduce the concept of relocation to the local EMS, whic

Souza Marisa

The concept of polytopes was a milestone in elementary integral group theory. In this article, we will extend the concept of contra-linearly stochastic lines to H-Positive Definite Monoids. We will show that by adding the Non-Gaussian assumption, the problem of ordinary Elementary Numerical Operator will have Sub-Canonically properties. Moreover, we will dis

M. Catacora-Rios, G. B. King, A. E. Lovell, F. M. Nunes

Background: Modern statistical tools provide the ability to compare the information content of observables and provide a path to explore which experiments would be most useful to give insight into and constrain theoretical models. Purpose: In this work we study three such tools in the context of nuclear reactions with the goal of constraining the optical pot

Stefano Guarino, Enrico Mastrostefano, Massimo Bernaschi, Alessandro Celestini

The emergence of social networks and the definition of suitable generative models for synthetic yet realistic social graphs are widely studied problems in the literature. By not being tied to any real data, random graph models cannot capture all the subtleties of real networks and are inadequate for many practical contexts -- including areas of research, suc

Sophia Epstein, Pavel Naumov

The paper suggests a definition of "know who" as a modality using Grove-Halpern semantics of names. It also introduces a logical system that describes the interplay between modalities "knows who", "knows", and "for all agents". The main technical result is a completeness theorem for the proposed system.

Manyi Li, Hao Zhang

We present the first single-view 3D reconstruction network aimed at recovering geometric details from an input image which encompass both topological shape structures and surface features. Our key idea is to train the network to learn a detail disentangled reconstruction consisting of two functions, one implicit field representing the coarse 3D shape and the

L. Mark W. Leggett, David. A. Ball

Two future scenarios that are not explicitly in the range of scenarios (the Representative Concentration Pathway scenarios) utilised by the IPCC. These two scenarios are the emissions trend under peak fossil fuel (for example, Mohr et al., 2015); and the climate sensitivity determinable from the relationship between first-difference CO2 and temperature recen

Pranav Hanagal, Kevin Leder, Zicheng Wang

We study large deviation events in the timing of disease recurrence. In particular, we are interested in modeling cancer treatment failure due to mutation-induced drug resistance. We first present a two-type branching process model of this phenomenon, where an initial population of cells that are sensitive to therapy can produce mutants that are resistant to

Utkarsh Verma, Narayan Rangaraj

Kidney exchange programs have been developed to overcome the compatibility challenges for patients with incompatible donors in kidney transplantation. A registry of such incompatible donor-recipient pairs is created, and compatibility is achieved through the exchange of donors. Single-center kidney exchange registries do not have a significant pool size for

Andrew Kassen, Varun Shankar, Aaron L Fogelson

We present new algorithms for the parallelization of Eulerian-Lagrangian interaction operations in the immersed boundary method. Our algorithms rely on two well-studied parallel primitives: key-value sort and segmented reduce. The use of these parallel primitives allows us to implement our algorithms on both graphics processing units (GPUs) and on other shar

Manuel Lopez Galvan

The aim of this paper is to investigate the use of close formula approximation for pricing European mortgage options. Under the assumption of logistic duration and normal mortgage rates the underlying price at the option expiry is approximated by shifted lognormal or regular lognormal distribution by matching moments. Once the price function is approximated

Siddharth Mysore, Bassel Mabsout, Renato Mancuso, Kate Saenko

A critical problem with the practical utility of controllers trained with deep Reinforcement Learning (RL) is the notable lack of smoothness in the actions learned by the RL policies. This trend often presents itself in the form of control signal oscillation and can result in poor control, high power consumption, and undue system wear. We introduce Condition

Karla. Z. Arellano-Córdova, César Esteban, Jorge García-Rojas, J. Eduardo Méndez-Delgado

We present optical spectra of nine Galactic H II regions observed with the 10.4 m Gran Telescopio Canarias telescope and located at Galactocentric distances (RG) from 4 to 8 kpc. The distances of the objects have been revised using Gaia DR2 parallaxes. We determine the electron temperature for all the nebulae, which allows a precise computation of their ioni

Igor Tsukerman

Electrostatic interactions in solvents play a major role in biophysical systems. There is a consensus in the literature that the dielectric response of aqueous solutions is nonlocal: polarization depends on the electric field not only at a given point but in the vicinity of that point as well. This is typically modeled via a convolution of the electric field

Jiayin Dong, Yan-Fei Jiang, Phil Armitage

Gas giant planets are expected to accrete most of their mass via a circumplanetary disk. If the planet is unmagnetized and initially slowly rotating, it will accrete gas via a radially narrow boundary layer and rapidly spin up. Radial broadening of the boundary layer as the planet spins up reduces the specific angular momentum of accreted gas, allowing the p

Yuanjie Chen, Shaoyun Huang, Dong Pan, Jianhong Xue

A dual-gate InSb nanosheet field-effect device is realized and is used to investigate the physical origin and the controllability of the spin-orbit interaction in a narrow bandgap semiconductor InSb nanosheet. We demonstrate that by applying a voltage over the dual gate, efficiently tuning of the spin-orbit interaction in the InSb nanosheet can be achieved.

S. V. Ludkowski

In the article random functions in modules over the octonion algebra and Cayley-Dickson algebras are investigated. For their study transition measures with values in the octonion algebra and Cayley-Dickson algebras are used. Stochastic integrals over these algebras are studied. They are applied to integration of stochastic PDEs. This approach permits subsequ

Edward Hermann Haeusler

A previous article shows that any linear height bounded normal proof of a tautology in the Natural Deduction for Minimal implicational logic $M_{\supset}$ is as huge as it is redundant. More precisely, any proof in a family of super-polynomially sized and linearly height bounded proofs have a sub-derivation that occurs super-polynomially many times in it. In

N. Jovanovic, B. Calvin, M. Porter, T. Schofield

The Keck Planet Imager and Characterizer (KPIC) is a purpose-built instrument for high-dispersion coronagraphy in the K and L bands on Keck. This instrument will provide the first high resolution (R$>$30,000) spectra of known directly imaged exoplanets and low-mass brown dwarf companions visible in the northern hemisphere. KPIC is developed in phases. Phase

Shinsuke Kawai, Nobuchika Okada, Satomi Okada

A scalar field having the Coleman-Weinberg type effective potential arises in various contexts of particle physics and serves as a useful framework for discussing cosmic inflation. According to recent studies based on the Markov chain Monte Carlo analysis, the coefficients of such an effective potential are severely constrained by the cosmological data. We i

Sergey V. Ludkowski

In this article smashed products of topological left quasigroups are scrutinized. Quotients of topological fan quasigroups are investigated. Skew smashed products of fan quasigroups and their structure also are studied.

Yufeng Luo, Roland Haas, Qian Zhang, Gabrielle Allen

Data sharing is essential in the numerical simulations research. We introduce a data repository, DataVault, that is designed for data sharing, search and analysis. A comparative study of existing repositories is performed to analyze features that are critical to a data repository. We describe the architecture, workflow, and deployment of DataVault, and provi

Javier Galan

Axions are a natural consequence of the Peccei-Quinn mechanism, the most compelling solution to the strong-CP problem. Similar axion-like particles (ALPs) also appear in a number of possible extensions of the Standard Model, notably in string theories. Both axions and ALPs are very well motivated candidates for Dark Matter, and in addition, they would be cop

Susanne Menden-Deuer, Medet Nursultanov, Sinead Collins, Tatiana Rynearson

Why, contrary to theoretical predictions, do marine microbe communities harbor tremendous phenotypic heterogeneity? How can so many marine microbe species competing in the same niche coexist? We discovered a unifying explanation for both phenomena by investigating a non-cooperative game that interpolates between individual-level competitions and species-leve

Xiang Li, Rebecca Boll, Daniel Rolles, Artem Rudenko

A simple model for sequential multiphoton ionization by ultra-intense x-rays is presented. The derived scaling of the ion yield with pulse energy quantitatively reproduces the experimental data, which shows that the ion yield increases according to the "power law" behavior typical of multiphoton ionization, followed by saturation at high pulse energies. The

Carlo Marconi, Albert Aloy, Jordi Tura, Anna Sanpera

Entanglement in symmetric quantum states and the theory of copositive matrices are intimately related concepts. For the simplest symmetric states, i.e., the diagonal symmetric (DS) states, it has been shown that there exists a correspondence between exceptional (non-exceptional) copositive matrices and non-decomposable (decomposable) Entanglement Witnesses (

Guillaume Lavigne, Christophe Caloz

We show that a properly designed bianisotropic metasurface placed at the interface between two arbitrary different media, or coating a dielectric medium exposed to the air, provides Brewster (reflectionless) transmission at arbitrary angles and for both the TM and TE polarizations. We present a rigorous derivation of the corresponding surface susceptibility

Maciej Fidrysiak, Józef Spałek

A nonzero-temperature technique for strongly correlated electron lattice systems, combining elements of both variational wave function (VWF) approach and expansion in the inverse number of fermionic flavors ($1/\mathcal{N}_f$), is developed. The departure point, VWF method, goes beyond the renormalized mean-field theory and provides semi-quantitative descrip

Don F. DeJongh, Ethan A. DeJongh, Victor Rykalin, Greg DeFillippo

Purpose: Currently, calculations of proton range in proton therapy patients are based on a conversion of CT Hounsfield Units of patient tissues into proton relative stopping power. Uncertainties in this conversion necessitate larger proximal and distal planned target volume margins. Proton CT can potentially reduce these uncertainties by directly measuring p

Zuoyue Li, Zhenqiang Li, Zhaopeng Cui, Rongjun Qin

We present a novel method for synthesizing both temporally and geometrically consistent street-view panoramic video from a single satellite image and camera trajectory. Existing cross-view synthesis approaches focus on images, while video synthesis in such a case has not yet received enough attention. For geometrical and temporal consistency, our approach ex

Davesh Maulik, Junliang Shen

We prove that the intersection cohomology (together with the perverse and the Hodge filtrations) for the moduli space of one-dimensional semistable sheaves supported in an ample curve class on a toric del Pezzo surface is independent of the Euler characteristic of the sheaves. We also prove an analogous result for the moduli space of semistable Higgs bundles

Antonio Capella, Lauro Morales

We study some particular cases of the $n$-well problem in two-dimensional linear elasticity. Assuming that every well in $\mathcal{U}\subset\mathbb{R}^{2\times 2}_\text{sym}$ belong to the same two-dimensional affine subspace, we characterize the symmetric lamination convex hull $L^e(\mathcal{U})$ for any number of wells in terms of the symmetric lamination

Christoph Feinauer, Carlo Lucibello

Pairwise models like the Ising model or the generalized Potts model have found many successful applications in fields like physics, biology, and economics. Closely connected is the problem of inverse statistical mechanics, where the goal is to infer the parameters of such models given observed data. An open problem in this field is the question of how to tra

Nadina Gheorghiu, Charles R. Ebbing, Timothy J. Haugan

In this paper, we present results on magnetization properties of boron nitride-carbon (BN-C) and boron carbide-carbon (B4C-C) granular mixtures. The temperature-dependent magnetization for field-cooled during cooling and field-cooled during warming shows a kind of thermal hysteresis that is always seen around a metamagnetic phase transition from an antiferro

Fleurianne Bertrand, Daniele Boffi, Henrik Schneider

In this paper, the discontinuous Petrov--Galerkin approximation of the Laplace eigenvalue problem is discussed. We consider in particular the primal and ultra weak formulations of the problem and prove the convergence together with a priori error estimates. Moreover, we propose two possible error estimators and perform the corresponding a posteriori error an

Mohammad H. Zhoolideh Haghighi, Sohrab Rahvar, M Reza Rahimi Tabar

We study the statistical mechanics of binary systems under gravitational interaction of the Modified Newtonian Dynamics (MOND) in three-dimensional space. Considering the binary systems, in the microcanonical and canonical ensembles, we show that in the microcanonical systems, unlike the Newtonian gravity, there is a sharp phase transition, with a high-tempe

P. Santos-Sanz, J. L. Ortiz, B. Sicardy, G. Benedetti-Rossi

We predicted a stellar occultation of the bright star Gaia DR1 4332852996360346368 (UCAC4 385-75921) (m$_{\rm V}$= 14.0 mag) by the centaur 2002 GZ$_{32}$ for 2017 May 20$^{\rm th}$. Our latest shadow path prediction was favourable to a large region in Europe. Observations were arranged in a broad region inside the nominal shadow path. Series of images were

Kaiyuan Li, Maverick Woo, Limin Jia

When a software transformation or software security task needs to analyze a given program binary, the first step is often disassembly. Since many modern disassemblers have become highly accurate on many binaries, we believe reliable disassembler benchmarking requires standardizing the set of binaries used and the disassembly ground truth about these binaries

R. Bowens, E. Viges, M. R. Meyer, D. Atkinson

We introduce the Michigan Infrared Test Thermal ELT N-band (MITTEN) Cryostat, a new facility for testing infrared detectors with a focus on mid-infrared (MIR) wavelengths (8-13 microns). New generations of large format, deep well, fast readout MIR detectors are now becoming available to the astronomical community. As one example, Teledyne Imaging Sensors (TI

Gustavo E. Medina, Ricardo R. Muñoz, Jeffrey L. Carlin, A. Katherina Vivas

The discovery of very distant stars in the halo of the Milky Way provides valuable tracers on the Milky Way mass and its formation. Beyond 100 kpc from the Galactic center, most of the stars are likely to be in faint dwarf galaxies or tidal debris from recently accreted dwarfs, making the outer reaches of the Galaxy important for understanding the Milky Way'

Octavio Fierro, Nicolas Mora, Julio Oliva

While cubic Quasi-topological gravity is unique, there is a family of quartic Quasi-topological gravities in five dimensions. These theories are defined by leading to a first order equation on spherically symmetric spacetimes, resembling the structure of the equations of Lovelock theories in higher-dimensions, and are also ghost free around AdS. Here we cons

Maykel Belluzi, Tomás Caraballo, Marcelo J. D. Nascimento, Karina Schiabel

This work is devoted to the study of the asymptotic behavior of nonautonomous reaction-diffusion equations in Dumbbell domains $\Omega_{\varepsilon} \subset \mathbb{R}^{N}$. Each $\Omega_{\varepsilon}$ is the union of a fixed open set $\Omega$ and a channel $R_{\varepsilon}$ that collapses to a line segment $R_0$ as $\varepsilon \rightarrow 0^{+}$. We first

David d'Enterria

This writeup summarizes the main experimental studies of the strong interaction, theoretically described by quantum chromodynamics (QCD), that were presented during the ICHEP-2020 conference. The latest results, measured mostly in p-p collisions at the LHC, are categorized in seven broad topics: (i) Extractions of the strong coupling constant $\alpha_s(m_{\r

Arvind Pillai, Halsey Lea, Faisal Khan, Glynn Dennis

Activity monitors are widely used to measure various physical activities (PA) as an indicator of mobility, fitness and general health. Similarly, real-time monitoring of longitudinal trends in step count has significant clinical potential as a personalized measure of disease related changes in daily activity. However, inconsistent step count accuracy across

Meriel Stein, Sebastian Elbaum, Lu Feng, Shili Sheng

Invariants are a set of properties over program attributes that are expected to be true during the execution of a program. Since developing those invariants manually can be costly and challenging, there are a myriad of approaches that support automated mining of likely invariants from sources such as program traces. Existing approaches, however, are not equi

Chen-En Tsai, James Hung, Youxin Hu, Da-Yung Wang

Total hip replacement is the most effective treatment for late stage osteoarthritis. However, adverse local tissue reactions (ALTRs) associated with fretting corrosion have been observed in patients with modular total hip implants. The purpose of this study is to increase the fretting corrosion resistance of the CoCrMo alloy and the associated metal ion rele

Fnu Hairi, Xin Liu, Lei Ying

This paper provides a recipe for deriving calculable approximation errors of mean-field models in heavy-traffic with the focus on the well-known load balancing algorithm---power-of-two-choices (Po2). The recipe combines Stein's method for linearized mean-field models and State Space Concentration (SSC) based on geometric tail bounds. In particular, we di

Nadia Ben Amor, Eric Michoulier, Aude Simon

This work is dedicated to the theoretical investigation of the influence of water clusters' organisation and size on the electronic spectrum of an interacting benzene (Bz) molecule using both TD-DFT and CASPT2 approaches. Two series of geometries, namely $Geo_{IEI}$ and $Geo_{IED}$ were extracted from two Bz-hexagonal ice configurations leading to maximum an

Kevin E. Andrade, Jackson Fuson, Sophia Gad-Nasr, Demao Kong

We analyze strongly lensed images in 8 galaxy clusters to measure their dark matter density profiles in the radial region between 10 kpc and 150 kpc, and use this to constrain the self-interaction cross section of dark matter (DM) particles. We infer the mass profiles of the central DM halos, bright central galaxies, key member galaxies, and DM subhalos for

Lingyun Ding, Richard M. McLaughlin

We study the long time behavior of an advection-diffusion equation with a random shear flow which depends on a stationary Ornstein-Uhlenbeck (OU) process in parallel-plate channels enforcing the no-flux boundary conditions. We derive a closed form formula for the long time asymptotics of the arbitrary $N$-point correlator using the ground state eigenvalue pe

James K Holland, Nicholas Hopper

Website Fingerprinting (WF) attacks are used by local passive attackers to determine the destination of encrypted internet traffic by comparing the sequences of packets sent to and received by the user to a previously recorded data set. As a result, WF attacks are of particular concern to privacy-enhancing technologies such as Tor. In response, a variety of

Jesus Malo, Jose Juan Esteve-Taboada, Guillermo Aguilar, Marianne Maertens

In many psychophysical detection and discrimination tasks human performance is thought to be limited by internal or inner noise when neuronal activity is converted into an overt behavioural response. It is unclear, however, to what extent the behaviourally limiting inner noise arises from early noise in the photoreceptors and the retina, or from late noise i

Jan Verschelde

Hardware double precision is often insufficient to solve large scientific problems accurately. Computing in higher precision defined by software causes significant computational overhead. The application of parallel algorithms compensates for this overhead. Newton's method to develop power series expansions of algebraic space curves is the use case for this

Arkaitz Zubiaga

Text classification, as the task consisting in assigning categories to textual instances, is a very common task in information science. Methods learning distributed representations of words, such as word embeddings, have become popular in recent years as the features to use for text classification tasks. Despite the increasing use of word embeddings for text

A. Pastore, M. Carnini

We present three different methods to estimate error bars on the predictions made using a neural network. All of them represent lower bounds for the extrapolation errors. For example, we did not include an analysis on robustness against small perturbations of the input data. At first, we illustrate the methods through a simple toy model, then, we apply them

Iman Bahmani Jafarloo

This is the Hadamard package for Macaulay2 which computes the Hadamard product of projective subvarieties.

Varvara V. Zubyuk, Pavel A. Shafirin, Maxim R. Shcherbakov, Gennady Shvets

Resonant photonic nanostructures exhibiting enhanced nonlinear responses and efficient frequency conversion are an emergent platform in nonlinear optics. High-index semiconductor metasurfaces with rapidly tuned high-Q resonances enable a novel class of time-variant metasurfaces, which expands the toolbox of color management at the nanoscale. Here, we report

Tapio Helin, Remo Kretschmann

In this paper we study properties of the Laplace approximation of the posterior distribution arising in nonlinear Bayesian inverse problems. Our work is motivated by Schillings et al. (2020), where it is shown that in such a setting the Laplace approximation error in Hellinger distance converges to zero in the order of the noise level. Here, we prove novel e

Ho Yin Chau, Frank Qiu, Yubei Chen, Bruno Olshausen

Discrete spatial patterns and their continuous transformations are two important regularities contained in natural signals. Lie groups and representation theory are mathematical tools that have been used in previous works to model continuous image transformations. On the other hand, sparse coding is an important tool for learning dictionaries of patterns in

Sam McArdle

Computational physics is an important tool for analysing, verifying, and -- at times -- replacing physical experiments. Nevertheless, simulating quantum systems and analysing quantum data has so far resisted an efficient classical treatment in full generality. While programmable quantum systems have been developed to address this challenge, the resources req

Susanne Menden-Deuer, Julie Rowlett

Using game theory we provide mathematical proof that if a species of asexually reproducing microbes does not possess maximum variability in competitive abilities amongst its individual organisms, then that species is vulnerable to replacement by competitors. Furthermore, we prove that such maximally variable species are neutral towards each other in competit

Carlo Nipoti, Giacomo Cherchi, Giuliano Iorio, Francesco Calura

Gas-poor galaxies can be modelled as composite collisionless stellar systems, with a dark matter halo and one or more stellar components, representing different stellar populations. The dynamical evolution of such composite systems is often studied with numerical N-body simulations, whose initial conditions typically require realizations with particles of st

Pavel Fileviez Perez, Clara Murgui, Alexis D. Plascencia

We discuss the correlation between dark matter and Higgs decays in gauge theories where the dark matter is predicted from anomaly cancellation. In these theories, the Higgs responsible for the breaking of the gauge symmetry generates the mass for the dark matter candidate. We investigate the Higgs decays in the minimal gauge theory for Baryon number. After i

Ievgen Dubovyk, Ayres Freitas, Janusz Gluza, Krzysztof Grzanka

Phenomenologically relevant electroweak precision pseudo-observables related to Z-boson physics are discussed in the context of the strong experimental demands of future $e^+e^-$ colliders. The recent completion of two-loop Z-boson results is summarized and a prospect for the 3-loop Standard Model calculation of the Z-boson decay pseudo-observable is given.

H. Al Kazwini, Q. Agobert, A. Siebert, B. Famaey

In the Gaia era, understanding the effects of the perturbations of the Galactic disc is of major importance in the context of dynamical modelling. In this theoretical paper we extend previous work in which, making use of the epicyclic approximation, the linearized Boltzmann equation had been used to explicitly compute, away from resonances, the perturbed dis

Sergio Contreras, Raul Angulo, Matteo Zennaro

We develop an extension of subhalo abundance matching (SHAM) capable of accurately reproducing the real and redshift-space clustering of galaxies in a state-of-the-art hydrodynamical simulation. Our method uses a low-resolution gravity-only simulation and it includes orphan and tidal disruption prescriptions for satellite galaxies, and a flexible amount of g

Celine Degrande, Matteo Maltoni

Interferences are not positive-definite and can change sign over the phase space. If the contributions of the regions where they are positive and negative nearly cancel each other, their effects can be hard to measure. In this paper, we propose a method to quantify the ability of an observable to separate these opposite contributions and therefore to revive

Sajad Abbar, Francesco Capozzi, Robert Glas, H. -Thomas Janka

We assess the occurrence of fast neutrino flavor instabilities in two three-dimensional state-of-the-art core-collapse supernova simulations performed using a two-moment three-species neutrino transport scheme: one with an exploding 9$\mathrm{M_{\odot}}$ and one with a non-exploding 20$\mathrm{M_{\odot}}$ model. Apart from confirming the presence of fast ins

Stephen M. Feeney, Hiranya V. Peiris, Samaya M. Nissanke, Daniel J. Mortlock

Gravitational wave (GW) and electromagnetic (EM) observations of neutron-star-black-hole (NSBH) mergers can provide precise local measurements of the Hubble constant ($H_0$), ideal for resolving the current $H_0$ tension. We perform end-to-end analyses of realistic populations of simulated NSBHs, incorporating both GW and EM selection for the first time. We

Alexander J. Richings, Claude-Andre Faucher-Giguere, Jonathan Stern

Observations of emission lines in Active Galactic Nuclei (AGN) often find fast (~1000 km s^-1) outflows extending to kiloparsec scales, seen in ionised, neutral atomic and molecular gas. In this work we present radiative transfer calculations of emission lines in hydrodynamic simulations of AGN outflows driven by a hot wind bubble, including non-equilibrium

Lucas Johns, Seth Koren

Hydrogen oscillation into a dark-sector state $H'$ has recently been proposed as a novel mechanism through which hydrogen can be cooled during the dark ages -- without direct couplings between the Standard Model and dark matter. In this work we demonstrate that the requisite mixing can appear naturally from a microphysical theory, and argue that the startlin

F. Lucertini, D. Nardiello, G. Piotto

Aims. We present a new technique to estimate the relative ages of multiple stellar populations hosted by five globular clusters: NGC 104 (47 Tuc), NGC 6121 (M4), NGC 6352, NGC 6362 and NGC 6723. Methods. We used the catalogs of the database "HST UV Globular cluster Survey (HUGS)" to create color-magnitude and two-color diagrams of the Globular Clusters. We i

Leyna Shackleton, Alexander Wietek, Antoine Georges, Subir Sachdev

We present exact diagonalization results on finite clusters of a $t$-$J$ model of spin-1/2 electrons with random all-to-all hopping and exchange interactions. We argue that such random models capture qualitatively the strong local correlations needed to describe the cuprates and related compounds, while avoiding lattice space group symmetry breaking orders.

Jordan Mirocha, Henri Lamarre, Adrian Liu

Models of the reionization and reheating of the intergalactic medium (IGM) at redshifts $z \gtrsim 6$ continue to grow more sophisticated in anticipation of near-future 21-cm, cosmic microwave background, and galaxy survey measurements. However, there are many potential sources of systematic uncertainty in models that could bias and/or degrade upcoming const

Amanpreet Kaur, Abraham D. Falcone, Michael C. Stroh

We utilize machine learning methods to distinguish BL Lacertae objects (BL Lac) from Flat Spectrum Radio Quasars (FSRQ) within a sample of likely X-ray blazar counterparts to Fermi 3FGL unassociated gamma-ray sources. From our previous work, we have extracted 84 sources that were classified as $\geq$ 99% likley to be blazars. We then utilize Swift$-$XRT, Fer

Sashwat Tanay, Leo C. Stein, José T. Gálvez Ghersi

Accurate and efficient modeling of the dynamics of binary black holes (BBHs) is crucial to their detection and parameter estimation through gravitational waves, both with LIGO/Virgo and LISA. General BBH configurations will have misaligned spins and eccentric orbits, eccentricity being particularly relevant at early times. Modeling these systems is both anal

Chad Bustard, Ellen G. Zweibel

The bulk propagation speed of GeV-energy cosmic rays is limited by frequent scattering off hydromagnetic waves. Most galaxy evolution simulations that account for this confinement assume the gas is fully ionized and cosmic rays are well-coupled to Alfv\'en waves; however, multiphase density inhomogeneities, frequently under-resolved in galaxy evolution simul

Lucas Johns, Seth Koren

The anomalous 21 cm absorption feature reported by EDGES has galvanized the study of scenarios in which dark matter (DM) siphons off thermal energy from the Standard Model (SM) gas. In a departure from the much-discussed models that achieve cooling by DM scattering directly with SM particles, we show that the same end can be achieved through neutral atomic h