December 2020 arXiv papers — page 95

Fotios K. Anagnostopoulos, Spyros Basilakos, Emmanuel N. Saridakis

We use data from Supernovae (SNIa) Pantheon sample, from Baryonic Acoustic Oscillations (BAO), and from cosmic chronometers measurements of the Hubble parameter (CC), alongside arguments from Big Bang Nucleosynthesis (BBN), in order to extract constraints on Myrzakulov $F(R,T)$ gravity. This is a connection-based theory belonging to the Riemann-Cartan subcla

Hamid Sarmadi, Rafael Muñoz-Salinas, Miguel A. Olivares-Mendez, Rafael Medina-Carnicer

Event cameras are a new type of image sensors that output changes in light intensity (events) instead of absolute intensity values. They have a very high temporal resolution and a high dynamic range. In this paper, we propose a method to detect and decode binary square markers using an event camera. We detect the edges of the markers by detecting line segmen

Bonny Banerjee

The phenomenon of self-organization has been of special interest to the neural network community for decades. In this paper, we study a variant of the Self-Organizing Map (SOM) that models the phenomenon of self-organization of the particles forming a string when the string is tightened from one or both ends. The proposed variant, called the String Tightenin

Baptiste Louf

We study large uniform random quadrangulations whose genus grow linearly with the number of faces, whose local convergence was recently established by Budzinski and the author arXiv:1902.00492,arXiv:2012.05813. Here we study several properties of these objects which are not captured by the local topology. Namely we show that balls around the root are planar

Fitash Ul Haq, Donghwan Shin, Lionel C. Briand, Thomas Stifter

Automatically detecting the positions of key-points (e.g., facial key-points or finger key-points) in an image is an essential problem in many applications, such as driver's gaze detection and drowsiness detection in automated driving systems. With the recent advances of Deep Neural Networks (DNNs), Key-Points detection DNNs (KP-DNNs) have been increasingly

JingJun Zhu, Xi Chen

Robust stimulated Raman exact passages are requisite for controlling nonlinear quantum systems, with the wide applications ranging from ultracold molecules, non-linear optics to superchemistry. Inspired by shortcuts to adiabaticity, we propose the fast-forward scaling of stimulated Raman adiabatic processes with the nonlinearity involved, describing the tran

Nathan Drenkow, Philippe Burlina, Neil Fendley, Onyekachi Odoemene

Searching for small objects in large images is a task that is both challenging for current deep learning systems and important in numerous real-world applications, such as remote sensing and medical imaging. Thorough scanning of very large images is computationally expensive, particularly at resolutions sufficient to capture small objects. The smaller an obj

Charles Corbière, Nicolas Thome, Antoine Saporta, Tuan-Hung Vu

Reliably quantifying the confidence of deep neural classifiers is a challenging yet fundamental requirement for deploying such models in safety-critical applications. In this paper, we introduce a novel target criterion for model confidence, namely the true class probability (TCP). We show that TCP offers better properties for confidence estimation than stan

Csaba Biró, Sida Wan

Let $\mathbf{k}$ denote the totally ordered set (or chain) on $k$ elements. The product $\mathbf{k}^t=\mathbf{k}\times\cdots\times\mathbf{k}$ is a poset called a grid. This paper discusses several loosely related results on the Ramsey theory of grids. Most of the results involve some application of the Product Ramsey Theorem.

Ahmed Khanfir, Anil Koyuncu, Mike Papadakis, Maxime Cordy

Much research on software engineering and software testing relies on experimental studies based on fault injection. Fault injection, however, is not often relevant to emulate real-world software faults since it "blindly" injects large numbers of faults. It remains indeed challenging to inject few but realistic faults that target a particular functionality in

Rodion Kononchuk, Suwun Suwunnarat, Martin S. Hilario, Anthony E. Baros

Millimeter wave (mm-wave) communications and radar receivers capable of processing small signals must be protected from high-power signals, which can damage sensitive receiver components. Many of these systems arguably can be protected by using photonic limiting techniques, in addition to electronic limiting circuits in receiver front-ends. Here we demonstra

Angelo Russomanno, Michele Fava, Markus Heyl

We use large-scale exact diagonalization to study the quantum Ising chain in a transverse field with long-range power-law interactions decaying with exponent $\alpha$. We numerically study various probes for quantum chaos and eigenstate thermalization {on} the level of eigenvalues and eigenstates. The level-spacing statistics yields a clear sign towards a Wi

Roberto Taverna, Lorenzo Marra, Stefano Bianchi, Mičhal Dovciak

The study of radiation emitted from black hole accretion discs represents a crucial way to understand the main physical properties of these sources, and in particular the black hole spin. Beside spectral analysis, polarimetry is becoming more and more important, motivated by the development of new techniques which will soon allow to perform measurements also

J. M. DeStefano, G. P. Marciaga, J. B. Flahavan, U. S. Shah

The Heusler compound ScInAu$_2$ was previously reported to have a superconducting ground state with a critical temperature of 3.0 K. Recent high throughput calculations have also predicted that the material harbors a topologically non-trivial band structure similar to that reported for beta-PdBi$_2$. In an effort to explore the interplay between the supercon

Mengzhi Chen, Tong Li, Jacek Dobaczewski, Witold Nazarewicz

Background: The presence of nuclear ground states with stable reflection-asymmetric shapes is supported by rich experimental evidence. Theoretical surveys of odd-multipolarity deformations predict the existence of pear-shaped isotopes in several fairly localized regions of the nuclear landscape in the vicinity of near-lying single-particle shells with $\Delt

Benjamin Knorr

We construct exact solutions to the functional renormalisation group equation of the O(N) model and the Gross-Neveu model at large N for $2<d<4$, without specifying the form of the regulator. This allows to investigate which quantities are independent of the choice of regulator without being plagued by truncation artefacts. We find that only universal quanti

Gabriele Perfetto, Benjamin Doyon

We derive an exact formula for the scaled cumulant generating function of the time-integrated current associated to an arbitrary ballistically transported conserved charge. Our results rely on the Euler-scale description of interacting, many-body, integrable models out of equilibrium given by the generalized hydrodynamics, and on the large deviation theory.

H. Rabus, W. B. Li, C. Villagrasa, J. Schuemann

Results of a Monte Carlo code intercomparison exercise for simulations of the dose enhancement from a gold nanoparticle (GNP) irradiated by X-rays have been recently reported. To highlight potential differences between codes, the dose enhancement ratios (DERs) were shown for the narrow-beam geometry used in the simulations, which leads to values significantl

Alexis Poncet, Olivier Bénichou, Pierre Illien

The Symmetric Exclusion Process (SEP), where particles hop on a 1D lattice with the restriction that there can only be one particle per site, is a paradigmatic model of interacting particle systems. Recently, it has been shown that the nature of the initial conditions - annealed or quenched - has a quantitative impact on the long-time properties of tracer di

Tau Raphael Rasethuntsa

This article considers the parametric estimation of $Pr(X<Y<Z)$ and its generalizations based on several well-known one-parameter and two-parameter continuous distributions. It is shown that for some one-parameter distributions and when there is a common known parameter in some two-parameter distributions, the uniformly minimum variance unbiased estimator ca

Maria J. Lo Faro, Giovanna Ruello, Antonio A. Leonardi, Dario Morganti

Disordered optical media are an emerging class of materials capable of strongly scattering light. Their study is relevant to investigate transport phenomena and for applications in imaging, sensing and energy storage. While such materials can be used to generate coherent light, their directional emission is typically hampered by their very multiple scatterin

Joel Bergé, Quentin Baghi, Alain Robert, Manuel Rodrigues

MICROSCOPE's space test of the weak equivalence principle (WEP) is based on the minute measurement of the difference of accelerations experienced by two test masses as they orbit the Earth. A detection of a violation of the WEP would appear at a well-known frequency $f_{\rm EP}$ depending on the satellite's orbital and spinning frequencies. Consequently, the

Joel Bergé, Quentin Baghi, Emilie Hardy, Gilles Métris

After performing highly sensitive acceleration measurements during two years of drag-free flight around the Earth, MICROSCOPE provided the best constraint on the Weak Equivalence Principle (WEP) to date. Beside being a technological challenge, this experiment required a specialised data analysis pipeline to look for a potential small signal buried in the noi

Alain Robert, Valerio Cipolla, Pascal Prieur, Pierre Touboul

This paper focus on the description of the design and performance of the MICROSCOPE satellite and its Drag-Free and Attitude Control System (DFACS). The satellite is derived from CNES' Myriade platform family, albeit with significant upgrades dictated by the unprecedented MICROSCOPE's mission requirements. The 300kg drag-free microsatellite has completed its

Viktor Rudnev, Vladislav Golyanik, Jiayi Wang, Hans-Peter Seidel

3D hand pose estimation from monocular videos is a long-standing and challenging problem, which is now seeing a strong upturn. In this work, we address it for the first time using a single event camera, i.e., an asynchronous vision sensor reacting on brightness changes. Our EventHands approach has characteristics previously not demonstrated with a single RGB

Pierre Touboul, Manuel Rodrigues, Gilles Métris, Ratana Chhun

The MICROSCOPE mission aimed to test the Weak Equivalence Principle (WEP) to a precision of $10^{-15}$. The WEP states that two bodies fall at the same rate on a gravitational field independently of their mass or composition. In MICROSCOPE, two masses of different compositions (titanium and platinum alloys) are placed on a quasi-circular trajectory around th

Paria Abbasi, Andreas Klingler, Tim Netzer

In this paper we show the existence of approximate completely positive semidefinite (cpsd) factorizations with a cpsd-rank bounded above (almost) independently from the cpsd-rank of the initial matrix. This is particularly relevant since the cpsd-rank of a matrix cannot, in general, be upper bounded by a function only depending on its size. For this purpose,

Michael A. Perlin, Diego Barberena, Ana Maria Rey

We consider the task of performing quantum state tomography on a $d$-level spin qudit, using only measurements of spin projection onto different quantization axes. After introducing a basis of operators closely related to the spherical harmonics, which obey the rotational symmetries of spin qudits, we map our quantum tomography task onto the classical proble

Jisu Kim, Su Houng Lee

We calculate the mass of the vector meson in the chiral symmetry restored vacuum. This is accomplished by separating the four quark operators appearing in the vector and axial vector meson sum rules into chiral symmetric and symmetry breaking parts depending on the contribution of the fermion zero modes. We then identify each part from the fit to the vector

Christoph P. Hofmann

We explore the low-energy regime of quantum chromodynamics subjected to an external magnetic field by deriving the two-loop representations for the entropy density and the magnetization within chiral perturbation theory (CHPT). At fixed temperature, the entropy density drops when the magnetic field becomes stronger. The magnetization induced at finite temper

Supanut Thanasilp, Jirawat Tangpanitanon, Marc-Antoine Lemonde, Ninnat Dangniam

Demonstrating the ability of existing quantum platforms to perform certain computational tasks intractable to classical computers represents a cornerstone in quantum computing. Despite the growing number of such proposed "quantum supreme" tasks, it remains an important challenge to identify their direct applications. In this work, we describe how the approac

Jani M. Taskinen, Pavel Kliuiev, Antti J. Moilanen, Päivi Törmä

Polarization textures of light may reflect fundamental phenomena such as topological defects, and can be utilized in engineering light beams. Three main routes are applied during their creation: spontaneous appearance in phase transitions, steering by an excitation beam, or structural engineering of the medium. We present an approach that uses all three in a

Oliver Shah, Yann Alibert, Ravit Helled, Klaus Mezger

Understanding the chemical interactions between water and Mg-silicates or iron is essential to constrain the interiors of water-rich planets. Hydration effects have, however, been mostly neglected by the astrophysics community so far. As such effects are unlikely to have major impacts on theoretical mass-radius relations this is justified as long as the meas

Jonathan Labadie-Bartz, Dietrich Baade, Alex C. Carciofi, Amanda Rubio

In photometry of $\gamma$ Cas (B0.5 IVe) from the SMEI and BRITE-Constellation satellites, indications of low-order non-radial pulsation have recently been found, which would establish an important commonality with the class of classical Be stars at large. New photometry with the TESS satellite has detected three frequency groups near 1.0 ($g1$), 2.4 ($g2$),

Lucas J. Stanek, Raymond C. Clay, M. W. C. Dharma-wardana, Mitchell A. Wood

Macroscopic simulations of dense plasmas rely on detailed microscopic information that can be computationally expensive and is difficult to verify experimentally. In this work, we delineate the accuracy boundary between microscale simulation methods by comparing Kohn-Sham density functional theory molecular dynamics (KS-MD) and radial pair potential molecula

Giulia Di Nunno, Michele Giordano

We study a stochastic differential game between two players, controlling a forward stochastic Volterra integral equation (FSVIE). Each player has to optimize his own performance functional which includes a backward stochastic differential equation (BSDE). The dynamics considered are driven by time-changed L\'evy noises, with absolutely continuous time-change

Mehmet Ozan Unal, Metin Ertas, Isa Yildirim

Low-dose CT imaging requires reconstruction from noisy indirect measurements which can be defined as an ill-posed linear inverse problem. In addition to conventional FBP method in CT imaging, recent compressed sensing based methods exploit handcrafted priors which are mostly simplistic and hard to determine. More recently, deep learning (DL) based methods ha

Francisco Javier García-Haro, Manuel Campos-Taberner, Álvaro Moreno, Håkan Torbern Tagesson

Spatially and temporally explicit canopy water content (CWC) data are important for monitoring vegetation status, and constitute essential information for studying ecosystem-climate interactions. Despite many efforts there is currently no operational CWC product available to users. In the context of the Satellite Application Facility for Land Surface Analysi

Yue Shao, Yicheng Hu, Victor M. Zavala

We study logistical investment flexibility provided by modular processing technologies for mitigating risk. Specifically, we propose a multi-stage stochastic programming formulation that determines optimal capacity expansion plans that mitigate demand uncertainty. The formulation accounts for multi-product dependencies between small/large units and for trade

Kirill Martynov, Kiran Garimella, Robert West

In many societies, appearing slim is considered attractive. The fashion industry has been attempting to cater to this trend by designing outfits that can enhance the appearance of slimness. Two anecdotal rules, widespread in the world of fashion, are (1) choose dark clothes and (2) avoid horizontal stripes, in order to appear slim. Thus far, empirical eviden

Nuno Freitas, Alain Kraus, Samir Siksek

Let $\ell \ne 3$ be a prime. We show that there are only finitely many cyclic number fields $F$ of degree $\ell$ for which the unit equation $$\lambda + \mu = 1, \qquad \lambda,~\mu \in \mathcal{O}_F^\times$$ has solutions. Our result is effective. For example, we deduce that the only cyclic quintic number field for which the unit equation has solutions is $

Julie Rowlett

In a non-cooperative game, players do not communicate with each other. Their only feedback is the payoff they receive resulting from the strategies they execute. It is important to note that within each level set of the total payoff function the payoff to each player is unchanging, and therefore understanding the structure of these level sets plays a key rol

Yang Liu, Alexandros Neophytou, Sunando Sengupta, Eric Sommerlade

We propose a self-supervised method for image relighting of single view images in the wild. The method is based on an auto-encoder which deconstructs an image into two separate encodings, relating to the scene illumination and content, respectively. In order to disentangle this embedding information without supervision, we exploit the assumption that some au

Montie Avery, Arnd Scheel

We establish selection of critical pulled fronts in invasion processes. Our result shows convergence to a pulled front with a logarithmic shift for open sets of steep initial data, including one-sided compactly supported initial conditions. We rely on robust, conceptual assumptions, namely existence and marginal spectral stability of a front traveling at the

W. Ikegami Andersson, A. Akram, T. Johansson, R. Kliemt

The upcoming PANDA experiment at FAIR will be among a new generation of particle physics experiments to employ a novel event filtering system realised purely in software, i.e. a software trigger. To educate its triggering decisions, online reconstruction algorithms need to offer outstanding performance in terms of efficiency and track quality. We present a m

Ross N. Greenwood

Geometric Algebra and Calculus are mathematical languages encoding fundamental geometric relations that theories of physics seem to respect. We propose criteria given which statistics of expressions in geometric algebra are computable in quantum theory, in such a way that preserves their algebraic properties. They are that one must be able to arbitrarily tra

Sanath Narayan, Hisham Cholakkal, Munawar Hayat, Fahad Shahbaz Khan

This work proposes a weakly-supervised temporal action localization framework, called D2-Net, which strives to temporally localize actions using video-level supervision. Our main contribution is the introduction of a novel loss formulation, which jointly enhances the discriminability of latent embeddings and robustness of the output temporal class activation

Wenlong Wang

We systematically construct a series of vector solitary waves in harmonically trapped one-dimensional three-, four-, and five-component Bose-Einstein condensates. These stationary states are continued in chemical potentials from the analytically tractable low-density linear limit of respective states, as independent linear quantum harmonic oscillator states,

T. Gastine, J. Wicht

The ongoing NASA's Juno mission puts new constraints on the internal dynamics of Jupiter. Data gathered by its onboard magnetometer reveal a dipole-dominated surface magnetic field accompanied by strong localised magnetic flux patches. The gravity measurements indicate that the fierce surface zonal jets extend several thousands of kilometers below the cloud

José A. Iglesias, Svetoslav Nakov

We consider the nonlinear Poisson-Boltzmann equation in the context of electrostatic models for a biological macromolecule, embedded in a bounded domain containing a solution of an arbitrary number of ionic species which is not necessarily charge neutral. The resulting semilinear elliptic equation combines several difficulties: exponential growth and lack of

Alvaro Moreno-Martinez, Marco Maneta, Gustau Camps-Valls, Luca Martino

Products derived from a single multispectral sensor are hampered by a limited spatial, spectral or temporal resolutions. Image fusion in general and downscaling/blending in particular allow to combine different multiresolution datasets. We present here an optimal interpolation approach to generate smoothed and gap-free time series of Landsat reflectance data

Georgios Petros Katsoulis, Matthew Benjamin Peters, André Staudte, Ravi Bhardwaj

For two-electron diatomic molecules, we investigate magnetic field effects in non-sequential double ionization where recollisions prevail. We do so by formulating a three-dimensional semi-classical model that fully accounts for the Coulomb singularities and for magnetic field effects during time propagation. Using this model, we identify a prominent signatur

Wang Yifan, Shihao Wu, Cengiz Oztireli, Olga Sorkine-Hornung

Neural implicit functions have emerged as a powerful representation for surfaces in 3D. Such a function can encode a high quality surface with intricate details into the parameters of a deep neural network. However, optimizing for the parameters for accurate and robust reconstructions remains a challenge, especially when the input data is noisy or incomplete

Itamar Cohen

Communication networks are used today everywhere and on every scale: starting from small Internet of Things (IoT) networks at home, via campus and enterprise networks, and up to tier-one networks of Internet providers. Accordingly, network devices should support a plethora of tasks with highly heterogeneous characteristics in terms of processing time, bandwi

René Haas, Leon Derczynski

Automatic language identification is a challenging problem. Discriminating between closely related languages is especially difficult. This paper presents a machine learning approach for automatic language identification for the Nordic languages, which often suffer miscategorisation by existing state-of-the-art tools. Concretely we will focus on discriminatio

Mimee Xu, Laurens van der Maaten, Awni Hannun

One of the most effective approaches to improving the performance of a machine learning model is to procure additional training data. A model owner seeking relevant training data from a data owner needs to appraise the data before acquiring it. However, without a formal agreement, the data owner does not want to share data. The resulting Catch-22 prevents ef

Paolo Dulio, Andrea Frosini

In the usual aim of discrete tomography, the reconstruction of an unknown discrete set is considered, by means of projection data collected along a set $U$ of discrete directions. Possible ambiguous reconstructions can arise if and only if switching components occur, namely, if and only if non-empty images exist having null projections along all the directio

Priyabrata Char, Prabir Kumar Dey, Amit Kundu, Indrani Chattopadhyay

Recently a new class of monogamy relations (actually, exponentially many) was provided by Christopher Eltschka et al. in terms of squared concurrence. Their approach restricted to the distribution of bipartite entanglement shared between different subsystems of a global state. We have critically analyzed those monogamy relations in three as well as in four q

Christos Kyrkou

The increasing need for automated visual monitoring and control for applications such as smart camera surveillance, traffic monitoring, and intelligent environments, necessitates the improvement of methods for visual active monitoring. Traditionally, the active monitoring task has been handled through a pipeline of modules such as detection, filtering, and c

Taro Kimura, Ali Zahabi

We establish the universal edge scaling limit of random partitions with the infinite-parameter distribution called the Schur measure. We explore the asymptotic behavior of the wave function, which is a building block of the corresponding kernel, based on the Schr{\"o}dinger-type differential equation. We show that the wave function is in general asymptotic t

Xingchen Zhao, Tao Peng, Zhenhuan Yi, Lida Zhang

We develop a method based on the cross-spectrum of an intensity-modulated CW laser, which can extract a signal from an extremely noisy environment and image objects hidden in turbid media. We theoretically analyzed our scheme and performed the experiment by scanning the object placed in between two ground glass diffusers. The image of the object is retrieved

Gavin Brown, Mark Bun, Vitaly Feldman, Adam Smith

Modern machine learning models are complex and frequently encode surprising amounts of information about individual inputs. In extreme cases, complex models appear to memorize entire input examples, including seemingly irrelevant information (social security numbers from text, for example). In this paper, we aim to understand whether this sort of memorizatio

F. Torra, J. Castañeda, C. Fabricius, L. Lindegren

The Gaia Early Data Release 3 (Gaia EDR3) contains results derived from 78 billion individual field-of-view transits of 2.5 billion sources collected by the European Space Agency's Gaia mission during its first 34 months of continuous scanning of the sky. We describe the input data, which have the form of onboard detections, and the modeling and processing t

Wenjie Wang, Ling-yu Duan, Hao Jiang, Peiguang Jing

With the rising incidence of some diseases, such as obesity and diabetes, a healthy diet is arousing increasing attention. However, most existing food-related research efforts focus on recipe retrieval, user preference-based food recommendation, cooking assistance, or the nutrition and calorie estimation of dishes, ignoring the personalized health-aware food

Femke van Ieperen, Ivan Kryven

We study site and bond percolation on directed simple random graphs with a given degree distribution and derive the expressions for the critical value of the percolation probability above which the giant strongly connected component emerges and the fraction of vertices in this component.

Matthias Hofer, Carmelo Sferrazza, Raffaello D'Andrea

Sensory feedback is essential for the control of soft robotic systems and to enable deployment in a variety of different tasks. Proprioception refers to sensing the robot's own state and is of crucial importance in order to deploy soft robotic systems outside of laboratory environments, i.e. where no external sensing, such as motion capture systems, is avail

Shing Yan Li

We study the brane world scenario of a single brane (or a single stack of branes) with codimension higher than one. When the extra dimensions are not small, localization of gravity around the brane is needed in order to reproduce the observable four-dimensional gravity. We focus on the case of noncompact extra dimensions, where the possibility of localized g

Julien Ferri, Vojtech Horný, Tünde Fülöp

Laser-plasma electron accelerators can be used to produce high-intensity X-rays, as electrons accelerated in wakefields emit radiation due to betatron oscillations.Such X-ray sources inherit the features of the electron beam; sub-femtosecond electron bunches produce betatron sources of the same duration, which in turn allow probing matter on ultrashort time

F. G. Ben, M. V. T. Machado

The study of how fast thermalization in heavy ion collisions occurs has been one of the central topics in the heavy ion community. In the weak coupling picture this thermalization occurs from "the bottom up": high energy partons, formed early in the collision, radiate low energy gluons which then proceed to equilibrate among themselves, forming a thermal bat

Nathan Drenkow, Neil Fendley, Philippe Burlina

Whilst adversarial attack detection has received considerable attention, it remains a fundamentally challenging problem from two perspectives. First, while threat models can be well-defined, attacker strategies may still vary widely within those constraints. Therefore, detection should be considered as an open-set problem, standing in contrast to most curren

Giacomo Mazza, Adriano Amaricci, Massimo Capone

We consider heterostructures obtained by stacking layers of two s-wave superconductors with significantly different coupling strengths, respectively in the weak- and strong-coupling regimes. The weak- and strong-coupling superconductors are chosen with similar critical temperatures for bulk systems. Using dynamical mean-field theory methods, we find an ubiqu

Arkadiusz Bochniak, Andrzej Sitarz

Motivated by the models of geometry with discrete spaces as additional dimensions we investigate the stability of cosmological solutions in models with two metrics of the Friedmann-Lema\^itre-Robertson-Walker type. We propose an effective gravity action that couples the two metrics in a similar manner as in the bimetric theory of gravity and analyse whether

Noor Awad, Neeratyoy Mallik, Frank Hutter

Neural architecture search (NAS) methods rely on a search strategy for deciding which architectures to evaluate next and a performance estimation strategy for assessing their performance (e.g., using full evaluations, multi-fidelity evaluations, or the one-shot model). In this paper, we focus on the search strategy. We introduce the simple yet powerful evolu

Chiara Plizzari, Marco Cannici, Matteo Matteucci

Skeleton-based human action recognition has achieved a great interest in recent years, as skeleton data has been demonstrated to be robust to illumination changes, body scales, dynamic camera views, and complex background. Nevertheless, an effective encoding of the latent information underlying the 3D skeleton is still an open problem. In this work, we propo

Florian Heinemann, Axel Munk, Yoav Zemel

We propose a hybrid resampling method to approximate finitely supported Wasserstein barycenters on large-scale datasets, which can be combined with any exact solver. Nonasymptotic bounds on the expected error of the objective value as well as the barycenters themselves allow to calibrate computational cost and statistical accuracy. The rate of these upper bo

D. W. Gardenier, J. van Leeuwen

Fast Radio Bursts (FRBs) are energetic, short, bright transients that occur frequently over the entire radio sky. The observational challenges following from their fleeting, generally one-off nature have prevented identification of the underlying sources producing the bursts. As the population of detected FRBs grows, the observed distributions of brightness,

Hai Viet Bui, Ali Mostafazadeh, Sema Seymen

A non-relativistic scalar particle moving on a curved surface undergoes a geometric scattering whose behavior is sensitive to the theoretically ambiguous values of the intrinsic and extrinsic curvature coefficients entering the expression for the quantum Hamiltonian operator. This suggests using the scattering data to settle the ambiguity in the definition o

Yibo Xu, Warren Adams, Akshay Gupte

It is well-known that the convex and concave envelope of a multilinear polynomial over a box are polyhedral functions. Exponential-sized extended and projected formulations for these envelopes are also known. We consider the convexification question for multilinear polynomials that are symmetric with respect to permutations of variables. Such a permutation-i

Boris Landa

It is well known that any positive matrix can be scaled to have prescribed row and column sums by multiplying its rows and columns by certain positive scaling factors (which are unique up to a positive scalar). This procedure is known as matrix scaling, and has found numerous applications in operations research, economics, image processing, and machine learn

Benoît Sohet, Yezekael Hayel, Olivier Beaude, Alban Jeandin

Electric Vehicles' (EVs) growing number has various consequences, from reducing greenhouse gas emissions and local pollution to altering traffic congestion and electricity consumption. More specifically, decisions of operators from both the transportation and the electrical systems are coupled due to EVs' decisions. Thus, decision-making requires a model of

Suryanarayana Maddu, Bevan L. Cheeseman, Christian L. Müller, Ivo F. Sbalzarini

We propose a statistical learning framework based on group-sparse regression that can be used to 1) enforce conservation laws, 2) ensure model equivalence, and 3) guarantee symmetries when learning or inferring differential-equation models from measurement data. Directly learning $\textit{interpretable}$ mathematical models from data has emerged as a valuabl

Omer Faruk Tuna, Ferhat Ozgur Catak, M. Taner Eskil

While state-of-the-art Deep Neural Network (DNN) models are considered to be robust to random perturbations, it was shown that these architectures are highly vulnerable to deliberately crafted perturbations, albeit being quasi-imperceptible. These vulnerabilities make it challenging to deploy DNN models in security-critical areas. In recent years, many resea

William Paul, Armin Hadzic, Neil Joshi, Fady Alajaji

We propose a novel method for enforcing AI fairness with respect to protected or sensitive factors. This method uses a dual strategy performing training and representation alteration (TARA) for the mitigation of prominent causes of AI bias by including: a) the use of representation learning alteration via adversarial independence to suppress the bias-inducin

N. N. Orlova, A. V. Timonina, N. N. Kolesnikov, E. V. Deviatov

We experimentally investigate transport properties of a hybrid structure, which consists of a thin single crystal SnSe flake on a top of 5~$\mu$m spaced Au leads. The structure initially is in highly-conductive state, while it can be switched to low-conductive one at high currents due to the Joule heating of the sample, which should be identified as $\alpha$

Alex Halle, L. Flavio Campanile, Alexander Hasse

Topology optimization is widely used by engineers during the initial product development process to get a first possible geometry design. The state-of-the-art is the iterative calculation, which requires both time and computational power. Some newly developed methods use artificial intelligence to accelerate the topology optimization. These require conventio

Rafael Gomes, Gustavo Granja

Let $p$ denote an odd prime. We show by example that the inequalities obtained in arXiv:1704.05827 for the behaviour of the cohomological index of a join of free $\Z/p$-actions are sharp. Namely, for all odd integers $k,l$ at least one of which is greater than one, we give examples of finite free $\Z/p$-CW complexes of cohomological indices $k$ and $l$ whose

Mehran Shakarami, Ashish Cherukuri, Nima Monshizadeh

This paper considers the problem of steering the aggregative behavior of a population of noncooperative price-taking agents towards a desired behavior. Different from conventional pricing schemes where the price is fully available for design, we consider the scenario where a system regulator broadcasts a price prediction signal that can be different from the

Deepthi S. Prabhu, Annapurni Subramaniam, Snehalata Sahu

A recent study of hot (20,000 to 30,000 K) extreme horizontal branch (EHB) stars in globular clusters (GCs) has led to the discovery of their variability. It is suggested that this variability is driven by the projected rotation of magnetic spots on the stellar surfaces and is expected to have higher amplitudes at shorter wavelengths. Here, we present the an

Hüseyin Bilge Yağcı, Hilmi Volkan Demir

Metasurfaces are subwavelength-thick constructs, consisting of discrete meta-atoms, providing discretized levels of phase accumulation that collectively approximate a designed optical functionality. The meta-atoms utilizing geometric phase with polarization-converting structures produced encouraging implementations of optical components including metalenses.

A. M. Badalian, B. L. G. Bakker

The masses of excited charmed mesons are shown to decrease by $\sim (50-150)$~MeV due to a flattening of the confining potential at large distances, which effectively takes into account open decay channels. The scale of the mass shifts is similar to that in charmonium for $\psi(4660)$ and $\chi_{c0}(4700)$. The following masses of the first excitations: $M(2

Nastassia Grimm, Jaiyul Yoo

Advances in upcoming weak lensing surveys pose new challenges for an accurate modeling of the lensing observables. The wide sky coverage of Euclid makes angular scales down to $l_\mathrm{min}=10$ accessible. At such large angular scales, general relativistic effects manifest themselves, and the lensing magnification cannot be correctly described by the stand

Peter Bugata, Peter Drotar

Feature selection is important step in machine learning since it has shown to improve prediction accuracy while depressing the curse of dimensionality of high dimensional data. The neural networks have experienced tremendous success in solving many nonlinear learning problems. Here, we propose new neural-network based feature selection approach that introduc

Marek Narozniak, Matthieu Dartiailh, Jonathan P. Dowling, Javad Shabani

We propose and analyze a physical system capable of performing topological quantum computation with Majorana zero modes (MZM) in a one-dimensional topological superconductor (1DTS). One of the leading methods to realize quantum gates in 1DTS is to use T-junctions, which allows one to maneuver MZMs such as to achieve braiding. In this paper, we propose a sche

Pritam P Shetty, Jayachandra Bingi

Diffraction is a manifestation of light at edge due to its wavelike nature. The well-known diffraction phenomena are Fresnel and Fraunhofer, they find variety of applications individually. But the synergy of two phenomena is not studied and understood, which is important to understand the compound optical instruments. This research studies and demonstrates t

Matthew Lang, Jake Witherington, Harriet Turner, Matt Owens

Data Assimilation (DA) has enabled huge improvements in the skill of terrestrial operational weather forecasting. In this study, we use a variational DA scheme with a computationally efficient solar wind model and in situ observations from STEREO-A, STEREO-B and ACE. This scheme enables solar-wind observations far from the Sun, such as at 1 AU, to update and

Goran Nakerst, Masudul Haque

According to the eigenstate thermalization hypothesis (ETH), the eigenstate-to-eigenstate fluctuations of expectation values of local observables should decrease with increasing system size. In approaching the thermodynamic limit - the number of sites and the particle number increasing at the same rate - the fluctuations should scale as $\sim D^{-1/2}$ with

Patricio Almirón, Mathias Schulze

We establish Kyoji Saito's continuous limit distribution for the spectrum of Newton non-degenerate hypersurface singularities. Investigating Saito's notion of dominant value in the case of irreducible plane curve singularities, we find that the log canonical threshold is strictly bounded below by the doubled inverse of the Milnor number. We show that this bo

M. Inglot, V. K. Dugaev, A. Dyrdał, J. Barnaś

Electron states localized at a magnetic domain wall in a graphene caplayer with Rashba spin-orbit interaction and coupled to a magnetic overlayer are studied theoretically. It is shown that two one-dimensional bands of edge modes propagating along the domain wall emerge in the energy gap for each Dirac point, and the modes associated with different Dirac poi

Andrea Barth, Robin Merkle

Motivated by the subordinated Brownian motion, we define a new class of (in general discontinuous) random fields on higher-dimensional parameter domains: the subordinated Gaussian random field. We investigate the pointwise marginal distribution of the constructed random fields, derive a L\'evy-Khinchin-type formula and semi-explicit formulas for the covarian

Ramsès Djidjou-Demasse, Arnaud Ducrot, Nicole Mideo, Gaëtan Texier

Many models of within-host malaria infection dynamics have been formulated since the pioneering work of Anderson et al. in 1989. Biologically, the goal of these models is to understand what governs the severity of infections, the patterns of infectiousness, and the variation thereof across individual hosts. Mathematically, these models are based on dynamical