Model selection in the average of inconsistent data: an analysis of the measured Planck-constant valuesWhen the data do not conform to the hypothesis of a known sampling-variance, the fitting of a constant to a set of measured values is a long debated problem. Given the data, fitting would require to…Giovanni Mana, Enrico Massa, Maria Predescu·Jul 18, 2020SaveLearn
Integrated VAC: A robust strategy for identifying eigenfunctions of dynamical operatorsOne approach to analyzing the dynamics of a physical system is to search for long-lived patterns in its motions. This approach has been particularly successful for molecular dynamics data, where…Chatipat Lorpaiboon, Erik Henning Thiede, Robert J. Webber et al.·Jul 15, 2020SaveLearn
Supervised learning from noisy observations: Combining machine-learning techniques with data assimilationData-driven prediction and physics-agnostic machine-learning methods have attracted increased interest in recent years achieving forecast horizons going well beyond those to be expected for chaotic…Georg A. Gottwald, Sebastian Reich·Jul 14, 2020SaveLearn
An encryption-decryption framework for validating single-particle imagingWe propose an encryption-decryption framework for validating diffraction intensity volumes reconstructed using single-particle imaging (SPI) with x-ray free-electron lasers (XFELs) when the ground…Zhou Shen, Colin Zhi Wei Teo, Kartik Ayyer et al.·Jul 6, 2020SaveLearn
Pileup corrections on higher-order cumulantsWe propose a method to remove the contributions of pileup events from higher-order cumulants and moments of event-by-event particle distributions. Assuming that the pileup events are given by the…Toshihiro Nonaka, Masakiyo Kitazawa, ShinIchi Esumi·Jun 29, 2020SaveLearn
Evidence for increasing frequency of extreme coastal sea levelsProjections of extreme sea levels (ESLs) are critical for managing coastal risks, but are made complicated by deep uncertainties. One key uncertainty is the choice of model structure used to estimate…Tony E. Wong, Travis Torline, Mingxuan Zhang·Jun 11, 2020SaveLearn
Multinomial, Poisson and Gaussian statistics in count data analysisIt is generally known that counting statistics is not correctly described by a Gaussian approximation. Nevertheless, in neutron scattering, it is common practice to apply this approximation to the…Jakob Lassa, Magnus Egede Bøggild, Per Hedegård et al.·Jun 6, 2020SaveLearn
Parameter-free and fast nonlinear piecewise filtering. Application to experimental physicsNumerous fields of nonlinear physics, very different in nature, produce signals and images, that share the common feature of being essentially constituted of piecewise homogeneous phases. Analyzing…Barbara Pascal, Nelly Pustelnik, Patrice Abry et al.·Jun 5, 2020SaveLearn
What limits the number of observations that can be effectively assimilated by EnKF?The ability of ensemble Kalman filter (EnKF) algorithms to extract information from observations is analyzed with the aid of the concept of the degrees of freedom for signal (DFS). A simple…Daisuke Hotta, Yoichiro Ota·May 31, 2020SaveLearn
Unidimensional and Multidimensional Methods for Recurrence Quantification Analysis with crqaRecurrence quantification analysis is a widely used method for characterizing patterns in time series. This article presents a comprehensive survey for conducting a wide range of recurrence-based…Moreno I. Coco, Dan Mønster, Giuseppe Leonardi et al.·May 28, 2020SaveLearn
Response and Uncertainty of the Parabolic Variance PVAR to Non-Integer Exponents of the Power LawOscillator fluctuations are described as the phase or frequency noise spectrum, or in terms of a wavelet variance as a function of the measurement time. The spectrum is generally approximated by the…François Vernotte, Siyuan Chen, Enrico Rubiola·May 27, 2020SaveLearn
Towards an improved Eigensystem Realization Algorithm for low-error guaranteesEigensystem Realization Algorithm (ERA) is a tool that can produce a reduced order model (ROM) from just input-output data of a given system. ERA creates the ROM while keeping the number of internal…Mohammad N. Murshed, Moajjem Hossain Chowdhury, Md. Nazmul Islam Shuzan et al.·May 27, 2020SaveLearn
Error estimation in the method of quasi-optimal weightsWe examine the problem of construction of confidence intervals within the basic single-parameter, single-iteration variation of the method of quasi-optimal weights. Two kinds of distortions of such…A. D. Morozov, A. V. Lokhov, F. V. Tkachov·May 26, 2020SaveLearn
A Fast Algorithm for Calculation of Thêo1Thêo1 is a frequency stability statistic which is similar to the Allan variance but can provide stability estimates at longer averaging factors and with higher confidence. However, the calculation of…Ben Lewis·May 23, 2020SaveLearn
A machine learning route between band mapping and band structureElectronic band structure (BS) and crystal structure are the two complementary identifiers of solid state materials. While convenient instruments and reconstruction algorithms have made large,…Rui Patrick Xian, Vincent Stimper, Marios Zacharias et al.·May 20, 2020SaveLearn
A deep learning approach to multi-track location and orientation in gaseous drift chambersAccurate measuring the location and orientation of individual particles in a beam monitoring system is of particular interest to researchers in multiple disciplines. Among feasible methods, gaseous…Pengcheng Ai, Dong Wang, Xiangming Sun et al.·May 20, 2020SaveLearn
Stochastic interpolation of sparsely sampled time series via multi-point fractional Brownian bridgesWe propose and test a method to interpolate sparsely sampled signals by a stochastic process with a broad range of spatial and/or temporal scales. To this end, we extend the notion of a fractional…J. Friedrich, S. Gallon, A. Pumir et al.·May 15, 2020SaveLearn
Comparison of different ML methods applied to the classification of events with ttbar in the final state at the ATLAS experimentThis contribution describes the experience with the application of different Machine Learning (ML) techniques to a physics analysis case. The use case chosen is the classification of top-antitop…Samuel Campo Martínez, José Salt, Santiago González de la Hoz et al.·May 14, 2020SaveLearn
Evaluating the phase dynamics of coupled oscillators via time-variant topological featuresBy characterizing the phase dynamics in coupled oscillators, we gain insights into the fundamental phenomena of complex systems. The collective dynamics in oscillatory systems are often described by…Kazuha Itabashi, Quoc Hoan Tran, Yoshihiko Hasegawa·May 7, 2020SaveLearn
Modelling attenuation and velocity of ultrasonics in reconstituted milk powderIn the context of food quality control, ultrasonics provide proven methods which are able to replace manual controls. The latter are subject to the lack of objectivity of human judgement. Automatic…Bernard Lacaze·May 7, 2020SaveLearn
Efficient Bayesian inversion for shape reconstruction of lithography masksBackground: Scatterometry is a fast, indirect and non-destructive optical method for quality control in the production of lithography masks. To solve the inverse problem in compliance with the…Nando Farchmin, Martin Hammerschmidt, Philipp-Immanuel Schneider et al.·May 5, 2020SaveLearn
Conservation Laws and Spin System Modeling through Principal Component AnalysisThis paper examines several applications of principal component analysis (PCA) to physical systems. The first of these demonstrates that the principal components in a basis of appropriate system…David Yevick·Apr 29, 2020SaveLearn
Parametric unfolding. Method and restrictionsParametric unfolding of a true distribution distorted due to finite resolution and limited efficiency for the registration of individual events is discussed. Details of the computational algorithm of…Nikolay Gagunashvili·Apr 27, 2020SaveLearn
MODULO: A software for Multiscale Proper Orthogonal Decomposition of dataIn the era of the Big Data revolution, methods for the automatic discovery of regularities in large datasets are becoming essential tools in applied sciences. This article presents an open software…Davide Ninni, Miguel A. Mendez·Apr 25, 2020SaveLearn
Bayesian machine scientist to compare data collapses for the Nikuradse datasetEver since Nikuradse's experiments on turbulent friction in 1933, there have been theoretical attempts to describe his measurements by collapsing the data into single-variable functions. However,…Ignasi Reichardt, Jordi Pallares Marta Sales-Pardo, Roger Guimera·Apr 25, 2020SaveLearn