Bayesian optimization for computationally extensive probability distributionsAn efficient method for finding a better maximizer of computationally extensive probability distributions is proposed on the basis of a Bayesian optimization technique. A key idea of the proposed…Ryo Tamura, Koji Hukushima·Mar 12, 2018SaveLearn
Towards an Information Geometric characterization/classification of Complex Systems. II. Critical Parameter values from the (c,d)-manifoldIn our previous paper (I) we derived information geometric objects from the two parameter generalized entropy of Hanel and Thurner (2011), using the c,d parameters as labels of the corresponding…Demetris P. K. Ghikas, Fotios D. Oikonomou·Mar 10, 2018SaveLearn
Three-dimensional convolutional neural networks for neutrinoless double-beta decay signal/background discrimination in high-pressure gaseous Time Projection ChamberIn the search for neutrinoless double-beta decay, the high-pressure gaseous Time Projection Chamber has a distinct advantage, because the ionization charge tracks produced by particle interactions…Pengcheng Ai, Dong Wang, Guangming Huang et al.·Mar 5, 2018SaveLearn
A new quantity for statistical analysis: "Scaling invariable Benford distance"For the first time, we introduce "Scaling invariable Benford distance" and "Benford cyclic graph", which can be used to analyze any data set. Using the quantity and the graph, we…Peiyan Luo, Yongqing Li·Mar 3, 2018SaveLearn
On the Study of Chaos and Memory Effects in the Bonhoeffer-van der Pol Oscillator with a Non-Ideal CapacitorIn this paper, the voltage fluctuations of the Bonhoeffer van der pol oscillator system with a non-ideal capacitor were investigated. Here, the capacitor was modeled, using a fractional differential…Jamieson Brechtl, Xie Xie, Karin A. Dahmen et al.·Mar 3, 2018SaveLearn
Sparse Identification of Nonlinear Dynamics for Rapid Model RecoveryBig data has become a critically enabling component of emerging mathematical methods aimed at the automated discovery of dynamical systems, where first principles modeling may be intractable.…Markus Quade, Markus Abel, J. Nathan Kutz et al.·Mar 2, 2018SaveLearn
Topological time-series analysis with delay-variant embeddingIdentifying the qualitative changes in time-series data provides insights into the dynamics associated with such data. Such qualitative changes can be detected through topological approaches, which…Quoc Hoan Tran, Yoshihiko Hasegawa·Mar 1, 2018SaveLearn
Quantifying Acoustophoretic Separation of Microparticle Populations by Mean-and-Covariance Dynamics for Gaussians in Mixture ModelsA method for the quantification of acoustophoretic separation and dispersion for microparticle populations featuring continuously distributed physical parameters is presented. The derivation of the…Fabio Garofalo·Feb 27, 2018SaveLearn
Gamma-ray intensities in multi-gated spectraThe level structure of nuclei offers a large amount and variety of information to improve our knowledge of the strong interaction and of mesoscopic quantum systems. Gamma spectroscopy is a powerful…Camille Ducoin, Guillaume Maquart, Olivier Stézowski·Feb 16, 2018SaveLearn
Two- and Multi-dimensional Curve Fitting using Bayesian InferenceFitting models to data using Bayesian inference is quite common, but when each point in parameter space gives a curve, fitting the curve to a data set requires new nuisance parameters, which specify…Andrew W. Steiner·Feb 14, 2018SaveLearn
Probabilistic modelling and reconstruction of strainThis paper deals with modelling and reconstruction of strain fields, relying upon data generated from neutron Bragg-edge measurements. We propose a probabilistic approach in which the strain field is…Carl Jidling, Johannes Hendriks, Niklas Wahlström et al.·Feb 10, 2018SaveLearn
Event-by-Event Efficiency Fluctuations and Efficiency Correction for Cumulants of Superposed Multiplicity Distributions in Relativistic Heavy-ion Collision ExperimentsWe performed systematic studies on the effects of event-by-event efficiency fluctuations on efficiency correction for cumulant analysis in relativistic heavy-ion collision experiments.…Shu He, Xiaofeng Luo·Feb 8, 2018SaveLearn
Dimension-scalable recurrence threshold estimationThe appropriate selection of recurrence thresholds is a key problem in applications of recurrence quantification analysis (RQA) and related methods across disciplines. Here, we discuss the…K. Hauke Krämer, Reik V. Donner, Jobst Heitzig et al.·Feb 5, 2018SaveLearn
On the Practical Applications of Information Field DynamicsIn this study we explore a new simulation scheme for partial differential equations known as Information Field Dynamics (IFD). Information field dynamics attempts to improve on existing simulation…Martin Dupont·Feb 3, 2018SaveLearn
Double symbolic joint entropy in nonlinear dynamic complexity analysisSymbolizations, the base of symbolic dynamic analysis, are classified as global static and local dynamic approaches which are combined by joint entropy in our works for nonlinear dynamic complexity…Wenpo Yao, Jun Wang·Feb 3, 2018SaveLearn
The footprint of atmospheric turbulence in power grid frequency measurementsFluctuating wind energy makes a stable grid operation challenging. Due to the direct contact with atmospheric turbulence, intermittent short-term variations in the wind speed are converted to power…Hauke Haehne, Jannik Schottler, Matthias Waechter et al.·Feb 2, 2018SaveLearn
Phase space reconstruction for non-uniformly sampled noisy time seriesAnalyzing data from paleoclimate archives such as tree rings or lake sediments offers the opportunity of inferring information on past climate variability. Often, such data sets are univariate and a…Jaqueline Lekscha, Reik V. Donner·Jan 29, 2018SaveLearn
Adaptive covariance inflation in the ensemble Kalman filter by Gaussian scale mixturesThis paper studies multiplicative inflation: the complementary scaling of the state covariance in the ensemble Kalman filter (EnKF). Firstly, error sources in the EnKF are catalogued and discussed in…Patrick N. Raanes, Marc Bocquet, Alberto Carrassi·Jan 25, 2018SaveLearn
State space reconstruction of spatially extended systems and of time delayed systems from the time series of a scalar variableThe space-time representation of high-dimensional dynamical systems that have a well defined characteristic time scale has proven to be very useful to deepen the understanding of such systems and to…Carlos Quintero-Quiroz, M. C. Torrent, Cristina Masoller·Jan 25, 2018SaveLearn
Differential symbolic entropy in nonlinear dynamics complexity analysisDifferential symbolic entropy, a measure for nonlinear dynamics complexity, is proposed in our contribution. With flexible controlling parameter, the chaotic deterministic measure takes advantage of…Wenpo Yao, Jun Wang·Jan 24, 2018SaveLearn
Characterizing Subcritical Assemblies with Time of Flight Fixed by Energy Estimation DistributionsWe present the Time of Flight Fixed by Energy Estimation (TOFFEE) as a measure of the fission chain dynamics in subcritical assemblies. TOFFEE is the time between correlated gamma rays and neutrons,…Mateusz Monterial, Peter Marleau, Sara Pozzi·Jan 24, 2018SaveLearn
Multivariate analysis of short time series in terms of ensembles of correlation matricesWhen dealing with non-stationary systems, for which many time series are available, it is common to divide time in epochs, i.e. smaller time intervals and deal with short time series in the hope to…Manan Vyas, T. Guhr, T. H. Seligman·Jan 23, 2018SaveLearn
Characterization of Time Series Via Rényi Complexity-Entropy CurvesOne of the most useful tools for distinguishing between chaotic and stochastic time series is the so-called complexity-entropy causality plane. This diagram involves two complexity measures: the…Max Jauregui, Luciano Zunino, Ervin K. Lenzi et al.·Jan 17, 2018SaveLearn
Calculating p-values and their significances with the Energy Test for large datasetsThe energy test method is a multi-dimensional test of whether two samples are consistent with arising from the same underlying population, through the calculation of a single test statistic (called…W. Barter, C. Burr, C. Parkes·Jan 16, 2018SaveLearn
Detecting dynamic spatial correlation patterns with generalized wavelet coherence and non-stationary surrogate dataTime series measured from real-world systems are generally noisy, complex and display statistical properties that evolve continuously over time. Here, we present a method that combines wavelet…Mario Chavez, Bernard Cazelles·Jan 15, 2018SaveLearn