Functional Decomposition: A new method for search and limit settingIn the analysis of High-Energy Physics data, it is frequently desired to separate resonant signals from a smooth, non-resonant background. This paper introduces a new technique - functional…Ryan Edgar, Dante Amidei, Christopher Grud et al.·May 11, 2018SaveLearn
Study of constraint and impact of a nuisance parameter in maximum likelihood methodMaximum likelihood method is widely used for parameter estimation in high energy physics. To consider various systematic uncertainties, tens of or even hundreds of nuisance parameters (NP) are…Li-Gang Xia·May 10, 2018SaveLearn
Differentiating resting brain states using ordinal symbolic analysisSymbolic methods of analysis are valuable tools for investigating complex time-dependent signals. In particular, the ordinal method defines sequences of symbols according to the ordering in which…C. Quintero-Quiroz, Luis Montesano, A. J. Pons et al.·May 10, 2018SaveLearn
Fitting a function to time-dependent ensemble averaged dataTime-dependent ensemble averages, i.e., trajectory-based averages of some observable, are of importance in many fields of science. A crucial objective when interpreting such data is to fit these…Karl Fogelmark, Michael A. Lomholt, Anders Irback et al.·May 8, 2018SaveLearn
Vector-Valued Spectral Analysis of Space-Time DataIdentifying coherent spatiotemporal patterns generated by complex dynamical systems is a central problem in many science and engineering disciplines. Here, we combine ideas from the theory of…Dimitrios Giannakis, Joanna Slawinska, Abbas Ourmazd et al.·May 7, 2018SaveLearn
Using Quantum Mechanics to Cluster Time SeriesIn this article we present a method by which we can reduce a time series into a single point in R13. We have chosen 13 dimensions so as to prevent too many points from being labeled as…Clark Alexander, Luke Shi, Sofya Akhmametyeva·May 4, 2018SaveLearn
A general procedure for detector-response correction of higher order cumulantsWe propose a general procedure for the detector-response correction (including efficiency correction) of higher order cumulants observed by the event-by-event analysis in heavy-ion collisions. This…Toshihiro Nonaka, Masakiyo Kitazawa, ShinIchi Esumi·May 1, 2018SaveLearn
Scaling property of the statistical Two-Sample Energy TestThe energy test is a powerful binning-free, multi-dimensional and distribution-free tool that can be applied to compare a measurement to a given prediction (goodness-of-fit) or to check whether two…G. Zech·Apr 27, 2018SaveLearn
reductus: a stateless Python data-reduction service with a browser frontendThe online data reduction service reductus transforms measurements in experimental science from laboratory coordinates into physically meaningful quantities with accurate estimation of uncertainties…Brian Maranville, William Ratcliff, Paul Kienzle·Apr 23, 2018SaveLearn
Modelling Reservoir Computing with the Discrete Nonlinear Schr\"odinger EquationWe formulate, using the discrete nonlinear Schroedinger equation (DNLS), a general approach to encode and process information based on reservoir computing. Reservoir computing is a promising avenue…Simone Borlenghi, Magnus Boman, Anna Delin·Apr 23, 2018SaveLearn
Causal network discovery by iterative conditioning: comparison of algorithmsEstimating causal interactions in complex dynamical systems is an important problem encountered in many fields of current science. While a theoretical solution for detecting the causal interactions…Jakub Kořenek, Jaroslav Hlinka·Apr 22, 2018SaveLearn
From Weakly Chaotic Dynamics to Deterministic Subdiffusion via Copula ModelingCopula modeling consists in finding a probabilistic distribution, called copula, whereby its coupling with the marginal distributions of a set of random variables produces their joint distribution.…Pierre Nazé·Apr 19, 2018SaveLearn
Visibility graphs for image processingThe family of image visibility graphs (IVGs) have been recently introduced as simple algorithms by which scalar fields can be mapped into graphs. Here we explore the usefulness of such operator in…Jacopo Iacovacci, Lucas Lacasa·Apr 19, 2018SaveLearn
Fusion of laser diffraction and chord length distribution data for estimation of particle size distribution using multi-objective optimisationThe in situ measurement of the particle size distribution (PSD) of a suspension of particles presents huge challenges. Various effects from the process could introduce noise to the data from which…Okpeafoh S. Agimelen, Carla Ferreira, Bilal Ahmed et al.·Apr 16, 2018SaveLearn
Machine Learning Peeling and Loss Modelling of Time-Domain ReflectometryA fundamental pursuit of microwave metrology is the determination of the characteristic impedance profile of microwave systems. Among other methods, this can be practically achieved by means of…J. R. Rinehart, J. H. Béjanin, T. C. Fraser et al.·Apr 13, 2018SaveLearn
Topological data analysis and diagnostics of compressible MHD turbulenceThe predictions of mean-field electrodynamics can now be probed using direct numerical simulations of random flows and magnetic fields. When modelling astrophysical MHD, it is important to verify…Irina Makarenko, Paul Bushby, Andrew Fletcher et al.·Apr 12, 2018SaveLearn
Statistical algorithms for particle trajectographyThe various algorithms used to extrapolate particle trajectories from measurements are often very time-consuming with computational complexities which are typically quadratic. In this article, we…Frédéric Magniette·Apr 11, 2018SaveLearn
Dependence of exponents on text length versus finite-size scaling for word-frequency distributionsSome authors have recently argued that a finite-size scaling law for the text-length dependence of word-frequency distributions cannot be conceptually valid. Here we give solid quantitative evidence…Alvaro Corral, Francesc Font-Clos·Apr 10, 2018SaveLearn
Parameter estimation with data-driven nonparametric likelihood functionsIn this paper, we consider a surrogate modeling approach using a data-driven nonparametric likelihood function constructed on a manifold on which the data lie (or to which they are close). The…Shixiao W. Jiang, John Harlim·Apr 9, 2018SaveLearn
Open or Closed? Information Flow Decided by Transfer Operators and Forecastability Quality MetricA basic systems question concerns the concept of closure, meaning autonomomy (closed) in the sense of describing the (sub)system as fully consistent within itself. Alternatively, the system may be…Erik M. Bollt·Apr 9, 2018SaveLearn
Method of fractal diversity in data science problemsThe parameter (SNR) is obtained for distinguishing the Gaussian function, the distribution of random variables in the absence of cross correlation, from other functions, which makes it possible to…Vitalii Vladimirov, Elena Vladimirova·Apr 8, 2018SaveLearn
Bayesian model selection with fractional Brownian motionWe implement Bayesian model selection and parameter estimation for the case of fractional Brownian motion with measurement noise and a constant drift. The approach is tested on artificial…Jens Krog, Lars H. Jacobsen, Frederik W. Lund et al.·Apr 4, 2018SaveLearn
A Priori Tests for the MIXMAX Random Number GeneratorWe define two a priori tests of pseudo-random number generators for the class of linear matrix-recursions. The first desirable property of a random number generator is the smallness of serial or…Spyros Konitopoulos, Konstantin G. Savvidy·Apr 3, 2018SaveLearn
Identifying the relevant dependencies of the neural network response on characteristics of the input spaceThe relation between the input and output spaces of neural networks (NNs) is investigated to identify those characteristics of the input space that have a large influence on the output for a given…Stefan Wunsch, Raphael Friese, Roger Wolf et al.·Mar 23, 2018SaveLearn
Statistical test for fractional Brownian motion based on detrending moving average algorithmMotivated by contemporary and rich applications of anomalous diffusion processes we propose a new statistical test for fractional Brownian motion, which is one of the most popular models for…Grzegorz Sikora·Mar 22, 2018SaveLearn