How Complex Is a Fractal? Head/tail Breaks and Fractional HierarchyA fractal bears a complex structure that is reflected in a scaling hierarchy, indicating that there are far more small things than large ones. This scaling hierarchy can be effectively derived using…Bin Jiang, Ding Ma·Feb 26, 2017SaveLearn
Visibility graphs of random scalar fields and spatial dataThe family of visibility algorithms were recently introduced as mappings between time series and graphs. Here we extend this method to characterize spatially extended data structures by mapping…Lucas Lacasa, Jacopo Iacovacci·Feb 25, 2017SaveLearn
Detecting dynamical changes in time series by using the Jensen Shannon DivergenceMost of the time series in nature are a mixture of signals with deterministic and random dynamics. Thus the distinction between these two characteristics becomes important. Distinguishing between…D. M. Mateos, L. Riveaud, P. W. Lamberti·Feb 24, 2017SaveLearn
More efficient formulas for efficiency correction of cumulants and effect of using averaged efficiencyWe derive formulas for the efficiency correction of cumulants with many efficiency bins. The derivation of the formulas is simpler than the previously suggested method, but the numerical cost is…Toshihiro Nonaka, Masakiyo Kitazawa, ShinIchi Esumi·Feb 23, 2017SaveLearn
STAR Data Reconstruction at NERSC/Cori, an adaptable Docker container approach for HPCAs HPC facilities grow their resources, adaptation of classic HEP/NP workflows becomes a need. Linux containers may very well offer a way to lower the bar to exploiting such resources and at the…Mustafa Mustafa, Jan Balewski, Jérôme Lauret et al.·Feb 21, 2017SaveLearn
Model-independent partial wave analysis using a massively-parallel fitting frameworkThe functionality of GooFit, a GPU-friendly framework for doing maximum-likelihood fits, has been extended to extract model-independent S-wave amplitudes in three-body decays such as $D+ …Liang Sun, Rafael Aoude, Alberto Correa Dos Reis et al.·Feb 19, 2017SaveLearn
A General Probabilistic Approach for Quantitative Assessment of LES Combustion ModelsThe Wasserstein metric is introduced as a probabilistic method to enable quantitative evaluations of LES combustion models. The Wasserstein metric can directly be evaluated from scatter data or…Ross Johnson, Hao Wu, Matthias Ihme·Feb 17, 2017SaveLearn
Measures of spike train synchrony for data with multiple time-scalesBackground: Measures of spike train synchrony are widely used in both experimental and computational neuroscience. Time-scale independent and parameter-free measures, such as the ISI-distance, the…Eero Satuvuori, Mario Mulansky, Nebojsa Bozanic et al.·Feb 17, 2017SaveLearn
Bayesian regression of piecewise homogeneous Poisson processesIn this paper, a Bayesian method for piecewise regression is adapted to handle counting processes data distributed as Poisson. A numerical code in Mathematica is developed and tested analyzing…Diego Sevilla·Feb 17, 2017SaveLearn
Approximate Bayes learning of stochastic differential equationsWe introduce a nonparametric approach for estimating drift and diffusion functions in systems of stochastic differential equations from observations of the state vector. Gaussian processes are used…Philipp Batz, Andreas Ruttor, Manfred Opper·Feb 17, 2017SaveLearn
Support Vector Machines and generalisation in HEPWe review the concept of Support Vector Machines (SVMs) and discuss examples of their use in a number of scenarios. Several SVM implementations have been used in HEP and we exemplify this algorithm…Adrian Bevan, Rodrigo Gamboa Goñi, Jon Hays et al.·Feb 15, 2017SaveLearn
Nanoparticle Size Distribution Quantification: Results of a SAXS Inter-Laboratory ComparisonWe present the first world-wide inter-laboratory comparison of small-angle X-ray scattering (SAXS) for nanoparticle sizing. The measurands in this comparison are the mean particle radius, the width…Brian R. Pauw, Claudia Kästner, Andreas F. Thünemann·Feb 13, 2017SaveLearn
Sparse Representation of Gravitational SoundGravitational Sound clips produced by the Laser Interferometer Gravitational-Wave Observatory (LIGO) and the Massachusetts Institute of Technology (MIT) are considered within the particular context…Laura Rebollo-Neira, A. Plastino·Feb 5, 2017SaveLearn
Optimal design of experiments by combining coarse and fine measurementsIn many contexts it is extremely costly to perform enough high quality experimental measurements to accurately parameterize a predictive quantitative model. However, it is often much easier to carry…Alpha A. Lee, Michael P. Brenner, Lucy J. Colwell·Feb 1, 2017SaveLearn
Analyzing a stochastic process driven by Ornstein-Uhlenbeck noiseA scalar Langevin-type process X(t) that is driven by Ornstein-Uhlenbeck noise η(t) is non-Markovian. However, the joint dynamics of X and η is described by a Markov process in two…B. Lehle, J. Peinke·Jan 31, 2017SaveLearn
Application of the Huang-Hilbert transform and natural time to the analysis of Seismic Electric Signal activitiesThe Huang-Hilbert transform is applied to Seismic Electric Signal (SES) activities in order to decompose them into a number of Intrinsic Mode Functions (IMFs) and study which of these functions…K. A. Papadopoulou, E. S. Skordas·Jan 31, 2017SaveLearn
Adaptive Filtering to Enhance Noise Immunity of Impedance and Admittance Spectroscopy: Comparison with Fourier TransformationThe time-domain technique for impedance spectroscopy consists of computing the excitation voltage and current response Fourier images by fast or discrete Fourier transformation and calculating their…Daniil D. Stupin, Sergei V. Koniakhin, Nikolay A. Verlov et al.·Jan 23, 2017SaveLearn
Single-View 3D Reconstruction of Correlated Gamma-Neutron SourcesWe describe a new method of 3D image reconstruction of neutron sources that emit correlated gammas (e.g. Cf-252, Am-Be). This category includes a vast majority of neutron sources important in nuclear…Mateusz Monterial, Peter Marleau, Sara A. Pozzi·Jan 16, 2017SaveLearn
Subsampling scaling: a theory about inference from partly observed systemsIn real-world applications, observations are often constrained to a small fraction of a system. Such spatial subsampling can be caused by the inaccessibility or the sheer size of the system, and…Anna Levina, Viola Priesemann·Jan 16, 2017SaveLearn
Combining Experiments with Systematic ErrorsWe consider fits to two or more datasets for which results from the sa me experiment share a common systematic uncertainty in addition to their individ ual statistical errors. This is important in…Roger John Barlow·Jan 11, 2017SaveLearn
Two-dimensional structure reconstruction with expectation and maximization algorithmIn this report, we applied expectation and maximization (EM) method described by Philips et al [1] to recover two-dimensional (2D) structure from multiple sparse signal images in random orientation.…Yun Zhao·Jan 9, 2017SaveLearn
Model selection for dynamical systems via sparse regression and information criteriaWe develop an algorithm for model selection which allows for the consideration of a combinatorially large number of candidate models governing a dynamical system. The innovation circumvents a…Niall M. Mangan, J. Nathan Kutz, Steven L. Brunton et al.·Jan 6, 2017SaveLearn
Markov State Models from short non-Equilibrium Simulations - Analysis and Correction of Estimation BiasMany state of the art methods for the thermodynamic and kinetic characterization of large and complex biomolecular systems by simulation rely on ensemble approaches, where data from large numbers of…Feliks Nüske, Hao Wu, Jan-Hendrik Prinz et al.·Jan 6, 2017SaveLearn
Change detection in complex dynamical systems using intrinsic phase and amplitude synchronizationWe present an approach for the detection of sharp change points (short-lived and persistent) in nonlinear and nonstationary dynamic systems under high levels of noise by tracking the local phase and…Ashif Sikandar Iquebal, Satish Bukkapatnam, Arun Srinivasa·Jan 3, 2017SaveLearn
A multifractal surrogate data generation algorithm that preserves pointwise Holder regularity structure, with initial applications to turbulenceAn algorithm is described that can generate random variants of a time series or image while preserving the probability distribution of original values and the pointwise Holder regularity. Thus, it…Christopher J Keylock·Jan 3, 2017SaveLearn