Model selection and hypothesis testing for large-scale network models with overlapping groupsThe effort to understand network systems in increasing detail has resulted in a diversity of methods designed to extract their large-scale structure from data. Unfortunately, many of these methods…Tiago P. Peixoto·Sep 10, 2014SaveLearn
A new time-frequency method to reveal quantum dynamics of atomic hydrogen in intense laser pulses: Synchrosqueezing TransformThis study introduces a new adaptive time-frequency (TF) analysis technique, synchrosqueezing transform (SST), to explore the dynamics of a laser-driven hydrogen atom at an ab initio level,…Yae-lin Sheu, Liang-Yan Hsu, Hau-tieng Wu et al.·Sep 10, 2014SaveLearn
Dimensionless Units in the SIThe International System of Units (SI) is supposed to be coherent. That is, when a combination of units is replaced by an equivalent unit, there is no additional numerical factor. Here we consider…Peter J. Mohr, William D. Phillips·Sep 8, 2014SaveLearn
Effect of Temperature on the Complexity of Solid Argon SystemWe study the measure of complexity in solid Argon system from the time series data of kinetic energy of single Argon atoms at different equilibrated temperatures. To account the inherent multi-scale…A Giri, S Dey, P Barat·Sep 7, 2014SaveLearn
Stochastic processes via the pathway modelAfter collecting data from observations or experiments, the next step is to build an appropriate mathematical or stochastic model to describe the data so that further studies can be done with the…A. M. Mathai, H. J. Haubold·Sep 6, 2014SaveLearn
Accounting for model error due to unresolved scales within ensemble Kalman filteringWe propose a method to account for model error due to unresolved scales in the context of the ensemble transform Kalman filter (ETKF). The approach extends to this class of algorithms the…Lewis Mitchell, Alberto Carrassi·Sep 2, 2014SaveLearn
Reply to "Local Filtering Fundamentally Against Wide Spectrum"After carefully studying the comment by Wang et al. (arXiv:1408.6420), we found it includes several mistakes and unjustified statements and Wang et al. lack very basic knowledge of dislocations.…Jianwei Miao, M. C. Scott, Chien-Chun Chen et al.·Sep 2, 2014SaveLearn
Fitting theory to data in the presence of background uncertaintiesWhen fitting theory to data in the presence of background uncertainties, the question of whether the spectral shape of the background happens to be similar to that of the theoretical model of…Byron Roe·Aug 29, 2014SaveLearn
Handling uncertainties in background shapes: the discrete profiling methodA common problem in data analysis is that the functional form, as well as the parameter values, of the underlying model which should describe a dataset is not known a priori. In these cases some…P. D. Dauncey, M. Kenzie, N. Wardle et al.·Aug 28, 2014SaveLearn
On the Expectation-Maximization Unfolding with SmoothingError propagation formulae are derived for the expectation-maximization iterative unfolding algorithm regularized by a smoothing step. The effective number of parameters in the fit to the observed…Igor Volobouev·Aug 27, 2014SaveLearn
Local Filtering Fundamentally Against Wide SpectrumChen et al. (1) applied three-dimensional (3D) Fourier filtering together with equal-slope tomographic reconstruction for an observation of nearly all the atoms in a multiply twinned platinum…Ge Wang, Hengyong Yu, Scott S. Verbridge et al.·Aug 27, 2014SaveLearn
Benford Analysis: A useful paradigm for spectroscopic analysisBenford's law is a statistical inference to predict the frequency of significant digits in naturally occurring numerical databases. In such databases this law predicts a higher occurrence of the…Gaurav Bhole, Abhishek Shukla, T. S. Mahesh·Aug 25, 2014SaveLearn
Estimation of Particle Size Distribution and Aspect Ratio of Non-Spherical Particles From Chord Length DistributionInformation about size and shape of particles produced in various manufacturing processes is very important for process and product development because design of downstream processes as well as final…Okpeafoh S. Agimelen, Peter Hamilton, Ian Haley et al.·Aug 19, 2014SaveLearn
Identifying transitions in finite systems by means of partition function zeros and microcanonical inflection-point analysis: A comparison for elastic flexible polymersFor the estimation of transition points of finite elastic, flexible polymers with chain lengths from 13 to 309 monomers, we compare systematically transition temperatures obtained by the Fisher…Julio C. S. Rocha, Stefan Schnabel, David P. Landau et al.·Aug 19, 2014SaveLearn
The physical limit of logical compare operationIn this paper two connected Szilard single molecule engines (with different temperature) model of Maxwell's demon are used to demonstrate and analysis the logical compare operation. The logical…Feng Pan, Heng-Liang Zhang, Jie Qi·Aug 3, 2014SaveLearn
A New Estimator of Intrinsic Dimension Based on the Multipoint Morisita IndexThe size of datasets has been increasing rapidly both in terms of number of variables and number of events. As a result, the empty space phenomenon and the curse of dimensionality complicate the…Jean Golay, Mikhail Kanevski·Aug 2, 2014SaveLearn
Characterization of graphs for protein structure modeling and recognition of solubilityThis paper deals with the relations among structural, topological, and chemical properties of the E.Coli proteome from the vantage point of the solubility/aggregation propensity of proteins. Each…Lorenzo Livi, Alessandro Giuliani, Alireza Sadeghian·Jul 30, 2014SaveLearn
Metrology and 1/f noise: linear regressions and confidence intervals in flicker noise context1/f noise is very common but is difficult to handle in a metrological way. After having recalled the main characteristics of stongly correlated noise, this paper will determine relationships giving…Francois Vernotte, Eric Lantz·Jul 29, 2014SaveLearn
Bayesian parameter estimation of core collapse supernovae using gravitational wave simulationsUsing the latest numerical simulations of rotating stellar core collapse, we present a Bayesian framework to extract the physical information encoded in noisy gravitational wave signals. We fit…Matthew C. Edwards, Renate Meyer, Nelson Christensen·Jul 28, 2014SaveLearn
Reference analysis of the signal + background model in counting experiments II. Approximate reference priorThe objective Bayesian treatment of a model representing two independent Poisson processes, labelled as "signal" and "background" and both contributing additively to the total number…Diego Casadei·Jul 22, 2014SaveLearn
Mantid - Data Analysis and Visualization Package for Neutron Scattering and μSR ExperimentsThe Mantid framework is a software solution developed for the analysis and visualization of neutron scattering and muon spin measurements. The framework is jointly developed by software engineers and…O. Arnold, J. C. Bilheux, J. M. Borreguero et al.·Jul 22, 2014SaveLearn
Convergent Cross-Mapping and Pairwise Asymmetric InferenceConvergent Cross-Mapping (CCM) is a technique for computing specific kinds of correlations between sets of times series. It was introduced by Sugihara et al. and is reported to be "a necessary…James M. McCracken, Robert S. Weigel·Jul 22, 2014SaveLearn
Visualization of short-term heart period variability with network tools as a method for quantifying autonomic driveSignals from heart transplant recipients can be considered to be a natural source of information for a better understanding of the impact of the autonomic nervous system on the complexity of heart…Danuta Makowiec, Beata Graff, Agnieszka Kaczkowska et al.·Jul 18, 2014SaveLearn
Identification of cross and autocorrelations in time series within an approach based on Wigner eigenspectrum of random matricesWe present an original and novel method based on random matrix approach that enables to distinguish the respective role of temporal autocorrelations inside given time series and cross correlations…Michal Sawa, Dariusz Grech·Jul 17, 2014SaveLearn
A Bayesian Approach for Parameter Estimation and Prediction using a Computationally Intensive ModelBayesian methods have been very successful in quantifying uncertainty in physics-based problems in parameter estimation and prediction. In these cases, physical measurements y are modeled as the best…Dave Higdon, Jordan D. McDonnell, Nicolas Schunck et al.·Jul 11, 2014SaveLearn