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Classification of probability densities on the basis of Pearson’s curves with application to coronal heating simulations
1Max-Planck-Institut für Aeronomie, Max-Planck-Str. 2, D-37191 Katlenburg-Lindau, Germany
2LPCE, CNRS UMR 6115 & Université d’Orléans, 3A av. de la Recherche Scientifique, F-45071 Orléans, France
3Kiev Polytechnic Institute, Department of Applied System Analysis, av. Pobedy 37, Kiev 03056, Ukraine
Abstract. An important task for the problem of coronal heating is to produce reliable evaluation of the statistical properties of energy release and eruptive events such as micro-and nanoflares in the solar corona. Different types of distributions for the peak flux, peak count rate measurements, pixel intensities, total energy flux or emission measures increases or waiting times have appeared in the literature. This raises the question of a precise evaluation and classification of such distributions. For this purpose, we use the method proposed by K. Pearson at the beginning of the last century, based on the relationship between the first 4 moments of the distribution. Pearson's technique encompasses and classifies a broad range of distributions, including some of those which have appeared in the literature about coronal heating. This technique is successfully applied to simulated data from the model of Krasnoselskikh et al. (2002). It allows to provide successful fits to the empirical distributions of the dissipated energy, and to classify them as a function of model parameters such as dissipation mechanisms and threshold.
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Citation: Podladchikova, O., Lefebvre, B., Krasnoselskikh, V., and Podladchikov, V.: Classification of probability densities on the basis of Pearson’s curves with application to coronal heating simulations, Nonlin. Processes Geophys., 10, 323-333, 2003. Bibtex EndNote Reference Manager
