Monte Carlo calculations of cluster statistics in continuum models of composite morphology

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Abstract
We describe a simple and efficient algorithm for sampling physical cluster statistics in Monte Carlo simulations of continuum morphology models. The algorithm produces a variety of information including the pair connectedness function, cluster size distribution, and mean cluster size. The approach can be applied to any system, given a definition of a physical cluster for that system. Results are presented for two types of models commonly used in studies of percolation phenomena; randomly centered spheres and the concentric shell (extended sphere) model. The simulation results are used to assess the accuracy of the predictions of the Percus–Yevick closure of the Ornstein–Zernike equation for the pair connectedness function.

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