Depth Profile Reconstruction from Rutherford Backscattering Data

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An adaptive kernel method in the Bayesian framework together with a new simulation program for Rutherford backscattering spectroscopy (RBS) have been applied to the analysis of RBS data. Even in the case of strongly overlapping RBS peaks a depth profile reconstruction without noise fitting has been achieved. The adaptive kernel method leads to the simplest depth profile consistent with the data. Erosion and redeposition rates of carbon divertor plates in the fusion experiment ASDEX Upgrade could be determined by RBS-analysis of thin film probes before and after exposition to plasma discharges.
8 pages, 5 figures. To appear in the 1998 Proceedings of the Eighteenth International Workshop on Maximum Entropy and Bayesian Methods. See also http://www.ipp.mpg.de/OP/maxent98/me98.html

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Data Analysis, Statistics and Probability

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http://salesiana.dossiersoluciones.com/handle/123456789/87626

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/physics/9811003
 http://arxiv.org/abs/physics/9811003

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arXiv