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Depth Profile Reconstruction from Rutherford Backscattering Data
[chapter]
1999
Maximum Entropy and Bayesian Methods Garching, Germany 1998
Preserved Fulltext
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
doi:10.1007/978-94-011-4710-1_11
fatcat:k32gbgq54vavzd2qebxofixqmm