Depth profile determination with confidence intervals from Rutherford backscattering data

Physics

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Scientific paper

A new simulation program for Rutherford backscattering spectroscopy (RBS) together with an adaptive kernel method in the Bayesian probability theory framework was applied to the analysis of RBS data. Reconstructed depth profiles are free from noise-induced ringing, even for strongly overlapping RBS peaks. This has been achieved by the use of the adaptive kernel method, which generates the least informative depth profile according to the data and in addition allows one to calculate the uncertainty of the obtained depth profiles. The method is applied to erosion measurements of carbon samples.

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