Simultaneous PIXE and RBS data analysis using Bayesian Inference with the DataFurnace code

TL;DR

This paper introduces an integrated Bayesian analysis method within the DataFurnace code for simultaneous RBS and PIXE data analysis, enabling more consistent and comprehensive sample characterization.

Contribution

It develops a novel approach combining PIXE and RBS data analysis using Bayesian inference in the DataFurnace software, incorporating the LibCPIXE library for enhanced capabilities.

Findings

Simultaneous analysis yields more consistent sample parameters.

The method improves accuracy over independent analyses.

Examples demonstrate the effectiveness of combined data fitting.

Abstract

The Rutherford Backscattering Spectroscopy (RBS) and Particle Induced X-ray Emission (PIXE) techniques can be used to obtain complementary information about the characteristics of a sample but, traditionally, a gap has separated the available computer codes for analyzing data from each technique, being hard to simultaneously analyze data from the same sample. The recent development of a free and open source library, LibCPIXE, for PIXE simulation and analysis of arbitrary multilayered samples, has permitted to integrate this technique into the DataFurnace code which already handles many other IBA techniques such as Rutherford and non-Rutherford backscattering, elastic recoil detection, and non-resonant nuclear reaction analysis. The fitting capabilities of DataFurnace can therefore now be applied to PIXE spectra as well, including the Bayesian Inference analysis and the simultaneous and coherent fitting of multiple spectra from different techniques. Various examples are presented in which the simultaneous RBS and PIXE analysis allows us to obtain consistent results that cannot be obtained by independent analysis of the data from each technique.