| Issue |
EPJ Web Conf.
Volume 205, 2019
XXI International Conference on Ultrafast Phenomena 2018 (UP 2018)
|
|
|---|---|---|
| Article Number | 09025 | |
| Number of page(s) | 3 | |
| Section | Ultrafast Photochemistry and Photosynthesis | |
| DOI | https://doi.org/10.1051/epjconf/201920509025 | |
| Published online | 16 April 2019 | |
https://doi.org/10.1051/epjconf/201920509025
Bayesian probability theory to identify false coincidences in coincidence experiments
1 Graz University of Technology, Inst. of Experimental Physics, 8010 Graz, Austria
2 Graz University of Technology, Inst. of Theoretical and Computational Physics, 8010 Graz, Austria
* Corresponding author: markus.koch@tugraz.at
Published online: 16 April 2019
We describe a Bayesian formalism to analyse femtosecond pump-probe photoionization experiments with photoelectron-photoion coincidence (PEPICO) detection. This approach overcomes the drawback of extraordinary long data acquisition times of PEPICO detection. In extension to simply excluding false coincidences as previously [1], we here present an investigation of their influence on the underlying spectrum. The software is provided at https://github.com/fslab-tugraz/PEPICOBayes/.
© The Authors, published by EDP Sciences, 2019
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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