Bayesian probability theory to identify false coincidences in coincidence experiments

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Abstract

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/.
Original languageEnglish
Title of host publicationUP2018 - Proceedings
PublisherEPJ Web of Conferences
Number of pages3
Volume205
DOIs
Publication statusPublished - Apr 2019
EventXXI International Conference on Ultrafast Phenomena - Hamburg, Germany
Duration: 15 Jul 201821 Jul 2018
Conference number: 21

Conference

ConferenceXXI International Conference on Ultrafast Phenomena
Abbreviated titleUP2018
CountryGermany
CityHamburg
Period15/07/1821/07/18

Fingerprint

photoelectrons
data acquisition
photoionization
pumps
formalism
computer programs
probes

Fields of Expertise

  • Advanced Materials Science

Cite this

Bayesian probability theory to identify false coincidences in coincidence experiments. / Heim, Pascal; Rumetshofer, Michael; Thaler, Bernhard; Ernst, Wolfgang E.; von der Linden, Wolfgang; Koch, Markus.

UP2018 - Proceedings. Vol. 205 EPJ Web of Conferences , 2019.

Research output: Chapter in Book/Report/Conference proceedingConference contributionResearchpeer-review

Heim, P, Rumetshofer, M, Thaler, B, Ernst, WE, von der Linden, W & Koch, M 2019, Bayesian probability theory to identify false coincidences in coincidence experiments. in UP2018 - Proceedings. vol. 205, EPJ Web of Conferences , XXI International Conference on Ultrafast Phenomena, Hamburg, Germany, 15/07/18. https://doi.org/10.1051/epjconf/201920509025
@inproceedings{73e2bf317a3c449a96a00effb63639a7,
title = "Bayesian probability theory to identify false coincidences in coincidence experiments",
abstract = "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/.",
author = "Pascal Heim and Michael Rumetshofer and Bernhard Thaler and Ernst, {Wolfgang E.} and {von der Linden}, Wolfgang and Markus Koch",
year = "2019",
month = "4",
doi = "10.1051/epjconf/201920509025",
language = "English",
volume = "205",
booktitle = "UP2018 - Proceedings",
publisher = "EPJ Web of Conferences",

}

TY - GEN

T1 - Bayesian probability theory to identify false coincidences in coincidence experiments

AU - Heim, Pascal

AU - Rumetshofer, Michael

AU - Thaler, Bernhard

AU - Ernst, Wolfgang E.

AU - von der Linden, Wolfgang

AU - Koch, Markus

PY - 2019/4

Y1 - 2019/4

N2 - 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/.

AB - 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/.

U2 - 10.1051/epjconf/201920509025

DO - 10.1051/epjconf/201920509025

M3 - Conference contribution

VL - 205

BT - UP2018 - Proceedings

PB - EPJ Web of Conferences

ER -