Bayesian probability theory to identify false coincidences in coincidence experiments

Pascal Heim; Michael Rumetshofer; Bernhard Thaler; Wolfgang E. Ernst; Wolfgang von der Linden; Markus Koch

doi:10.1051/epjconf/201920509025

Bayesian probability theory to identify false coincidences in coincidence experiments

Pascal Heim, Michael Rumetshofer, Bernhard Thaler, Wolfgang E. Ernst, Wolfgang von der Linden, Markus Koch

Publikation: Beitrag in Buch/Bericht/Konferenzband › Beitrag in einem Konferenzband › Begutachtung

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/.

Originalsprache	englisch
Titel	UP2018 - Proceedings
Herausgeber (Verlag)	EPJ Web of Conferences
Seitenumfang	3
Band	205
DOIs	https://doi.org/10.1051/epjconf/201920509025
Publikationsstatus	Veröffentlicht - Apr. 2019
Veranstaltung	XXI International Conference on Ultrafast Phenomena - Hamburg, Deutschland Dauer: 15 Juli 2018 → 21 Juli 2018 Konferenznummer: 21

Konferenz

Konferenz	XXI International Conference on Ultrafast Phenomena
Kurztitel	UP2018
Land/Gebiet	Deutschland
Ort	Hamburg
Zeitraum	15/07/18 → 21/07/18

Fields of Expertise

Advanced Materials Science

Zugriff auf Dokument

10.1051/epjconf/201920509025

FWF - ESR in He nanodroplets - ESR in He-Tröpfchen für Magnetismus- und Spindynamikstudien
Ernst, W., VOLK, A., Poms, J., Ratschek, M. & Koch, M.
15/10/10 → 10/10/14
Projekt: Forschungsprojekt

Dieses zitieren

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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 = apr,

doi = "10.1051/epjconf/201920509025",

language = "English",

volume = "205",

booktitle = "UP2018 - Proceedings",

publisher = "EPJ Web of Conferences ",

note = "XXI International Conference on Ultrafast Phenomena, UP2018 ; Conference date: 15-07-2018 Through 21-07-2018",

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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

N1 - Conference code: 21

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 paper

VL - 205

BT - UP2018 - Proceedings

PB - EPJ Web of Conferences

T2 - XXI International Conference on Ultrafast Phenomena

Y2 - 15 July 2018 through 21 July 2018

ER -

Bayesian probability theory to identify false coincidences in coincidence experiments

Abstract

Konferenz

Fields of Expertise

Zugriff auf Dokument

Fingerprint

Projekte

FWF - ESR in He nanodroplets - ESR in He-Tröpfchen für Magnetismus- und Spindynamikstudien

Dieses zitieren