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

Research output: Chapter in Book/Report/Conference proceeding › Conference paper › peer-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 language	English
Title of host publication	UP2018 - Proceedings
Publisher	EPJ Web of Conferences
Number of pages	3
Volume	205
DOIs	https://doi.org/10.1051/epjconf/201920509025
Publication status	Published - Apr 2019
Event	XXI International Conference on Ultrafast Phenomena - Hamburg, Germany Duration: 15 Jul 2018 → 21 Jul 2018 Conference number: 21

Conference

Conference	XXI International Conference on Ultrafast Phenomena
Abbreviated title	UP2018
Country/Territory	Germany
City	Hamburg
Period	15/07/18 → 21/07/18

Fields of Expertise

Advanced Materials Science

Access to Document

10.1051/epjconf/201920509025

FWF - ESR in He nanodroplets - ESR in He nanodroplets to study magnetism and spin dynamics
Ernst, W. (Project manager on research unit), Poms, J. (Attendee / Assistant), Koch, M. (Consortium manager resp. coordinator with external organisations), Ratschek, M. (Attendee / Assistant) & VOLK, A. (Attendee / Assistant)
11/10/10 → 10/10/13
Project: Research project

Cite this

@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 = 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",

}

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

Conference

Fields of Expertise

Access to Document

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Projects

FWF - ESR in He nanodroplets - ESR in He nanodroplets to study magnetism and spin dynamics

Cite this