A1 Journal article (refereed)
Applying machine learning methods for the analysis of two-dimensional mass spectra (2023)

Gao, Z., Solders, A., Al-Adili, A., Beliuskina, O., Eronen, T., Kankainen, A., Lantz, M., Moore, I. D., Nesterenko, D. A., Penttilä, H., Pomp, S., Sjöstrand, H., the IGISOL team. (2023). Applying machine learning methods for the analysis of two-dimensional mass spectra. European Physical Journal A, 59, Article 169. https://doi.org/10.1140/epja/s10050-023-01080-x

JYU authors or editors

Beliuskina, Olga
Eronen, Tommi
Kankainen, Anu
Moore, Iain
Nesterenko, Dmitrii
Penttilä, Heikki

Publication details

All authors or editors: Gao, Z.; Solders, A.; Al-Adili, A.; Beliuskina, O.; Eronen, T.; Kankainen, A.; Lantz, M.; Moore, I. D.; Nesterenko, D. A.; Penttilä, H.; et al.

Journal or series: European Physical Journal A

ISSN: 1434-6001

eISSN: 1434-601X

Publication year: 2023

Publication date: 25/07/2023

Volume: 59

Article number: 169

Publisher: Springer

Publication country: Germany

Publication language: English

DOI: https://doi.org/10.1140/epja/s10050-023-01080-x

Publication open access: Openly available

Publication channel open access: Partially open access channel

Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/88890

Abstract

In a measurement of isomeric yield-ratios in fission, the Phase-Imaging Ion-Cyclotron-Resonance technique, which projects the radial motions of ions in the Penning trap (JYFLTRAP) onto a position-sensitive micro-channel plate detector, has been applied. To obtain the yield ratio, that is the relative population of two states of an isomer pair, a novel analysis procedure has been developed to determine the number of detected ions in each state, as well as corrections for the detector efficiency and decay losses. In order to determine the population of the states in cases where their mass difference is too small to reach full separation, a Bayesian Gaussian Mixture model was implemented. The position-dependent efficiency of the micro-channel plate detector was calibrated by mapping it with 133133Cs++ ions, and a Gaussian Process was trained with the position data to construct an efficiency function that could be used to correct the recorded distributions. The obtained numbers of counts of excited and ground-state ions were used to derive the isomeric yield ratio, taking into account decay losses as well as feeding from precursors.

Keywords: nuclear physics; machine learning; mass (physics); nuclear fission; research equipment