A1 Journal article (refereed)
Estimating mean lifetime from partially observed events in nuclear physics (2022)
Karvanen, J., Niilo‐Rämä, M., Sarén, J., & Kärkkäinen, S. (2022). Estimating mean lifetime from partially observed events in nuclear physics. Journal of the Royal Statistical Society Series C: Applied Statistics, 71(1), 3-26. https://doi.org/10.1111/rssc.12519
JYU authors or editors
Publication details
All authors or editors: Karvanen, Juha; Niilo‐Rämä, Mikko; Sarén, Jan; Kärkkäinen, Salme
Journal or series: Journal of the Royal Statistical Society Series C: Applied Statistics
ISSN: 0035-9254
eISSN: 1467-9876
Publication year: 2022
Publication date: 04/08/2021
Volume: 71
Issue number: 1
Pages range: 3-26
Publisher: John Wiley & Sons
Publication country: United Kingdom
Publication language: English
DOI: https://doi.org/10.1111/rssc.12519
Publication open access: Openly available
Publication channel open access: Partially open access channel
Publication is parallel published (JYX): https://jyx.jyu.fi/handle/123456789/77319
Abstract
The mean lifetime is an important characteristic of particles to be identified in nuclear physics. State-of-the-art particle detectors can identify the arrivals of single radioactive nuclei as well as their subsequent radioactive decays (departures). Challenges arise when the arrivals and departures are unmatched and the departures are only partially observed. An inefficient solution is to run experiments where the arrival rate is set very low to allow for the matching of arrivals and departures. We propose an estimation method that works for a wide range of arrival rates. The method combines an initial estimator and a numerical bias correction technique. Simulations and examples based on data on the alpha decays of Lutetium isotope 155 demonstrate that the method produces unbiased estimates regardless of the arrival rate. As a practical benefit, the estimation method enables the use of all data collected in the particle detector, which will lead to more accurate estimates and, in some cases, to shorter experiments.
Keywords: nuclear physics; radioactivity; statistical models; estimating (statistical methods)
Free keywords: design of experiments; missing data; noisy binary search; Poisson process; radioactive decay
Contributing organizations
Ministry reporting: Yes
VIRTA submission year: 2022
JUFO rating: 2