English

Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics

Instrumentation and Detectors 2026-01-23 v1 Data Analysis, Statistics and Probability

Abstract

High-purity germanium (HPGe) gamma-ray detectors are core instruments in nuclear physics and astrophysics experiments, where long-term stability and reliable extraction of decay parameters are essential. However, the standard exponential decay analyses of the detector time-series data are often affected by the strong correlations between the fitted parameters and the sensitivity to detector-related fluctuations and outliers. In this study, we present a robust analysis framework for HPGe detector decay data based on pairwise ratios and the Steiner's most frequent value (MFV) statistic. By forming point-to-point ratios of background-subtracted net counts, the dependence on the absolute detector response is eliminated, removing the amplitude-lifetime correlation inherent to conventional regression. The resulting pairwise lifetime estimates exhibit heavy-tailed behavior, which is efficiently summarized using the MFV, a robust estimator designed for such distributions. For the case study, a long and stable dataset from an HPGe detector was used. This data was gathered during a low-temperature nuclear physics experiment focused on observing the 216 keV gamma-ray line in 97-Ru. Using measurements spanning approximately 10 half-lives, we obtain a mean lifetime of tau = 4.0959 +/- 0.0007 (stat) +/- 0.0110 (syst) d, corresponding to a half-life of T1/2 = 2.8391 +/- 0.0005 (stat) +/- 0.0076 (syst) d. These results demonstrate that the pairwise-MFV approach provides a robust and reproducible tool for analyzing long-duration HPGe detector data in nuclear physics and nuclear astrophysics experiments, particularly for precision decay measurements, detector-stability studies, and low-background monitoring.

Cite

@article{arxiv.2601.00872,
  title  = {Robust Lifetime Estimation from HPGe Radiation-Sensor Time Series Using Pairwise Ratios and MFV Statistics},
  author = {Victor V. Golovko},
  journal= {arXiv preprint arXiv:2601.00872},
  year   = {2026}
}

Comments

This document consists of 24 pages, includes 3 figures, and 1 table. It has been submitted for publication. The data repository will become publicly accessible once the manuscript is accepted

R2 v1 2026-07-01T08:48:51.183Z