Statistical analysis of absolute photopeak efficiency of clover HPGe detectors

被引：0

作者：

Dey, P. ^{[1
]}

Palit, R. ^{[1
]}

Das, Biswajit ^{[1
]}

Kundu, A. ^{[1
]}

Malik, Vishal ^{[1
]}

机构：

[1] Tata Inst Fundamental Res, Dept Nucl & Atom Phys, Mumbai 400005, India

来源：

NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT | 2025年 / 1072卷

关键词：

Absolute photopeak efficiency; y-ray detectors; Machine learning method; Bayesian analysis; Markov chain Monte Carlo method; NUCLEAR-DATA SHEETS; GE(LI) DETECTOR; P VALUE;

D O I：

10.1016/j.nima.2024.170129

中图分类号：

TH7 [仪器、仪表];

学科分类号：

0804 ; 080401 ; 081102 ;

摘要：

The variation of absolute photopeak efficiency of an array of clover HPGe detectors as a function of y-ray energy has been obtained using statistical model analysis. Machine learning technique has been implemented for determining the energy-dependent polynomial of photopeak efficiency. The distribution of parameters of the best-fit model has been deduced by incorporating Markov chain Monte Carlo method working with the basic framework of Bayesian analysis which also provides the correlation between the parameters. This method has the advantage of calculating the posterior probability distribution by maximizing the likelihood function of the experimental data over standard least-squares method. Excellent agreement among the results procured from machine learning, Markov chain Monte Carlo, and least-squares method has been achieved and the correct prediction of the nature of the variation extrapolation region as well as interpolation region has been discussed.

引用

页数：10