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Estimation of the Neutron Lifetime: Comparison of Methods Which Account for Background
Published
Author(s)
Kevin J. Coakley, Grace L. Yang
Abstract
In the first stage of each run of a neutron lifetime experiment, a magnetic trap is filled with neutrons. In the second stage of each run, neutron decay events are observed. In a separate experiment of multiple runs, only background signals are measured after refilling the trap. In one approach, the mean lifetime of the neutron is estimated by fitting a two-parameter exponential model to the background-corrected data. In a second approach, the neutron lifetime is estimated by fitting a more complicated model to the neutron decay plus background data and the background only data coming from both experiments. In the second approach, we assume knowledge of a statistical model for the background. For each approach, we compute the asymptotic standard deviation of the lifetime estimate in terms of the time spent filling, the trap, Tf, the time spent observing decay events, Td, and the ratio, R, of the number of runs of background only experiments to primary neutron decay plus background experiments. For each approach, we minimize the asymptotic standard error of the lifetime estimate in terms of Tf, Td and R, for various cases. In one case, the background rate is assumed to be stationary. In another case, the background rate is nonstationary. The comparison of the two approaches is made on the basis of the minimized asymptotic standard deviations. For both cases, the second approach of joint estimation strategy is superior to the background-correction estimation strategy for all cases studied.
Citation
Physical Review C (Nuclear Physics)
Volume
ume 65
Issue
No. 6
Pub Type
Journals
Keywords
background-correction, design of experiments, magnetic trap, neutron lifetime, parametric inference, ultra cold neutrons
Citation
Coakley, K.
and Yang, G.
(2002),
Estimation of the Neutron Lifetime: Comparison of Methods Which Account for Background, Physical Review C (Nuclear Physics)
(Accessed December 14, 2024)