MFV approach to robust estimate of neutron lifetime

TL;DR

This paper introduces a new statistical method based on the most frequent value to robustly estimate neutron lifetime from diverse measurements, providing a more reliable result than median statistics.

Contribution

The paper presents a novel MFV-based approach for neutron lifetime estimation that is effective regardless of the underlying distribution shape, improving robustness over traditional median statistics.

Findings

MFV estimate of neutron lifetime: 881.16^{+2.25}_{-2.35} s

Median statistics estimate: 881.5^{+5.5}_{-3} s

Detected non-Gaussianity in measurement distributions

Abstract

Aiming at evaluating the lifetime of the neutron, we introduce a novel statistical method to analyse the updated compilation of precise measurements including the 2022 dataset of Particle Data Group (PDG). Based on the minimization for the information loss principle, unlike the median statistics method, we apply the most frequent value (MFV) procedure to estimate the neutron lifetime, irrespective of the Gaussian or non-Gaussian distributions. Providing a more robust way, the calculated result of the MFV is $\tau_n=881.16^{+2.25}_{-2.35}$ s with statistical bootstrap errors, while the result of median statistics is $\tau_n=881.5^{+5.5}_{-3}$ s according to the binomial distribution. Using the different central estimates, we also construct the error distributions of neutron lifetime measurements and find the non-Gaussianity, which is still meaningful.