Combination and checks of highly correlated measurements of the muon precession frequency in magnetic field for the final FNAL measurement of the muon magnetic anomaly

We describe the procedures developed to assess the consistency of and combine the multiple measurements of the muon spin-precession frequency $\omega_a$ performed by the Muon g-2 collaboration for its 2025 determination of the muon magnetic anomaly. Building on the methods introduced in the 2023 Muon g-2 analysis, we evaluate the correlations among multiple $\omega_a$ measurements on the same data by using bootstrap techniques. This approach enables robust consistency checks and a statistically sound combination of the independent analyses.

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Publication Details

Published
2026-01-30
DOI
https://doi.org/10.22323/1.485.0324
Primary Topic
Computational Physics and Python Applications
Type
article
Field-Weighted Citation Impact
0.00

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article

Combination and checks of highly correlated measurements of the muon precession frequency in magnetic field for the final FNAL measurement of the muon magnetic anomaly

Alberto Lusiani
Computational Physics and Python Applications
article

Combination and checks of highly correlated measurements of the muon precession frequency in magnetic field for the final FNAL measurement of the muon magnetic anomaly

Alberto Lusiani
article en

Abstract

We describe the procedures developed to assess the consistency of and combine the multiple measurements of the muon spin-precession frequency $\omega_a$ performed by the Muon g-2 collaboration for its 2025 determination of the muon magnetic anomaly. Building on the methods introduced in the 2023 Muon g-2 analysis, we evaluate the correlations among multiple $\omega_a$ measurements on the same data by using bootstrap techniques. This approach enables robust consistency checks and a statistically sound combination of the independent analyses.

U.S. Department of Energy, European Commission, Istituto Nazionale di Fisica Nucleare, Fermilab
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Computational Physics and Python Applications
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