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arXiv · 2306.17385

Modeling the $R$-ratio and hadronic contributions to $g-2$ with a Treed Gaussian Process

Andrew Fowlie·Qiao Li
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Abstract

The BNL and FNAL measurements of the anomalous magnetic moment of the muon disagree with the Standard Model (SM) prediction by more than $4σ$. The hadronic vacuum polarization (HVP) contributions are the dominant source of uncertainty in the SM prediction. There are, however, tensions between different estimates of the HVP contributions, including data-driven estimates based on measurements of the $R$-ratio. To investigate that tension, we modeled the unknown $R$-ratio as a function of CM energy with a treed Gaussian process (TGP). This is a principled and general method grounded in data-science that allows complete uncertainty quantification and automatically balances over- and under-fitting to noisy data. Our tool yields exploratory results are similar to previous ones and we find no indication that the $R$-ratio was previously mismodeled. Whilst we advance some aspects of modeling the $R$-ratio and develop new tools for doing so, a competitive estimate of the HVP contributions requires domain-specific expertise and a carefully curated database of measurements.

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Andrew Fowlie, Qiao Li. 2023-10-18. Modeling the $R$-ratio and hadronic contributions to $g-2$ with a Treed Gaussian Process. https://doi.org/10.1140/epjc%2Fs10052-023-12110-9

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