Updated determination of the solar neutrino fluxes from solar neutrino data

TL;DR

This paper updates the determination of solar neutrino fluxes using a Bayesian analysis of global neutrino data, comparing different solar models and highlighting the potential for neutrino data to refine solar model predictions.

Contribution

It introduces a Bayesian framework to reconstruct solar neutrino fluxes and compares low and high metallicity solar models using current data.

Findings

Both solar models fit the data equally well.

Neutrino data can improve solar model accuracy.

Bayesian analysis provides detailed flux and parameter estimates.

Abstract

We present an update of the determination of the solar neutrino fluxes from a global analysis of the solar and terrestrial neutrino data in the framework of three-neutrino mixing. Using a Bayesian analysis we reconstruct the posterior probability distribution function for the eight normalization parameters of the solar neutrino fluxes plus the relevant masses and mixing, with and without imposing the luminosity constraint. We then use these results to compare the description provided by different Standard Solar Models. Our results show that, at present, both models with low and high metallicity can describe the data with equivalent statistical agreement. We also argue that even with the present experimental precision the solar neutrino data have the potential to improve the accuracy of the solar model predictions.