Frequentist analyses of solar neutrino data (updated including KamLAND and SNO data)

TL;DR

This paper applies frequentist statistical methods to analyze solar neutrino data, including recent KamLAND, SNO, and SK results, revealing that detailed analysis reduces the viability of certain neutrino oscillation solutions.

Contribution

It introduces a comprehensive frequentist analysis of solar neutrino data, incorporating recent experimental results and comparing different confidence region construction methods.

Findings

Good agreement with Delta chi^2 approximation for total rates

Reduced goodness-of-fit for SMA and LOW solutions with full data

Updated analysis includes KamLAND, SNO, and SK data

Abstract

The solar neutrino data are analyzed in a frequentist framework, using the Crow-Gardner and Feldman-Cousins prescriptions for the construction of confidence regions. Including in the fit only the total rates measured by the various experiments, both methods give results similar to the commonly used Delta chi^2-cut approximation. When fitting the full data set, the Delta chi^2-cut still gives a good approximation of the Feldman-Cousins regions. However, a careful statistical analysis significantly reduces the goodness-of-fit of the SMA and LOW solutions. In the addenda we discuss the implications of the latest KamLAND, SNO and SK data.