Constraining white dwarf structure and neutrino physics in 47 Tucanae

TL;DR

This study uses advanced statistical methods to analyze white dwarf cooling in 47 Tucanae, constraining hydrogen layer thickness and neutrino physics, with implications for stellar evolution models.

Contribution

It introduces a direct, unbinned maximum likelihood fitting approach combining HST data, stellar evolution models, and MCMC to analyze white dwarf properties in a globular cluster.

Findings

Thicker hydrogen layers are preferred in white dwarfs.

Neutrino production rates in models are consistent with observations.

The data do not constrain the number of neutrino species.

Abstract

We present a robust statistical analysis of the white dwarf cooling sequence in 47 Tucanae. We combine HST UV and optical data in the core of the cluster, Modules for Experiments in Stellar Evolution (MESA) white dwarf cooling models, white dwarf atmosphere models, artificial star tests, and a Markov Chain Monte Carlo (MCMC) sampling method to fit white dwarf cooling models to our data directly. We use a technique known as the unbinned maximum likelihood to fit these models to our data without binning. We use these data to constrain neutrino production and the thickness of the hydrogen layer in these white dwarfs. The data prefer thicker hydrogen layers $(q_\mathrm{H}=3.2\e{-5})$ and we can strongly rule out thin layers $(q_\mathrm{H}=10^{-6})$. The neutrino rates currently in the models are consistent with the data. This analysis does not provide a constraint on the number of neutrino species.