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 \times 10 ^ { -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 .