How Bayesian methods can improve $R$-matrix analyses of data: the example of the $dt$ Reaction

Understand

The $^3{\rm H}(d,n)^4{\rm He}$ reaction is of significant interest in nuclear astrophysics and nuclear applications.

• It is an important, early step in big-bang nucleosynthesis and a key process in nuclear fusion reactors.
• We use one- and two-level $R$-matrix approximations to analyze data on the cross section for this reaction at center-of-mass energies below 215 keV.
• We critically examine the data sets using a Bayesian statistical model that allows for both common-mode and additional point-to-point uncertainties.