Astrophysical S-factors, thermonuclear rates, and electron screening potential for the $^3$He(d,p)$^{4}$He Big Bang reaction via a hierarchical Bayesian model

TL;DR

This paper introduces a hierarchical Bayesian framework combined with R-matrix theory to accurately estimate the S-factors and thermonuclear rates of the $^3$He(d,p)$^{4}$He reaction, considering all uncertainties and electron screening effects.

Contribution

It is the first to embed R-matrix nuclear reaction modeling within a hierarchical Bayesian framework for rate estimation, including channel radii and boundary conditions.

Findings

Improved estimates of thermonuclear rates for the reaction.

First Bayesian R-matrix analysis incorporating systematic uncertainties.

Enhanced understanding of electron screening effects at low energies.

Abstract

We developed a hierarchical Bayesian framework to estimate S-factors and thermonuclear rates for the $^3$He(d,p)$^{4}$He reaction, which impacts the primordial abundances of $^3$He and $^7$Li. The available data are evaluated and all direct measurements are taken into account in our analysis for which we can estimate separate uncertainties for systematic and statistical effects. For the nuclear reaction model, we adopt a single-level, two-channel approximation of R-matrix theory, suitably modified to take the effects of electron screening at lower energies into account. Apart from the usual resonance parameters (resonance location and reduced widths for the incoming and outgoing reaction channel), we include for the first time the channel radii and boundary condition in the fitting process. Our new analysis of the $^3$He(d,p)$^{4}$He S-factor data results in improved estimates for the thermonuclear rates. This work represents the first nuclear rate evaluation using the R-matrix theory embedded into a hierarchical Bayesian framework, properly accounting for all known sources of uncertainty. Therefore, it provides a test bed for future studies of more complex reactions.