Hierarchical Bayesian Thermonuclear Rate for the $^7$Be(n,p)$^7$Li Big Bang Nucleosynthesis Reaction
Rafael S. de Souza, Tan Hong Kiat, Alain Coc, Christian Iliadis

TL;DR
This paper develops a hierarchical Bayesian model to derive precise thermonuclear reaction rates for $^7$Be(n,p)$^7$Li, crucial for understanding primordial element abundances in Big Bang nucleosynthesis.
Contribution
It introduces a novel hierarchical Bayesian approach to analyze experimental data, providing more accurate and less biased reaction rates for $^7$Be(n,p)$^7$Li.
Findings
Reaction rate uncertainties are reduced to 1.5-2.0% at temperatures ≤1 GK.
Most commonly used rates in Big Bang simulations have overly optimistic uncertainties.
The model accounts for data discrepancies and physical parameter variations.
Abstract
Big bang nucleosynthesis provides the earliest probe of standard model physics, at a time when the universe was less than a thousand seconds old. It determines the abundances of the lightest nuclides, which give rise to the subsequent history of the visible matter in the Universe. This work derives new Be(n,p)Li thermonuclear reaction rates based on all available experimental information. This reaction sensitively impacts the primordial abundances of Be and Li during big bang nucleosynthesis. We critically evaluate all available data and disregard experimental results that are questionable. For the nuclear model, we adopt an incoherent sum of single-level, two-channel R-matrix approximation expressions, which are implemented into a hierarchical Bayesian model, to analyze the remaining six data sets we deem most reliable. In the fitting of the data, we consistently…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
