Advice on describing Bayesian analysis of neutron and X-ray reflectometry

TL;DR

This paper offers practical advice for clearly reporting Bayesian analysis results in neutron and X-ray reflectometry to enhance reproducibility and understanding within the scientific community.

Contribution

It provides specific guidelines on reporting Bayesian analysis, including initial conditions, priors, and posterior probabilities, tailored for reflectometry research.

Findings

Improved clarity in reporting Bayesian analysis enhances reproducibility.

Guidelines help standardize presentation of Bayesian results.

Better reporting practices increase the usability of reflectometry data.

Abstract

Driven by the availability of modern software and hardware, Bayesian analysis is becoming more popular in neutron and X-ray reflectometry analysis. The understandability and replicability of these analyses may be harmed by inconsistencies in how the probability distributions central to Bayesian methods are represented in the literature. Herein, we provide advice on how to report the results of Bayesian analysis as applied to neutron and X-ray reflectometry. This includes the clear reporting of initial starting conditions, the prior probabilities, and results of any analysis, and the posterior probabilities that are the Bayesian equivalent of the error bar, to enable replicability and improve understanding. We believe that this advice, grounded in our experience working in the field, will enable greater analytical reproducibility among the reflectometry community, as well as improve the quality and usability of results.