Bayesian model selection with future 21cm observations of the epoch of reionization

Abstract

We apply Bayesian statistics to perform model selection on different reionization scenarios via the MULTINEST algorithm. Initially, we recover the results shown by 21CMMC for the parameter estimation of 21CMFAST models. We proceed to test several toy models of the epoch of reionization defined in contrasting morphology and scale. We find that LOFAR observations are unlikely to allow model selection even with long integration times. HERA would require 61 dipoles to perform the same analysis in 1080 h, and becomes comparable to the Square Kilometre Array (SKA) with 217 dipoles. We find the SKA requires only 324 h of observation to conclusively distinguish between our models. Once model selection is achievable, an analysis of observational priors is performed finding that neutral fraction checks at specific redshifts add little to no inference. We show the difficulties in model selection at the level of distinguishing fiducial parameters within a model or distinguishing galaxies with a constant versus power-law mass-to-light ratio. Finally, we explore the use of the Savage–Dickey density ratio to show the redundancy of the parameter Rmfp within 21CMFAST.