Exploring the Model Dependence of MCMC-Based 21 cm Power Spectrum Parameter Constraints

TL;DR

This paper examines how the choice of semi-numerical models affects the constraints on the Epoch of Reionization derived from 21 cm power spectrum data using MCMC methods, highlighting model dependence issues.

Contribution

It demonstrates the sensitivity of 21CMMC parameter constraints to the underlying bubble-finding algorithm in semi-numerical simulations.

Findings

Performance depends on model agreement with mock data

Model dependence impacts astrophysical parameter constraints

Motivates development of model-independent analysis methods

Abstract

Detection and analysis of the cosmic 21 cm signal of neutral hydrogen has long been considered the most promising route towards exploration of the Epoch of Reionization (EoR). 21CMMC, a Markov Chain Monte Carlo sampler of the semi-numerical simulation code 21cmFAST, has already been used in conjunction with published upper limits on the 21 cm signal from the Murchison Widefield Array (MWA), the LOw Frequency ARray (LOFAR), and the Hydrogen Epoch of Reionization Array (HERA) to constrain the astrophysics of the EoR. Here we investigate the extent to which analysis of the EoR performed using 21CMMC is dependent on the underlying semi-numerical model. We used 21cmFAST to simulate two datasets of 21 cm light-cones which differ only in the algorithm used to identify ionized regions (the so-called "bubble-finding" algorithm). We then tested 21CMMC's ability to return key astrophysical parameters when using the different bubble-finding algorithms. We find that the performance of 21CMMC depends sensitively on the agreement between the astrophysical model of our mock data and the model used for sampling. This result has important implications for the analysis of the 21 cm signal performed using 21CMMC and further motivates investigation into model-independent analysis techniques for 21 cm EoR data.