Use of time dependent data in Bayesian global 21-cm foreground and signal modelling

Abstract

Global 21-cm cosmology aims to investigate the cosmic dawn and epoch of reionization by measuring the sky averaged H I absorption signal, which requires, accurate modelling of, or correction for, the bright radio foregrounds and distortions arising from chromaticity of the antenna beam. We investigate the effect of improving foreground modelling by fitting data sets from many observation times simultaneously in a single Bayesian analysis, fitting for the same parameter set by performing these fits on simulated data. We find that for a hexagonal dipole antenna, this simultaneous fitting produces a significant improvement in the accuracy of the recovered 21-cm signal, relative to fitting a time average of the data. Furthermore, the recovered models of the foreground are also seen to become more accurate by up to a factor of ∼2–3 relative to time averaged fitting. For a less chromatic log spiral antenna, no significant improvement in signal recovery was found by this process. However, the modelling of the foregrounds was still significantly improved. We also investigate extending this technique to fit multiple data sets from different antennas simultaneously for the same parameters. This is also found to improve both 21-cm signal and foreground modelling, to a higher degree than fitting data set from multiple times from the same antenna.