Speaker
Description
Accurate modelling of the Galactic radio foreground is essential for detecting the cosmological 21cm signal. Such a model can aid foreground mitigation in both ongoing searches for the global EoR signal and upcoming efforts by instruments such as HERA to detect the 21cm brightness temperature power spectrum. In this talk, we outline a new low frequency global sky model, the Bayesian Global Sky Model (B-GSM). We extend on traditional PCA based models e.g. GSM by introducing a Bayesian framework to determine components and spectra.
In B-GSM, nested sampling is used to sample the posterior distributions of component maps and their spectra, and to determine Bayesian evidence values for different variations of model. Model comparisons, using this Bayesian evidence, allow the choice of number of components and spectral parametrisation to be guided by the data. This results in a data driven reconstruction of the Galactic foreground, with the components and spectra inferred from data across the whole sky, and with inherent quantification of uncertainty in the models predictions.
We present preliminary results from this model and outline future work that we will conduct in this area
