C M Trott

Understanding the temporal characteristics of data from low-frequency radio telescopes is of importance in devising suitable calibration strategies. Application of time-series analysis techniques to data from radio telescopes can reveal a wealth of information that can aid in calibration. In this paper, we investigate singular spectrum analysis (SSA) as an analysis tool for radio data. We show the intimate connection between SSA and Fourier techniques. We develop the relevant mathematics starting with an idealized periodic dataset and proceeding to include various non-ideal behaviours. We propose a novel technique to obtain long-term gain changes in data, leveraging the periodicity arising from sky drift through the antenna beams. We also simulate several plausible scenarios and apply the techniques to a 30-day time series data collected during 2021 June from SITARA – a short-spacing two element interferometer for global 21-cm detection. Applying the techniques to real data, we find that the first reconstructed component – the trend – has a strong anti-correlation with the local temperature suggesting temperature fluctuations as the most likely origin for the observed variations in the data. We also study the limitations of the calibration in the presence of diurnal gain variations and find that such variations are the likely impediment to calibrating SITARA data with SSA.

We investigate the contribution of extended radio sources such as Centaurus A, and Galactic supernova remnants (SNRs) to our ability to detect the statistical 21-cm signal from the Epoch of Reionisation (EoR) with the Murchison Widefield Array (MWA). These sources are typically ignored because they are in highly attenuated parts of the MWA primary beam, however, in aggregate, these sources have apparent flux densities of $10\, \rm {Jy}$ on angular scales we expect to detect the 21-cm signal. We create bespoke multicomponent 2D Gaussian models for Galactic SNRs and for Centaurus A, and simulate the visibilities for two MWA snapshot observations. We grid those visibilities and then Fourier transform them with respect to frequency, averaging them both spherically and cylindrically to produce the 1D and 2D power spectra. We compare the simulated 1D power spectra to the expected 21-$\rm {cm}$ power spectrum. We find that although these extended sources are in highly attenuated parts of the MWA primary beam pattern, collectively they have enough power (∼104−105 $\rm {mK^2}\, {\it h^{-3}} \, \rm {Mpc^{3}}$) on EoR significant modes $(|{\boldsymbol k}| \lesssim 0.1\, h\, \rm {Mpc^{-1}})$ to prohibit detection of the 21-$\rm {cm}$ signal (∼104 $\rm {mK^2}\, {\it h^{-3}} \, \rm {Mpc^{3}}$). We find that $50{-}90{{\ \rm per\ cent}}$ of sources must be removed in order to reduce leakage to a level of $\sim 10{-}20{{\ \rm per\ cent}}$ of the 21-$\rm {cm}$ power spectrum on EoR significant modes. The effects of wide-field extended sources will have implications on the detectability of the 21-$\rm {cm}$ signal for the MWA and with the future Square Kilometre Array (SKA).