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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.

 

Preparing for a first detection of the 21-cm signal during reionization by large-scale interferometer experiments requires rigorous testing of the data analysis and reduction pipelines. Validating that these do not erroneously add/remove features mimicking the signal (e.g. from side lobes or large-scale power leakage) requires simulations extending beyond the primary field of view. However, the Murchison Wide Field Array (MWA) with a field of view of ∼252 deg2 would require simulations spanning several Gpcs, which are currently infeasible. To address this, we developed a simplified version of the seminumerical reionization simulation code 21cmfast, sacrificing some physical accuracy (linear structure formation) in favour of extremely large volumes. We then constructed a 7.5 Gpc comoving volume specifically tailored to the binned spectral resolution of the MWA (∼1.17 cMpc), required for validating the pipeline used in the 2020 MWA 21-cm power spectrum (PS) upper limits. With this large-volume simulation, we then explored: (i) whether smaller volume simulations are biased by missing large-scale modes, (ii) non-Gaussianity in the cosmic variance uncertainty, (iii) biases in the recovered 21-cm PS following foreground wedge avoidance, and (iv) the impact of tiling smaller simulations to achieve large volumes. We found (i) no biases from missing large-scale power, (ii) significant contribution from non-Gaussianity, as expected, (iii) a 10–20 per cent overestimate of the 21-cm PS following wedge mode excision, and (iv) tiling smaller simulations underestimates the large-scale power and cosmic variance.

 

Abstract Precise instrumental calibration is of crucial importance to 21-cm cosmology experiments. The Murchison Widefield Array’s (MWA) Phase II compact configuration offers us opportunities for both redundant calibration and sky-based calibration algorithms; using the two in tandem is a potential approach to mitigate calibration errors caused by inaccurate sky models. The MWA Epoch of Reionization (EoR) experiment targets three patches of the sky (dubbed EoR0, EoR1, and EoR2) with deep observations. Previous work in Li et al. (2018) and (2019) studied the effect of tandem calibration on the EoR0 field and found that it yielded no significant improvement in the power spectrum (PS) over sky-based calibration alone. In this work, we apply similar techniques to the EoR1 field and find a distinct result: the improvements in the PS from tandem calibration are significant. To understand this result, we analyse both the calibration solutions themselves and the effects on the PS over three nights of EoR1 observations. We conclude that the presence of the bright radio galaxy Fornax A in EoR1 degrades the performance of sky-based calibration, which in turn enables redundant calibration to have a larger impact. These results suggest that redundant calibration can indeed mitigate some level of model incompleteness error.