4.4 Article

The impact of tandem redundant/sky-based calibration in MWA Phase II data analysis

Publisher

CAMBRIDGE UNIV PRESS
DOI: 10.1017/pasa.2020.37

Keywords

instrumentation; interferometers; methods; data analysis; cosmology; observations; dark ages; reionisation; first stars

Funding

  1. NSF [1613040, 1506024, 1613855, 1643011]
  2. Galkin Foundation
  3. Ministry of Education, Culture, Sports, and Science and Technology (MEXT) of Japan [15H05896, 16H05999, 17H01110]
  4. JSPS
  5. Western Australian Government
  6. Australian Government
  7. Australian Research Council Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) [CE170100013]
  8. ARC [FT180100321]
  9. Western Australian State government
  10. Australian Research Council LIEF [LE160100031]
  11. Dunlap Institute for Astronomy and Astrophysics at the University of Toronto

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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.

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