The Correlation Calibration of PAPER-64 data
Tamirat G. Gogo, Yin-Zhe Ma, Piyanat Kittiwisit, Jonathan L. Sievers,, Aaron R. Parsons, Jonathan C. Pober, Daniel C. Jacobs, Carina Cheng, Matthew, Kolopanis, Adrian Liu, Saul A. Kohn, James E. Aguirre, Zaki S. Ali, Gianni, Bernardi, Richard F. Bradley, David R. DeBoer

TL;DR
This paper introduces a hybrid calibration method called CorrCal for 21-cm EoR experiments, which improves calibration accuracy by combining sky model and array redundancy information, leading to better foreground removal.
Contribution
The paper presents CorrCal, a novel hybrid calibration scheme that relaxes array redundancy assumptions and incorporates sky data, improving calibration accuracy for 21-cm EoR observations.
Findings
Approximately 6% improvement in power spectra near the foreground wedge limit.
Reduced spectral structure in data after CorrCal calibration.
Foundation for future calibration algorithm enhancements.
Abstract
Observation of redshifted 21-cm signal from the Epoch of Reionization (EoR) is challenging due to contamination from the bright foreground sources that exceed the signal by several orders of magnitude. The removal of this very high foreground relies on accurate calibration to keep the intrinsic property of the foreground with frequency. Commonly employed calibration techniques for these experiments are the sky model-based and the redundant baseline-based calibration approaches. However, the sky model-based and redundant baseline-based calibration methods could suffer from sky-modeling error and array redundancy imperfection issues, respectively. In this work, we introduce the hybrid correlation calibration ("CorrCal") scheme, which aims to bridge the gap between redundant and sky-based calibration by relaxing redundancy of the array and including sky information into the calibration…
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