Effects of model incompleteness on the drift-scan calibration of radio telescopes

TL;DR

This paper investigates how model incompleteness affects the calibration of radio telescopes like HERA and EDGES, revealing biases caused by sky and beam inaccuracies and proposing partial mitigation strategies.

Contribution

It provides a detailed analysis of calibration biases due to model inaccuracies and explores the impact of time-dependent gain models in radio telescope calibration.

Findings

Biases in receiver gain and temperature estimates due to sky and beam errors.

Spectrally variable gain errors caused by model incompleteness.

Partial mitigation of biases using time-dependent gain models.

Abstract

Precision calibration poses challenges to experiments probing the redshifted 21-cm signal of neutral hydrogen from the Cosmic Dawn and Epoch of Reionization (z~30-6). In both interferometric and global signal experiments, systematic calibration is the leading source of error. Though many aspects of calibration have been studied, the overlap between the two types of instruments has received less attention. We investigate the sky based calibration of total power measurements with a HERA dish and an EDGES style antenna to understand the role of auto-correlations in the calibration of an interferometer and the role of sky in calibrating a total power instrument. Using simulations we study various scenarios such as time variable gain, incomplete sky calibration model, and primary beam model. We find that temporal gain drifts, sky model incompleteness, and beam inaccuracies cause biases in the receiver gain amplitude and the receiver temperature estimates. In some cases, these biases mix spectral structure between beam and sky resulting in spectrally variable gain errors. Applying the calibration method to the HERA and EDGES data, we find good agreement with calibration via the more standard methods. Although instrumental gains are consistent with beam and sky errors similar in scale to those simulated, the receiver temperatures show significant deviations from expected values. While we show that it is possible to partially mitigate biases due to model inaccuracies by incorporating a time-dependent gain model in calibration, the resulting errors on calibration products are larger and more correlated. Completely addressing these biases will require more accurate sky and primary beam models.