Solution intervals considered harmful: on the optimality of radio interferometric gain solutions

TL;DR

This paper examines how solution interval choices in radio interferometric calibration affect data quality, demonstrating the impact of various factors and proposing an automatic selection algorithm to optimize calibration outcomes.

Contribution

It introduces an algorithm for automatic solution interval selection and discusses the importance of regularized calibration methods without solution intervals.

Findings

The algorithm effectively selects solution intervals balancing gain variability and noise.

Proper solution interval choice improves calibration and imaging results.

Regularized calibration methods are advantageous over traditional solution interval approaches.

Abstract

Solution intervals are often used to improve the signal-to-noise ratio during radio interferometric gain calibration. This work investigates how factors such as the noise level, intrinsic gain variability, degree of model incompleteness, and the presence of radio frequency interference impact the selection of solution intervals for calibration. We perform different interferometric simulations to demonstrate how these factors, in combination with the choice of solution intervals, affect calibration and imaging outputs and discuss practical guidelines for choosing optimal solution intervals. Furthermore, we present an algorithm capable of automatically selecting suitable solution intervals during calibration. By applying the algorithm to both simulated and real data, we show that it can successfully choose solution intervals that strike a good balance between capturing intrinsic gain variability and not fitting noise as long as the data are not too inhomogeneously flagged. Furthermore, we elaborate on several practical aspects that emphasize the need to develop regularised calibration algorithms that do not require solution intervals.