Solving Self-calibration of ALMA Data with an Optimization Method

Abstract

We reformulate the gain correction problem of the radio interferometry as an optimization problem with regularization, which is solved efficiently with an iterative algorithm. Combining this new method with our previously proposed imaging method, PRIISM, the whole process of the self-calibration of radio interferometry is redefined as a single optimization problem with regularization. As a result, the gains are corrected, and an image is estimated. We tested the new approach with ALMA observation data and found it provides promising results.