WS-Snapshot: An effective algorithm for wide-field and large-scale imaging

Abstract

The Square Kilometre Array (SKA) is the largest radio interferometer under construction in the world. The high accuracy, wide-field and large size imaging significantly challenge the construction of the Science Data Processor (SDP) of SKA. We propose a hybrid imaging method based on improved W-Stacking and snapshots. The w range is reduced by fitting the snapshot $uv$ plane, thus effectively enhancing the performance of the improved W-Stacking algorithm. We present a detailed implementation of WS-Snapshot. With full-scale SKA1-LOW simulations, we present the imaging performance and imaging quality results for different parameter cases. The results show that the WS-Snapshot method enables more efficient distributed processing and significantly reduces the computational time overhead within an acceptable accuracy range, which would be crucial for subsequent SKA science studies.