A Study on Optimal Experiential W-plane for Wide-Field Gridding Algorithm

Astronomy data processing platform is facing unprecedented big data challenge. SKA(square kilometer array) as the biggest radio synthesis telescope, its generated data rate of averaged visibilities will be hundred gigabit per second. SKA-SDP handles big data and extremely large computing cost by data processing pipeline. Gridding algorithm will take a large proportion of compute load. How to save power cost and improve the computational efficiency, on the prerequisite of guaranteed imaging quality, need to be well-considered. W-projection and w-stacking are two gridding algorithms possibly to be used in SKA-SDP; The paper presents a study on the effect of w-plane in those algorithms. Based on SKA continuum imaging pipeline and simulation observation, we analyze the effect of w-plane to the imaging results. Our experimental results show that w-plane is a crucial parameter for performance promotion, and w-plane should be bigger than experimental value in w-projection algorithm. Compared with w-projection algorithm, w-stacking has advantage in run time, yet w-plane has great effect on w-stacking algorithm. The presented paper is a basic work for study on large field imaging, and a new w-plane for w-projection and w-stacking algorithm is proposed. Our study can serve as a reference for designs of SKA data processing pipeline.