Performance evaluation of baseline-dependent averaging based onfull-scale SKA1-LOW simulation

TL;DR

This paper evaluates baseline-dependent averaging (BDA) for SKA1-LOW, showing it can significantly reduce data volume while maintaining imaging quality, based on full-scale simulations.

Contribution

It develops and implements a comprehensive BDA module within RASCIL and systematically assesses its performance using realistic SKA1-LOW simulations.

Findings

Data volume reduced by 50% to 85% with BDA.

Smaller maximum time interval ($t_{max}$) results in less imaging degradation.

BDA effectively balances data reduction and image quality in SKA simulations.

Abstract

The Square Kilometre Array (SKA) is the largest radio interferometer under construction in the world. Its immense amount of visibility data poses a considerable challenge to the subsequent processing by the science data processor (SDP). Baseline dependent averaging (BDA), which reduces the amount of visibility data based on the baseline distribution of the radio interferometer, has become a focus of SKA SDP development. This paper developed and implemented a full-featured BDA module based on Radio Astronomy Simulation, Calibration and Imaging Library (RASCIL). Simulated observations were then performed with RASCIL based on a full-scale SKA1-LOW configuration. The performance of the BDA was systematically investigated and evaluated based on the simulated data. The experimental results presented that the amount of visibility data is reduced by about 50\% to 85\% for different time intervals ($\Delta t_{max}$). In addition, different $\Delta t_{max}$ have a significant effect on the imaging quality. The smaller the $\Delta t_{max}$, the smaller the degradation of the imaging quality.