Interferometric Imaging with PURIFY: Real Observations + Wide-field Corrections

Thurs 4 July, 2019 @12:00 PM, level 6, David Caro Building
Luke Pratley, Mullard Space Science Laboratory, University College London



The standard methods in radio interferometry for reconstructing images, such as CLEAN and its variants, have served the community well over the last few decades and have survived largely because they are pragmatic. However, they produce reconstructed interferometric images that are limited in quality and scalability for big data. In this work, we demonstrate the use of computationally distributed state-of-the-art sparse image reconstruction algorithms which have been implemented in the PURIFY software package. We do this by applying PURIFY to real interferometric observations from the Very Large Array (VLA) and the Australia Telescope Compact Array (ATCA), where PURIFY out performs CLEAN in modelling structure shown by the residuals. Lastly, we use PURIFY in wide-field imaging at low frequencies, where the w-projection algorithm models wide-fields of view with the non-coplanar w-term.The required accuracy and computational cost of these corrections is one of the largest unsolved challenges facing next generation radio interferometers. We show that the same calculation can be performed with a radially symmetric w-projection kernel, where we use one dimensional adaptive quadrature to calculate the resulting Hankel transform, decreasing the computation required for kernel generation by several orders of magnitude, whilst preserving the accuracy. We demonstrate the potential of our radially symmetric w-projection kernel via sparse image reconstruction, using the software package PURIFY. We develop a distributed w-stacking and w-projection hybrid algorithm where we apply exact w-term corrections for each measurement from observations from the Murchison Widefield Array (MWA), showing that it allows full wide-field correction for real data sets.