PURIFY provides functionality to perform radio interferometric imaging, i.e. to
recover images from the Fourier measurements taken by radio
interferometric telescopes. PURIFY leverages recent developments in the field of
compressive sensing and convex optimisation, adapted, in some cases extended, and applied to radio interferometric imaging.
PURIFY itself contains functionality specific to radio interferometry, whereas all sparse optimisation functionality is implemented in the companion code SOPT. SOPT provides very general algorithms for solving sparse regularisation problems and is being applied in many areas become radio interferometry.
Since version 3.0, PURIFY and SOPT are highly parallelised and distributed and run efficiently on large computing clusters, with many CPU or GPU cores on each node. PURIFY can be applied to very large data-sets, including 50 billion visibilites (measurements) and beyond.
Version 1.0 of PURIFY and SOPT was implemented by Rafael Carrillo and Jason McEwen, in collaboaration with Yves Wiaux. PURIFY was then completely redesigned and reimplemented at UCL, in collaboration with UCL’s Research Development Software Group. Development of version 2.0 and onwards has been led by Jason McEwen and developed exclusively at UCL.