fast-resolve: Fast Bayesian Radio Interferometric Imaging
Jakob Roth, Philipp Frank, Hertzog L. Bester, Oleg M. Smirnov,, R\"udiger Westermann, Torsten A. En{\ss}lin

TL;DR
Fast-resolve is a new Bayesian radio interferometric imaging algorithm that significantly reduces computational time, enabling analysis of larger datasets while maintaining accuracy, thus broadening the practical application of Bayesian imaging methods.
Contribution
The paper introduces fast-resolve, a computationally efficient Bayesian imaging algorithm that combines CLEAN shortcuts with resolve, allowing faster processing of large radio interferometric datasets.
Findings
Fast-resolve is about 144 times faster than resolve on VLA Cygnus A data.
Fast-resolve maintains accuracy comparable to resolve.
The algorithm enables processing of large MeerKAT datasets previously infeasible.
Abstract
Context: Interferometric imaging is algorithmically and computationally challenging as there is no unique inversion from the measurement data back to the sky maps, and the datasets can be very large. Many imaging methods already exist, but most of them focus either on the accuracy or the computational aspect. Aims: This paper aims to reduce the computational complexity of the Bayesian imaging algorithm resolve, enabling the application of Bayesian imaging for larger datasets. Methods: By combining computational shortcuts of the CLEAN algorithm with the Bayesian imaging algorithm resolve we developed an accurate and fast imaging algorithm which we name fast-resolve. Results: We validate the accuracy of the presented fast-resolve algorithm by comparing it with results from resolve on VLA Cygnus A data. Furthermore, we demonstrate the computational advantages of fast-resolve on a large…
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Taxonomy
TopicsMicrowave Imaging and Scattering Analysis · Radio Astronomy Observations and Technology · Microwave and Dielectric Measurement Techniques
