The inverse imaging task in radio interferometry is a key limiting factor to retrieving Bayesian uncertainties in radio astronomy in a computationally effective manner. We use a score-based prior derived from optical images of galaxies to recover images of protoplanetary disks from the DSHARP survey. We demonstrate that our method produces plausible posterior samples despite the misspecified galaxy prior. We show that our approach produces results which are competitive with existing radio interferometry imaging algorithms.
@article{arxiv.2311.18012,
title = {Bayesian Imaging for Radio Interferometry with Score-Based Priors},
author = {Noe Dia and M. J. Yantovski-Barth and Alexandre Adam and Micah Bowles and Pablo Lemos and Anna M. M. Scaife and Yashar Hezaveh and Laurence Perreault-Levasseur},
journal= {arXiv preprint arXiv:2311.18012},
year = {2023}
}
Comments
10+4 pages, 6 figures, Machine Learning and the Physical Sciences Workshop, NeurIPS 2023