We present a new reconstruction of the Event Horizon Telescope (EHT) image of the M87 black hole from the 2017 data set. We use PRIMO, a novel dictionary-learning based algorithm that uses high-fidelity simulations of accreting black holes as a training set. By learning the correlations between the different regions of the space of interferometric data, this approach allows us to recover high-fidelity images even in the presence of sparse coverage and reach the nominal resolution of the EHT array. The black hole image comprises a thin bright ring with a diameter of 41.5±0.6μas and a fractional width that is at least a factor of two smaller than previously reported. This improvement has important implications for measuring the mass of the central black hole in M87 based on the EHT images.
@article{arxiv.2304.06079,
title = {The Image of the M87 Black Hole Reconstructed with PRIMO},
author = {Lia Medeiros and Dimitrios Psaltis and Tod R. Lauer and Feryal Ozel},
journal= {arXiv preprint arXiv:2304.06079},
year = {2023}
}