High School AI Enhanced image of M87 black hole

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A new reconstruction of the M87 black hole image has been achieved using the Event Horizon Telescope's 2017 data set, employing the innovative PRIMO algorithm. This method leverages high-fidelity simulations of black holes to enhance image quality despite sparse data coverage. The algorithm effectively identifies correlations within interferometric data, resulting in improved resolution of the black hole's features. This advancement marks a significant step in astrophysical imaging techniques. The findings contribute to a deeper understanding of black hole dynamics and their environments.
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TL;DR
A reconstruction of the Event Horizon Telescope (EHT) image of the M87 black hole from the 2017 data set
https://iopscience.iop.org/article/10.3847/2041-8213/acc32d

From the abstract, "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."

Back drop from the original study, https://eventhorizontelescope.org/blog/astronomers-reveal-first-image-black-hole-heart-our-galaxy

Smithsonian article.

https://www.smithsonianmag.com/smar...image-of-a-supermassive-black-hole-180981990/
 
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