First Sharp Image of a Black Hole!
1A team of researchers, including an astronomer with NSF’s #noirlab, has developed a new machine-learning technique to enhance the fidelity and sharpness of radio interferometry images. To demonstrate the power of their new approach, which is called PRIMO, the team created a new, high-fidelity version of the iconic Event Horizon Telescope's image of the supermassive black hole at the center of Messier 87, a giant elliptical galaxy located 55 million light-years from Earth.
The iconic image of the supermassive black hole at the center of Messier 87 has received its first official makeover, thanks to a new machine-learning technique known as PRIMO. This new image better illustrates the full extent of the object’s dark central region and the surprisingly narrow outer ring. To achieve this result, a team of researchers used the original 2017 data obtained by the Event Horizon Telescope (EHT) collaboration and created a new image that, for the first time, represents the full resolution of the EHT. [1]
PRIMO, which stands for principal-component interferometric modeling, was developed by EHT members Lia Medeiros (Institute for Advanced Study), Dimitrios Psaltis (Georgia Tech), Tod Lauer (NSF’s NOIRLab), and Feryal Ozel (Georgia Tech). A paper describing their work is published in The Astrophysical Journal Letters.
In 2017 the EHT collaboration used a network of seven radio telescopes at different locations around the world to form an Earth-sized virtual telescope with the power and resolution capable of observing the “shadow” of a black hole’s event horizon. [2] Though this technique allowed astronomers to see remarkably fine details, it lacked the collecting power of an actual Earth-sized telescope, leaving gaps in the data. The researchers’ new machine-learning technique helped fill in those gaps.