We as humans have been gazing at space and the stars in all their glory for a long time. Whether we are looking at the different constellations through a telescope or astronomers are looking at planets through satellite images, it is an activity that is carried out daily by thousands throughout the world. But while stars and the moon are relatively easy to observe, black holes are not so simple.
According to NASA, the definition of a black hole is a place in space where gravity pulls so much that even light can not escape it and the reason of this pulling is so powerful because a significant amount of matter has been squeezed into a small amount of space. Because of their size and distance from us, astronomers have been unable to produce images of black holes, but a team from MIT’s Computer Science and Artificial Intelligence Laboratory and Harvard University are looking to change that.
By developing a new algorithm that would gather data collected from various radio telescopes worldwide, through a project called Event Horizon Telescope, in a hope to create one large radio telescope dish. Currently, there are six observatories around the globe that have already signed up to take part, with more expecting to follow. There would, of course, be gaps in the areas the telescopes could not reach, but that is where Katie Bouman and her algorithm called CHIRP (Continuous High-resolution Image Reconstruction using Patch priors) come in.
The introduction of the algorithm CHIRP will fill in the gaps that the telescopes cannot reach and can be adapted to be used with any imaging system that uses radio interferometry, like the Event Horizon Telescope. The refined images that the CHIRP will create is the massive leap forward for this field and can only help in the deeper understanding of black holes and more.
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