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First time: Photo of black hole!

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posted on Apr, 11 2019 @ 11:11 PM
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a reply to: wildespace

I'm willing to bet, 3D models make it look like a doughnut. It's going to be neat when the first live feed video/s from a satellite/s approaching the BH can be watched.

Although it may require a micro satellite swarm to get any useful data for compilation. Something panoramic as the swarm approaches would be best in my opinion.
edit on 11-4-2019 by ADVISOR because: Correction made



posted on Apr, 12 2019 @ 02:24 AM
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Uh Oh..The media gave Katie Bouman credit, where credit wasn't due.


As the mainstream media attempts to give researcher Katie Bouman credit for the first “photos” of a black hole, it appears her role may have been mostly supervisory, and that other researchers did the majority of the leg work.

According to data provided publicly by GitHub, Bouman made 2,410 contributions to the over 900,000 lines of code required to create the first-of-its-kind black hole image, or 0.26 per cent. Bouman’s contributions also occurred toward the end of the work on the code.
Source: bigleaguepolitics.com...

Why did the media like Katie so much? Or, was it Katie herself who took too much credit, I wonder?



posted on Apr, 12 2019 @ 08:03 AM
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a reply to: buddha

Well technically you can't see a donut hole either, or any hole. You just know it's there because you see the stuff around it an behind.



posted on Apr, 12 2019 @ 10:55 AM
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Ah, so she didn't develop the algorithm that was used, she just helped create it.

Bouman developed an algorithm known as Continuous High-resolution Image Reconstruction using Patch priors, or CHIRP. This algorithm was ultimately not used to create the image of the supermassive black hole inside the core of the galaxy Messier 87. An algorithm that was used was the CLEAN algorithm which was introduced by Jan Högbom.

Bouman was responsible at MIT for an algorithm used in creating the first images of a black hole, published in April 2019, providing computational support to learn about general relativity in the strong-field regime. The machine learning algorithm fills in gaps in data produced by telescopes from around the world. Bouman led efforts in "the verification of images and selection of imaging parameters" for the Event Horizon Telescope.

en.wikipedia.org...
edit on 12-4-2019 by wildespace because: (no reason given)



posted on Apr, 12 2019 @ 06:34 PM
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Still, big kudos to her for her work on the project.

Here's her TED talk from a couple of years ago, explaining the algorithm:


www.youtube.com...



posted on Apr, 13 2019 @ 04:37 PM
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originally posted by: wildespace
Ah, so she didn't develop the algorithm that was used, she just helped create it.

Bouman developed an algorithm known as Continuous High-resolution Image Reconstruction using Patch priors, or CHIRP. This algorithm was ultimately not used to create the image of the supermassive black hole inside the core of the galaxy Messier 87. An algorithm that was used was the CLEAN algorithm which was introduced by Jan Högbom.

Bouman was responsible at MIT for an algorithm used in creating the first images of a black hole, published in April 2019, providing computational support to learn about general relativity in the strong-field regime. The machine learning algorithm fills in gaps in data produced by telescopes from around the world. Bouman led efforts in "the verification of images and selection of imaging parameters" for the Event Horizon Telescope.

en.wikipedia.org...


Yeah, but carewemust's link from bigleagupolitics was also not accurate when it said Andrew Chael entered 850,000 lines of the code for the software used to analyze the data that resulted in this image.

Chael himself refukes that story and says it is not true that he entered so much of the code, and he also gave a lot of the credit for the image to Katie Bouman saying that she was the one who stitched together the data from the four different groups working on it.

Chael was part of one of the four groups who worked intentionally separately using different algorithms and techniques in order to take any bias out of the work. Obe of Bouman's contribuions was taking each of results of those separate groups and stitched them together into a single result.

www.mercurynews.com...


edit on 4/13/2019 by Soylent Green Is People because: (no reason given)



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