Research papers are full of bias and overfitting, bending conclusions to get more money. They should train the method on blurry images of well known subjects, then take new pictures of the black hole reconstructed without knowing what it is.
Fast fourier transforms in Python is actually beginner stuff taught in image analysis courses. Difference mapping is just to subtract one image from another to get rid of the background noise. Shape fitting assumes that one knows the type of shape, because it only approximates parameters and coefficients of your shape.
It was a computer generated image from the start. So it was make believe from the start. All based on the belief that black holes are real. Without any factual base to any of it.
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