What you can do is to use methods where you [have] do not need any calibration whatsoever and you can still can get pretty good results.
So here on the bottom at the top is the truth image, and this is simulated data, as we are increasing the amount of amplitude error and you can see here ... it's hard to see ... but it breaks down once you add too much gain here. But if we use just closure quantities - we are invariant to that.
So that really, actually, been a really huge step for the project, because we had such bad gains.
~~~~~~~
They also deleted multiple critical comments from that video presentation.
E.g. "Pratik Maitra" posted multiple comments that later disappeared.
Do you think the fact that the CT scanner at your local hospital needs to be calibrated and computationally reconstructed from X-ray intensities mean it does not result in an "image"?
When we use side-scan sonar to create representations of the ocean floor (e.g. https://commons.wikimedia.org/wiki/File:Laevavrakk_"Aid".png), they are computationally reconstructed from the raw data which are not intrinsically recognized as pixels without reconstruction. Are these not "images"?
What is your actual contention here? Is it that any representation which is not the result of a traditional visible-light camera doesn't count as an "image"?
If so it's an irrelevant distinction to make. If not, you need to articulate in a specific and informed way why the way they reconstructed the image was wrong or could be improved.
It seems from your blog that you don't really understand what a "prior" is and why it might be useful for this kind of signal processing.
> CT scanner at your local hospital needs to be calibrated
Of course the scanner (and any other measurement tool) need to be calibrated. Specifically, the scanner (and telescope) needs to be pre-calibrated based on already known samples.
In case of telescope, it needs to be precalibrated based on known images of remote stars.
Katie Bouman (the face of EHT imaging team), however, claims: "you [have] do not need any calibration whatsoever and you can still can get pretty good results"
EHT team tested for some biases, but did not test for the most significant bias.
Because they try to make an image of a black hole, their strongest bias is to see a black hole in anything.
So they should have tested if their final implementation of "imaging method" does NOT see black hole when incoming sparse data does not contain the black hole.
Unfortunately, there is no such test in the presentation.
EHT team tested that "imaging method" that was trained for recognizing a disk (without a hole) - is still able to recognize black hole. See it at [31:55]
But they did not test the reverse: train an imaging method for recognizing black hole, but then feed sparse disk data to that imaging method. Would it be able to see disk or still would see a black hole?
How about trying to feed sparse data of 2 bright stars. Would this imaging method that was trained to recognize black holes -- still be able to see these 2 stars?
Unfortunately, there was no testing like that ... or worse -- they did such testing, but then discarded the results, because it does not impress the public and financial sponsors.
Write a paper or blog post that convincingly makes your case and shows that you deeply understand their approach so are qualified to criticize its flaws.
If you actually believe their result is fake, then it's not like the people you need to convince are hacker news readers; you need to convince other physicists who are in a position to agree with you and do something about it.
Anyway if you go around pointing out things like "comments were deleted! they must be covering something up" you are just (rightly) written off as a conspiracy theorist.
Writing a blog post that you do not succeed in publicizing is the same as not writing a blog post.
Convincing people is not a side effect, it is the goal of a post, or of your strong stance.
The people you need to convince are people who know this subject well. You are in the wrong place. Physicists or data analysis people, whatever, people here are not deeply informed on this, and their opinions, whichever way they go on this, would be pretty irrelevant to the truth of the matter.
Comments were almost certainly deleted for entirely different reasons than suppression of the truth. Scientists, in reality, welcome well-reasoned criticism. Bizarre and ill-argued salvos, however, may very well be ignored or deleted.
![https://commons.wikimedia.org/wiki/File:Laevavrakk_"Aid".png](https://commons.wikimedia.org/wiki/File:Laevavrakk_"Aid".png){kind=link}
The data manipulations that this EHT team did to process their raw data - is NOT acceptable from the perspective or a correct scientific experiment.
They got their images only when they allowed themselves to creatively interpret data from their telescopes
~~~~~~~
https://youtu.be/UGL_OL3OrCE?t=1177
19:37
What you can do is to use methods where you [have] do not need any calibration whatsoever and you can still can get pretty good results.
So here on the bottom at the top is the truth image, and this is simulated data, as we are increasing the amount of amplitude error and you can see here ... it's hard to see ... but it breaks down once you add too much gain here. But if we use just closure quantities - we are invariant to that. So that really, actually, been a really huge step for the project, because we had such bad gains.
~~~~~~~
They also deleted multiple critical comments from that video presentation.
E.g. "Pratik Maitra" posted multiple comments that later disappeared.