As I read it, by “invalid” they mean not 1 or 2 you suggested but (3) your reconstruction process is assuming something which is the actual cause of most of the non-randomness in your output, and would produce a plausible-looking image when run on any random set of pixels.
For the example you gave (3) is clearly not true—there’s no way that any random set of pixels would produce something so correlated with the original image, when the reconstruction algorithm doesn’t itself embed the original image. But as far as I know LIGO doesn’t know the original image, so the fact that they get something structured-looking out of noise isn’t meaningful? Or at least that’s how I interpret nixtaken’s argument; this is really not my area of expertise.
Kirsten is claiming that my algorithm is invalid, even though (so it seems to me) it demonstrably does a decent job of reconstructing the original image I gave it despite the corruption of the rows and columns. Of course she can still claim that the EHT team’s reconstruction algorithm doesn’t have that property, that it only gives plausible output images because it’s been constructed in such a way that it can’t do otherwise, but at the moment I’m not arguing that the EHT team’s reconstruction algorithm is any good, I’m arguing only that one specific thing Kirsten claimed about it is flatly untrue: namely, that if the phases are corrupted in anything like the way Bouman describes then there is literally no way to get any actual phase information from the data. The point of the image reconstruction I’m demonstrating here is that you can have corruption with a similar sort of pattern that’s just as severe but still be able to do a lot of reconstruction, because although the individual measurements’ phases are hopelessly corrupt (in my example: the individual pixels’ values are hopelessly corrupt) there is still good information to be had about their relationships.
[EDITED to add:] … Or maybe I misunderstood? Perhaps “This method is invalid” she means that somehow anything that has the same sort of shape as what I’m doing here is bad, even if it demonstrably gives good results. If so, then I guess my problem is that she hasn’t enabled me to understand why she considers it “invalid”. Her objections all seem to me like science-by-slogan: describe something in a way that makes it sound silly, and you’ve shown it’s no good. Unfortunately, all sorts of things that can be made to sound silly turn out to be not silly at all, so when faced with a claim that something that demonstrably works is no good I’m going to need more than slogans to convince me.
As I read it, by “invalid” they mean not 1 or 2 you suggested but (3) your reconstruction process is assuming something which is the actual cause of most of the non-randomness in your output, and would produce a plausible-looking image when run on any random set of pixels.
For the example you gave (3) is clearly not true—there’s no way that any random set of pixels would produce something so correlated with the original image, when the reconstruction algorithm doesn’t itself embed the original image. But as far as I know LIGO doesn’t know the original image, so the fact that they get something structured-looking out of noise isn’t meaningful? Or at least that’s how I interpret nixtaken’s argument; this is really not my area of expertise.
Kirsten is claiming that my algorithm is invalid, even though (so it seems to me) it demonstrably does a decent job of reconstructing the original image I gave it despite the corruption of the rows and columns. Of course she can still claim that the EHT team’s reconstruction algorithm doesn’t have that property, that it only gives plausible output images because it’s been constructed in such a way that it can’t do otherwise, but at the moment I’m not arguing that the EHT team’s reconstruction algorithm is any good, I’m arguing only that one specific thing Kirsten claimed about it is flatly untrue: namely, that if the phases are corrupted in anything like the way Bouman describes then there is literally no way to get any actual phase information from the data. The point of the image reconstruction I’m demonstrating here is that you can have corruption with a similar sort of pattern that’s just as severe but still be able to do a lot of reconstruction, because although the individual measurements’ phases are hopelessly corrupt (in my example: the individual pixels’ values are hopelessly corrupt) there is still good information to be had about their relationships.
[EDITED to add:] … Or maybe I misunderstood? Perhaps “This method is invalid” she means that somehow anything that has the same sort of shape as what I’m doing here is bad, even if it demonstrably gives good results. If so, then I guess my problem is that she hasn’t enabled me to understand why she considers it “invalid”. Her objections all seem to me like science-by-slogan: describe something in a way that makes it sound silly, and you’ve shown it’s no good. Unfortunately, all sorts of things that can be made to sound silly turn out to be not silly at all, so when faced with a claim that something that demonstrably works is no good I’m going to need more than slogans to convince me.