Gurzadyan & Penrose wrote the kind of paper that should never have passed basic peer review. And even when "everyone" pointed out Gurzadyan does not have a clue about data analysis they still stuck to it.
I have no idea about this paper and if Penrose has found a better data analyst to collaborate with this time. Just be aware that while Penrose may be brilliant about the things he knows something about, his name on a data analysis paper is not any guarantee about the data analysis being sound.
"Turned out to be not statistically significant" is a very polite way of saying it... they initially said "up to 6 sigma significance", while it was obvious to anyone in the field that the data analysis in the paper was borderline crackpot.
Example of a Gurzadyan takedown. See my comment on OP for more links.
How would you recommend someone to get up to speed on data reduction to the point where they would be able to recognize such errors and know how to tease out a signal without making similar mistakes?
Well I did a PhD in CMB analysis so that is how I know. Not sure if such things will ever be controllable by people who are not researchers in the field (or at least doing similar kind of data analysis). It is a shame the peer review system cannot be relied on more; I hope a revolution happens there (on the line of "N accredited researchers trust/distrust this paper").
I'm completely uninformed on this, but I thought that in order to evaporate completely, a black hole must first shrink until it is very small, at which point the amount of energy released by its final disappearance would be rather a small amount irrespective of the original size. Why would the original size of it make any difference?
But that's the thing with information panspermia isn't? You beam genetic information via quasars across universes, which then somehow magically turn back into people.
It's indistinguishable from magic, only it's got some math trappings. I read this, and it struck me as basically the 20th century equivalent of demonology and angelology, which was basically just religion fanfic with some feudlistic political science thrown on top. (If God is the king, who is the viscount?)
Eh, it’s not totally crackpot. If you knew something about the physics and initial conditions of the child universe you could “stir the pot” enough with your signal (whatever mechanism it is) to trigger natural processes of complexity formation which eventually leads to life (e.g. make sure galaxies form fast enough in the early universe to create heavy metals before inflation pulls everything apart), then project a compressed scan of your consciousness as a signal on the background radiation. Eventually intelligent life will form, find it, get curious about its structure, decipher it, and simulate it.
Makes good hard science fiction. Not something I’d give high priors for having actually happened, but it doesn’t mean we shouldn’t look.
But information isn't physical. I download the human genome, I don't get a clone of Craig Venter. I get some mosfets that were manufactured in a factory set. There's no mechanism that even makes sense for any of this. It's basically "But if I multiply time by -1..." There's no evidence for any of this, and no plausible mechanism of these pre-initial conditions to come about. It's just magic people from outside the universe.
That's the thing that makes it crackpot.
Sure Penrose did some good science before, but this isn't it. This is just bullshit. It happens. Tesla made a lot of discoveries with alternating current, and high voltage electricity, but then he died convinced he was talking to a martian civilization, and was on the cusp inventing a death ray. Watson and Crick discovered the structure of DNA, but in they're later years abandoned molecular biology and started to embrace various quackery that tarnished their legacy.
Penrose & Gurzadyan committed this travesty:
https://arxiv.org/abs/1011.3706
...and the entire CMB analysis community quickly rushed to point out the numerous basic errors done in the statistical analysis.
E.g. http://iopscience.iop.org/article/10.1088/2041-8205/733/2/L2...
Gurzadyan & Penrose wrote the kind of paper that should never have passed basic peer review. And even when "everyone" pointed out Gurzadyan does not have a clue about data analysis they still stuck to it.
I have no idea about this paper and if Penrose has found a better data analyst to collaborate with this time. Just be aware that while Penrose may be brilliant about the things he knows something about, his name on a data analysis paper is not any guarantee about the data analysis being sound.
Edit: Another less polite and clearer exposition of Gurzadyan's "methods" https://www.aanda.org/articles/aa/full_html/2012/02/aa17344-...