This is mainly Gurzadyan&#x27;s work, and it shows such a complete lack of understanding for basic statistical analysis it&#x27;s not even funny. They basically assume that if you have an i.i.d. random vector x, then a linearly transformed vector z = Q x, with Q some linear map, should also have coeffients without correlations.<p>For a start look here: <a href="http:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1105.5051" rel="nofollow">http:&#x2F;&#x2F;arxiv.org&#x2F;abs&#x2F;1105.5051</a> -- beyond explaining the fallacies it has references to 3 independent analyses that failed to reproduce the result on the same data set.<p>The only interesting discussion to be had here is one about journals and peer review practices (i.e., how A&amp;A could let something like this slip through).<p>That said, the randomness (or nature of randomness) in the CMB is actively researched (such a how close the random signal is to Gaussian). And anything you think is &quot;CMB&quot; run the risk of being foregrounds or systematics which would not be &quot;random&quot; in one sense.