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> There are concepts like "k-dimensional equidistribution" etc. etc... where in some ways the requirements of a PRNG are far, far, higher than a cryptographically sound PRNG

Huh? If you can chew through however many gigabytes of the supposed CSPRNG’s output, do some statistics, and with a non-negligible probability tell if the bytes in fact came from the CSPRNG in question or an actual iid random source, then you’ve got a distinguisher and the CSPRNG is broken.

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It all comes down to actual specific statistical tests, and how hard they are to break in specific applications.

No CSPRNG is absolutely perfect, no CSPRNG has ever absolutely passed every statistical test thrown at it.

In MCMC, it stresses very different statistical tests than the typical CSPRNG tests.

Every PRNG is absolutely broken if you want to be absolute about it. MCMC and crypto applications push on different aspects where statistical issues will cause application level failures.

See e.g. this paper https://www.cs.hmc.edu/tr/hmc-cs-2014-0905.pdf

(it's not the end all be all, but it's a good survey of why this stuff matters and why it's different)

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