These are not known to be significant and there is no logical reason to believe 
they are significant. However, they are interesting and worthy of thought. Many 
here will have already done so, but a refresher never hurts.

Pi can be calculated as a function, but any specific digit can also be 
calculated directly, which implies the digits are non-random in some sense. The 
overall distribution is equivalent to random, but the next two points show 
that's not a measure of true randomness, merely a pre-requisite.

Next, the distribution of prime numbers is similar in nature to the 
distribution of quantum states of particles. There are systems where the energy 
states do match the pattern of primes.

Primes are not quite random. If you know the last digit of a prime number, then 
you can predict the last digit of the next prime number significantly better 
than average. Apparently, in some cases, you've a 60%+ chance of doing so. 
That's not random.

What can we deduce from this? Directly, nothing whatsoever.

Indirectly, however, it starts to look interesting. If you do not need infinite 
precision and infinite range, because everything can be inferred from a finite 
set of finite-length seeds, you can have the effects of infinity without 
needing it to be physically explained (infinities cause physicists to break out 
in a nasty rash).

This obviously has interesting implications for mathematical realism, ideas of 
simulated universes, etc, as it's much easier for mathematics to generate 
results than for physics to. Obviously physics can produce this continuous 
padding to the accuracy of the universe, that's implied by quantum foam. 
However, amplifying pure noise usually produces pure noise. Chaos produces 
something other than noise precisely because it's not random. It's not 
predictable, but it's entirely deterministic.

So, either we have to suppose quantum foam is deterministic in and of itself, 
or it's deterministic because there's something beneath physics that determines 
it. At least, if the above reasoning is both necessary and sufficient. If it's 
wrong or has gaps, then the conclusion obviously is obviously also wrong.

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