numpy performance and random numbers

[sturlamolden]

On 19 Des, 22:58, sturlamolden <sturlamol... at yahoo.no> wrote:

> If you pick two random states (using any PRNG), you need error-
> checking that states are always unique, i.e. that each PRNG never
> reaches the starting state of the other(s).

Another note on this:

Ideally, we would e.g. know how to find (analytically) MT states that
are very far apart. But to my knowledge no such equation has been
derived.

But often in Monte Carlo simulations, the PRNG is not the dominant
computational bottleneck. So we can simply start N PRNGs from N
consequtive states, and for each PRNG only use every N-th pseudorandom
deviate.