Polynomial time samplable distributions
This paper studies distributions which can be sampled by randomized algorithms in time polynomial in the length of their outputs. Those distributions are called “polynomial-time samplable” and important to average-case complexity theory, cryptography, and statistical physics. This paper shows that those distributions are exactly as hard as #P-functions to compute deterministically and at least as hard as NP-sets to approximate by deterministic protocols.
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