Random Permutations in Computational Complexity
Abstract
Classical results of Bennett and Gill (1981) show that with probability 1, relative to a random oracle , and with probability 1, relative to a random permutation . Whether holds relative to a random oracle remains open. While the random oracle separation has been extended to specific individually random oracles--such as Martin-L\"of random or resource-bounded random oracles--no analogous result is known for individually random permutations. We introduce a new resource-bounded measure framework for analyzing individually random permutations. We define permutation martingales and permutation betting games that characterize measure-zero sets in the space of permutations, enabling formal definitions of resource-bounded random permutations. Our main result shows that for every polynomial-time betting-game random permutation . This is the first separation result relative to individually random permutations, rather than an almost-everywhere separation. We also strengthen a quantum separation of Bennett, Bernstein, Brassard, and Vazirani (1997) by showing that for every polynomial-space random permutation . We investigate the relationship between random permutations and random oracles. We prove that random oracles are polynomial-time reducible from random permutations. The converse--whether every random permutation is reducible from a random oracle--remains open. We show that if is not a measurable subset of , then holds with probability 1 relative to a random oracle . Conversely, establishing this random oracle separation with time-bounded measure would imply is a measure 0 subset of .
Cite
@article{arxiv.2511.08786,
title = {Random Permutations in Computational Complexity},
author = {John M. Hitchcock and Adewale Sekoni and Hadi Shafei},
journal= {arXiv preprint arXiv:2511.08786},
year = {2025}
}