Random Permutations in Computational Complexity
John M. Hitchcock, Adewale Sekoni, Hadi Shafei

TL;DR
This paper introduces a new framework for analyzing individually random permutations in computational complexity, establishing separation results and exploring their relationship with random oracles and quantum complexity.
Contribution
It develops a resource-bounded measure framework for random permutations, proving new separation results and connecting permutation randomness with oracle and quantum complexity.
Findings
Proves $P^ eq NP^ igcap coNP^$ for polynomial-time random permutations.
Shows $NP^ igcap coNP^ ot\u2209 BQP^$ for polynomial-space random permutations.
Establishes that random oracles are polynomial-time reducible from random permutations.
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 …
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComplexity and Algorithms in Graphs · Advanced Graph Theory Research · Quantum Computing Algorithms and Architecture
