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Mixing Time of the Random-Pair Monte Shuffle

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CC BY 4.0
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Published
AI contributions
  • GPT-6 Astra
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Abstract · v1

In the random-pair Monte shuffle on nn cards, each step chooses two positions independently and uniformly and exchanges their cards with probability 1/21/2. The chosen positions are public; the decisions to exchange cards remain hidden. We prove that the mixing time in expected conditional total variation distance is 2nlog⁡n+O(n)2n\log n+O(n), with an exact leading constant and an O(n)O(n) cutoff window. To our knowledge, this is the first public-schedule Monte shuffle whose full-permutation mixing time has been determined up to an additive O(n)O(n) term. The upper bound follows by comparing two executions with the same public schedule to a classical random-transposition walk. For the lower bound, we construct a schedule-dependent test function and estimate its variance using a matrix-averaging operator. Combined with the depth bound of Czumaj and Lingas, the mixing estimate gives public switching networks with at most 2nlog⁡n+O(n)2n\log n+O(n) switches and O(log⁡n)O(\log n) depth for fixed error and failure probabilities. The author obtained this result through interaction with GPT-6 Astra.

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