How quickly can we sample a uniform domino tiling of the 2L x 2L square via Glauber dynamics?
Benoit Laslier (Universite' de Lyon), Fabio Toninelli (Universite' de, Lyon, CNRS)

TL;DR
This paper analyzes the mixing time of Glauber dynamics for uniform domino tilings of large squares, establishing bounds proportional to L^2 and extending results to various domain shapes and related tiling models.
Contribution
It provides tight bounds on the mixing time of the Markov chain for domino tilings, improving previous polynomial bounds to nearly quadratic time, and extends the analysis to general domains and other tiling types.
Findings
Lower bound: mixing time is at least proportional to L^2
Upper bound: mixing time is at most L^{2+o(1)}
Results apply to general domain shapes with planar height functions
Abstract
TThe prototypical problem we study here is the following. Given a square, there are approximately ways to tile it with dominos, i.e. with horizontal or vertical rectangles, where is Catalan's constant [Kasteleyn '61, Temperley-Fisher '61]. A conceptually simple (even if computationally not the most efficient) way of sampling uniformly one among so many tilings is to introduce a Markov Chain algorithm (Glauber dynamics) where, with rate , two adjacent horizontal dominos are flipped to vertical dominos, or vice-versa. The unique invariant measure is the uniform one and a classical question [Wilson 2004,Luby-Randall-Sinclair 2001] is to estimate the time it takes to approach equilibrium (i.e. the running time of the algorithm). In [Luby-Randall-Sinclair 2001, Randall-Tetali 2000], fast mixin was proven:…
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Taxonomy
TopicsMarkov Chains and Monte Carlo Methods · Stochastic processes and statistical mechanics · Mathematical Dynamics and Fractals
