Sampling 3-colourings of regular bipartite graphs
David Galvin

TL;DR
This paper analyzes the rapidity of convergence of Markov chains for 3-colorings of regular bipartite graphs, showing exponential mixing under certain conditions and revealing structural properties of colorings in high-dimensional hypercubes.
Contribution
It establishes conditions under which Markov chains for 3-colorings mix rapidly and provides new combinatorial insights into color distributions in high-dimensional hypercubes.
Findings
Markov chain convergence is exponential for large degree graphs with certain expansion properties.
Glauber dynamics on hypercubes mix slowly, with mixing time exponential in the dimension.
In uniform 3-colorings of hypercubes, the probability of balanced color distribution across bipartite parts is exponentially small.
Abstract
We show that if is a regular bipartite graph for which the expansion of subsets of a single parity of is reasonably good and which satisfies a certain local condition (that the union of the neighbourhoods of adjacent vertices does not contain too many pairwise non-adjacent vertices), and if is a Markov chain on the set of proper 3-colourings of which updates the colour of at most vertices at each step and whose stationary distribution is uniform, then for and sufficiently large the convergence to stationarity of is (essentially) exponential in . In particular, if is the -dimensional hypercube (the graph on vertex set in which two strings are adjacent if they differ on exactly one coordinate) then the convergence to stationarity of the well-known Glauber (single-site update) dynamics is…
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Taxonomy
TopicsLimits and Structures in Graph Theory · Markov Chains and Monte Carlo Methods · Stochastic processes and statistical mechanics
