
The two-parameter Macdonald polynomials are a central object of algebraic combinatorics and representation theory. We give a Markov chain on partitions of k with eigenfunctions the coefficients of the Macdonald polynomials when expanded in the power sum polynomials. The Markov chain has stationary distribution a new two-parameter family of measures on partitions, the inverse of the Macdonald weight (rescaled). The uniform distribution on permutations and the Ewens sampling formula are special cases. The Markov chain is a version of the auxiliary variables algorithm of statistical physics. Properties of the Macdonald polynomials allow a sharp analysis of the running time. In natural cases, a bounded number of steps suffice for arbitrarily large k.
auxiliary variables, Markov chain, Probability (math.PR), rates of convergence, measures on partitions, random permutations, 05E05, FOS: Mathematics, 60J10, Mathematics - Combinatorics, Macdonald polynomials, Combinatorics (math.CO), Representation Theory (math.RT), Mathematics - Probability, Mathematics - Representation Theory
auxiliary variables, Markov chain, Probability (math.PR), rates of convergence, measures on partitions, random permutations, 05E05, FOS: Mathematics, 60J10, Mathematics - Combinatorics, Macdonald polynomials, Combinatorics (math.CO), Representation Theory (math.RT), Mathematics - Probability, Mathematics - Representation Theory
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