Perfect Sampling in Infinite Spin Systems via Strong Spatial Mixing
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We present a simple algorithm that perfectly samples configurations from the unique Gibbs measure of a spin system on a potentially infinite graph G. The sampling algorithm assumes strong spatial mixing together with subexponential growth of G. It produces a finite window onto a perfect sample from the Gibbs distribution. The run-time is linear in the size of the window.
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