counting independent sets up to the tree threshold
Consider the problem of approximately counting weighted independent sets of a graph G with activity ?, i.e., where the weight of an independent set I is ? |I| . We present a novel analysis yielding a deterministic approximation scheme which runs in polynomial time for any graph of maximum degree ? and ?< ? c =(?-1) ?-1 /(?-2) ? . This improves on the previously known general bound of ? ? (2 ? ?-2). The new regime includes the interesting case of ?=1 (uniform weights) and ? ? 5. The previous bound required ? ? 4 for uniform approximate counting and there is evidence that for ? ? 6 the problem is hard. Note that ? c is the critical activity for uniqueness of the Gibbs measure on the regular tree of degree ?, i.e., for ? ? ? c the probability that the root is in the independent set is asymptotically independent of the configuration on the leaves far below. Indeed, our analysis is focused on establishing decay of correlations with distance in the above weighted distribution. We show that on any graph of maximum degree ? correlations decay with distance at least as fast as they do on the regular tree of the same degree. This resolves an open conjecture in statistical physics. Our comparison of a general graph with the tree uses an algorithmic argument yielding the approximation scheme mentioned above. Also, by existing arguments, establishing decay of correlations for all graphs and ?<? c gives that the Glauber dynamics is rapidly mixing in this regime. However, the implication from decay of correlations to rapid mixing of the dynamics is only known to hold for graphs of subexponential growth, and hence, our result regarding the Glauber dynamics is limited to this class of graphs.
independent sets approximate counting glauber dynamics strong spatial mixing hard-core model