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Counting independent sets in unbalanced bipartite graphs
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Counting independent sets in unbalanced bipartite graphs
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We give an FPTAS for approximating the partition function of the hard-core model for bipartite graphs when there is sufficient imbalance in the degrees or fugacities between the sides $(L,R)$ of the bipartition. This includes, among others, the biregular case when $\lambda=1$ (approximating the number of independent sets of $G$) and $\Delta_R \geq 7\Delta_L \log(\Delta_L)$. Our approximation algorithm is based on truncating the cluster expansion of a polymer model partition function that expresses the hard-core partition function in terms of deviations from independent sets that are empty on one side of the bipartition. As a consequence of the method, we also prove that the hard-core model on such graphs exhibits exponential decay of correlations by utilizing connections between the cluster expansion and joint cumulants.
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Cited by 1 Pith paper
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Efficient Algorithms for Weakly-Interacting Quantum Spin Systems
A cluster-expansion FPTAS for the partition function and an approximate sampler for weakly-interacting quantum spin systems at arbitrary temperature are claimed, but a key bound in the proof fails.
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