Assign to each vertex of the one-dimensional torus i.i.d. weights with a heavy-tail of index tau -1 > 0. Connect then each couple of vertices with probability roughly proportional to the product of their weights and that decays polynomially with exponent alpha > 0 in their distance. The resulting graph is called scale-free percolation. The goal of this work is to study the mixing time of the simple random walk on this structure. We depict a rich phase diagram in alpha and tau. In particular we prove that the presence of hubs can speed up the mixing of the chain. We use different techniques for each phase, the most interesting of which is a bootstrap procedure to reduce the model from a phase where the degrees have bounded averages to a setting with unbounded averages. (c) 2023 Published by Elsevier B.V.
Cipriani, A., Salvi, M. (2024). Scale-free percolation mixing time. STOCHASTIC PROCESSES AND THEIR APPLICATIONS, 167 [10.1016/j.spa.2023.104236].
Scale-free percolation mixing time
Salvi, Michele
2024-01-01
Abstract
Assign to each vertex of the one-dimensional torus i.i.d. weights with a heavy-tail of index tau -1 > 0. Connect then each couple of vertices with probability roughly proportional to the product of their weights and that decays polynomially with exponent alpha > 0 in their distance. The resulting graph is called scale-free percolation. The goal of this work is to study the mixing time of the simple random walk on this structure. We depict a rich phase diagram in alpha and tau. In particular we prove that the presence of hubs can speed up the mixing of the chain. We use different techniques for each phase, the most interesting of which is a bootstrap procedure to reduce the model from a phase where the degrees have bounded averages to a setting with unbounded averages. (c) 2023 Published by Elsevier B.V.File | Dimensione | Formato | |
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