TY - GEN
T1 - Random-cluster dynamics in ℤ2
AU - Blanca, Antonio
AU - Sinclair, Alistair
N1 - Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2016
Y1 - 2016
N2 - The random-cluster model has been widely studied as a unifying framework for random graphs, spin systems and electrical networks, but its dynamics have so far largely resisted analysis. In this paper we analyze the Glauber dynamics of the random-cluster model in the canonical case where the underlying graph is an n × n box in the Cartesian lattice ℤ2. Our main result is a O(n2 log n) upper bound for the mixing time at all values of the model parameter p except the critical point p = pc(q), and for all values of the second model parameter q ≤ 1. We also provide a matching lower bound proving that our result is tight. Our analysis takes as its starting point the recent breakthrough by Beffara and Duminil-Copin on the location of the random-cluster phase transition in ℤ2. It is reminiscent of similar results for spin systems such as the Ising and Potts models, but requires the reworking of several standard tools in the context of the random-cluster model, which is not a spin system in the usual sense.
AB - The random-cluster model has been widely studied as a unifying framework for random graphs, spin systems and electrical networks, but its dynamics have so far largely resisted analysis. In this paper we analyze the Glauber dynamics of the random-cluster model in the canonical case where the underlying graph is an n × n box in the Cartesian lattice ℤ2. Our main result is a O(n2 log n) upper bound for the mixing time at all values of the model parameter p except the critical point p = pc(q), and for all values of the second model parameter q ≤ 1. We also provide a matching lower bound proving that our result is tight. Our analysis takes as its starting point the recent breakthrough by Beffara and Duminil-Copin on the location of the random-cluster phase transition in ℤ2. It is reminiscent of similar results for spin systems such as the Ising and Potts models, but requires the reworking of several standard tools in the context of the random-cluster model, which is not a spin system in the usual sense.
UR - https://www.scopus.com/pages/publications/84962856959
UR - https://www.scopus.com/inward/citedby.url?scp=84962856959&partnerID=8YFLogxK
U2 - 10.1137/1.9781611974331.ch37
DO - 10.1137/1.9781611974331.ch37
M3 - Conference contribution
AN - SCOPUS:84962856959
T3 - Proceedings of the Annual ACM-SIAM Symposium on Discrete Algorithms
SP - 498
EP - 513
BT - 27th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2016
A2 - Krauthgamer, Robert
PB - Association for Computing Machinery
T2 - 27th Annual ACM-SIAM Symposium on Discrete Algorithms, SODA 2016
Y2 - 10 January 2016 through 12 January 2016
ER -