DocumentCode :
2226051
Title :
Mixing Time Power Laws at Criticality
Author :
Long, Yun ; Nachmias, Asaf ; Peres, Yuval
Author_Institution :
U.C. Berkeley, Berkeley
fYear :
2007
fDate :
21-23 Oct. 2007
Firstpage :
205
Lastpage :
214
Abstract :
We study the mixing time of some Markov chains converging to critical physical models. These models are indexed by a parameter beta and there exists some critical value betac where the model undergoes a phase transition. According to physics lore, the mixing time of such Markov chains is often of logarithmic order outside the critical regime, when beta ne betac, and satisfies-some power law at criticality, when beta = betac. We prove this in the two following settings: 1. Lazy random walk on the critical percolation cluster of "mean-field" graphs, which include the complete graph and random d-regular graphs. The critical mixing time here is of order Theta(n). This answers a question of Benjamini, Kozma and Wormald. 2. Swendsen-Wang dynamics on the complete, graph. The critical mixing time, here is of order Theta(n1/4). This improves results of Cooper, Dyer, Frieze and Rue. In both settings, the main tool is understanding the Markov chain dynamics via properties of critical percolation on the underlying graph.
Keywords :
Markov processes; graph theory; Markov chains; critical mixing time; critical percolation cluster; critical physical models; lazy random walk; mean-field graphs; phase transition; random d-regular graphs; time power laws; Clustering algorithms; Computer science; Lattices; Mathematics; Physics; Sampling methods; Size measurement; Temperature distribution; Time measurement; Tree graphs;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Foundations of Computer Science, 2007. FOCS '07. 48th Annual IEEE Symposium on
Conference_Location :
Providence, RI
ISSN :
0272-5428
Print_ISBN :
978-0-7695-3010-9
Type :
conf
DOI :
10.1109/FOCS.2007.49
Filename :
4389493
Link To Document :
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