Percolation in half spaces and Markov fields on branching planes.

We study two sets of models: independent percolation models in half spaces Zᵈ⁻¹ x Z₊, and Ising/Potts models as well as the Fortuin-Kasteleyn (FK) random cluster models on branching planes T x Z, where Z is the one-dimensional lattice, Z₊ = {0,1,2,...} and T is a Bethe lattice. We prove that for ind...

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Bibliographic Details
Main Author: Wu, Chuntao.
Other Authors: Newman, Charles M.
Language:en
Published: The University of Arizona. 1990
Subjects:
Online Access:http://hdl.handle.net/10150/185296
Description
Summary:We study two sets of models: independent percolation models in half spaces Zᵈ⁻¹ x Z₊, and Ising/Potts models as well as the Fortuin-Kasteleyn (FK) random cluster models on branching planes T x Z, where Z is the one-dimensional lattice, Z₊ = {0,1,2,...} and T is a Bethe lattice. We prove that for independent percolation in half spaces, the infinite cluster is unique whenever it exists. For the Ising/Potts models on branching planes, there are (at least) two phase transitions; that is, there exist(s) a unique Gibbs state, tree-like nonunique Gibbs states or plane-like nonunique Gibbs states corresponding to high temperature, intermediate temperature or low temperature. In the low temperature plus phase, the plus infinite cluster is unique and it "traps" the space T x Z and prevents co-existence of the minus infinite cluster. For the FK random cluster models (which are dependent percolation models) on T x Z, the number of infinite (open) clusters may be zero, infinity or one depending on the value of p--the probability of each bond being open. This is an extension of Grimmett and Newman's results for independent percolation on T x Z. We also prove that both the independent percolation model and the FK random cluster models satisfy a finite island property when p is close to 1. Chapter 1 is an introduction. Chapter 2 contains the proof of the uniqueness theorem for independent percolation in half spaces. The proof utilizes only a large deviation estimate and translation invariance of the models along the hyperplane Zᵈ⁻¹ x {0}. The Ising/Potts models and the FK random cluster models on the branching planes are studied in Chapter 3. The methods are to use the FK representation of Ising/Potts systems as dependent percolation models to carry over Grimmett and Newman's results for independent percolation to the Ising/Potts models. However, in order to prove the plane-like behavior of the Ising/Potts models, the corresponding results for independent percolation are not sufficient and this led us to investigate independent percolation again and prove a new finite island property. Chapters 2 and 3 are independent. Readers with basic knowledge of percolation and Ising models can omit chapter 1 and read chapters 2 and 3 directly.