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研究生: 伊凱馬
Badr Saleh Badr Mohamed Elkamash
論文名稱: Mixing Time for Ising Model (On Two Special Graphs: the Line and the Circle)
指導教授: 方向
Xiang Fang
口試委員:
學位類別: 碩士
Master
系所名稱: 理學院 - 數學系
Department of Mathematics
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 67
中文關鍵詞: 伊辛模型格勞伯動力混合時間馬爾可夫鏈路徑耦合
外文關鍵詞: Ising Model, Glauber Dynamics, Mixing Time, Markov Chains, Path Coupling
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  • 在本論文中,我們研究了Ising模型的Glauber動力學。基於[10]的專著,我們提供了馬爾可夫鏈混合時間一般理論的詳細介紹,尤其是收斂到平穩測度的速率。
    然後,我們計算出Ising模型的兩個特殊(也許是最重要)案例的細節:直線和圓。
    我們的貢獻是
    (1) 我們針對這兩種特殊情況獲得了改進的估計;和
    (2) 我們提供了許多細節和例子和圖片示例來說明該理論。
    更詳細地,我們證明在高溫下快速混合。我們確定混合時間是log(n)和log(1/e)的多項式。或者,顯示tmix在log(n)也足以進行快速混合。我們證明了Glauber動力學的混合時間為在高溫下具有n個頂點的直線和圓上的(鐵磁)伊辛模型的上限為n log n/e。


    In this thesis we study Glauber dynamics of one dimensional Ising models. We provide a detailed presentation of the general theory of the mixing times of Markov chains, especially the rate of convergence to stationary measures, based on the monograph of [10].
    Then we work out the details of two special (and perhaps the most important) cases of Ising models: the line and the circle. Our contribution is that
    (1) we obtain improved estimates for these two special cases; and
    (2) we provide many examples with details and pictures to illustrate the theory.
    In more details, we prove a fast mixing at high temperature. We establish that the mixing time is a polynomial in log(n) and log(1/e). Alternatively, we show that tmix is a polynomial in log(n). It is also enough for fast mixing. We show that the mixing time of Glauber dynamics for the (ferromagnetic) Ising model on a line and a circle with n vertices at high temperature has an upper bound of n log n/e.

    Chinese Abstract i English Abstract ii Acknowledgement iii Table of Contents v List of Figures vi 1 Introduction 1 1.1 Background . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1 1.2 Our Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 1.3 Future Work . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 1.4 Organization . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 2 Convergence Theorem for Markov Chains 4 2.1 Basic De nitions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 2.2 Uniqueness of Stationary Distributions . . . . . . . . . . . . . . . . . . . . 6 2.3 Existence of Stationary Distributions . . . . . . . . . . . . . . . . . . . . . 8 2.4 The Convergence Theorem . . . . . . . . . . . . . . . . . . . . . . . . . . . 14 2.5 The Mixing Time . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19 3 The Ising Model 20 3.1 Ising Model on the Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . 20 3.2 Ising Model on the Circle . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 4 The Glauber Dynamics 25 4.1 Glauber Dynamics for Some Models . . . . . . . . . . . . . . . . . . . . . . 25 4.1.1 Graph Colouring . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 4.1.2 Hardcore Con guration . . . . . . . . . . . . . . . . . . . . . . . . . 26 4.1.3 Hardcore Model with Fugacity . . . . . . . . . . . . . . . . . . . . . 28 4.2 The Glauber Dynamics for the Gibbs Distribution L . . . . . . . . . . . 30 5 The Path Coupling Technique 35 5.1 Coupling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 35 5.2 The Transportation Metric . . . . . . . . . . . . . . . . . . . . . . . . . . . 36 5.3 Path Coupling . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 44 6 Fast Mixing in Ising Model 47 6.1 On the Line . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 48 6.2 On the Circle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 52 References 56

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