| 研究生: |
王守朋 Wang, Shou-Peng |
|---|---|
| 論文名稱: |
在高維度下受波氏分配自我相斥隨機漫步的均場行為 Mean-field behavior for self-avoiding walks with Poisson interactions in high dimensions |
| 指導教授: |
陳隆奇
CHEN, LUNG-CHI |
| 口試委員: |
洪芷漪
張書銓 陳隆奇 |
| 學位類別: |
碩士
Master |
| 系所名稱: |
理學院 - 應用數學系 Department of Mathematical Sciences |
| 論文出版年: | 2020 |
| 畢業學年度: | 108 |
| 語文別: | 英文 |
| 論文頁數: | 51 |
| 中文關鍵詞: | 雖機漫步 |
| 外文關鍵詞: | self-avoiding walk |
| DOI URL: | http://doi.org/10.6814/NCCU202000775 |
| 相關次數: | 點閱:246 下載:29 |
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self-avoiding walk是線性聚合物的模型。它是機率和統計力學中一個重要而有趣的模型。一些重要問題已經解決(c.f.[5]). 然而,許多重要問題仍未解決,特別是涉及關鍵指數的問題,尤其是遠程模型的關鍵指數。
在本文中,我們獲得了對於一個特殊的長域模型,其單步分佈是波松分佈的特殊敏感度模型,其敏感性指數滿足均值場行為,且其值大於上臨界值d(c) = 4 。參數 lambda > lambda(d) 的類型分佈,其中lambda(d)取決於維度。
為此,我們選擇一組特殊的 bootstrapping functions,它們類似於[4],並使用lace expansion分析有關bootstrapping functions的複雜部分。 此外,對於d>4,我們得到lambda(d)的確切值。
Self-avoiding walk is a model for linear polymers.
It is an important and interesting model in Probability and Statistical mechanics.
Some of the important problems had been solved (c.f.[5]). However,
many of the important problems remain unsolved, particularly those involving critical exponents, especially the critical exponents for long-range models.
In this thesis, we see Lace expansion to obtain that the critical exponent of the susceptibility satisfies the mean-field behavior with the dimensions above the upper critical dimension (d(c) = 4) for a special loge-range model in which each one-step distribution is the Poisson-type distribution with parameter lambda > lambda(d) where lambda(d) depends on the dimensions. To achieve this, we choose a particular set of bootstrapping functions which is similar as [4] and using a notoriously complicated part of the lace expansion analysis. Moreover we get the exactly value of lambda(d) for d > 4.
1 Introduction 1
2 Models and Main Results 3
2.1 Notations and Definitions 3
2.2 Main results and their proofs 6
3 The lace expansion for selfavoiding walk 10
4 Diagrammatic bounds estimate 14
4.1 Diagrammatic bounds on the lace expansion coefficients 14
4.2 Diagramatic bounds on the bootstrapping argument 25
5 Random walk estimate 29
5.1 The diagrams bound of randomwalk quantities for p = 1
29
5.2 The diagrams bound of randomwalk quantities for p > 1
35
6 Proof of Proposition 2.2.7 2.2.9 40
6.1 Proof of Proposition 2.2.7 40
6.2 Proof of Proposition 2.2.8 - 2.2.9 and Lemma 4.1.1 44
Appendix A 48
Bibliography 50
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