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研究生: 彭兆宏
Peng, Jhao-Hong
論文名稱: 哈里斯準則對淬火無序二維量子自旋系統的有效性
Validity of Harris criterion for two-dimensional quantum spin systems with quenched disorder
指導教授: 江府峻
Jiang, Fu-Jiun
學位類別: 碩士
Master
系所名稱: 物理學系
Department of Physics
論文出版年: 2020
畢業學年度: 108
語文別: 英文
論文頁數: 41
英文關鍵詞: quenched disorder, Harris criterion
DOI URL: http://doi.org/10.6345/NTNU202000095
論文種類: 學術論文
相關次數: 點閱:147下載:22
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  • Inspired by many evidence showing that the Harris criterion could be violated in quantum phase transitions, we study the second-order quantum phase transition of a spin-1/2 antiferromagnetic Heisenberg model with a specific quenched disorder. In particular, various strengths of randomness are considered in our investigation. The studied models will undergo quantum phase transitions by tuning the dimerized-couplings which are close related to the strength of randomness. In addition, the strength of the employed randomness is controlled by a parameter $p$ which is in the range from 0 to 1, where the clean model corresponds to $p=0$.

    In this study, we use the stochastic series expansion with efficient loop-update to perform the large-scale quantum Monte Carlo simulation and compute certain physical observables of the model. The critical exponent of the correlation length is evaluated from the finite-size scaling analysis with the Binder ratios as the observables. In order to estimate the statistical uncertainties in a self-consistent way, we analyze the data in the Bayesian inference framework.

    In the case of $p=0$, we find that the critical exponent of the correlation length $\nu$ is 0.702(9) which is in reasonably good agreement with the result of $\mathcal{O}(3)$ universality class, and doesn't fulfill the Harris inequality $\nu>2/d$, where $d$ is the spatial dimension and is 2 in this case. Remarkably, while we find that those $\nu$ of $p \le 0.8$ do not fulfill the Harris inequality $\nu > 2/d$, the $\nu$ associated with $p = 0.9$ satisfies such. This interesting phenomenon is not pointed out explicitly before in the literature.

    Chapter1 Introduction 1 Chapter2 Critical Phenomenon 5 Chapter3 Stochastic Series Expansion Method 13 Chapter4 Simulation and Data Analysis 25 Chapter5 Conclusion 37

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