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Critical behavior for the model of random spatial permutations.

机译:随机空间排列模型的关键行为。

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摘要

We examine a phase transition in a model of random spatial permutations which originates in a study of the interacting Bose gas. Permutations are weighted according to point positions; the low-temperature onset of the appearance of arbitrarily long cycles is connected to the phase transition of Bose-Einstein condensates. In our simplified model, point positions are held fixed on the fully occupied cubic lattice and interactions are expressed as Ewens-type weights on cycle lengths of permutations. The critical temperature of the transition to long cycles depends on an interaction-strength parameter alpha. For weak interactions, the shift in critical temperature is expected to be linear in alpha with constant of linearity c. Using Markov chain Monte Carlo methods and finite-size scaling, we find c = 0.618+/-0.086. This finding matches a similar analytical result of Ueltschi and Betz. We also examine the mean longest cycle length as a fraction of the number of sites in long cycles, recovering an earlier result of Shepp and Lloyd for non-spatial permutations. The plan of this paper is as follows. We begin with a non-technical discussion of the historical context of the project, along with a mention of alternative approaches. Relevant previous works are cited, thus annotating the bibliography. The random-cycle approach to the BEC problem requires a model of spatial permutations. This model it is of its own probabilistic interest; it is developed mathematically, without reference to the Bose gas. Our Markov-chain Monte Carlo algorithms for sampling from the random-cycle distribution---the swap-only, swap-and-reverse, band-update, and worm algorithms---are presented, compared, and contrasted. Finite-size scaling techniques are used to obtain information about infinite-volume quantities from finite-volume computational data.
机译:我们检查了随机空间排列模型中的相变,该模型源自对相互作用的玻色气体的研究。排列根据点位置加权;任意长周期出现的低温开始与Bose-Einstein冷凝物的相变有关。在我们的简化模型中,点位置保持固定在完全占据的立方晶格上,并且交互作用表示为排列周期长度上的Ewens型权重。向长循环过渡的临界温度取决于相互作用强度参数alpha。对于弱相互作用,预计临界温度的变化在α中具有线性常数c。使用马尔可夫链蒙特卡罗方法和有限大小缩放,我们发现c = 0.618 +/- 0.086。这一发现与Ueltschi和Betz的类似分析结果相符。我们还检查了平均最长周期长度,它是长周期中位点数量的一部分,从而恢复了Shepp和Lloyd对于非空间排列的早期结果。本文的计划如下。我们从项目历史背景的非技术性讨论开始,并提及替代方法。引用了以前的相关著作,从而对参考书目进行了注释。解决BEC问题的随机循环方法需要空间排列模型。此模型具有其自身的概率意义;它是在数学上开发的,无需参考Bose气体。我们介绍,比较和对比了用于随机周期分布的马尔可夫链蒙特卡罗算法-仅交换,交换和反向,频带更新和蠕虫算法-。有限尺寸缩放技术用于从有限体积的计算数据中获取有关无限体积数量的信息。

著录项

  • 作者

    Kerl, John.;

  • 作者单位

    The University of Arizona.;

  • 授予单位 The University of Arizona.;
  • 学科 Mathematics.;Physics Condensed Matter.
  • 学位 Ph.D.
  • 年度 2010
  • 页码 206 p.
  • 总页数 206
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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