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Exceptional Times for the Discrete Web and Predictability in Ising Models

机译:Ising模型中离散Web和可预测性的特殊时间

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摘要

The dynamical discrete web (DyDW) is a system of one-dimensional coalescing random walks that evolves in an extra dynamical time parameter, tau. At any deterministic tau the paths behave as coalescing simple symmetric random walks. It has been shown by Fontes, Newman, Ravishankar and Schertzer that there exist exceptional dynamical times, tau, at which the path from the origin is K-subdiffusive, meaning the path is bounded above by j plus the square root of t for all t, where t is the random walk time, and j is some constant. In this thesis we consider for the first time the existence of superdiffusive exceptional times. To be specific, we consider tau such that the limsup of the path from the origin divided by the square root of t times the log of t is greater than or equal to C. We show that such exceptional times exist for small values of C, but they do not exist for large C. Another goal of this thesis is to establish the existence of exceptional times for which the path from the origin is K-subdiffusive in both directions, i.e., tau such that absolute value of the path from the origin is bounded above by j plus the square root of t for all t. We also obtain upper and lower bounds for the Hausdorff dimensions of these two-sided subdiffusive exceptional times. For the superdiffusive exceptional times we are able to get a lower bound on Hausdorff dimension but not an upper bound. This thesis concludes with a brief description of recent joint work with Charles Newman and Daniel Stein on dynamical Ising models. We consider Ising models with symmetric i.i.d. initial conditions evolving under zero temperature dynamics. The main goal is to examine the relative importance of the initial conditions versus the dynamics in determining the state of the system at large times.
机译:动态离散网(DyDW)是一维合并随机游动的系统,该系统在额外的动态时间参数tau中演化。在任何确定的tau上,路径的行为都像合并简单对称随机游走一样。丰特斯(Fontes),纽曼(Newman),拉维尚卡(Ravishankar)和谢尔策(Schertzer)已证明存在特殊的动力学时间tau,在该时间处,从原点开始的路径是K次扩散的,这意味着该路径的边界是j加上所有t的t的平方根,其中t是随机行走时间,而j是某个常数。在本文中,我们首次考虑了超扩散例外时间的存在。具体来说,我们认为tau使得从原点开始的路径的limsup除以t的平方根乘以t的对数等于或大于C。我们证明,对于C的较小值,存在这种例外时间,本论文的另一个目标是,确定异常时刻的存在,即从原点开始的路径在两个方向上都是K次扩散的,即tau,使得从原点开始的路径的绝对值由j加上所有t的t的平方根作为边界。我们还获得了这两个次亚扩散特殊时间的Hausdorff维数的上限和下限。对于超扩散例外时间,我们能够获得Hausdorff维数的下限,而没有上限。本文最后简要描述了与查尔斯·纽曼和丹尼尔·斯坦因在动力伊辛模型上的最新合作。我们考虑对称i.i.d的Ising模型。初始条件在零温度动态条件下发展。主要目标是检验在确定系统状态时初始条件与动力学的相对重要性。

著录项

  • 作者

    Jenkins, Dan.;

  • 作者单位

    New York University.;

  • 授予单位 New York University.;
  • 学科 Mathematics.;Statistics.
  • 学位 Ph.D.
  • 年度 2014
  • 页码 73 p.
  • 总页数 73
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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