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有限时间辫指数。

Finite-time braiding exponents.

作者信息

Budišić Marko, Thiffeault Jean-Luc

机构信息

Department of Mathematics, University of Wisconsin, Madison, Wisconsin 53706, USA.

出版信息

Chaos. 2015 Aug;25(8):087407. doi: 10.1063/1.4927438.

DOI:10.1063/1.4927438
PMID:26328578
Abstract

Topological entropy of a dynamical system is an upper bound for the sum of positive Lyapunov exponents; in practice, it is strongly indicative of the presence of mixing in a subset of the domain. Topological entropy can be computed by partition methods, by estimating the maximal growth rate of material lines or other material elements, or by counting the unstable periodic orbits of the flow. All these methods require detailed knowledge of the velocity field that is not always available, for example, when ocean flows are measured using a small number of floating sensors. We propose an alternative calculation, applicable to two-dimensional flows, that uses only a sparse set of flow trajectories as its input. To represent the sparse set of trajectories, we use braids, algebraic objects that record how trajectories exchange positions with respect to a projection axis. Material curves advected by the flow are represented as simplified loop coordinates. The exponential rate at which a braid stretches loops over a finite time interval is the Finite-Time Braiding Exponent (FTBE). We study FTBEs through numerical simulations of the Aref Blinking Vortex flow, as a representative of a general class of flows having a single invariant component with positive topological entropy. The FTBEs approach the value of the topological entropy from below as the length and number of trajectories is increased; we conjecture that this result holds for a general class of ergodic, mixing systems. Furthermore, FTBEs are computed robustly with respect to the numerical time step, details of braid representation, and choice of initial conditions. We find that, in the class of systems we describe, trajectories can be re-used to form different braids, which greatly reduces the amount of data needed to assess the complexity of the flow.

摘要

动力系统的拓扑熵是正李雅普诺夫指数之和的上界;在实际中,它强烈表明在定义域的一个子集中存在混合现象。拓扑熵可以通过划分方法、估计物质线或其他物质元素的最大增长率,或者通过计算流的不稳定周期轨道来计算。所有这些方法都需要速度场的详细知识,而这并非总是可得的,例如,当使用少量漂浮传感器测量海洋流时。我们提出一种适用于二维流的替代计算方法,它仅使用一组稀疏的流轨迹作为输入。为了表示轨迹的稀疏集,我们使用辫子,辫子是一种代数对象,用于记录轨迹相对于投影轴如何交换位置。由流平流的物质曲线表示为简化的环坐标。辫子在有限时间间隔内拉伸环的指数速率就是有限时间辫子指数(FTBE)。我们通过对阿雷夫闪烁涡旋流进行数值模拟来研究FTBE,阿雷夫闪烁涡旋流是具有正拓扑熵的单个不变分量的一般流类的代表。随着轨迹长度和数量的增加,FTBE从下方接近拓扑熵的值;我们推测这个结果适用于一般的遍历混合系统类。此外,FTBE对于数值时间步长、辫子表示的细节以及初始条件的选择都能稳健地计算。我们发现,在我们所描述的系统类中,轨迹可以被重新用于形成不同的辫子,这大大减少了评估流的复杂性所需的数据量。

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Finite-time braiding exponents.有限时间辫指数。
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