论文标题
一维混沌图的奇异灵敏度分析
Ergodic Sensitivity Analysis of One-Dimensional Chaotic Maps
论文作者
论文摘要
从计算的角度来看，混乱的动力学系统中的灵敏度分析是一项具有挑战性的任务。在这项工作中，我们提出了一种新方法的数值研究，称为太空敏感性或S3算法。 S3算法是一种基于双曲线动力学理论，是一种细分，混乱系统的统计数据，是一种细分，混乱系统的统计数据。我们在一维混沌图上说明了S3，揭示了其计算优势比同一统计响应的幼稚有限差计算计算。此外，我们提供了S3算法的关键组件（包括密度梯度函数）的直观解释。
Sensitivity analysis in chaotic dynamical systems is a challenging task from a computational point of view. In this work, we present a numerical investigation of a novel approach, known as the space-split sensitivity or S3 algorithm. The S3 algorithm is an ergodic-averaging method to differentiate statistics in ergodic, chaotic systems, rigorously based on the theory of hyperbolic dynamics. We illustrate S3 on one-dimensional chaotic maps, revealing its computational advantage over naive finite difference computations of the same statistical response. In addition, we provide an intuitive explanation of the key components of the S3 algorithm, including the density gradient function.
