Shadowability of Statistical Averages in Chaotic Systems

作     者：Ying-Cheng Lai Zonghua Liu Guo-Wei Wei Choy-Heng Lai 

作者机构：Department of Mathematics and Center for Systems Science and Engineering Research Arizona State University Tempe Arizona 85287 Departments of Electrical Engineering and Physics Arizona State University Tempe Arizona 85287 Department of Computational Science National University of Singapore Singapore 117543 Singapore Department of Physics National University of Singapore Singapore 117543 Singapore 

出 版 物：《Physical Review Letters》 (Phys Rev Lett)

年 卷 期：2002年第89卷第18期

页      面：184101-184101页

核心收录：

学科分类：07[理学] 0702[理学-物理学] 

基　　金：National Science Foundation, NSF, (PHY-9996454) Air Force Office of Scientific Research, AFOSR, (F49620-98-1-0400) 

主　　题：.true situations scaling trajectory algebraic unstable Shadowability Statistical Averages Chaotic noise amplitude numerical trajectories Lyapunov exponents 

摘      要：We ask whether statistical averages in chaotic systems can be computed or measured reliably under the influence of noise. Situations are identified where the invariance of such averages breaks down as the noise amplitude increases through a critical level. An algebraic scaling law is obtained which relates the change of the averages to the noise variation. This breakdown of shadowability of statistical averages, as characterized by the algebraic scaling law, can be expected in both low- and high-dimensional chaotic systems.