{"title":"利用加权伯克霍夫平均数计算 Lyapunov 指数","authors":"E. Sander, J. D. Meiss","doi":"arxiv-2409.08496","DOIUrl":null,"url":null,"abstract":"The Lyapunov exponents of a dynamical system measure the average rate of\nexponential stretching along an orbit. Positive exponents are often taken as a\ndefining characteristic of chaotic dynamics. However, the standard\northogonalization-based method for computing Lyapunov exponents converges\nslowly -- if at all. Many alternatively techniques have been developed to\ndistinguish between regular and chaotic orbits, though most do not compute the\nexponents. We compute the Lyapunov spectrum in three ways: the standard method,\nthe weighted Birkhoff average (WBA), and the ``mean exponential growth rate for\nnearby orbits'' (MEGNO). The latter two improve convergence for nonchaotic\norbits, but the WBA is fastest. However, for chaotic orbits the three methods\nconvergence at similar, slow rates. Though the original MEGNO method does not\ncompute Lyapunov exponents, we show how to reformulate it as a weighted average\nthat does.","PeriodicalId":501035,"journal":{"name":"arXiv - MATH - Dynamical Systems","volume":"65 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Computing Lyapunov Exponents using Weighted Birkhoff Averages\",\"authors\":\"E. Sander, J. D. Meiss\",\"doi\":\"arxiv-2409.08496\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The Lyapunov exponents of a dynamical system measure the average rate of\\nexponential stretching along an orbit. Positive exponents are often taken as a\\ndefining characteristic of chaotic dynamics. However, the standard\\northogonalization-based method for computing Lyapunov exponents converges\\nslowly -- if at all. Many alternatively techniques have been developed to\\ndistinguish between regular and chaotic orbits, though most do not compute the\\nexponents. We compute the Lyapunov spectrum in three ways: the standard method,\\nthe weighted Birkhoff average (WBA), and the ``mean exponential growth rate for\\nnearby orbits'' (MEGNO). The latter two improve convergence for nonchaotic\\norbits, but the WBA is fastest. However, for chaotic orbits the three methods\\nconvergence at similar, slow rates. Though the original MEGNO method does not\\ncompute Lyapunov exponents, we show how to reformulate it as a weighted average\\nthat does.\",\"PeriodicalId\":501035,\"journal\":{\"name\":\"arXiv - MATH - Dynamical Systems\",\"volume\":\"65 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"arXiv - MATH - Dynamical Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/arxiv-2409.08496\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"arXiv - MATH - Dynamical Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/arxiv-2409.08496","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Computing Lyapunov Exponents using Weighted Birkhoff Averages
The Lyapunov exponents of a dynamical system measure the average rate of
exponential stretching along an orbit. Positive exponents are often taken as a
defining characteristic of chaotic dynamics. However, the standard
orthogonalization-based method for computing Lyapunov exponents converges
slowly -- if at all. Many alternatively techniques have been developed to
distinguish between regular and chaotic orbits, though most do not compute the
exponents. We compute the Lyapunov spectrum in three ways: the standard method,
the weighted Birkhoff average (WBA), and the ``mean exponential growth rate for
nearby orbits'' (MEGNO). The latter two improve convergence for nonchaotic
orbits, but the WBA is fastest. However, for chaotic orbits the three methods
convergence at similar, slow rates. Though the original MEGNO method does not
compute Lyapunov exponents, we show how to reformulate it as a weighted average
that does.