The attractors in the complex Lorenz model

Xavier Gómez-Mont, José Job Flores-Godoy, Guillermo Fernández-Anaya

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

We address the question of finding the attractors of the complex Lorenz model (CLM), which is obtained by extending the space from R3 to C3, and defining the model by the same equations as the classical Lorenz model (LM). We have numerical evidence of 2 strong attractors un-related to the Lorenz attractor. We calculate its Lyapunov exponents and show that 2 of them are 0, and the other 4 are double and negative. Hence the attractors are non-chaotic. We show that they have a quasi-periodic nature. To decipher the structure of these attractors, we introduce the imaginary Lorenz model (ILM), which is defined in the same space C3 by multiplying with i = √-1 the Lorenz equations. Both models locally commute, and with its help we account for the double Lyapunov exponent 0 and show that the basin of attraction of each attractor is a big open set of C3. The chaotic limit set L ∪ ℂ3 obtained from the classical Lorenz attractor L0 of (LM) by moving it with the (ILM) has 2 positive Lyapunov exponents, but only captures a set of 6D-volume 0 in its basin of attraction.

Original languageEnglish
Title of host publication3rd IFAC Conference on Analysis and Control of Chaotic Systems, CHAOS 2012
PublisherIFAC Secretariat
Pages87-92
Number of pages6
Edition12
ISBN (Print)9783902823021
DOIs
StatePublished - 2012
Externally publishedYes
Event3rd IFAC Conference on Analysis and Control of Chaotic Systems, CHAOS 2012 - Cancun, Mexico
Duration: 20 Jun 201222 Jun 2012

Publication series

NameIFAC Proceedings Volumes (IFAC-PapersOnline)
Number12
Volume45
ISSN (Print)1474-6670

Conference

Conference3rd IFAC Conference on Analysis and Control of Chaotic Systems, CHAOS 2012
Country/TerritoryMexico
CityCancun
Period20/06/1222/06/12

Keywords

  • Chaos
  • Complex systems
  • Differential equations
  • Dynamic model
  • Nonlinear analysis
  • Nonlinear equations

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