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Statistical properties of dynamical systems – Simulation and abstract computation

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  • Galatolo, Stefano
  • Hoyrup, Mathieu
  • Rojas, Cristóbal

Abstract

We survey an area of recent development, relating dynamics to theoretical computer science. We discuss some aspects of the theoretical simulation and computation of the long term behavior of dynamical systems. We will focus on the statistical limiting behavior and invariant measures. We present a general method allowing the algorithmic approximation at any given accuracy of invariant measures. The method can be applied in many interesting cases, as we shall explain. On the other hand, we exhibit some examples where the algorithmic approximation of invariant measures is not possible. We also explain how it is possible to compute the speed of convergence of ergodic averages (when the system is known exactly) and how this entails the computation of arbitrarily good approximations of points of the space having typical statistical behaviour (a sort of constructive version of the pointwise ergodic theorem).

Suggested Citation

  • Galatolo, Stefano & Hoyrup, Mathieu & Rojas, Cristóbal, 2012. "Statistical properties of dynamical systems – Simulation and abstract computation," Chaos, Solitons & Fractals, Elsevier, vol. 45(1), pages 1-14.
    • Handle: RePEc:eee:chsofr:v:45:y:2012:i:1:p:1-14
    DOI: 10.1016/j.chaos.2011.09.011
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    Cited by:

    1. Liao, Shijun, 2013. "On the numerical simulation of propagation of micro-level inherent uncertainty for chaotic dynamic systems," Chaos, Solitons & Fractals, Elsevier, vol. 47(C), pages 1-12.

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