We provide the code that supports the results reported in the manuscript Monte Carlo sampling in diffusive dynamical systems. We implement here the Metropolis-Hastings algorithm for the estimation of a weighted distribution of the displacement.
In the folder Examples
we illustrate its basic use for two dynamical systems: Lorentz gas and Box map. For its use in other deterministic dynamical systems the dynamics should be introduced and the function rMCMC
. The steps to do it are always the same, namely:
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The dynamical system is coded, taking care of defining it for both positive and negative times. You might use the package DynamicalSystems.jl .
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The main parameters, i.e. the mean Lyapunov exponent and the diffusion coefficient are estimated or passed if they are previously known.
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The two proposals are coded based on the dynamics. It would depend on the nature of the dynamical system (e.g. map or flow) and its dimension.
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The observable (r_t) is defined and used inside
rMCMC
. In our examples, it is thedistance
for the Lorentz gas andabs(evolution - 1/2)
for the box map.