A Fourier-Galerkin method with explicit error bounds rigorously computes stationary measures and Lyapunov exponents, proving noise-induced order transitions in Gaussian-noise perturbed unimodal maps.
A pseudospectral approach to rigorous numerical estimation of resonances of transfer operators
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abstract
{Ruelle-Pollicott} resonances, isolated eigenvalues of a transfer operator acting on suitably chosen Banach spaces, play a fundamental role in understanding the statistical properties of chaotic dynamical systems. In this paper, we introduce a pseudospectral approach, inspired by Householder's theorem, for the rigorous, computer-assisted estimation of resonances, providing regions where resonances must exist and precluding the presence of resonances elsewhere. The approach is general, and applies to the transfer operators of a wide variety of chaotic systems, including Anosov/ Axiom A diffeomorphisms and piecewise expanding maps. We implement this approach computationally for a class of analytic uniformly expanding maps of the circle. We anticipate that the pseudospectral framework developed here will be broadly applicable to other spectral problems in dynamical systems and beyond.
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A Fourier-Galerkin method with explicit error bounds rigorously computes stationary measures and Lyapunov exponents, proving noise-induced order transitions in Gaussian-noise perturbed unimodal maps.