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Lagrange approximation of transfer operators associated with holomorphic data
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We show that spectral data of transfer operators given by holomorphic data can be approximated using an effective numerical scheme based on Lagrange interpolation. In particular, we show that for one-dimensional systems satisfying certain complex contraction properties, spectral data of the approximants converge exponentially to the spectral data of the transfer operator with the exponential rate determined by the respective complex contraction ratios of the underlying systems. We demonstrate the effectiveness of this scheme by numerically computing eigenvalues of transfer operators arising from interval and circle maps, as well as Lyapunov exponents of (positive) random matrix products and iterated function systems, based on examples taken from the literature.
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A pseudospectral approach to rigorous numerical estimation of resonances of transfer operators
A pseudospectral, computer-assisted framework yields certified enclosures and exclosures of Ruelle-Pollicott resonances for analytic expanding circle maps, demonstrated on a Blaschke benchmark and a perturbed doubling map.
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