Estimating long-term behavior of periodically driven flows without trajectory integration
Gary Froyland, P\'eter Koltai

TL;DR
This paper develops a theoretical framework and numerical methods to analyze the long-term behavior of periodically driven flows, both deterministic and stochastic, without relying on trajectory integration, by leveraging the time-extended phase space and generators.
Contribution
It introduces a novel approach using generators on the time-extended phase space to study transport and escape rates, avoiding costly trajectory integration.
Findings
Established relationships between original and extended representations for transport analysis
Quantified decay rates of observables in stochastic periodically driven flows
Developed efficient numerical schemes based on the generator approach
Abstract
Periodically driven flows are fundamental models of chaotic behavior and the study of their transport properties is an active area of research. A well-known analytic construction is the augmentation of phase space with an additional time dimension; in this augmented space, the flow becomes autonomous or time-independent. We prove several results concerning the connections between the original time-periodic representation and the time-extended representation, focusing on transport properties. In the deterministic setting, these include single-period outflows and time-asymptotic escape rates from time-parameterized families of sets. We also consider stochastic differential equations with time-periodic advection term. In this stochastic setting one has a time-periodic generator (the differential operator given by the right-hand-side of the corresponding time-periodic Fokker-Planck…
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