Coarse Variables of Autonomous ODE Systems and Their Evolution
Likun Tan, Amit Acharya, Kaushik Dayal

TL;DR
This paper develops methods to model the slow, coarse behavior of autonomous ODE systems using two types of variables: time averages of phase functions and scalar functions that evolve autonomously, tested on Lorenz and Hamiltonian systems.
Contribution
It introduces practical approaches for constructing coarse evolution equations for autonomous ODE systems using invariant manifolds and autonomous scalar variables, with computational validation.
Findings
Coarse models accurately predict slow dynamics of Lorenz and Hamiltonian systems.
Invariant manifold approach effectively captures fast dynamics influence.
Autonomous scalar variables can be approximated to evolve independently.
Abstract
Given an autonomous system of ordinary differential equations (ODE), we consider developing practical models for the deterministic, slow/coarse behavior of the ODE system. Two types of coarse variables are considered. The first type consists of running finite time averages of phase functions. Approaches to construct the coarse evolution equation for this type are discussed and implemented on a 'Forced' Lorenz system and a singularly perturbed system whose fast flow does not necessarily converge to an equilibrium. We explore two strategies. In one, we compute (locally) invariant manifolds of the fast dynamics, parameterized by the slow variables. In the other, the choice of our coarse variables automatically guarantees them to be 'slow' in a precise sense. This allows their evolution to be phrased in terms of averaging utilizing limit measures (probability distributions) of the fast…
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