Practical application of KAM theory to galactic dynamics: I. Motivation and methodology

TL;DR

This paper explores the application of a numerical KAM theory approach to galactic dynamics, enabling the identification of regular and irregular orbits, and providing insights into the structure and evolution of galaxies.

Contribution

It introduces a numerical KAM procedure tailored for galactic dynamics, capable of constructing regular orbits and analyzing irregularities, including weak chaos and bifurcations.

Findings

Numerical KAM method effectively identifies regular and irregular orbits.

The approach reveals the morphology of perturbed orbits and potential causes of irregularity.

Models with significant stochasticity are common in galactic dynamics.

Abstract

Our understanding of the mechanisms governing the structure and secular evolution galaxies assume nearly integrable Hamiltonians with regular orbits; our perturbation theories are founded on the averaging theorem for isolated resonances. On the other hand, it is well-known that dynamical systems with many degrees of freedom are irregular in all but special cases. The best developed framework for studying the breakdown of regularity and the onset is the Kolmogorov-Arnold-Moser (KAM) theory. Here, we use a numerical version of the KAM procedure to construct regular orbits (tori) and locate irregular orbits (broken tori). Irregular orbits are most often classified in astronomical dynamics by their exponential divergence using Lyapunov exponents. Although their computation is numerically challenging, the procedure is straightforward and they are often used to estimate the measure of regularity. The numerical KAM approach has several advantages: 1) it provides the morphology of perturbed orbits; 2) its constructive nature allows the tori to be used as basis for studying secular evolution; 3) for broken tori, clues to the cause of the irregularity may be found by studying the largest, diverging Fourier terms; and 4) it is more likely to detect weak chaos and orbits close to bifurcation. Conversely, it is not a general technique and works most cleanly for small perturbations. We develop a perturbation theory that includes chaos by retaining an arbitrary number of interacting terms rather than eliminating all but one using the averaging theorem. The companion papers show that models with significant stochasticity seem to be the rule, not the exception.