Semimartingale driven mechanics and reduction by symmetry for stochastic and dissipative dynamical systems

TL;DR

This paper develops a mathematically rigorous framework for stochastic mechanics using semimartingale-driven equations, symmetry reduction, and dissipation, preserving geometric structures and measures in stochastic dynamical systems.

Contribution

It introduces a stochastic Hamilton-Pontryagin principle and derives stochastic Euler-Lagrange and Euler-Poincaré equations, including dissipation that maintains the Gibbs measure.

Findings

Derived stochastic Euler-Lagrange equations driven by semimartingales.

Applied symmetry reduction to obtain stochastic Euler-Poincaré equations.

Developed a dissipation framework that preserves the Gibbs measure.

Abstract

The recent interest in structure preserving stochastic Lagrangian and Hamiltonian systems raises questions regarding how such models are to be understood and the principles through which they are to be derived. By considering a mathematically sound extension of the Hamilton-Pontryagin principle, we derive a stochastic analogue of the Euler-Lagrange equations, driven by independent semimartingales. Using this as a starting point, we can apply symmetry reduction carefully to derive non-canonical stochastic Lagrangian / Hamiltonian systems, including the stochastic Euler-Poincar\'e / Lie-Poisson equations, studied extensively in the literature. Furthermore, we develop a framework to include dissipation that balances the structure-preserving noise in such a way that the overall stochastic dynamics preserves the Gibbs measure on the symplectic manifold, where the dynamics effectively take place. In particular, this leads to a new derivation of double-bracket dissipation by considering Lie group invariant stochastic dissipative dynamics, taking place on the cotangent bundle of the group.