On Irreversibility and Stochastic Systems; Part Two
Giorgio Picci

TL;DR
This paper explores how irreversibility in dynamical systems can be characterized through different forward and backward stochastic representations, linking deterministic Hamiltonian systems with stochastic diffusions via heat baths.
Contribution
It demonstrates that heat baths induce stochastic diffusions in deterministic systems and connects these stochastic models to Hamiltonian frameworks, extending understanding of irreversibility.
Findings
Heat baths induce dissipative stochastic diffusions.
Forward-backward representations can describe deterministic systems with heat baths.
Stationary processes with rational spectra relate to lossless deterministic systems.
Abstract
We attempt to characterize irreversibility of a dynamical system from the existence of different forward and backward mathematical representations depending on the direction of the time arrow. Such different representations have been studied intensively and are shown to exist for stochastic diffusion models. In this setting one has however to face the preliminary justification of the existence of a stochastic description for physical systems which are traditionally described by classical mechanics as inherently deterministic and conservative. In part one of this paper we have addressed this modeling problem from a deterministic viewpoint for linear systems. We have shown that there are forward-backward representations which can describe conservative finite dimensional deterministic systems when they are coupled to an infinite-dimensional conservative heat bath. A key observation is…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced Thermodynamics and Statistical Mechanics · stochastic dynamics and bifurcation · Control and Stability of Dynamical Systems
