Energy distribution of inelastic gas in a box is dominated by a power law -- a derivation in the framework of sample space reducing processes
S. Thurner, J. Korbel, R. Hanel

TL;DR
This paper derives the energy distribution of an inelastic gas in a box using sample space reducing processes, revealing power-law behaviors influenced by driving rate and restitution, confirmed by simulations.
Contribution
It introduces SSR processes as an alternative to Boltzmann approaches for deriving energy distributions in dissipative systems, highlighting power-law solutions.
Findings
Energy distribution follows power laws over entire energy range.
Power-law exponents decrease with increased driving rate.
Results are validated through molecular dynamics simulations.
Abstract
We use the framework of sample space reducing processes (SSR) as an alternative to Boltzmann equation based approaches, to derive the energy and velocity distribution functions of an inelastic gas in a box as an example for a dissipative, driven system. SSR processes do not assume molecular chaos and are characterized by a specific type of eigenvalue equation whose solutions represent stationary distribution functions. The equations incorporate the geometry of inelastic collisions and a driving mechanism in a transparent way. Energy is injected by boosting particles that hit the walls of the container to high energies. The numerical solution of the resulting equations yields power laws over the entire energy region. The exponents decrease with the driving rate from about to below and depend on the coefficient of restitution. Results are confirmed with a molecular dynamics…
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
TopicsTheoretical and Computational Physics · Material Dynamics and Properties · Advanced Thermodynamics and Statistical Mechanics
