Equilibrium solution for cold dynamical systems and self-similarity
C. Alard

TL;DR
This paper analytically investigates how cold initial conditions in dynamical systems evolve towards self-similarity, revealing the mechanisms and conditions that facilitate this convergence near equilibrium.
Contribution
It establishes a theoretical link between cold initial states and self-similarity, extending the analysis with perturbative methods and practical induction mechanisms.
Findings
Cold solutions can evolve into self-similar states after several dynamical times.
Perturbative analysis shows the power-law potential tends to strengthen and propagate.
A broad range of initial conditions are compatible with self-similar solutions.
Abstract
Numerical simulations demonstrate a link between dynamically cold initial solutions and an evolution towards self-similarity. However the nature of this link is not fully understood. In this work the link between cold initial conditions and self-similarity near equilibrium is established. The evolution towards self-similarity is analyzed using an analytical solution in a power-law potential. The analytical solution indicates a convergence towards self-similarity after a number of dynamical times even if the inital conditions are far from self-similarity. The power-law model is extended by using perturbative analysis. The perturbative analysis shows that once the power-law potential is initiated it tends to become stronger and propagate. This behavior demonstrates the mechanism behind the convergence towards auto-similarity. The cold solutions are compatible with a broad range of…
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 · Quantum chaos and dynamical systems · Mathematical Biology Tumor Growth
