Ratchet current and scaling properties in a nontwist mapping
Matheus Rolim Sales, Daniel Borin, Leonardo Costa de Souza, Jos\'e, Danilo Szezech Jr., Ricardo Luiz Viana, Iber\^e Luiz Caldas, and Edson Denis, Leonel

TL;DR
This paper studies particle transport in a nontwist map, revealing exponential and power-law decay regimes, asymmetry-induced ratchet current, and scaling laws for diffusion through numerical simulations.
Contribution
It introduces a phenomenological framework with scaling hypotheses to describe diffusion and uncovers the origin of ratchet current due to phase space asymmetry.
Findings
Exponential decay of survival probability in predominantly chaotic regions.
Power-law tail indicating stickiness in mixed regions.
Asymmetry causes a ratchet current in phase space.
Abstract
We investigate the transport of particles in the chaotic component of phase space for a two-dimensional, area-preserving nontwist map. The survival probability for particles within the chaotic sea is described by an exponential decay for regions in phase space predominantly chaotic and it is scaling invariant in this case. Alternatively, when considering mixed chaotic and regular regions, there is a deviation from the exponential decay, characterized by a power law tail for long times, a signature of the stickiness effect. Furthermore, due to the asymmetry of the chaotic component of phase space with respect to the line , there is an unbalanced stickiness which generates a ratchet current in phase space. Finally, we perform a phenomenological description of the diffusion of chaotic particles by identifying three scaling hypotheses, and obtaining the critical exponents via…
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.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum chaos and dynamical systems · Power System Optimization and Stability
