Abstract

We argue that typical mechanical systems subjected to a monotonous parameter drift whose timescale is comparable to that of the internal dynamics can be considered to undergo their own climate change. Because of their chaotic dynamics, there are many permitted states at any instant, and their time dependence can be followed—in analogy with the real climate—by monitoring parallel dynamical evolutions originating from different initial conditions. To this end an ensemble view is needed, enabling one to compute ensemble averages characterizing the instantaneous state of the system. We illustrate this on the examples of (i) driven dissipative and (ii) Hamiltonian systems and of (iii) non-driven dissipative ones. We show that in order to find the most transparent view, attention should be paid to the choice of the initial ensemble. While the choice of this ensemble is arbitrary in the case of driven dissipative systems (i), in the Hamiltonian case (ii) either KAM tori or chaotic seas should be taken, and in the third class (iii) the best choice is the KAM tori of the dissipation-free limit. In all cases, the time evolution of the chosen ensemble on snapshots illustrates nicely the geometrical changes occurring in the phase space, including the strengthening, weakening or disappearance of chaos. Furthermore, we show that a Smale horseshoe (a chaotic saddle) that is changing in time is present in all cases. Its disappearance is a geometrical sign of the vanishing of chaos. The so-called ensemble-averaged pairwise distance is found to provide an easily accessible quantitative measure for the strength of chaos in the ensemble. Its slope can be considered as an instantaneous Lyapunov exponent whose zero value signals the vanishing of chaos. Paradigmatic low-dimensional bistable systems are used as illustrative examples whose driving in (i, ii) is chosen to decay in time in order to maintain an analogy with case (iii) where the total energy decreases all the time.

Highlights

  • One of the most relevant phenomena experienced by everyone in our days is climate change

  • One can accept that there is a multitude of possible states, and in a stationary case, one can speak of parallel states of the climate

  • On a more quantitative level, we show that the pairwise distance of trajectories averaged over the parallel dynamical evolutions, the socalled ensemble-averaged pairwise distance (EAPD), is a quantity which faithfully represents the strength of chaos in all cases by providing instantaneous values of the Lyapunov exponent as well

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Summary

Introduction

One of the most relevant phenomena experienced by everyone in our days is climate change. The dynamics of a general system is chaotic-like, and has external time dependence and since the tools of standard chaos science, e.g., periodic orbit theory [12], are only defined for stationary systems, they cannot be used in the presence of parameter drift. Such systems, possess a plethora of permitted states, i.e., internal variability, whose time dependence can be described by following an ensemble, i.e., by accepting the snapshot view. This method enables us to identify the instant when chaos disappears as the time when this Lyapunov exponent vanishes

The model
Snapshot hyperbolic points and snapshot nodes
Snapshot attractors
Snapshot attractors and unstable manifolds of the snapshot hyperbolic point
Time-dependent basin boundaries and snapshot stable manifolds
Snapshot horseshoes
Strength of chaos
The choice of ensembles
Snapshot hyperbolic and elliptic points
Evolution of the snapshot phase portrait
Hamiltonian snapshot horseshoes
50. For every distance r0
Magnetic pendulum
Time-dependent basin structures
Evolution of initially Hamiltonian tori
Conclusions and discussions
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