Lyapunov and Reversibility error invariant indicators
Federico Panichi, Giorgio Turchetti

TL;DR
This paper surveys Lyapunov and Reversibility Error indicators, introduces their invariant generalizations, and demonstrates their effectiveness in characterizing Hamiltonian system dynamics with improved robustness and new analytical tools.
Contribution
The paper proposes a generalization of Lyapunov and Reversibility Error indicators to make them invariant to initial conditions, and introduces higher-order invariant indicators for dynamical analysis.
Findings
Invariant indicators effectively characterize Hamiltonian dynamics.
Reversibility Error Method (REM) is practical and accurate.
Indicators depend on positive Lyapunov exponents.
Abstract
In this review, we present a survey of the Lyapunov Error and Reversibility Error (\cite{Faranda2012}), and we propose a generalization to make them invariant to the choice of initial conditions. We first define a process as the evolution in time of a a map or a flow, we then introduce the covariance matrix of a given process, and use their trace to compute LE and RE. The determinant of the covariance matrices is used to compute all invariant indicators of higher order. In this way, two set of invariant indicators are proposed within the framework introduced here, one for the Reversibility and one for the Lyapunov Errors, respectively. LE and RE which have been used in the literature, are the \textit{first-order} invariant indicators in their respective sets. The new sets of invariant indicators have the same fundamental meaning, the set for RE is used to characterize the…
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Taxonomy
TopicsQuantum chaos and dynamical systems · Chaos control and synchronization · Control and Stability of Dynamical Systems
