The present work consists on a study of the dynamical stability of a 3-body system, taking advantage of the Shannon entropy approachto estimate the diffusivity (D S ) in a Delaunay's action-like phase space. We outline the main features of a numerical computation ofD S from the solutions of the equations of motion, and therefrom how to estimate a macroscopic instability time-scale τ inst (roughlyspeaking, the lifetime of the system) associated to a given set of initial conditions. Through such estimates we characterize the system?sspace of initial conditions in terms of its orbital stability, applying numerical integrations on the construction of dynamical maps. Wecompare these measures of chaotic diffusion with other indicators, firstly in...
We propose a novel method applied to extrasolar planetary dynamics to describe the system stability....
We present numerical evidence that diffusion in the herein studied multidimensional near-integrable ...
Data assimilation (DA) aims at optimally merging observational data and model outputs to create a co...
In this work it is shown that the Shannon entropy is an efficient dynamical indicator that provides ...
In the present effort, we revisit the Shannon entropy approach for the study of both the extent and ...
In the present work, we introduce two new estimators of chaotic diffusion based on the Shannon entro...
In the present work we extend and generalize the formulation of the Shannon entropy as a measure of ...
Caos e instabilidade: conceitos diferentes, com distintas implicações, e por vezes correlacionados. ...
The long-term dynamical evolution is a crucial point in recent planetary research. Although the amou...
In the present work, we investigate phase correlations by recourse to the Shannon entropy. Using the...
Chaotic diffusion is supposed to be responsible for orbital instabilities in planetary systems after...
In this paper we discuss the relevance of diffusive processes in multidimensional Hamiltonian system...
We present a numerical study of the application of the Shannon entropy technique to the planar restr...
Because the Solar System is chaotic, the orbital evolution of the Earth's orbit beyond 60 Myr cannot...
This is the first monograph dedicated entirely to problems of stability and chaotic behaviour in pla...
We propose a novel method applied to extrasolar planetary dynamics to describe the system stability....
We present numerical evidence that diffusion in the herein studied multidimensional near-integrable ...
Data assimilation (DA) aims at optimally merging observational data and model outputs to create a co...
In this work it is shown that the Shannon entropy is an efficient dynamical indicator that provides ...
In the present effort, we revisit the Shannon entropy approach for the study of both the extent and ...
In the present work, we introduce two new estimators of chaotic diffusion based on the Shannon entro...
In the present work we extend and generalize the formulation of the Shannon entropy as a measure of ...
Caos e instabilidade: conceitos diferentes, com distintas implicações, e por vezes correlacionados. ...
The long-term dynamical evolution is a crucial point in recent planetary research. Although the amou...
In the present work, we investigate phase correlations by recourse to the Shannon entropy. Using the...
Chaotic diffusion is supposed to be responsible for orbital instabilities in planetary systems after...
In this paper we discuss the relevance of diffusive processes in multidimensional Hamiltonian system...
We present a numerical study of the application of the Shannon entropy technique to the planar restr...
Because the Solar System is chaotic, the orbital evolution of the Earth's orbit beyond 60 Myr cannot...
This is the first monograph dedicated entirely to problems of stability and chaotic behaviour in pla...
We propose a novel method applied to extrasolar planetary dynamics to describe the system stability....
We present numerical evidence that diffusion in the herein studied multidimensional near-integrable ...
Data assimilation (DA) aims at optimally merging observational data and model outputs to create a co...