Chaos identification through the auto-correlation function indicator (ACFI)

Autor:	Valerio Carruba, Safwan Aljbaae, Rita C. Domingos, Mariela Huaman, William Barletta
Rok vydání:	2019
Předmět:	Space and Planetary Science Astronomy and Astrophysics
Zdroj:	Proceedings of the International Astronomical Union. 15:108-112
ISSN:	1743-9221 1743-9213
Popis:	Close encounters or resonances overlaps can create chaotic motion in small bodies in the Solar System. Approaches that measure the separation rate of trajectories that start infinitesimally near, or changes in the frequency power spectrum of time series, among others, can discover chaotic motion. In this paper, we introduce the ACF index (ACFI), which is based on the auto-correlation function of time series. Auto-correlation coefficients measure the correlation of a time-series with a lagged duplicate of itself. By counting the number of auto-correlation coefficients that are larger than 5% after a certain amount of time has passed, we can assess how the time series auto-correlates with each other. This allows for the detection of chaotic time-series characterized by low ACFI values.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::587f4ea6291296552e62216d24672e52 https://doi.org/10.1017/s1743921321001307 Zobrazit plný text záznamu