4.6 Article

Chaotic diffusion of the fundamental frequencies in the Solar System

期刊

ASTRONOMY & ASTROPHYSICS
卷 654, 期 -, 页码 -

出版社

EDP SCIENCES S A
DOI: 10.1051/0004-6361/202140989

关键词

chaos; diffusion; celestial mechanics; methods; statistical

资金

  1. CFM Foundation for Research
  2. European Research Council (ERC) under the European Union [AstroGeo-885250]
  3. French Agence Nationale de la Recherche (ANR) [AstroMeso ANR-19-CE31-0002-01]

向作者/读者索取更多资源

This study conducted a statistical analysis of 120,000 orbital solutions of the Solar System, exploring the impact of orbital variations on astronomical calibration of geological records and demonstrating the accuracy of results under uncertainty. The results of the secular model were found to be in good agreement with those of the direct integrations of a comprehensive model of the Solar System.
The long-term variations in the orbit of the Earth govern the insolation on its surface and hence its climate. The use of the astronomical signal, whose imprint has been recovered in the geological records, has revolutionized the determination of the geological timescales. However, the orbital variations beyond 60 Myr cannot be reliably predicted because of the chaotic dynamics of the planetary orbits in the Solar System. Taking this dynamical uncertainty to account is necessary for a complete astronomical calibration of geological records. Our work addresses this problem with a statistical analysis of 120 000 orbital solutions of the secular model of the Solar System ranging from 500 Myr to 5 Gyr. We obtain the marginal probability density functions of the fundamental secular frequencies using kernel density estimation. The uncertainty of the density estimation is also obtained here in the form of confidence intervals determined by the moving block bootstrap method. The results of the secular model are shown to be in good agreement with those of the direct integrations of a comprehensive model of the Solar System. Application of our work is illustrated on two geological data sets: the Newark-Hartford records and the Libsack core.

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