Empirical stability criteria for 3D hierarchical triple systems I: Circumbinary planets
Nikolaos Georgakarakos, Siegfried Eggl, Mohamad Ali-Dib, Ian, Dobbs-Dixon

TL;DR
This paper provides empirical stability criteria and machine learning tools for predicting the long-term stability of circumbinary planets in hierarchical triple systems, considering a wide range of orbital parameters.
Contribution
It introduces new empirical formulas and a machine learning model trained on extensive simulations to predict circumbinary planetary stability.
Findings
Empirical stability boundaries accurately predict system stability.
Machine learning model performs well in classifying stable and unstable systems.
Application of criteria confirms stability of known Kepler and TESS circumbinary planets.
Abstract
In this work we revisit the problem of the dynamical stability of hierarchical triple systems with applications to circumbinary planetary orbits. We carry out more than 3 10^8 numerical simulations of planets between the size of Mercury and the lower fusion boundary (13 Jupiter masses) which revolve around the center of mass of a stellar binary over long timescales. For the first time, three dimensional and eccentric planetary orbits are considered. We explore systems with a variety of binary and planetary mass ratios, binary and planetary eccentricities from 0 to 0.9 and orbital mutual inclinations ranging from 0 to 180 degrees. The simulation time is set to 10^6 planetary orbital periods. We classify the results of those long term numerical integrations into three categories: stable, unstable and mixed. We provide empirical expressions in the form of multidimensional, parameterized…
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Taxonomy
TopicsScientific Research and Discoveries · Matrix Theory and Algorithms · Optimization and Search Problems
