A Bayesian Monte Carlo assessment of orbital stability in the late stages of planetary system formation
Jassyr Salas, Frank Bautista, Germ\'an Chaparro

TL;DR
This study uses Bayesian Monte Carlo methods to classify planetary systems and assess their orbital stability during late-stage formation, revealing that significant changes are rare but more common in systems with close-in, massive planets.
Contribution
Introduces a novel classification scheme for planetary systems validated with ABC methods and applies Bayesian Monte Carlo techniques to evaluate orbital stability in synthetic systems.
Findings
Less than 10% of systems experience orbital configuration changes.
Changes are more frequent in systems with close-in, massive planets.
Systems with F- and G-type stars and high metallicity are more prone to instability.
Abstract
The final orbital configuration of a planetary system is shaped by both its early star-disk environment and late-stage gravitational interactions. Assessing the relative importance of each of these factors is not straightforward due to the observed diversity of planetary systems compounded by observational biases. Our goal is to understand how a planetary system may change when planetesimal accretion and planet migrations stop and secular gravitational effects take over. Our approach starts with a novel classification of planetary systems based on their orbital architecture, validated using Approximate Bayesian Computation methods. We apply this scheme to observed planetary systems and also to synthetic systems hosting planets, synthesized from a Monte Carlo planet population model. Our classification scheme robustly yields four system classes according to their…
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