Hierarchical Bayesian calibration of tidal orbit decay rates among hot Jupiters
Andrew Collier Cameron, Moira Jardine

TL;DR
This paper develops a hierarchical Bayesian model to estimate stellar tidal dissipation parameters from hot Jupiter orbital data, revealing their values and temperature dependence with implications for planetary evolution.
Contribution
It introduces a novel generative Bayesian framework to infer tidal dissipation rates from observed hot Jupiter distributions, validated with mock data and applied to real survey results.
Findings
Estimated $ m log_{10} Q_s'$ as 8.26 for 223 systems in equilibrium-tide regime.
Found no significant dependence of $Q_s'$ on stellar temperature.
Predicted minimal transit timing variations for WASP-18 over 20 years.
Abstract
Transiting hot Jupiters occupy a wedge-shaped region in the mass ratio-orbital separation diagram. Its upper boundary is eroded by tidal spiral-in of massive, close-in planets and is sensitive to the stellar tidal dissipation parameter . We develop a simple generative model of the orbital separation distribution of the known population of transiting hot Jupiters, subject to tidal orbital decay, XUV-driven evaporation and observational selection bias. From the joint likelihood of the observed orbital separations of hot Jupiters discovered in ground-based wide-field transit surveys, measured with respect to the hyperparameters of the underlying population model, we recover narrow posterior probability distributions for in two different tidal forcing frequency regimes. We validate the method using mock samples of transiting planets with known tidal parameters. We find that…
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