Extrasolar planet population synthesis II: Statistical comparison with observation
Christoph Mordasini, Yann Alibert, Willy Benz, Dominique Naef

TL;DR
This paper compares synthetic exoplanet populations with observed data using statistical tests, validating models of planet formation and predicting future discoveries as detection methods improve.
Contribution
It introduces a statistical framework for comparing synthetic and observed exoplanet populations, validating planet formation models and predicting undetected planets.
Findings
Some models match observed properties reasonably well.
The detected planets are just a small fraction of the total population.
Predictions for future survey capabilities and undetected planets.
Abstract
This is the second paper in a series of papers showing the results of extrasolar planet population synthesis calculations. In the companion paper (Paper I), we have presented in detail our methods. By applying an observational detection bias for radial velocity surveys, we identify the potentially detectable synthetic planets. The properties of these planets are compared in quantitative statistical tests with the properties of a carefully selected sub-population of actual exoplanets. We use a two dimensional Kolmogorov-Smirnov test to compare the mass-distance distributions of synthetic and observed planets, as well as 1D KS tests to compare the mass, the semimajor axis and the [Fe/H] distributions. We find that some models can account to a reasonable degree of significance for the observed properties. We concurrently account for many other observed features, e.g. the "metallicity…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsStellar, planetary, and galactic studies · Astronomy and Astrophysical Research · Scientific Research and Discoveries
