Planetary Population Synthesis View Full Text


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Chapter Info

DATE

2018-11-03

AUTHORS

Christoph Mordasini

ABSTRACT

In stellar astrophysics, the technique of population synthesis has been successfully used for several decades. For planets, it is in contrast still a young method which only became important in recent years because of the rapid increase of the number of known extrasolar planets and the associated growth of statistical observational constraints. With planetary population synthesis, the theory of planet formation and evolution can be put to the test against these constraints. In this review of planetary population synthesis, we first briefly list key observational constraints. Then, the workflow in the method and its two main components are presented, namely, global end-to-end models that predict planetary system properties directly from protoplanetary disk properties and probability distributions for these initial conditions. An overview of various population synthesis models in the literature is given. The sub-models for the physical processes considered in global models are described: the evolution of the protoplanetary disk, planets’ accretion of solids and gas, orbital migration, and N-body interactions among concurrently growing protoplanets. Next, typical population synthesis results are illustrated in the form of new syntheses obtained with the latest generation of the Bern model. Planetary formation tracks, the distribution of planets in the mass-distance and radius-distance plane, the planetary mass function, and the distributions of planetary radii, semimajor axes, and luminosities are shown, linked to underlying physical processes, and compared with their observational counterparts. We finish by highlighting the most important predictions made by population synthesis models and discuss the lessons learned from these predictions – both those later observationally confirmed and those rejected. More... »

PAGES

2425-2474

Book

TITLE

Handbook of Exoplanets

ISBN

978-3-319-55332-0
978-3-319-55333-7

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-319-55333-7_143

DOI

http://dx.doi.org/10.1007/978-3-319-55333-7_143

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1107988006


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