The New Generation Planetary Population Synthesis (NGPPS)

Abstract

Context. State-of-the-art planet formation models are now capable of accounting for the full spectrum of known planet types. This comes at the cost of an increasing complexity of the models, which calls into question whether established links between their initial conditions and the calculated planetary observables are preserved. Aims. In this paper, we take a data-driven approach to investigate the relations between clusters of synthetic planets with similar properties and their formation history. Methods. We trained a Gaussian mixture model on typical exoplanet observables computed by a global model of planet formation to identify clusters of similar planets. We then traced back the formation histories of the planets associated with them and pinpointed their differences. Using the cluster affiliation as labels, we trained a random forest classifier to predict planet species from properties of the originating protoplanetary disk. Results. Without presupposing any planet types, we identified four distinct classes in our synthetic population. They roughly correspond to the observed populations of (sub-)Neptunes, giant planets, and (super-)Earths, plus an additional unobserved class we denote as “icy cores”. These groups emerge already within the first 0.1 Myr of the formation phase and are predicted from disk properties with an overall accuracy of >90%. The most reliable predictors are the initial orbital distance of planetary nuclei and the total planetesimal mass available. Giant planets form only in a particular region of this parameter space that is in agreement with purely analytical predictions. Including N-body interactions between the planets decreases the predictability, especially for sub-Neptunes that frequently undergo giant collisions and turn into super-Earths. Conclusions. The processes covered by current core accretion models of planet formation are largely predictable and reproduce the known demographic features in the exoplanet population. The impact of gravitational interactions highlights the need for N-body integrators for realistic predictions of systems of low-mass planets.

Discovery and mass measurement of the hot, transiting, Earth-sized planet GJ 3929 b

“…Sabotta et al 2021;Cloutier et al 2021). Moreover, combinations of terrestrial planets and sub-Neptunes are also commonly predicted by population synthesis models based on the core accretion paradigm of planet formation (Emsenhuber et al 2021;Schlecker et al 2021;Burn et al 2021). Following the angular momentum deficit stability criterium from Laskar & Petit (2017), the system would be stable for eccentricities of the outer companion candidate up to 0.45.…”

Discovery and mass measurement of the hot, transiting, Earth-sized planet, GJ 3929 b

“…Sabotta et al 2021;Cloutier et al 2021). Moreover, combinations of terrestrial planets and sub-Neptunes are also commonly predicted by population synthesis models based on the core accretion paradigm of planet formation (Emsenhuber et al 2021;Schlecker et al 2021;Burn et al 2021). Following the angular momentum deficit stability criterium from Laskar & Petit (2017), the system would be stable for eccentricities of the outer companion candidate up to 0.45.…”

Interpreting the Atmospheric Composition of Exoplanets: Sensitivity to Planet Formation Assumptions

“…Accounting for the effects of N-body interactions when trying to invert planet formation thus seems challenging. Interestingly, it has recently been shown that while N-body interactions tend to randomize the process of planet formation, machine-learning techniques such as random forests still allow us to predict the outcome of planet formation quite accurately (Schlecker et al 2021). In this work the authors show that the initial parameters of the planet formation model described in , mainly the initial location of the planetary embryo and the dust mass of the disk, may be used to predict which class a forming planet will belong to (super-Earths, Neptune-like, giant planets, etc.).…”

“…The distribution of bulk planetary properties such as mass, radius, and orbital parameters encodes critical information that constrains planet formation models (see, e.g., Ida & Lin 2004;Alibert et al 2005;Mordasini et al 2009;Hasegawa & Pudritz 2011;Lambrechts & Johansen 2012;Bitsch et al 2015;Nayakshin & Fletcher 2015;Cridland et al 2016;Schlecker et al 2021). In addition, the chemical composition of planet atmospheres has long been regarded as a key to unlocking the process of planet formation (e.g., Gautier & Owen 1989;Owen & Encrenaz 2003) and is the explicit goal of many atmospheric characterization studies (see, e.g., Madhusudhan 2019, for a recent review).…”