Introduction
Understanding
planetary formation is principally a theoretical task. However, the
relevant processes that occur during this phase are poorly constrained,
from how solids grow from dust to Earth-like planets or cores of giant
planets, to how planetary migration affects the architecture of the
systems. To determine if these model represent the reality, we need to
compare them with observations.
Planetary formation and evolution
models have many unknowns. As individual systems of extrasolar planets
provide a low number of data, the comparison has to be performed at the
population level to provide meaningful constraints on the models. Here,
we present a framework for this purpose. It encompasses the Bern global
model of planetary formation and evolution, the distribution of
protoplanetary disc properties to perform planetary population
synthesis, and the comparison of the synthetic planetary population with
the combined Coralie-HARPS GTO survey [1].
Methodology
The Generation III Bern model is a global model of planetary formation and evolution [2]. It tracks the relevant processes that occur during the formation and evolution of planetary systems.
The
formation stage tracks the evolution of a viscous accretion disc, whose
viscosity is provided by the standard α-parametrisation. Solids are
represented by planetesimals, whose dynamical state is given by the drag
from the gas and the stirring from the other planetesimals and the
growing protoplanets.
A fixed number of protoplanetary seeds
(1-100) are placed at the beginning of the formation. These protoplanets
accrete planetesimals from the disc and cores of other protoplanets
core upon collision. The gaseous envelope's structure is retrieved by
solving the standard 1D internal structure equations. They allow to
retrieve the envelope mass and the gas accretion rate (in the attached
phase), or the radius (in the detached phase). The formation stages also
include gas-driven planetary migration and the gravitational
interactions between the protoplanets by means on an N-body.
Once
the formation stage is finished, the model transitions to the
evolutionary phase, where planets are followed individually to 10 Gyr.
The planetary evolution model includes thermodynamical evolution
(cooling and contraction), atmospheric escape, bloating, and migration
due to tides raised on the star.
This model is used to compute a
synthetic population of planetary systems. Observational data are used
to constrain the initial conditions of the protoplanetary disc: their
mass, metallicities (i.e. dust to gas ratio), radial extend and life
times [3]. We selected the same number of systems as in the
combined Coralie-HARPS GTO survey sample (822) so that we can also
compare the absolute number of planets. We assume that each system is
observed from a random direction to compute the inclination of the orbit
of each planet. This enables to compute the effective mass Msin(i) of
the planet. The detection probability of each planet is computed from
completeness curves of the survey [1].
Results
In
the synthetic population, we detect 317 planets while 161 planets were
detected in the actual combined Coralie-HARPS sample. Hence, the model
forms about twice the number of planets that are observed. Nevertheless,
the multiplicity (i.e. the mean number of planets per system) is
similar in the two populations: The 317 synthetic planets are found
around 204 stars, while the actually observed 161 planets are
distributed in 102 systems. this indicates that the system architectures
are more similar than the absolute frequencies.
The
mass-period diagram (Figure 1) shows the planets in the synthetic
population (black circles) and the ones found in the Coralie-HARPS
survey (red circles). The two populations have similar clusters on super
Earths at about 10 days and giant planets at about 1000 days. However,
the synthetic planets are more concentrated in these regions and there
are relatively few synthetic planets in between or hot-Jupiters.
The
mass histogram (Figure 2) shows for the synthetic population (black),
the observed sample (red), and the synthetic population scaled so that
it has the same total value as the observed sample (blue). It reveals
that both super-Earths and giant are too numerous in the synthetic
population. However, there is disproportionately more giant planets
coupled to a lack of Saturn-mass planets in the synthetic population.
Discussion
The
whole framework provides a powerful framework to quantitatively
constrain models of planetary formation and evolution. We obtained that
our model [2] is too efficient by a factor two in absolute
terms, although the mean multiplicity is similar in the two samples
(synthetic and observed). This excess of planets is caused by an
overabundance of giant planets coupled with a relative lack of planets
at intermediate masses (20 to 200 MEarth), which suggest that the gas accretion rate in our model is too high.
It
is possible to statistically compare many more quantities, such as
eccentricity or stellar parameter like its metallicity to see if the
metallicity effect (e.g., [4]) is retrieved in the synthetic
population. Also, different system architectures or (anti)correlated
occurrence of different planet types can be compared. We will present
these results during the conference.
In case the synthetic
population does not retrieve the trends of the observed sample, it means
that the formation model needs to be modified. Once the observed
population can be satisfactorily reproduced, we can 1) determine how the
physical processes work to form exoplanetary systems and 2) make
predictions about the underlying population.
Our global model
predicts the quantities necessary for comparison with different
observational techniques, such as radius for transits and luminosity for
direct imaging. We have parallel efforts to perform comparison with
other surveys, such as Kepler [5,6] or SPHERE [7].
References
[1] Mayor, M. et al. arXiv:1109.2497 (2011)
[2] Emsenhuber, A., Mordasini, C., Burn, R., Alibert, Y., Benz, W., and Asphaug, E.: NGPPS I. A&A (subm.)
[3] Emsenhuber, A., Mordasini, C., Burn, R., Alibert, Y., Benz, W., and Asphaug, E.: NGPPS II. A&A (in prep.)
[4] Adibekyan, V. Geosciences, 9, 105 (2019).
[5] Mulders, G. D. et al. ApJ, 887, 157 (2019).
[6] Mishra, L. et al. EPSC abstract (2020)
[7] Vigan, A. et al. A&A (subm.)