Modelling the Milky Way’s exoplanet population based on cosmological galaxy simulations

¹ Departament de Física Quàntica i Astrofísica (FQA), Universitat de Barcelona (UB), Martí i Franquès 1, 08028 Barcelona, Spain
² Institut de Ciències del Cosmos (ICCUB), Universitat de Barcelona (UB), Martí i Franquès 1, 08028 Barcelona, Spain
³ Institut d’Estudis Espacials de Catalunya (IEEC), Edifici RDIT, Campus UPC, 08860 Castelldefels (Barcelona), Spain
⁴ Observatori Fabra, Reial Acadèmia de Ciències i Arts de Barcelona, Rambla dels Estudis, 115, 08002 Barcelona, Spain
⁵ Department of Astronomy, School of Physics and Astronomy, Shanghai Jiao Tong University, 800 Dongchuan Road, Shanghai 200240, China
⁶ State Key Laboratory of Dark Matter Physics, School of Physics and Astronomy, Shanghai Jiao Tong University, Shanghai 200240, China
⁷ Observatório Nacional, MCTI, Rua Gal. José Cristino 77, Rio de Janeiro 20921-400, RJ, Brasil
⁸ Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK
⁹ Universidade Federal de Sergipe, Av. Marechal Rondon, S/N, 49000-000 São Cristóvão, SE, Brazil
¹⁰ Mullard Space Science Laboratory, University College London, Holmbury St. Mary, Dorking, Surrey RH5 6NT, UK
¹¹ National Astronomical Observatory of Japan, 2-21-1 Osawa, Mitaka, Tokyo 181-8588, Japan
¹² Laboratòrio Nacional de Astrofísica, Rua Estados Unidos 154, 37504-364 Itajubá, MG, Brazil
¹³ Instituto Nacional de Pesquisas Espaciais/MCTI, Av. dos Astronautas 1758, São José dos Campos, SP, Brazil

^★ Corresponding author: This email address is being protected from spambots. You need JavaScript enabled to view it.

Received: 31 August 2025
Accepted: 13 November 2025

Abstract

Context. Exoplanet transit and radial-velocity surveys have allowed us to explore the exoplanet population in our Galactic surroundings. The planet populations in more remote areas of the Milky Way (MW) will become accessible with future instrumentation.

Aims. In this paper, we aim to simulate realistic exoplanet populations across different regions of the MW by combining state-of-the-art cosmological simulations of our Galaxy with exoplanet formation models and observations.

Methods. We model the exoplanet populations around simulated single stars, using planet occurrence rate and multiplicity depending on stellar mass, metallicity, and planet type, and assign them physical parameters such as mass and orbital period.

Results. Focussing first on the solar vicinity, we find mostly metallicity-driven differences in the distributions of non-hosting and planet-hosting single stars. In our simulated solar neighbourhood, 52.5% of all planets are Earth-like (23% of them located in the Habitable Zone), 44% are super-Earths or Neptunes, and 3.5% are giant planets. A detailed comparison with the census of Kepler exoplanets and candidates shows that, when taking into account the most relevant selection effects, we obtain a similar distribution of exoplanets compared to the observed population. However, we also detect some significant differences in the exoplanet and host star distributions (e.g. more planets around F-type and red-giant stars compared to the observations) that we attribute mostly to a too strong recent star formation and a too large disc scale height in the simulation compared to the solar neighbourhood, as well as to some caveats in our exoplanet population synthesis that will be addressed in future work. Extending our analysis to other regions of the simulated MW and to other galaxies within the same suite of simulations, we find that the relative percentages of Earth-like, super-Earth or Neptunes, and giant planets remain largely consistent as long as the simulated galaxy matches the morphology and mass of the MW.

Conclusions. We have created a fast and flexible framework to produce exoplanet populations based on MW-like simulations that can easily be adapted to produce predictions for the yields of future exoplanet detection missions.