Initial conditions for the article "Influence of Stellar Dynamical Tides on Mean-Motion Resonances and Resonant Chain Stability"

This repository contains the initial conditions to reproduce the results of the article: "Influence of Stellar Dynamical Tides on Mean-Motion Resonances and Resonant Chain Stability". These simulations were done with Posidonius (https://github.com/DynaClim/posidonius) with version commit 491c643 (07/03/2025). The file initial_conditions.zip contains all simulations referenced in the paper, including the .json files used to initialize the simulations and the corresponding .py scripts that define the explicit system configurations and generate the .json files. To reproduce the results presented in Sec. 5, the simulations can be launched directly from the provided .json files by following the standard execution procedure described in Posidonius. Alternatively, the .json files can be regenerated using the supplied .py scripts. This regeneration step is only necessary if modifications have been made to the Posidonius source code. The simulations can be separated into three sets, including systems with single-planet in 5 Earth masses: Tidal model Stellar model $M_{\star} (M_\odot)$ $R_{\star} (R_\odot)$ $P_{\star, 0} (day)$ $M_{p} (M_\oplus)$ $R_{p} (R_\oplus)$ $a$ (AU) $e$ $dt$ 1 Kaula CTL G+17 1 evolving 1.91 5 1.57 0.03 0.00 0.1 Adaptive Set (1) corresponds to the simulations in single_planet directory: sma_03_kaula_outward sma_03_CTL_outward where the filenames encode the initial semi-major axis, the adopted stellar tidal model, and the direction of orbital migration. In all simulations, we adopted the symplectic WHFast (Rein & Tamayo 2015 [1]) integrator with a fixed time step $dt$. Only one specific case in set~(1) was computed using the non-symplectic IAS15 (Rein & Spiegel 2015 [2]) integrator with an adaptive time step. In addition, stellar wind torque was included in all simulations. We adopted the wind model of Bouvier et al. (1997) [3], with parameters calibrated to reproduce the present-day solar rotation rate. The specific parameter values can be found in the corresponding Python configuration files. For systems of two-planet: Tidal model$_{\star, p}$ Stellar model $P_{\star} (day)$ $P_{p_{1/2}} (day)$ MMR$_{1-2}$ $a_{1/2}$ (AU) $e_{1/2}$ $T_\text{mig}$ dt 2 Kaula/CTL G+17 6.0 Psuedo sync. 2:1 0.031/0.048 0.16/0.01 N/A 0.1 3 Kaula/CTL G+17 1.91 Psuedo sync. 2:1 3:2 4:3 0.031/0.048 0.036/0.047 0.036/0.043 0.16/0.01 0.04/0.03 0.04/0.03 N/A 5e3 5e3 0.1 4 Kaula/CTL G+17 1.2 Psuedo sync. 2:1 3:2 4:3 0.068/0.108 0.067/0.088 0.067/0.081 0.04/0.03 0.04/0.03 0.04/0.03 5e3 5e3 5e3 0.2 Set (2) - (4) corresponds to the simulations in two_planet directory: Set (2): sma_03_mmr_21_divergent Set (3): sma_03_mmr_21_convergent sma_03_mmr_32_convergent sma_03_mmr_43_convergent Set (4): sma_05_mmr_21_convergent sma_05_mmr_32_convergent sma_05_mmr_43_convergent where the filenames encode the initial semi-major axis, the associated MMR, and the migration type (divergent or convergent). For selected simulations, a temporary protoplanetary disk was included for a duration $T_\text{mig}$ to ensure that the planetary system was captured into the desired mean-motion resonance and anchored at the prescribed initial semi-major axis prior to tidal evolution. The specific disk parameters and implementation details are provided in the corresponding Python configuration files. Similarly, for systems of three-planet: Tidal model$_{\star, p}$ Stellar model $P_{\star} (day)$ $P_{p_{1/2/3}} (day)$ MMR$_{1-2/2-3}$ $a_{1/2/3}$ (AU) $e_{1/2}$ $T_\text{mig}$ dt 5 Kaula/CTL G+17 1.91 Psuedo sync. 2:1/2:1 2:1/3:2 3:2/3:2 0.031/0.049/0.078 0.031/0.049/0.064 0.031/0.041/0.053 0.16/0.01 0.04/0.03 0.04/0.03 5e2 5e2 1e3 0.1 6 Kaula/CTL G+17 1.2 Psuedo sync. 2:1/2:1 2:1/3:2 3:2/3:2 0.055/0.087/0.139 0.055/0.087/0.114 0.055/0.072/0.094 0.04/0.03 0.04/0.03 0.04/0.03 1.5e3 1.5e3 1.5e3 0.2 Set (5) - (6) corresponds to the simulations in three_planet directory: Set (5): sma_03_mmr_21_21_convergent sma_03_mmr_21_32_convergent sma_03_mmr_32_32_convergent Set (6): sma_05_mmr_21_21_convergent sma_05_mmr_21_32_convergent sma_05_mmr_32_32_convergent where the filenames encode the initial semi-major axis, the associated MMRs (resonant chain), and the migration type (all convergent). For the stellar evolution data, we adopted models computed with STAREVOL (Amard et al. 2016 [4]; Gallet et al. 2017 [5]), and improved the smoothness of the input profiles through linear interpolation. To reproduce the simulations exactly, the file M_10_Z_0134.dat included in this database should be replaced with the corresponding file located in posidonius/input/Gallet_Bolmont_2017, as provided in the standard Posidonius installation. Please make sure to run pip install . in the terminal before launching a new simulation with the code. The tidal spectrum data are provided in the archive stellar_love_number.zip. These data are also distributed with the standard Posidonius installation under /input/love_numbers/Kwok_et_al_2026. They are included here for completeness and for users who wish to access the spectra independently. The tidal spectra are named according to the stellar structural and rotational parameters. For example, in the file alpha0.51600_P8p0_Ek1em5.txt, alpha denotes the stellar aspect ratio in radius, $R_{\star,\text{core}}/R_\star$, P denotes the stellar spin period (in days) adopted for computing the spectrum ($P_{\star,\text{spec}}$), and Ek denotes the Ekman number. To use a different spectrum in the simulations, users must set the parameter spectrum_stellar_spin_period in the corresponding .py configuration files to match the value of P before generating the .json files that initiate the simulations. The file results.zip contains all the raw simulation data (files named *_history.bin),as running the code itself can be computationally expensive prior to further optimization. Please follow the instructions on GitHub to run the analysis scripts or to generate your own data.