From: Machine learning applied to simulations of collisions between rotating, differentiated planets
Parameter | Range | Unit | Description |
---|---|---|---|
\(M_{\mathrm{tot}}\) | 0.1–2 | \(\mathrm{M}_{\oplus }\) | Total mass (\(M_{\mathrm{targ}} + M_{\mathrm{proj}}\)) |
γ | 0.1–1 | – | Mass ratio (\(M_{\mathrm{proj}} \div M_{\mathrm{targ}}\)) |
\(b_{\infty }\) | 0–1 | \(\mathrm{R}_{\mathrm{grav}}\) | Asymptotic impact parameter |
\(v_{\infty }\) | 0.1–10 | \(\mathrm{v}_{\mathrm{esc}}\) | Asymptotic impact velocity |
\(F^{\mathrm{core}}_{\mathrm{targ}}\) | 0.1–0.9 | – | Target core mass fraction |
\(\Omega _{\mathrm{targ}}\) | 0–0.9 | \(\Omega _{\mathrm{crit}}\) | Target rotation rate |
\(\theta _{\mathrm{targ}}\) | 0–180 | deg | Target obliquity |
\(\phi _{\mathrm{targ}}\) | 0–360 | deg | Target azimuth |
\(F^{\mathrm{core}}_{\mathrm{proj}}\) | 0.1–0.9 | – | Projectile core mass fraction |
\(\Omega _{\mathrm{proj}}\) | 0–0.9 | \(\Omega _{\mathrm{crit}}\) | Projectile rotation rate |
\(\theta _{\mathrm{proj}}\) | 0–180 | deg | Projectile obliquity |
\(\phi _{\mathrm{proj}}\) | 0–360 | deg | Projectile azimuth |