Grid-based exoplanet atmospheric mass-loss predictions via neural networks

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Volume 694 (February 2025)

A&A, 694 (2025) A88

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Table 2

Parameters of the planets employed to test the impact of different mass-loss prescriptions on atmospheric evolution.

N_sim	M_*	$T_{eq}^{()}$ $T_{{\rm{eq}}}^{()}$	a	$M_{pl}^{0}$ $M_{{\rm{pl}}}^0$	$f_{at}^{0}$ $f_{{\rm{at}}}^0$
	(M_⊙)	(K)	(AU)	(M_⊕)
1	0.9	500	0.2689	5	0.064
2	0.9	500	0.2689	9	0.116
3	0.9	500	0.2689	17	0.200
4	0.9	500	0.2689	30	0.300
5	0.9	1000	0.0672	5	0.026
6	0.9	1000	0.0672	9	0.050
7	0.9	1000	0.0672	17	0.098
8	0.9	1000	0.0672	30	0.165
9	0.9	1700	0.0233	5	0.010
10	0.9	1700	0.0233	9	0.025
11	0.9	1700	0.0233	17	0.050
12	0.9	1700	0.0233	30	0.090
13	0.7	1700	0.0113	5	0.010
14	0.7	1700	0.0113	9	0.025
15	0.7	1700	0.0113	17	0.050
16	0.7	1700	0.0113	30	0.090
17	0.5	500	0.0603	5	0.064
18	0.5	500	0.0603	9	0.116
19	0.5	500	0.0603	17	0.200
20	0.5	500	0.0603	30	0.300
21	0.5	1000	0.0151	5	0.026
22	0.5	1000	0.0151	9	0.050
23	0.5	1000	0.0151	17	0.098
24	0.5	1000	0.0151	30	0.165
25	0.5	1000	0.0151	17	0.196

Notes. ^(*)T_eq values are given as an average value as the actual values of T_eq vary across planetary evolution according to the stellar L_bol input.

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