NeuralCMS: A deep learning approach to study Jupiter’s interior

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Table B.1.

Parameter range of the training and validation datasets.

Parameter	Lower value	Upper value	Observation
Y_proto	0.270	0.286	0.278 ± 0.006^a
T_1bar (K)	159	190	166.1 ± 0.8^b; 170.3 ± 3.8^c
Z₁	0.005	0.06	$\approx 0.046 = 3 Z_{protosolar}^{d}$ $\approx0.046=3Z_{\mathrm{protosolar}}^{d}$
P₁₂ (Mbar)	0.5	5
m_dilute	0.11	0.6
Z_dilute	0.01	0.45
r_core (r/R_J)	0	0.12

J₂ × 10⁶	10632	16452	14696.5735 ± 0.0017^e
J₄ × 10⁶	−696.5	−369.5	−586.6085 ± 0.0024^e
J₆ × 10⁶	19.92	42.37	34.2007 ± 0.0067^e
J₈ × 10⁶	−3.151	−1.356	−2.422 ± 0.021^e
Mass (10²⁷ kg)	1.732	2.590	1.8983 ± 0.0005^f

Notes. In all models we kept Z₁ ≤ Z_dilute. The lower part of the table shows the model outputs. ^(a)Serenelli & Basu (2010), ^(b)Seiff et al. (1998), ^(c)Gupta et al. (2022), ^(d)Howard et al. (2023a), ^(e)Durante et al. (2020), ^(f)see Sect. 2.

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