Using autoencoders and deep transfer learning to determine the stellar parameters of 286 CARMENES M dwarfs

Open Access

Table 4

Mean difference ( $\bar{Δ}$ $\bar \Delta$ ; literature–this work), root mean square error (rmse), and Pearson correlation coefficient (r_p) for the comparison between our results and the literature.

Reference	T_eff (K)			log g (dex)			[Fe/H] (dex)			υ sin i (km s⁻¹ )
	$\bar{Δ}$ $\bar \Delta$	rmse	r_p	$\bar{Δ}$ $\bar \Delta$	rmse	r_p	$\bar{Δ}$ $\bar \Delta$	rmse	r_p	$\bar{Δ}$ $\bar \Delta$	rmse	r_p
Bello23	−117	180	0.87	…	…	…	0.01	0.14	0.60	…	…	…
Mar21	−19	102	0.94	0.12	0.18	0.39	−0.11	0.16	0.65	…	…	…
Pass19	−80	117	0.96	0.00	0.05	0.86	0.06	0.15	0.52	…	…	…
Pass20	−35	51	0.99	−0.04	0.06	0.93	0.23	0.25	0.76	1.64	1.94	0.99
Rein 18^(a)	…	…	…	…	…	…	…	…	…	−0.86	1.51	0.98
Schw19	−40	93	0.96	0.13	0.14	0.89	0.00	0.10	0.63	…	…	…

Notes. ^(a)From Reiners et al. (2018).

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.