Gaia 500-pc white dwarf population

The classified sample is compared with other already published catalogs and with our own higher resolution Gran Telescopio Canarias (GTC) spectra, enabling the construction of a golden sample of well-classified objects. The Random Forest spectral classification of the 500-pc white dwarf population achieves an excellent global accuracy of 0.91 and an F1-score of 0.88 for the DA versus non-DA classification. In addition, we obtain a very high accuracy of 0.76 and a global F1-score of 0.62 for the non-DA subtype classification.

In particular, our classification shows an excellent recall for DAs, DBs and DCs (>90%), and a very good precision (>=80%) for DQs, DZs and DOs. Unfortunately, our algorithm does not perform well in correctly classifying subtypes given the low resolution of the Gaia spectra. The use of machine learning techniques, particularly the Random Forest algorithm, has enabled us to spectrally classify 78920 white dwarfs - an increase of 543.6% over those previously labeled - with reasonable accuracy.

Having an estimate of the spectral type for the vast majority of white dwarfs up to 500pc provides the possibility of making better estimates of cooling ages, star formation rates, and stellar evolution processes, among other fundamental aspects for the study of the white dwarf population.