The Quasar Catalogue for S-PLUS DR4 (QuCatS) and the estimation of photometric redshifts
This paper provides a catalogue of photometrically selected quasars with the photo-z predictions from three machine learning methods: Random Forest, Flexible Conditional Density Estimation (FlexCoDE), and Bayesian Mixture Density Network (BMDN). The catalogue provided with this work covers the S-PLUS DR4 area (∼3000 square degrees), containing 645 980, 244 912, 144 991 sources with the probability of being a quasar higher than, 80 per cent, 90 per cent, 95 per cent up to r < 21.3 and good photometry quality in the detection image. More quasar candidates can be retrieved from the S-PLUS data base by considering less restrictive selection criteria.
On the discovery of stars, quasars, and galaxies in the Southern Hemisphere with S-PLUS DR2
This paper provides a catalogue of stars, quasars, and galaxies for S-PLUS DR2 in the Stripe 82 region. We show that narrow-band photometry improve the classification performance. Moreover, we show that our classification is robust against missing values. In this paper, one can find a direct link to download the classification and probabilities for Stripe 82 S-PLUS DR. Classification and probabilities for all released S-PLUS fields up to this date are avaialble through https://splus.cloud (the documentation page in this website reports the updated classification performance for S-PLUS DR4).