Date: September 24, 2020, 12:45 (Santiago, Chile)
Speaker: , Herbig Ae/Be stars are high-mass Pre-Main Sequence objects which are key to understanding the formation mechanisms of high-mass stars and the evolution of their protoplanetary discs. Historically, the study of the general properties of these objects has been hampered by the lack of a well-defined, homogeneous sample, and because few and mostly serendipitously discovered sources were known. As a consequence, many open problems involving high-mass star formation suffer from biases and lack of completeness. Applying Machine Learning techniques to Gaia DR2 data we have constructed a large and homogeneous catalogue of Pre-Main Sequence stars with, at least, 1361 new Herbig Ae/Be candidates. Classical techniques are not efficient for identifying these objects mainly because of their similarity with classical Be stars, with which they share many characteristics. By focusing on disentangling these two types of objects, our algorithm has also identified 693 new classical Be stars. This catalogue of new high-mass Pre-Main Sequence stars increases the number of known objects of the class by an order of magnitude. In this talk, I discuss the methodology used and the general properties of the new sources. Furthermore, I present the results of independent spectroscopic observations conducted for a selection of 145 new Herbig Ae/Be and 14 new classical Be stars.