Catalogue of new Herbig Ae/Be and classical Be stars

Abstract

Context. The intermediate-mass pre-main sequence Herbig Ae/Be stars are key to understanding the differences in formation mechanisms between low- and high-mass stars. The study of the general properties of these objects is hampered by the lack of a well-defined, homogeneous sample, and because few and mostly serendipitously discovered sources are known. Aims. Our goal is to identify new Herbig Ae/Be candidates to create a homogeneous and well defined catalogue of these objects. Methods. We have applied machine learning techniques to 4 150 983 sources with data from Gaia DR2, 2MASS, WISE, and IPHAS or VPHAS+. Several observables were chosen to identify new Herbig Ae/Be candidates based on our current knowledge of this class, which is characterised by infrared excesses, photometric variabilities, and Hα emission lines. Classical techniques are not efficient for identifying new Herbig Ae/Be stars 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 new classical Be stars. Results. We have obtained a large catalogue of 8470 new pre-main sequence candidates and another catalogue of 693 new classical Be candidates with a completeness of 78.8 ± 1.4% and 85.5 ± 1.2%, respectively. Of the catalogue of pre-main sequence candidates, at least 1361 sources are potentially new Herbig Ae/Be candidates according to their position in the Hertzsprung-Russell diagram. In this study we present the methodology used, evaluate the quality of the catalogues, and perform an analysis of their flaws and biases. For this assessment, we make use of observables that have not been accounted for by the algorithm and hence are selection-independent, such as coordinates and parallax based distances. The catalogue of new Herbig Ae/Be stars that we present here increases the number of known objects of the class by an order of magnitude.

Kinematic Properties of Open Star Clusters with Data from the Gaia DR2 Catalogue

“…The PMS sample consists of 8470 candidates for young pre-main-sequence stars. The completeness of this sample was estimated in [12] to be 78.8%, and its members are both Herbig Ae/Be and T Tauri stars. Out of the above three samples, this is the richest in stars and, therefore, in this paper it is the main one for our kinematic analysis.…”

“…The selection of young stars in [12] was made using machine learning techniques based on data from the Gaia DR2 catalogue by invoking infrared 2MASS, WISE, IPHAS, and VPHAS+ photometric measurements. A total of 4 150 983 objects were identified by them.…”

“…Note that an analysis of 48 photometric differences provides a basis for the classification selection of stars in [12]. They were calculated using data from the Gaia DR2 catalogue, where the photometric G BP , G and G RP bands have mean wavelengths of 0.50, 0.59, and 0.77 µm, respectively, the and bands from the IPHAS and VPHAS+ catalogues have 0.62 and 0.66 µm, respectively, the J, H, and K s bands from the 2MASS catalogue have 1.24, 1.66, and 2.16 µm, respectively, and the W1, W2, W3 and W4 bands from the WISE catalogue have 3.4, 4.6, 12, and 22 µm, respectively.…”

“…In this paper we usually calculate the distances via the trigonometric parallaxes. However, apart from the Gaia DR2 parallaxes, the distances calculated in [27] by taking into account the peculiarities in the distribution of stars in the Galaxy are given in [12]. This method is similar to the correction for the Lutz-Kelker bias [28], which can be taken into account at large relative parallax errors.…”

“…The goal of this paper is to refine the Galactic rotation parameters based on the sample of young stars from [12] and to determine the parameters of the residual velocity ellipsoid for these stars. Only multiband photometry was used in [12] for the selection of stars and, therefore, confirming the youth of these stars based on a kinematic analysis is a topical problem.…”