We present a catalogue of 73,221 white dwarf candidates extracted from the astrometric and photometric data of the recently published Gaia DR2 catalogue. White dwarfs were selected from the Gaia Hertzsprung-Russell diagram with the aid of the most updated population synthesis simulator. Our analysis shows that Gaia has virtually identified all white dwarfs within 100 pc from the Sun. Hence, our sub-population of 8,555 white dwarfs within this distance limit and the colour range considered, − 0.52 < (G BP − G RP ) < 0.80, is the largest and most complete volume-limited sample of such objects to date. From this sub-sample we identified 8,343 CO-core and 212 ONe-core white dwarf candidates and derived a white dwarf space density of 4.9±0.4×10 −3 pc −3 . A bifurcation in the Hertzsprung-Russell diagram for these sources, which our models do not predict, is clearly visible. We used the Virtual Observatory tool VOSA to derive effective temperatures and luminosities for our sources by fitting their spectral energy distributions, that we built from the UV to the NIR using publicly available photometry through the Virtual Observatory. From these parameters, we derived the white dwarf radii. Interpolating the radii and effective temperatures in hydrogen-rich white dwarf cooling sequences, we derived the surface gravities and masses. The Gaia 100 pc white dwarf population is clearly dominated by cool (∼ 8,000 K) objects and reveals a significant population of massive (M ∼ 0.8M ) white dwarfs, of which no more than ∼ 30−40 % can be attributed to hydrogen-deficient atmospheres, and whose origin remains uncertain.

Gaia-DR2 has provided an unprecedented number of white dwarf candidates of our Galaxy. In particular, it is estimated that Gaia-DR2 has observed nearly 400 000 of these objects and close to 18 000 up to 100 pc from the Sun. This large quantity of data requires a thorough analysis in order to uncover their main Galactic population properties, in particular the thin and thick disk and halo components. Taking advantage of recent developments in artificial intelligence techniques, we make use of a detailed Random Forest algorithm to analyse an 8-dimensional space (equatorial coordinates, parallax, proper motion components and photometric magnitudes) of accurate data provided by Gaia-DR2 within 100 pc from the Sun. With the aid of a thorough and robust population synthesis code we simulated the different components of the Galactic white dwarf population to optimize the information extracted from the algorithm for disentangling the different population components. The algorithm is first tested in a known simulated sample achieving an accuracy of 85.3%. Our methodology is thoroughly compared to standard methods based on kinematic criteria demonstrating that our algorithm substantially improves previous approaches. Once trained, the algorithm is then applied to the Gaia-DR2 100 pc white dwarf sample, identifying 12 227 thin disk, 1410 thick disk and 95 halo white dwarf candidates, which represent a proportion of 74:25:1, respectively. Hence, the numerical spatial densities are (3.6 ± 0.4) × 10 −3 pc −3 , (1.2 ± 0.4) × 10 −3 pc −3 and (4.8 ± 0.4) × 10 −5 pc −3 for the thin disk, thick disk and halo components, respectively. The populations thus obtained represent the most complete and volume-limited samples to date of the different components of the Galactic white dwarf population.

Context. The Ophiuchus cloud complex is one of the best laboratories to study the earlier stages of the stellar and protoplanetary disc evolution. The wealth of accurate astrometric measurements contained in the Gaia Data Release 2 can be used to update the census of Ophiuchus member candidates. Aims. We seek to find potential new members of Ophiuchus and identify those surrounded by a circumstellar disc. Methods. We constructed a control sample composed of 188 bona fide Ophiuchus members. Using this sample as a reference we applied three different density-based machine learning clustering algorithms (DBSCAN, OPTICS, and HDBSCAN) to a sample drawn from the Gaia catalogue centred on the Ophiuchus cloud. The clustering analysis was applied in the five astrometric dimensions defined by the three-dimensional Cartesian space and the proper motions in right ascension and declination. Results. The three clustering algorithms systematically identify a similar set of candidate members in a main cluster with astrometric properties consistent with those of the control sample. The increased flexibility of the OPTICS and HDBSCAN algorithms enable these methods to identify a secondary cluster. We constructed a common sample containing 391 member candidates including 166 new objects, which have not yet been discussed in the literature. By combining the Gaia data with 2MASS and WISE photometry, we built the spectral energy distributions from 0.5 µm to 22 µm for a subset of 48 objects and found a total of 41 discs, including 11 Class II and 1 Class III new discs. Conclusions. Density-based clustering algorithms are a promising tool to identify candidate members of star forming regions in large astrometric databases. By combining the Gaia data with infrared catalogues, it is possible to discover new protoplanetary discs. If confirmed, the candidate members discussed in this work would represent an increment of roughly 40 − 50% of the current census of Ophiuchus.

Aims. We analyzed the velocity space of the thin and thick-disk Gaia white dwarf population within 100 pc looking for signatures of the Hercules stellar stream. We aimed to identify those objects belonging to the Hercules stream and, by taking advantage of white dwarf stars as reliable cosmochronometers, to derive a first age distribution. Methods. We applied a kernel density estimation to the UV velocity space of white dwarfs. For the region where a clear overdensity of stars was found, we created a 5-D space of dynamic variables. We applied a hierarchichal clustering method, HDBSCAN, to this 5-D space, identifying those white dwarfs that share similar kinematic characteristics. Finally, under general assumptions and from their photometric properties, we derived an age estimate for each object. Results. The Hercules stream was firstly revealed as an overdensity in the UV velocity space of the thick-disk white dwarf population. Three substreams were then found: Hercules a and Hercules b, formed by thick-disk stars with an age distribution peaked 4 Gyr in the past and extended to very old ages; and Hercules c, with a ratio of 65:35 thin:thick stars and a more uniform age distribution younger than 10 Gyr