Context. Gravitational waves from black-hole (BH) merging events have revealed a population of extra-galactic BHs residing in short-period binaries with masses that are higher than expected based on most stellar evolution models – and also higher than known stellar-origin black holes in our Galaxy. It has been proposed that those high-mass BHs are the remnants of massive metal-poor stars. Aims. Gaia astrometry is expected to uncover many Galactic wide-binary systems containing dormant BHs, which may not have been detected before. The study of this population will provide new information on the BH-mass distribution in binaries and shed light on their formation mechanisms and progenitors. Methods. As part of the validation efforts in preparation for the fourth Gaia data release (DR4), we analysed the preliminary astrometric binary solutions, obtained by the Gaia Non-Single Star pipeline, to verify their significance and to minimise false-detection rates in high-mass-function orbital solutions. Results. The astrometric binary solution of one source, Gaia BH3, implies the presence of a 32.70 ± 0.82 M_⊙ BH in a binary system with a period of 11.6 yr. Gaia radial velocities independently validate the astrometric orbit. Broad-band photometric and spectroscopic data show that the visible component is an old, very metal-poor giant of the Galactic halo, at a distance of 590 pc. Conclusions. The BH in the Gaia BH3 system is more massive than any other Galactic stellar-origin BH known thus far. The low metallicity of the star companion supports the scenario that metal-poor massive stars are progenitors of the high-mass BHs detected by gravitational-wave telescopes. The Galactic orbit of the system and its metallicity indicate that it might belong to the Sequoia halo substructure. Alternatively, and more plausibly, it could belong to the ED-2 stream, which likely originated from a globular cluster that had been disrupted by the Milky Way.

Context.Gaiahas been in operations since 2014, and two full data releases (DR) have been delivered so far: DR1 in 2016 and DR2 in 2018. The thirdGaiadata release expands from the early data release (EDR3) in 2020, which contained the five-parameter astrometric solution and mean photometry for 1.8 billion sources by providing 34 months of multi-epoch observations that allowed us to systematically probe, characterise, and classify variable celestial phenomena.Aims.We present a summary of the variability processing and analysis of the photometric and spectroscopic time series of 1.8 billion sources carried out forGaiaDR3.Methods.We used statistical and machine learning methods to characterise and classify the variable sources. Training sets were built from a global revision of major published variable star catalogues. For a subset of classes, specific detailed studies were conducted to confirm their class membership and to derive parameters that are adapted to the peculiarity of the considered class.Results.In total, 10.5 million objects are identified as variable inGaiaDR3 and have associated time series inG,G_BP, andG_RPand, in some cases, radial velocity time series. The DR3 variable sources subdivide into 9.5 million variable stars and 1 million active galactic nuclei or ‘quasars’. In addition, supervised classification identified 2.5 million galaxies thanks to spurious variability induced by the extent of these objects. The variability analysis output in the DR3 archive amounts to 17 tables, containing a total of 365 parameters. We publish 35 types and subtypes of variable objects. For 11 variable types, additional specific object parameters are published. Here, we provide an overview of the estimated completeness and contamination of most variability classes.Conclusions.Thanks toGaia, we present the largest whole-sky variability analysis based on coherent photometric, astrometric, and spectroscopic data. FutureGaiadata releases will more than double the span of time series and the number of observations, allowing the publication of an even richer catalogue.

Context.GaiaDR3 contains 1.8 billion sources withG-band photometry, 1.5 billion of which withG_BPandG_RPphotometry, complemented by positions on the sky, parallax, and proper motion. The median number of field-of-view transits in the three photometric bands is between 40 and 44 measurements per source and covers 34 months of data collection.Aims.We pursue a classification of Galactic and extra-galactic objects that are detected as variable byGaiaacross the whole sky.Methods.Supervised machine learning (eXtreme Gradient Boosting and Random Forest) was employed to generate multi-class, binary, and meta-classifiers that classified variable objects with photometric time series in theG,G_BP, andG_RPbands.Results.Classification results comprise 12.4 million sources (selected from a much larger set of potential variable objects) and include about 9 million variable stars classified into 22 variability types in the Milky Way and nearby galaxies such as the Magellanic Clouds and Andromeda, plus thousands of supernova explosions in distant galaxies, 1 million active galactic nuclei, and almost 2.5 million galaxies. The identification of galaxies was made possible by the artificial variability of extended objects as detected byGaia, so they were published in thegalaxy_candidatestable of theGaiaDR3 archive, separate from the classifications of genuine variability (in thevari_classifier_resulttable). The latter contains 24 variability classes or class groups of periodic and non-periodic variables (pulsating, eclipsing, rotating, eruptive, cataclysmic, stochastic, and microlensing), with amplitudes from a few milli-magnitudes to several magnitudes.

Context. The third Gaia Data Release covers 34 months of data and includes the second Gaia catalogue of long-period variables (LPVs), with G variability amplitudes larger than 0.1 mag (5–95% quantile range). Aims. The paper describes the production and content of the second Gaia catalogue of LPVs and the methods we used to compute the published variability parameters and identify C-star candidates. Methods. We applied various filtering criteria to minimise contamination from variable star types other than LPVs. The period and amplitude of the detected variability were derived from model fits to the G-band light curve wherever possible. C stars were identified using their molecular signature in the low-resolution RP spectra. Results. The catalogue contains 1 720 558 LPV candidates, including 392 240 stars with published periods (ranging from 35 to ∼1000 days) and 546 468 stars classified as C-star candidates. Comparison with literature data (OGLE and ASAS-SN) leads to an estimated completeness of 80%. The recovery rate is about 90% for the most regular stars (typically miras) and 60% for SRVs and irregular stars. At the same time, the number of known LPVs is increased by a factor of 6 with respect to literature data for amplitudes larger than 0.1 mag in G, and the contamination is estimated to be below 2%. Our C-star classification, based on solid theoretical arguments, is consistent with spectroscopically identified C stars in the literature. Caution must be taken in crowded regions, however, where the signal-ro-noise ratio of the RP spectra can become very low, or if the source is reddened by some kind of extinction. The quality and potential of the catalogue are illustrated by presenting and discussing LPVs in the solar neighbourhood, in globular clusters, and in galaxies of the Local Group. Conclusions. This is the largest all-sky LPVs catalogue to date. The photometric depth reaches G = 20 mag. This is a unique dataset for research into the late stages of stellar evolution.

We have computed, based on 17 infrared radial velocities, the first set of orbital elements for the M giant in the symbiotic binary V2116 Ophiuchi. The giant's companion is a neutron star, the bright X-ray source GX 1+4. We find an orbital period of 1161 days by far the longest of any known X-ray binary. The orbit has a modest eccentricity of 0.10 with an orbital circularization time of less than 10^6 years. The large mass function of the orbit significantly restricts the mass of the M giant. Adopting a neutron-star mass of 1.35M(Sun), the maximum mass of the M giant is 1.22M(Sun), making it the less massive star. Derived abundances indicate a slightly subsolar metallicity. Carbon and nitrogen are in the expected ratio resulting from the red-giant first dredge-up phase. The lack of O-17 suggests that the M-giant has a mass less than 1.3M(Sun), consistent with our maximum mass. The red giant radius is 103R(Sun), much smaller than the estimated Roche lobe radius. Thus, the mass loss of the red giant is via a stellar wind. Although the M giant companion to the neutron star has a mass similar to the late-type star in low-mass X-ray binaries, its near-solar abundances and apparent runaway velocity are not fully consistent with the properties of this class of stars.Comment: In press to The Astrophysical Journal (10 April 2006 issue). 23 page

Astronomy & Astrophysics (A&A) is an international journal which publishes papers on all aspects of astronomy and astrophysics