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.

We present coordinated multiwavelength observations of the bright, nearby BL Lacertae object Mrk 421 taken in 2013 January–March, involving GASP-WEBT, Swift, NuSTAR, Fermi-LAT, MAGIC, VERITAS, and other collaborations and instruments, providing data from radio to very high energy (VHE) γ-ray bands. NuSTAR yielded previously unattainable sensitivity in the 3–79 keV range, revealing that the spectrum softens when the source is dimmer until the X-ray spectral shape saturates into a steep power law, with no evidence for an exponential cutoff or additional hard components up to ∼80 keV. For the first time, we observed both the synchrotron and the inverse-Compton peaks of the spectral energy distribution (SED) simultaneously shifted to frequencies below the typical quiescent state by an order of magnitude. The fractional variability as a function of photon energy shows a double-bump structure that relates to the two bumps of the broadband SED. In each bump, the variability increases with energy, which, in the framework of the synchrotron self-Compton model, implies that the electrons with higher energies are more variable. The measured multi band variability, the significant X-ray-to-VHE correlation down to some of the lowest fluxes ever observed in both bands, the lack of correlation between optical/UV and X-ray flux, the low degree of polarization and its significant (random) variations, the short estimated electron cooling time, and the significantly longer variability timescale observed in the NuSTAR light curves point toward in situ electron acceleration and suggest that there are multiple compact regions contributing to the broadband emission of Mrk 421 during low-activity states.

Since the launch of the Fermi satellite, BL Lacertae has been moderately active at γ-rays and optical frequencies until 2011 May, when the source started a series of strong flares. The exceptional optical sampling achieved by the GLAST–AGILE Support Program of the Whole Earth Blazar Telescope in collaboration with the Steward Observatory allows us to perform a detailed comparison with the daily γ-ray observations by Fermi. Discrete correlation analysis between the optical and γ-ray emission reveals correlation with a time lag of 0 ± 1 d, which suggests cospatiality of the corresponding jet emitting regions. A better definition of the time lag is hindered by the daily gaps in the sampling of the extremely fast flux variations. In general, optical flares present more structure and develop on longer time-scales than corresponding γ-ray flares. Observations at X-rays and at millimetre wavelengths reveal a common trend, which suggests that the region producing the mm and X-ray radiation is located downstream from the optical and γ-ray-emitting zone in the jet. The mean optical degree of polarization slightly decreases over the considered period and in general it is higher when the flux is lower. The optical electric vector polarization angle (EVPA) shows a preferred orientation of about 15°, nearly aligned with the radio core EVPA and mean jet direction. Oscillations around it increase during the 2011–2012 outburst. We investigate the effects of a geometrical interpretation of the long-term flux variability on the polarization. A helical magnetic field model predicts an evolution of the mean polarization that is in reasonable agreement with the observations. These can be fully explained by introducing slight variations in the compression factor in a transverse shock waves model.

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.