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. The third Gaia Data Release (DR3) provided photometric time series of more than 2 million long-period variable (LPV) candidates. Anticipating the publication of full radial-velocity data planned with Data Release 4, this Focused Product Release (FPR) provides radial-velocity time series for a selection of LPV candidates with high-quality observations. Aims. We describe the production and content of the Gaia catalog of LPV radial-velocity time series, and the methods used to compute the variability parameters published as part of the Gaia FPR. Methods. Starting from the DR3 catalog of LPV candidates, we applied several filters to construct a sample of sources with high-quality radial-velocity measurements. We modeled their radial-velocity and photometric time series to derive their periods and amplitudes, and further refined the sample by requiring compatibility between the radial-velocity period and at least one of the G, G_BP, or G_RP photometric periods. Results. The catalog includes radial-velocity time series and variability parameters for 9614 sources in the magnitude range 6 ≲ G/mag ≲ 14, including a flagged top-quality subsample of 6093 stars whose radial-velocity periods are fully compatible with the values derived from the G, G_BP, and G_RP photometric time series. The radial-velocity time series contain a mean of 24 measurements per source taken unevenly over a duration of about three years. We identify the great majority of the sources (88%) as genuine LPV candidates, with about half of them showing a pulsation period and the other half displaying a long secondary period. The remaining 12% of the catalog consists of candidate ellipsoidal binaries. Quality checks against radial velocities available in the literature show excellent agreement. We provide some illustrative examples and cautionary remarks. Conclusions. The publication of radial-velocity time series for almost ten thousand LPV candidates constitutes, by far, the largest such database available to date in the literature. The availability of simultaneous photometric measurements gives a unique added value to the Gaia catalog.

Context. We report the exploitation of a sample of Solar System observations based on data from the third Gaia Data Release (Gaia DR3) of nearly 157 000 asteroids. It extends the epoch astrometric solution over the time coverage planned for the Gaia DR4, which is not expected before the end of 2025. This data set covers more than one full orbital period for the vast majority of these asteroids. The orbital solutions are derived from the Gaia data alone over a relatively short arc compared to the observation history of many of these asteroids. Aims. The work aims to produce orbital elements for a large set of asteroids based on 66 months of accurate astrometry provided by Gaia and to assess the accuracy of these orbital solutions with a comparison to the best available orbits derived from independent observations. A second validation is performed with accurate occultation timings. Methods. We processed the raw astrometric measurements of Gaia to obtain astrometric positions of moving objects with 1D sub-mas accuracy at the bright end. For each asteroid that we matched to the data, an orbit fitting was attempted in the form of the best fit of the initial conditions at the median epoch. The force model included Newtonian and relativistic accelerations to derive the observation equations, which were solved with a linear least-squares fit. Results. Orbits are provided in the form of state vectors in the International Celestial Reference Frame for 156 764 asteroids, including near-Earth objects, main-belt asteroids, and Trojans. For the asteroids with the best observations, the (formal) relative uncertainty σ_a/a is better than 10⁻¹⁰. Results are compared to orbits available from the Jet Propulsion Laboratory and MPC. Their orbits are based on much longer data arcs, but from positions of lower quality. The relative differences in semi-major axes have a mean of 5 × 10⁻¹⁰ and a scatter of 5 × 10⁻⁹.

Context. Gaia’s readout window strategy is challenged by very dense fields in the sky. Therefore, in addition to standard Gaia observations, full Sky Mapper (SM) images were recorded for nine selected regions in the sky. A new software pipeline exploits these Service Interface Function (SIF) images of crowded fields (CFs), making use of the availability of the full two-dimensional (2D) information. This new pipeline produced half a million additional Gaia sources in the region of the omega Centauri (ω Cen) cluster, which are published with this Focused Product Release. We discuss the dedicated SIF CF data reduction pipeline, validate its data products, and introduce their Gaia archive table. Aims. Our aim is to improve the completeness of the Gaia source inventory in a very dense region in the sky, ω Cen. Methods. An adapted version of Gaia’s Source Detection and Image Parameter Determination software located sources in the 2D SIF CF images. These source detections were clustered and assigned to new SIF CF or existing Gaia sources by Gaia s cross-match software. For the new sources, astrometry was calculated using the Astrometric Global Iterative Solution software, and photometry was obtained in the Gaia DR3 reference system. We validated the results by comparing them to the public Gaia DR3 catalogue and external Hubble Space Telescope data. Results. With this Focused Product Release, 526 587 new sources have been added to the Gaia catalogue in ω Cen. Apart from positions and brightnesses, the additional catalogue contains parallaxes and proper motions, but no meaningful colour information. While SIF CF source parameters generally have a lower precision than nominal Gaia sources, in the cluster centre they increase the depth of the combined catalogue by three magnitudes and improve the source density by a factor of ten. Conclusions. This first SIF CF data publication already adds great value to the Gaia catalogue. It demonstrates what to expect for the fourth Gaia catalogue, which will contain additional sources for all nine SIF CF regions.

Quasars are essential for astrometry in the sense that they are spatially stationary because of their large distance from the Sun. The European Space Agency (ESA) astrometric satellite Gaia is scanning the whole sky with unprecedented accuracy up to the level of a few μas. However, Gaia ’s two-fields-of-view-observation strategy may introduce a parallax bias in the Gaia catalog. Since it presents no significant parallax, a quasar is the perfect natural object to detect such bias. More importantly, quasars can be used to construct a celestial reference frame in the optical wavelengths for the Gaia mission. In this paper, we compile a list of known quasars that have been published in the literatures. The final compilation (designated as Known Quasars Catalog for Gaia mission, KQCG) contains 1 842 076 objects, among which 797 632 objects are found in Gaia DR1 after cross-identifications. Redshift, color information and position uncertainties of the objects are also provided if available. This catalog will be very useful for the Gaia mission.

Introduction: The China Space Station Telescope (CSST) will enter a low Earth orbit around 2024 and operate for 10 years, with seven of those years devoted to surveying the area of the median-to-high Galactic latitude and median-to-high Ecliptic latitude of the sky. To maximize the scientific output of CSST, it is important to optimize the survey schedule. We aim to evaluate the astrometric capability of CSST for a given survey schedule and to provide independent suggestions for the optimization of the survey strategy.Methods: We first construct the astrometric model and then conduct simulated observations based on the given survey schedule. The astrometric solution is obtained by analyzing the simulated observation data. And then we evaluate the astrometric capability of CSST by analyzing the properties of the astrometric solution.Results: The accuracy of parallax and proper motion of CSST is better than 1 mas (⋅ yr⁻¹) for the sources of 18–22 mag in g band, and about 1∼10 mas (⋅ yr⁻¹) for the sources of 22–26 mag in g band, respectively. The results from real survey could be worse since the assumptions are optimistic and simple.Discussion: Optimizing the survey schedule can improve the astrometric accuracy of CSST. In the future, we will improve the astrometric capability of CSST by continuously iterating and optimizing the survey schedule.