The Detection of Transiting Exoplanets by Gaia

Context: The space telescope Gaia is dedicated mainly to performing high-precision astrometry, but also spectroscopy and epoch photometry which can be used to study various types of photometric variability. One such variability type is exoplanetary transits. The photometric data accumulated so far have finally matured enough to allow the detection of some exoplanets. Aims: In order to fully exploit the scientific potential of Gaia, we search its photometric data for the signatures of exoplanetary transits. Methods: The search relies on a version of the Box-Least-Square (BLS) method, applied to a set of stars prioritized by machine-learning classification methods. An independent photometric validation was obtained using the public full-frame images of TESS. In order to validate the first two candidates, radial-velocity follow-up observations were performed using the spectrograph PEPSI of the Large Binocular Telescope (LBT). Results: The radial-velocity measurements confirm that two of the candidates are indeed hot Jupiters. Thus, they are the first exoplanets detected by Gaia - Gaia-1b and Gaia-2b. Conclusions: Gaia-1b and Gaia-2b demonstrate that the approach presented in this paper is indeed effective. This approach will be used to assemble a set of additional exoplanet candidates, to be released in Gaia third data release, ensuring better fulfillment of the exoplanet detection potential of Gaia.Comment: Accepted for publication in A&A, 8 pages, 8 figure

Gaia Data Release 3: The first Gaia catalogue of variable AGN

One of the novelties of the Gaia-DR3 with respect to the previous data releases is the publication of the multiband light curves of about 1 million AGN. The goal of this work was the creation of a catalogue of variable AGN, whose selection was based on Gaia data only. We first present the implementation of the methods to estimate the variability parameters into a specific object study module for AGN. Then we describe the selection procedure that led to the definition of the high-purity variable AGN sample and analyse the properties of the selected sources. We started from a sample of millions of sources, which were identified as AGN candidates by 11 different classifiers based on variability processing. Because the focus was on the variability properties, we first defined some pre-requisites in terms of number of data points and mandatory variability parameters. Then a series of filters was applied using only Gaia data and the Gaia Celestial Reference Frame 3 (Gaia-CRF3) sample as a reference.The resulting Gaia AGN variable sample, named GLEAN, contains about 872000 objects, more than 21000 of which are new identifications. We checked the presence of contaminants by cross-matching the selected sources with a variety of galaxies and stellar catalogues. The completeness of GLEAN with respect to the variable AGN in the last Sloan Digital Sky Survey quasar catalogue is about 47%, while that based on the variable AGN of the Gaia-CRF3 sample is around 51%. From both a comparison with other AGN catalogues and an investigation of possible contaminants, we conclude that purity can be expected to be above 95%. Multiwavelength properties of these sources are investigated. In particular, we estimate that about 4% of them are radio-loud. We finally explore the possibility to evaluate the time lags between the flux variations of the multiple images of strongly lensed quasars, and show one case.Comment: 19 pages, 31 figures, 2 table. This paper is part of Gaia Data Release 3 (DR3). In press for A&

Gaia Data Release 3: Gaia scan-angle-dependent signals and spurious periods

Context. Gaia Data Release 3 (Gaia DR3) time series data may contain spurious signals related to the time-dependent scan angle. Aims. We aim to explain the origin of scan-angle-dependent signals and how they can lead to spurious periods, provide statistics to identify them in the data, and suggest how to deal with them in Gaia DR3 data and in future releases. Methods. Using real Gaia (DR3) data alongside numerical and analytical models, we visualise and explain the features observed in the data. Results. We demonstrated with Gaia (DR3) data that source structure (multiplicity or extendedness) or pollution from close-by bright objects can cause biases in the image parameter determination from which photometric, astrometric, and (indirectly) radial velocity time series are derived. These biases are a function of the time-dependent scan direction of the instrument and thus can introduce scan-angle-dependent signals, which due to the scanning-law-induced sampling of Gaia can result in specific spurious periodic signals. Numerical simulations in which a period search is performed on Gaia time series with a scan-angle-dependent signal qualitatively reproduce the general structure observed in the spurious period distribution of photometry and astrometry, and the associated spatial distributions on the sky. A variety of statistics allows for the deeper understanding and identification of affected sources. Conclusions. The origin of the scan-angle-dependent signals and subsequent spurious periods is well understood and is mostly caused by fixed-orientation optical pairs with a separation < 0.5'' (including binaries with P ≈ 5 y) and (cores of) distant galaxies. Although most of the sources with affected derived parameters have been filtered out from the Gaia archive nss-two-body-orbit and several vari-tables, Gaia DR3 data remain that should be treated with care (no sources were filtered from gaia-source). Finally, the various statistics discussed in the paper can be used to identify and filter affected sources and also reveal new information about them that is not available through other means, especially in terms of binarity on sub-arcsecond scale.SCOPUS: ar.jinfo:eu-repo/semantics/publishe