No Arabic abstract
Since July 2014, the Gaia mission has been engaged in a high-spatial-resolution, time-resolved, precise, accurate astrometric, and photometric survey of the entire sky. Aims: We present the Gaia Science Alerts project, which has been in operation since 1 June 2016. We describe the system which has been developed to enable the discovery and publication of transient photometric events as seen by Gaia. Methods: We outline the data handling, timings, and performances, and we describe the transient detection algorithms and filtering procedures needed to manage the high false alarm rate. We identify two classes of events: (1) sources which are new to Gaia and (2) Gaia sources which have undergone a significant brightening or fading. Validation of the Gaia transit astrometry and photometry was performed, followed by testing of the source environment to minimise contamination from Solar System objects, bright stars, and fainter near-neighbours. Results: We show that the Gaia Science Alerts project suffers from very low contamination, that is there are very few false-positives. We find that the external completeness for supernovae, $C_E=0.46$, is dominated by the Gaia scanning law and the requirement of detections from both fields-of-view. Where we have two or more scans the internal completeness is $C_I=0.79$ at 3 arcsec or larger from the centres of galaxies, but it drops closer in, especially within 1 arcsec. Conclusions: The per-transit photometry for Gaia transients is precise to 1 per cent at $G=13$, and 3 per cent at $G=19$. The per-transit astrometry is accurate to 55 milliarcseconds when compared to Gaia DR2. The Gaia Science Alerts project is one of the most homogeneous and productive transient surveys in operation, and it is the only survey which covers the whole sky at high spatial resolution (subarcsecond), including the Galactic plane and bulge.
Gaia Photometric Science Alerts (GPSA) publishes Gaia G magnitudes and Blue Photometer (BP) and Red Photometer (RP) low-resolution epoch spectra of transient events. 27 high-resolution spectra from Gaias Radial Velocity Spectrometer (RVS) of 12 GPSAs have also been published. These 27 RVS epoch spectra are presented next to their corresponding BP and RP epoch spectra in a single place for the first time. We also present one new RVS spectrum of a 13th GPSA that could not be published by the GPSA system. Of the 13 GPSA with RVS spectra, five are photometrically classified as unknown, five as supernovae (three as SN Ia, one as SN II, one as SN IIP), one as a cataclysmic variable, one as a binary microlensing event and one as a young stellar object. The five GPSAs classified as unknown are potential scientific opportunities, while all of them are a preview of the epoch RVS spectra that will be published in Gaias fourth data release.
Gaia is a European Space Agency (ESA) astrometry space mission, and a successor to the ESA Hipparcos mission. Gaias main goal is to collect high-precision astrometric data (i.e. positions, parallaxes, and proper motions) for the brightest 1 billion objects in the sky. These data, complemented with multi-band, multi-epoch photometric and spectroscopic data collected from the same observing platform, will allow astronomers to reconstruct the formation history, structure, and evolution of the Galaxy. Gaia will observe the whole sky for 5 years, providing a unique opportunity for the discovery of large numbers of transient and anomalous events, e.g. supernovae, novae and microlensing events, GRB afterglows, fallback supernovae, and other theoretical or unexpected phenomena. The Photometric Science Alerts team has been tasked with the early detection, classification and prompt release of anomalous sources in the Gaia data stream. In this paper, we discuss the challenges we face in preparing to use Gaia to search for transient phenomena at optical wavelengths.
Self-Organizing Map (SOM) is a promising tool for exploring large multi-dimensional data sets. It is quick and convenient to train in an unsupervised fashion and, as an outcome, it produces natural clusters of data patterns. An example of application of SOM to the new OGLE-III data set is presented along with some preliminary results. Once tested on OGLE data, the SOM technique will also be implemented within the Gaia missions photometry and spectrometry analysis, in particular, in so-called classification-based Science Alerts. SOM will be used as a basis of this system as the changes in brightness and spectral behaviour of a star can be easily and quickly traced on a map trained in advance with simulated and/or real data from other surveys.
The standard errors of the end-of-mission Gaia astrometry have been re-assessed after conclusion of the in-orbit commissioning phase of the mission. An analytical relation is provided for the parallax standard error as function of Gaia G magnitude (and V-I colour) which supersedes the pre-launch relation provided in de Bruijne (2012).
Context. This paper presents an overview of the photometric data that are part of the first Gaia data release. Aims. The principles of the processing and the main characteristics of the Gaia photometric data are presented. Methods. The calibration strategy is outlined briefly and the main properties of the resulting photometry are presented. Results. Relations with other broadband photometric systems are provided. The overall precision for the Gaia photometry is shown to be at the milli-magnitude level and has a clear potential to improve further in future releases.