Subscribe to the gold package and get unlimited access to Shamra Academy
Register a new userRVS Spectra of Gaia Photometric Science Alerts
89
0
0.0
(
0
)
Authors
George Seabroke
Ask ChatGPT about the research
No Arabic abstract
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 We also present one new RVS spectrum of a 13th GPSA that could not be published by the GPSA system.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.
rate research
Read More
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.
The Gaia mission is a magnitude-limited whole-sky survey that collects an impressive quantity of astrometric, spectro-photometric and spectroscopic data. Among all the on-board instruments, the Radial Velocity Spectrometer (RVS) produces millions of spectra up to a magnitude of G$_{RVS} sim 16$. For the brightest RVS targets, stellar atmospheric parameters and individual chemical abundances are automatically estimated by the Generalized Stellar Parametriser - spectroscopy group (GSP-Spec). These data will be published with the third Gaia Data Release. Some major ingredients of the determination of these stellar parameters include the atomic and molecular line lists that are adopted to compute reference synthetic spectra, on which the parametrisation methods rely. We aim to build such a specific line list optimised for the analysis of RVS late-type star spectra. Starting from the Gaia-ESO line lists, we first compared the observed and synthetic spectra of six well-known reference late-type stars in the wavelength range covered by the RVS instrument. We then improved the quality of the atomic data for the transitions presenting the largest mismatches. The new line list is found to produce very high-quality synthetic spectra for the tested reference stars and has thus been adopted within GSP-Spec.
Among the myriad of data collected by the ESA Gaia satellite, about 150 million spectra will be delivered by the Radial Velocity Spectrometer (RVS) for stars as faint as G_RVS~16. A specific stellar parametrization will be performed for most of these RVS spectra. Some individual chemical abundances will also be estimated for the brightest targets. We describe the different parametrization codes that have been specifically developed or adapted for RVS spectra within the GSP-spec working group of the analysis consortium. The tested codes are based on optimization (FERRE and GAUGUIN), projection (MATISSE) or pattern recognition methods (Artificial Neural Networks). We present and discuss their expected performances in the recovered stellar atmospheric parameters (Teff, log(g), [M/H]) for B- to K- type stars. The performances for the determinations of [alpha/Fe] ratios are also presented for cool stars. For all the considered stellar types, stars brighter than G_RVS~12.5 will be very efficiently parametrized by the GSP-spec pipeline, including solid estimations of [alpha/Fe]. Typical internal errors for FGK metal-rich and metal-intermediate stars are around 40K in Teff , 0.1dex in log(g), 0.04dex in [M/H], and 0.03dex in [alpha/Fe] at G_RVS=10.3. Similar accuracies in Teff and [M/H] are found for A-type stars, while the log(g) derivation is more accurate. For the faintest stars, with G_RVS>13-14, a spectrophotometric Teff input will allow the improvement of the final GSP-spec parametrization. The reported results show that the contribution of the RVS based stellar parameters will be unique in the brighter part of the Gaia survey allowing crucial age estimations, and accurate chemical abundances. This will constitute a unique and precious sample for which many pieces of the Milky Way history puzzle will be available, with unprecedented precision and statistical relevance.
In this letter, we have carried out an independent validation of the Gaia EDR3 photometry using about 10,000 Landolt standard stars from Clem & Landolt (2013). Using a machine learning technique, the UBVRI magnitudes are converted into the Gaia magnitudes and colors and then compared to those in the EDR3, with the effect of metallicity incorporated. Our result confirms the significant improvements in the calibration process of the Gaia EDR3. Yet modest trends up to 10 mmag with G magnitude are found for all the magnitudes and colors for the 10 < G < 19 mag range, particularly for the bright and faint ends. With the aid of synthetic magnitudes computed on the CALSPEC spectra with the Gaia EDR3 passbands, absolute corrections are further obtained, paving the way for optimal usage of the Gaia EDR3 photometry in high accuracy investigations.
Gaia is the next astrometry mission of the European Space Agency (ESA), following up on the success of the Hipparcos mission. With a focal plane containing 106 CCD detectors, Gaia will survey the entire sky and repeatedly observe the brightest 1,000 million objects, down to 20th magnitude, during its 5-year lifetime. Gaias science data comprises absolute astrometry, broad-band photometry, and low-resolution spectro-photometry. Spectroscopic data with a resolving power of 11,500 will be obtained for the brightest 150 million sources, down to 17th magnitude. The thermo-mechanical stability of the spacecraft, combined with the selection of the L2 Lissajous point of the Sun-Earth/Moon system for operations, allows stellar parallaxes to be measured with standard errors less than 10 micro-arcsecond (muas) for stars brighter than 12th magnitude, 25 muas for stars at 15th magnitude, and 300 muas at magnitude 20. Photometric standard errors are in the milli-magnitude regime. The spectroscopic data allows the measurement of radial velocities with errors of 15 km/s at magnitude 17. Gaias primary science goal is to unravel the kinematical, dynamical, and chemical structure and evolution of the Milky Way. In addition, Gaias data will touch many other areas of science, e.g., stellar physics, solar-system bodies, fundamental physics, and exo-planets. The Gaia spacecraft is currently in the qualification and production phase. With a launch in 2013, the final catalogue is expected in 2021. The science community in Europe, organised in the Data Processing and Analysis Consortium (DPAC), is responsible for the processing of the data.
Log in to be able to interact and post comments
comments
Fetching comments
Sign in to be able to follow your search criteria
