5.6 SpectroPhotometric Standard Stars
Author(s): Elena Pancino, Nicoletta Sanna, Monica Rainer
The external calibration model described above requires the use of as many calibrators as possible, compatible with the feasibility of the corresponding on-ground observing campaign. The grid of spectro-photometric standard stars (SPSS) should include a wide range of spectral types to account for colour dependencies of the spectral energy distribution (SED). Smooth spectra are desirable, but featureless spectra are not useful, because the lack of features might induce small wavelength calibation errors that in turn could induce large flux errors on the steep blue part (400 nm) of the spectrum. The inclusion of spectral features is thus desirable, both narrow (atomic lines) and wide (molecular bands), but too many features would make the flux level uncertain. The Gaia end-of-mission requirement for the SPSS flux precision is 1%, and their flux calibration should be tied to Vega (Bohlin and Gilliland 2004; Bohlin 2007, 2014) to within 3%. This sets an approximate number of required calibrators of about 200, observable all year round from the Northern and Southern hemispheres, and with a suitable magnitude range (– mag) to be observed by both Gaia and several 2–4 m class ground-based telescopes with a good signal-to-noise ratio (i.e., well above 100).
Because no existing set of SPSS in the literature simultaneously meets all these requirements, while at the same time covering the whole Gaia spectral range (330–1050 nm), an initial selection of approximately 300 SPSS candidates was made. These candidates cover all spectral types from hot WD and O/B to cold M stars, i.e., with a temperature range – K. A substantial observational effort (Pancino et al. 2012; Altavilla et al. 2015; Pancino et al. 2021) to collect the required data and to monitor for constancy (Marinoni et al. 2016) started in 2006 and was completed in 2015. Additional ground-based absolute photometry was collected to validate the spectra (Altavilla et al. 2021). The campaign was awarded more than 5000 hours of observing time, mostly in visitor mode, at six different facilities: DOLORES@TNG in La Palma, EFOSC2@NTT and ROSS@REM in La Silla, CAFOS@2.2 m in Calar Alto, BFOSC@Cassini in Loiano, and LaRuca@1.5 m in San Pedro Mártir. Some additional photometric data were acquired with Meia@TJO in Catalonia. The survey produced more than 100,000 imaging and spectroscopic frames, that are presently being analysed (Altavilla et al. 2015). The raw data, flux tables, and intermediate data products are collected at the ASI Space Science Data Center in the SPSS@SSDC database.
Three internal releases of SPSS flux tables were prepared so far, a pre-launch version (V0) to test the instrument performance and the pipelines, a first post-launch version (V1) to actually calibrate the photometry for Gaia DR1 and Gaia DR2, and a second improved release to calibrate Gaia DR3. Both V0 and V1 contain the best 93 SPSS, i.e. about 50% of the final sample, observed in strictly photometric conditions and monitored for constancy on timescales of 1–2 hours to exclude stars with magnitude variations larger than 10 mmag (Marinoni et al. 2016). The quality of the flux tables in V1 already meets the formal Gaia requirements (precision 1% and accuracy 3%), and is sufficient to calibrate integrated Gaia magnitudes G, G, and G, and therefore was also used to calibrate Gaia DR2. The current SPSS V2 release brought the following improvements: more spectra for each SPSS, more SPSS (113 in total), and fringing mitigation to allow for a better calibration not only of Gaia photometry, but also spectroscopy. The accuracy of the V2 calibration is 1%, exceeding the initial requirement, with a major improvement on the blue spectral range (500 nm). The Gaia SPSS grid is about 1% brighter than the current CALSPEC grid and about 1% fainter than Landolt (Landolt 1992). The absolute reference scale is in fact tied to the CALSPEC Vega obtained before 2014 (Bohlin et al. 2014), which is on the same scale of the latest CALSPEC revision (Bohlin et al. 2020) to better than 0.5%.
Figure 5.45 shows an SPSS V2 view in the absolute colour-magnitude plane.