The reference frame
The reference frame of Gaia DR2 is nominally aligned with ICRS and
non-rotating with respect to the distant universe. This was achieved by means
of a subset of 492 009 primary sources assumed to be quasars. These
included 2844 sources provisionally identified as the optical counterparts of VLBI
sources in a prototype version of ICRF3, and 489 163 sources found by cross-matching
AGIS02.1 with the AllWISE AGN catalogue (Secrest et al. 2015, 2016).
The spin of the reference frame in Gaia DR2 is globally non-rotating to within mas yr
in all three axes. Particular attention was given to a possible dependence of the spin parameters on
colour (using the effective wavenumber ) and magnitude (). The results
suggest a small systematic dependence on colour, e.g. by mas yr over the range
corresponding to roughly =0 to 2 mag. As this result was derived for quasars that are typically
fainter than 15th magnitude, it does not necessarily represent the quality of the Gaia DR2 reference frame for
much brighter objects.
Indeed, Fig. 4 in (Lindegren et al. 2018) suggests that the bright () reference
frame of Gaia DR2 has a significant (0.15 mas yr) spin
relative to the fainter quasars. The points in the left part of the diagram were
calculated from stellar proper motion differences between the current solution and
Gaia DR1 (TGAS). Although based on a much shorter
stretch of observations than the present solution, TGAS provides a valuable
comparison for the proper motions thanks to its 24 yr time difference from
the Hipparcos epoch.
The most reasonable explanation are systematics in the Gaia DR2 proper motions of the bright sources.
The gradual change between magnitudes 12 and 10 suggests an origin in the gated observations,
which dominate for , or possibly in observations of window class 0,
which dominate for . A more comprehensive analysis of the faint Gaia DR2 reference
frame and the optical properties of the VLBI sources is given by Mignard et al. (2018).
The secondary solution was checked in a few selected areas using images obtained with the
ESO VLT Survey Telescope (VST) for the GBOT project Section 3.2.2 and, for
some very high-density areas in the Baade’s window region, with the HST Advanced Camera
for Surveys (ACS/WFC). These did not check the astrometric precision of the secondary solution
but rather the reality of the stars selected based on the astrometric quality indicators (number
of matched observations and excess source noise).
Parallax zero point
Global astrometric satellites like Hipparcos and Gaia are able to
measure absolute parallaxes, i.e. without zero-point error, but this capability is
susceptible to various instrumental effects, in particular to a certain kind of
basic-angle variations. As discussed by Butkevich et al. (2017), periodic
variations of the basic angle () are observationally almost indistinguishable
from a global parallax shift.
It is believed that the basic-angle corrector derived from BAM data
(Section 2.4.4) does a very good job of eliminating basic-angle variations,
but a remaining small variations cannot be excluded. This would then show up as a
small offset in the parallaxes. For this reason it is extremely important to investigate the
parallax zero point by external means, i.e. using astrophysical sources with known parallaxes.
It is also important to check possible dependences of the zero point on other
factors such as position, magnitude, and colour, which could be created by
errors in the calibration model.
The quasars are almost ideal for checking the parallax zero point thanks to their
extremely small parallaxes (as for redshift ), large number,
availability over most of the celestial sphere, and, in most cases, nearly point-like
appearance. Main drawbacks are their faintness and peculiar colours. In order to create the
largest possible quasar sample for validation purposes, a new cross-match of the final Gaia DR2
data with the AllWISE AGN catalogue Secrest et al. (2015) was made, choosing in each
case the nearest positional match. The results and discussion of this comparison are outlined in
Section 5.2 of Lindegren et al. (2018).