Are the simple ways to do an all-sky QSO selection with Gaia and WISE?

 What are good ways to select QSO samples before GDR3 ?

Goal

• Gaia will provide a QSO category with redshifts in DR3. There will be ~6M candidates; but, of course,  a significant fraction of them may not be QSOs. I.e. sample purity will be an  issue. And, redshift aliasing (from identification of the emission lines) may also be an issue.
• Are there ways to
1. reduce the non-QSO contamination?
2. help break redshift ambiguities?
• Here we focus on 1. ,  by asking how well (completeness and purity) can one select QSO samples with existing all-sky information.
• specifically we want to use Gaia and WISE only. 
• for the moment we'll stick to G<20, else Gaia data constraints become weak.
• we'll also stick to | b | >20 deg for now, to reduce near-plane contaminants.
• We want to exploit the three simple conditions
• quasars have 0 parallax  ("consistent with")
• quasars have 0 proper motion ("consistent with")
• most quasars z< 4 have W1-W2 > 0.5  (while most stars etc have W1-W2~0).

           Are the first two conditions sensible? The two plots below show the statistics of these quantities for the sample of 150k SDSS DR16 quasars G<20, selected independent of Gaia.

How far do we get with this?  Proposed approach: try it out on Stripe 82 and then apply to whole sky

Stripe 82 Experiment

• Basic numbers
• 8967 QSOs in S82, of which 5471 are G<20; of those 5242 also have a WISE match (<2").
• if we query:   

SELECT *

FROM gaiaedr3.gaia_source

WHERE  phot_g_mean_mag < 20.0

and parallax_over_error between -3 and 3

and  (pm*pm)/(pmra_error*pmra_error+pmdec_error*pmdec_error) < 9

and dec between -1.2 and 1.2 and (ra < 58 or ra > 309)

we get 20516 sources, of which 13040 have WISE matches.

         Their color distribution looks like this (plot below is for all sky with same Gaia Query)

         

This is the color-color distribution of non-moving, no-parallax Gaia sources G<20: top left lump: QSOs; sources with W1-W2~0 stars of all kinds of colors (presumably distant Giants, and -- se later LMC/SMC stars). For orientation, here the color distribution of spec. confirmed S82 QSO with G<20

This suggests to make a color cut as indicated below. Note that it turns out that S82 likely has overlooked quite a number of red/reddened QSO, which are in a plume towards the bottom-right.

What does that selection yield in S82?

Completeness: From the initial 20k sources Gaia selected, 13k have a WISE match, and 6500 are in the (blue) color-cut region above (compared to 5242 know S82 QSOs with WISE and G<20), after applying basic Gaia quality flags.  Of the 5242 QSOs with spectra, 4827 are picked up bi this selection: 92% completeness.

Purity: But there are 24% more sources in the Gaia-WISE-selected sample in S82 [TBD: need to check boundaries..] than spectroscopically conformed S82 QSOs. Conjecture: this is mostly (but not only), because SDSS is incomplete in red (reddened?) QSO, as the following plot suggests:

Here blue is the S82-spec sample, and gray the Gaia-WISE selection.

Last but not least, what if one applies the G<20, no-proper-motion, no-pls, red-in-(W1-W2) selection fo the entire sky with |b|>20?   

• the initial Gaia query yields 4.88M sources
• of these, 1.95M sources have a WISE match within 2"
• if one then makes the (B-R) -- (W1-W2) color cut (blue region a few plots up), one gets 747,000 QSO candidates with a sky distribution like this:

First addendum:

Are there smarter Gaia-WISE colors to single out QSOs?

Conjecture: yes, e.g the "dumbest" color, G-W1 vs W1-W2

if you then select the red area

You get a sky-distribution that is astoundingly uniform

What do we see:

• basic uniformity across sky. Yay!
• vestiges of the bulge, the magellanic clouds and one cluster with tidal tails in the North???
• imprint of dust-dimming
• a few articfacts that smell of Gaia-sky-scan

Second addendum:

What if we push to G=21?  Same procedure as above, yields another 600k objects with a rather uniform sky distribution..

Addendum  3:

What about photometric redshifts? Good enough to help with aliasing?

A qualitative look at the color-color plane looks promising:

And, using nearest neighbour, or NN (2nd plot) on z = f(G,BP,RP,W1,W2,A_G) yields

which looks "OK".

Questions:

• is that sample (700k after further cleaning) interesting, if we get phot-z + Gaia-spec-z for most?
• what happens if one pushed the same procedure fainter?