Information on resource 'Three-dimensional maps of the interstellar dust extinction curve within the Milky Way galaxy'

Example: A Dust Map

As an example of what one can do with this data, consider the following ADQL query to generate an all-sky maps of the mean extinction and means of ξ and R(55) for stars at a distance between 400 pc and 600 pc:

SELECT
        source_id/140737488355328 AS hpx,
        avg(ext/(err_ext*err_ext+0.0001)) AS mean_ext_num,
        avg(1/(err_ext*err_ext+0.0001)) AS mean_ext_denom,
        avg(xi/(err_xi*err_xi+0.0001)) as mean_xi_num,
        avg(1/(err_xi*err_xi+0.0001)) as mean_xi_denom,
        avg(r55*r55*r55/(err_r55*err_r55+0.0001)) as mean_inv_r55_num,
        avg(r55*r55*r55*r55/(err_r55*err_r55+0.0001)) as mean_inv_r55_denom
FROM xpparams2.main
WHERE
        mod_parallax BETWEEN 1.67 and 2.5
        AND quality_flags < 8
        AND mod_parallax/err_mod_parallax > 5
        AND err_ext < 0.5
GROUP BY hpx

This exploits the fact that Gaia source ids can be converted to HEALPixes to produce a map and shows how to do useful quality cuts that allow relatively careless use of the data. Note that we calculate means weighted by the inverse variance for robustness.

If you use TOPCAT to execute this on the GAVO DC TAP service (select Asynchronous mode and make sure you set Max Rows to something more than 50000, because that is how many pixels our map will have), you can do a sphere plot, then add a Healpix control. In it, select the table resulting from this query, manually set the HEALPix level to 6 and configure the Axis to Aitoff projection in the Galactic system to arrive such a plot of mean_ext_num/mean_ext_denom:

With this data, you can also get an idea of what sort of dust there is via the R(55) (or, if you prefer, ξ) parameter. Because 1/R(55) is better behaved than R(55) (as the extinction curve flattens and then tilts slightly blueward, the parameter R(55) first goes to infinity and then discontinuously jumps to negative infinity), we calculate the inverse-variance-weighted mean of 1/R(55). Below are plots of ξ (top) and R(55) (calculated by inverting the 1/R(55) map):

Note that in regions of low extinction, the measurements of ξ (and consequently R(55)) are noisy, and should be treated with caution.

Example: Metallicity of a Globular Cluster

Try the following query yielding data on Omega Cen and illustrating how to match with the local Gaia DR3 catalogue in order to constrain proper motions:

SELECT
        xpp.*,
        g.pmra, g.pmdec, g.phot_g_mean_mag, g.phot_bp_mean_mag,
        g.phot_rp_mean_mag
FROM xpparams2.main as xpp JOIN gaia.edr3lite as g USING (source_id)
WHERE
        distance(xpp.ra, xpp.dec, 201.697, -47.479472)<0.5
        AND distance(g.pmra, g.pmdec, -3.24, -6.73)<1.25
        AND xpp.quality_flags < 8
        AND xpp.mod_parallax/xpp.err_mod_parallax > 5.
        AND xpp.feh_confidence > 0.5
        AND xpp.err_fe_h < 0.2

Again in TOPCAT, try a 3d plot of RA, Dec and 1/mod_parallax. You will want to manually cut the parallax axis a bit to get rid of (presumably spurious) background stars. Make fe_h the aux axis in the “Form“ tab. If you look “from above“, you will see that the quality cuts have punched a hole into the (crowded) cluster. If you look from the side, you can see that the cluster stars are (by and large) rather metal-poor compared to foreground stars:

Converting between ξ and R(55)

We have used C source code to turn the ξ as used by 2025Sci...387.1209Z into the more common slope parameter R(55). Since it may be useful in other contexts, too, here is extinction_curve.c and extinction_curve.h.