Table information for 'prdust.map_union'

This resource is only available through this site's TAP service (access url: http://dc.zah.uni-heidelberg.de/tap).

You will want to use some sort of client to query TAP services; examples for those include:

See TAP info on this site for details.

General

Table Description: This is a view of the dust maps in the five orders, generated by splitting the larger pixels from the higher orders into HEALPixes of order 10. This means, in particular, that the spatial resolution for all pixels with original_order!=10. Use this for convenient joins to other tables.

This table is available for ADQL queries and through the TAP endpoint.

Resource Description:

A 3D map of interstellar dust reddening, covering three quarters of the sky (declinations greater than -30 degrees) out to a distance of several kiloparsecs. The map is based on high-quality stellar photometry of 800 million stars from Pan-STARRS 1 and 2MASS.

The map is available for five HEALPix levels (6 through 10), published here as separate tables, map6 through map10. A union of the coverage is provided as map_union. Use its coverage column to match against other tables.

See http://argonaut.rc.fas.harvard.edu/ for more details.

For a list of all services and tables belonging to this table's resource, see Information on resource 'Bayestar17 3D Dust Mapping with Pan-STARRS 1'

Citing this table

This table has an associated publication. If you use data from it, it may be appropriate to reference 2018arXiv180103555G (ADS BibTeX entry for the publication) either in addition to or instead of the service reference.

Reference the Table

To cite the table as such, we suggest the following BibTeX entry:

@MISC{vo:prdust_map_union,
  year=2018,
  title={Joined Bayestar17 3D Dust Map},
  author={Green, G.M. and Schlafly, E.F. and Finkbeiner, D. and Rix, H.-W. and Martin, N. and Burgett, W. and Draper, P.W. and Flewelling, H. and Hodapp, K. and Kaiser, N. and Kudritzki, R.-P. and Magnier, E.A. and Metcalfe, N. and Tonry, J.L. and Wainscoat, R and Waters, C.},
  url={http://dc.zah.uni-heidelberg.de/tableinfo/prdust.map_union},
  howpublished={{VO} resource provided by the {GAVO} Data Center}
}

Fields

Sorted by DB column index. [Sort alphabetically]

NameTable Head DescriptionUnitUCD
healpix HEALPix The healpix (in galactic l, b) for which this data applies. This is of the order given in the hpx_order column, and thus it's not usually useful for querying. Query against the coverage column instead. N/A pos.healpix
coverage Coverage Area (as order-10-healpix interval) covered by this healpix. N/A phys.angArea
converged Converged? 1 if the line-of-sight reddening fit converged, 0 otherwise. N/A meta.code
dm_reliable_min Min. Rel. Minimum reliable distance modulus. mag N/A
dm_reliable_max Max. Rel. Maximum reliable distance modulus. mag N/A
n_stars # Stars Number of stars used to fit the line-of-sight reddening. N/A meta.number
n_good # Good The number of stars in the sightline with good convergence, and which passed a cut on Bayesian evidence (termed "good" stars). N/A meta.number
n_dwarfs # Dwarf The number of "good" stars which are inferred to be Main-Sequence stars. N/A meta.number
grdiagnostic G-R conv. Gelman-Rubin convergence diagnostic in each HEALpix; a HEALpix can be considered good if diagnostic is below 1.2. N/A N/A
best_fit E(B-V) for 4 .. 19 mag (0.5 mag bin size) The best-fit (maximum proability density) line-of-sight reddening, in units of SFD-equivalent E(B-V), in each distance bin; the bins are 4 .. 19 mag of distance modulus, spaced 0.5 mags. [Note e] mag phys.absorption
samples 18 samples/bin of E(B-V) from MCMC chain 18 samples of E(B-V) in each distance bin drawn from the MCMC chain; the bins are 4 .. 19 mag of distance modulus, spaced 0.5 mags. This information can be used to estimate the reliability of best_fit (e.g., a standard deviation). [Note e] mag phys.absorption;src.sample
hpx_order Src. order The HEALPix order healpix is given for. The dust map is not regularly sampled, which is why orders vary over the sky. For querying, it is simpler to look at coverage than at healpix+order. N/A meta.number;pos.healpix

Columns that are parts of indices are marked like this.

Other

VOResource

VO nerds may sometimes need VOResource XML for this table.

Notes

Note e

Note that the reddening is given in units of “SFD-like” E(B-V). They are meant to be comparable to the E(B-V) reported by 1998wfsc.conf..297S. Due to a subsequent recalibration of SFD (2011ApJ...737..103S), the true E(B-V) is 0.884 times the reddening reported here.

To convert to extinction in Pan-STARRS 1 or 2MASS passbands, multiply the reddening reported here by

g 3.384
r 2.483
i 1.838
z 1.414
y 1.126
J 0.650
H 0.327
Ks 0.161

The issue is discussed in somewhat more detail in http://argonaut.skymaps.info/usage#units.

More Information on the Base Resource

These tables lets you do dereddening of photometry provided you have:

You will usually join two of the arrays in map_union to your table. Because of boring technicalities, that is a bit ideomatic; you need to compute an order-10 healpix and see if that is contained in this tables coverage. In a cartoon:

SELECT
  mytable.*,
  best_fit, grdiagnostic
FROM mytable
JOIN prdust.map_union
ON (1=ivo_interval_has(
  CAST(ivo_healpix_index(10, l, b) AS INTEGER), coverage))

Yes, you have to use galactic longitude and latitude in the arguments of ivo_healpix_index; and the odd cast is necessary because coverage contains normal integer intervals.

If you have equatorial coordinates ra and dec, on this service there's the gavo_transform user defined function to your rescue. Just write:

CAST(ivo_healpix_index(10,
  gavo_transform('ICRS', 'GALACTIC', POINT(ra, dec))
    ) AS INTEGER), coverage)

in the second argument of ivo_interval_has above.

The next step is to estimate a distance modulus. If you have a good parallax estimate and your TAP service supports the in_unit UDF, you might get away with:

5*log10(1./in_unit(parallax, 'arcsec'))-5 AS dist_mod

You will certainly want to do better than this in almost all science use cases (see 2018arXiv180409376L for a through discussion in the context of Gaia DR2).

From dist_mod, you can compute the distance bin in the best_fit and grdiagostic columns with:

ROUND((dist_mod-4)*2)+1 AS dist_mod_bin

With this, you can add an E(B-V) to a local table somewhat like this:

SELECT
        q.*,
        best_fit[dist_mod_bin] as eb_v
FROM (
        SELECT (
                CAST(ivo_healpix_index(10, l, b) AS INTEGER) AS cat_hpx,
                ROUND((dist_mod-4)*2)+1 AS dist_mod_bin,
                mytable.*
        FROM mytable) AS q
JOIN prdust.map_union
ON (1=ivo_interval_has(cat_hpx, coverage))
WHERE grdiagnostic[dist_mod_bin]<1.2

To turn E(B-V) into extinctions, there are several recipes. See, for instance 1998ApJ...500..525S.

You'll find a worked-out example on this at

Copyright and such:

To the extent possible under law, the publisher has waived all copyright and related or neighboring rights to 3D Dust Maps. For details, see the Creative Commons CC0 1.0 Public Domain dedication. Of course, you should still give proper credit when using this data as required by good scientific practice.

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