SVA1 GOLD object catalog:
SVA1 limiting magnitude maps
SVA1 good-region footprint
Column Name | Data Type | Description |
---|---|---|
COADD_OBJECTS_ID | INT (8) | Unique object identifier (can be used to match against other SVA1 catalogs) |
RA DEC | FLOAT (8) FLOAT (8) | Celestial coordinates in decimal degrees (J2000) corresponding to the i-band windowed |
MODEST_CLASS | INT (2) | Integer object classification schema built on SPREAD_MODEL,
|
FLAGS_[G,R,I,Z] | INT (4) | SExtractor flags values (precut on FLAGS < 4)
|
BADFLAG | INT (4) | SVA1 GOLD flag definitions:
|
MAG_AUTO_[G,R,I,Z] MAGERR_AUTO_[G,R,I,Z] | FLOAT (4) FLOAT (4) | AUTO magnitudes from SExtractor. |
MAG_PSF_[G,R,I,Z] MAGERR_PSF_[G,R,I,Z] | FLOAT (4) FLOAT (4) | PSF magnitudes form SExtractor. NOT RECOMMENDED (see above). |
SPREAD_MODEL_[G,R,I,Z] SPREADERR_MODEL_[G,R,I,Z] | FLOAT (4) FLOAT (4) | Linear discriminant between the best fitting local PSF model and a slightly more extended galaxy model (Desai et al. 2012) |
CLASS_STAR_[G,R,I,Z] | FLOAT (4) | Neural-network star galaxy classification from SExtractor (Bertin & Arnouts 1996) |
FLUX_RADIUS_[G,R,I,Z] | FLOAT (4) | Radius in pixels (0.263"/pix) of a circle centered on the object barycenter that |
The SVA1 GOLD survey depth is estimated for the AUTO magnitudes appropriate for galaxies following the procedure of Rykoff et al. (2015). Maps of the 10σ galaxy limiting magnitude were generated by fitting the MAGERR_AUTO vs MAG_AUTO relationship on large pixels and correlating with small-scale spatially varying survey characteristics (Leistedt et al. 2015). These maps are distributed in nested HEALPix format (nside=4096).
We also distribute a "good region" footprint which masks regions with imaging artifacts (as identified by a high density of objects with "crazy colors"), regions close to bright 2MASS stars, and regions where objects have large astrometric offsets between filters. A detailed description of the creation of the good region footprint can be found in Section 2.1 of Jarvis et al. (2015).
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The DES Data Management system is supported by the National Science Foundation under Grant Number (1138766).