Images and Catalogues
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The photometry for the D2 and D3 is directly tied to the SDSS photometry.
There are a thousand or so standards in every field.
Thus, the systematic errors between the SDSS and the CFHTLS are effectively
nil, with the possible exception of some aperture effects.
The systematic errors in the SDSS are quoted as 2-3%.
The systematics for the D1 and D4 which are not in the SDSS will be larger.
Over several photometric nights,
"secondary standards" were set up the these fields
using the SDSS fields as "primary standards".
The night-to-night scatter for the secondary standards,
(typically 0.02 to 0.03 magnitudes) is an indicator of the potential
systematic error. However, since the magnitude of the "secondary standards"
are averaged over several nights, the systematic error on
the average should be lower. Adding in quadrature SDSS systematic error (0.025 mags) to the
systematic error in transferring from the "primary" to "secondary"
standards (0.025 mags) we get 0.035 magnitudes of total systetmatic error.
The pointings of the Wide fields overlap each other.
Comparing the magnitudes of sources measured in one
pointing to the magnitudes measured in adjacent
pointings, gives an idea of the internal consistency
of the zero-points.
Photometric offsets were measured between all 171
Wide pointings. The figure at right shows the results.
The mean offset for all filters is about 0.01 magnitudes.
At least some of the pointings of each of the Wide fields as well as
the D2 and D3 fields lie within the SDSS. This makes it possible to
directly compare the magnitudes in those fields to an external
reference. The figure at right shows a typical comparison between the
SDSS (transformed to the MegaCam system as described
here) and the CFHTLS for
the 5 bands.
The agreement is very good. At bright magnitudes, for g, r and i bands,
there are deviations. This is caused by the brightest stars saturating.
There is no evidence for systematic shifts greater than 0.01 magnitudes
There is also relatively little scatter (at least at moderate magnitudes).
This argues that the colour terms in the SDSS-MegaCam transformation
are fairly accurate.
Similar comparisons have been done for every pointing overlaping the
SDSS. The figure at right summarizes the results. The offsets are
typically slightly larger than the internal photometric residuals shown
above, at about 0.015 magnitudes.
A useful diagnostic of photometry is to examine the colours of
stars. Stars have a relatively constrained locus in colour space. Any
offsets between the observed and synthetic colours indicates a
zeropoint error. This test can be applied to the pointings
that do not lie in the SDSS cannot be checked directly.
The top left panel of the figure at right illustrates the selection of stars.
The plot shows half-light radius plotted as magnitude. On this plot,
the galaxies occupy a range of magnitudes and radii while the
stars show up as a well defined horizontal locus, turning up at the bright
end where the stars saturate.
The red points indicate the very conservative
cuts in magnitude and radius to select stars for further analysis.
The other 3 plots plots show the colours of the stars selected from the CFHTLS in this
manner in black overlaid on top of the transformed SDSS star colours
shown in green.
No systematic shifts seem to be visible.
The limiting magnitudes of the images were tested by adding fake
galaxies to the images and then trying to recover them using the
same parameters used to generate the real image catalogues.
The fake galaxies used were taken from the images themselves,
rather than adding completely artificial galaxies.
A set of 40 bright, isolated galaxies was selected out of the field
and assembled into a master list. Postage stamps of these galaxies were
cut out of the field. The galaxies were faded in both surface
brightness and magnitude through a combination of scaling the
pixel values and resampling the images.
To test the recovery rate at a given magnitude and surface brightness,
galaxy postage stamps are selected from the master list, faded as
described above to the magnitude and surface brightness in question
and then added to the image at random locations.
SExtractor is then run on new image. The fraction of fake galaxies
found gives the recovery rate at that magnitude and surface brightness,
An illustration of adding the galaxies is shown at right. The same
galaxy has been added multiple times to the image. The galaxy has
faded to various magnitudes and surface brightnesses. The red boxes contain the galaxy. The boxes are
labeled by mag/surface brightness. Note the galaxy at I=23,
μI=25 accidentally ended up near a bright galaxy and is
only partially visible. Normally of course, the galaxies are not
placed in such a regular grid.
To test the false-positive rate, The original image was multiplied by
-1; the noise peaks became noise troughs and vice-versa. SExtractor
was run, using the same detection criteria. Since there are no real
negative galaxies, all the objects thus detected are spurious.
The magnitude/surface brightness plot at right shows the results of
The black points are real objects. The bottom edge of the black points
is the locus of point-like objects.
The green points show the false-positive
The red numbers show
the percent of artificial galaxies that were recovered at that
The blue contour
lines shows the 70% and 50% completeness levels.
Deriving a single limiting magnitude from such a plot is slightly
difficult. The cleaner cut in the false positives
seems to be in surface brightness. Extended objects
become harder to detect at brighter magnitudes whereas
stellar objects are detectable a magnitude or so fainter.
Point source limiting magnitudes were also calculated. Point sources
were added to the images in a similiar manner to the above, but only
scaling with magnitude. For the Deep fields in particular, the images
are effectively crowded. An artifical source added to the image stands
a signifcant of ending up close enough to a real source that it will
not be detected. To compensate for this, sources were added to
two images. The first is just the original image. The second
is the original with all the real sources removed
and their pixels replaced with values matching the background
noise characteristics (a blank iamge). The differences between the two completeness
limits is shown in the following figure.
The figure at right shows the completeness limits for a Deep
field. The blue line shows the
fraction of artificial point sources that can be recovered from the
blank image. The red lines shows the
same for the original image. It is consistently a few 10ths
of magnitude less deep. The black points show the number counts
of real sources (the absolute vertical scaling may be slightly off in
this plot). The green points show
the number counts for false positive detections. The 50% completeness
limit for this image (D2, g-band, best-seeing image) is 27.2 magnitudes.
The blank-image 50% completeness limits are the ones
quote in the tables on this page.