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The MegaPipe
CFHTLS pages


Images and Catalogues
Ancillary Information
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Stephen.Gwyn@nrc.ca

Checks on Photometry

Systematic Errors

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.


Internal comparisons
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. Zero-point offsets between CFHTLS Wide pointings

External comparisons
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. Magnitude comparison
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. Photometric offsets with respect to the SDSS
Star Colours

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.

Star Colours
Limiting Magnitudes
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. Example of added galaxies
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 such simulations. 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 detections. The red numbers show the percent of artificial galaxies that were recovered at that magnitude/surface brightness. The blue contour lines shows the 70% and 50% completeness levels.

Limiting magnitude and surface brightness
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. Limiting magnitude for a Deep field
The blank-image 50% completeness limits are the ones quote in the tables on this page.