galaxy shape measurement for weak-lensing surveys
weak gravitational lensing
need measurements of the shapes
of large numbers of galaxies from faint imaging surveys.
Miller, Kitching, Heymans, Heavens & van Waerbeke (2007)
Kitching, Miller, Heymans, van Waerbeke & Heavens (2008)
we describe a Bayesian model-fitting approach to galaxy shape measurement
that is fast enough to be used for large weak-lensing surveys.
The method provides optimum (maximum signal-to-noise) shape measurement
for each galaxy in a survey, with unbiased correction for the
point-spread function (PSF).
The output for each galaxy is a Bayesian "posterior probability surface"
of the two ellipticity parameters, marginalised over the galaxy
size, brightness and position. The code currently takes around 1-2 secs
per galaxy using a standard single-processor desktop machine.
There are several steps in the shape and shear measurement process:
- Basic image reduction - standard methods are used to bias-correct
and flat-field images. If fringing is present it is important to
defringe. It is best also to determine and remove the sky background,
especially if this varies over an image. Any camera image distortion should be removed
if appropriate (although care is needed in this step if images are poorly
- Galaxy and star detection and classification - this can be achieved
using standard analysis code such as
Accurate star-galaxy discrimination is important as stars are used to
define the PSF.
- PSF creation, by combining many images of stars into a position-dependent
- Shape measurement as described by
Miller et al. (2007) and
Kitching et al. (2008).
If multiple images exist for a galaxy, the method allows optimum
combination of information.
Once the ellipticity probability surface has been obtained
for each galaxy, that information
may be used to create either maps or statistical measures of the shear
caused by weak lensing.
New code has been developed to carry out steps (3) and (4) above.
The algorithm and code have so far been tested on the
Shear TEsting Program (STEP)
If you are interested in using this code, please register on the accompanying page.
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