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.

1. 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 sampled).
2. Galaxy and star detection and classification - this can be achieved using standard analysis code such as SExtractor. Accurate star-galaxy discrimination is important as stars are used to define the PSF.
3. PSF creation, by combining many images of stars into a position-dependent PSF.
4. 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.

Download a presentation on lensfit from here.

The lensfit team are:

• Lance Miller (Oxford)
• Tom Kitching (Oxford)
• Catherine Heymans (UBC)
• Alan Heavens (Edinburgh)
• Ludo Van Waerbeke (UBC)