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We present a technique to measure lightcurves of time-variable point sourceson a spatially structured background from imaging data. The technique wasdeveloped to measure light curves of SNLS supernovae in order to infer theirdistances. This photometry technique performs simultaneous PSF photometry atthe same sky position on an image series. We describe two implementations ofthe method: one that resamples images before measuring fluxes, and one whichdoes not. In both instances, we sketch the key algorithms involved and presentthe validation using semi-artificial sources introduced in real images in orderto assess the accuracy of the supernova flux measurements relative to that ofsurrounding stars. We describe the methods required to anchor these PSF fluxesto calibrated aperture catalogs, in order to derive SN magnitudes. We find amarginally significant bias of 2 mmag of the after-resampling method, and nobias at the mmag accuracy for the non-resampling method. Given surrounding starmagnitudes, we determine the systematic uncertainty of SN magnitudes to be lessthan 1.5 mmag, which represents about one third of the current photometriccalibration uncertainty affecting SN measurements. The SN photometry deliversseveral by-products: bright star PSF flux mea- surements which have arepeatability of about 0.6%, as for aperture measurements; we measure relativeastrometric positions with a noise floor of 2.4 mas for a single-image brightstar measurement; we show that in all bands of the MegaCam instrument, starsexhibit a profile linearly broadening with flux by about 0.5% over the wholebrightness range.

Photometry of supernovae in an image series : methods and application to the Supernova Legacy Survey (SNLS)