We present a new method for optimally extracting point-source time
variability information from a series of images. Differential photometry is
generally best accomplished by subtracting two images separated in time, since
this removes all constant objects in the field. By removing background sources
such as the host galaxies of supernovae, such subtractions make possible the
measurement of the proper flux of point-source objects superimposed on extended
sources. In traditional difference photometry, a single image is designated as
the ``template'' image and subtracted from all other observations. This
procedure does not take all the available information into account and for
sub-optimal template images may produce poor results. Given N total
observations of an object, we show how to obtain an estimate of the vector of
fluxes from the individual images using the antisymmetric matrix of flux
differences formed from the N(N-1)/2 distinct possible subtractions and provide
a prescription for estimating the associated uncertainties. We then demonstrate
how this method improves results over the standard procedure of designating one
image as a ``template'' and differencing against only that image.Comment: Accepted to AJ. To be published in November 2005 issue. 16 page, 2
figures, 2 tables. Source code available at
http://www.ctio.noao.edu/essence/nn2