New Variable Star Discovery Technique

[Glenn Gombert <gleng@infinet.com>]

Hello,

        Emmanual Bertin (who wrote SExtractor) forwarded a very interesting
URL that describes a new method by his college Christophe Alard:"
http://xxx.lanl.gov/abs/astro-ph/9712287."   That has been used to discover
new variable stars in the OGLE II Survey looking at the Galactic Bulge. It
looks like a very interesting technique to apply to TASS Images. Shown below
is a summary from the above URL:

  "We present a new method designed for optimal subtraction of two images
with different seeing. Using image subtraction appears to be essential for
the full analysis of the microlensing survey images, however a perfect
subtraction of two images is not easy as it requires the derivation of an
extremely accurate convolution kernel. Some empirical attempts to find the
kernel have used the Fourier transform of bright stars, but solving the
statistical problem of finding the best kernel solution has never really
been tackled. We demonstrate that it is possible to derive an optimal kernel
solution from a simple least square analysis using all the pixels of both
images, and also show that it is possible to fit the differential background
variation at the same time. We also show that PSF variations can also be
easily handled by the method. 
        To demonstrate the practical efficiency of the method, we analyzed
some images from a Galactic Bulge field monitored by the OGLE II project. We
find that the residuals in the subtracted images are very close to the
photon noise expectations. We also present some light curves of variable
stars, and show that, despite high crowding levels, we get an error
distribution close to that expected from photon noise alone. We thus
demonstrate that nearly optimal differential photometry can be achieved even
in very crowded fields. We suggest that this algorithm might be particularly
important for microlensing surveys, where the photometric accuracy and
completeness levels could be very significantly improved by using this method. "

"Clear Skies"
Glenn G. 
Glenn Gombert <gleng@infinet.com>