Computer Science
Scientific paper
Aug 2006
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2006iaujd...9e..39m&link_type=abstract
Supernovae: One Millennium After SN1006, 26th meeting of the IAU, Joint Discussion 9, 17-18 August 2006, Prague, Czech Republic,
Computer Science
Scientific paper
We present a supernova search pipeline developed for our deep imaging survey with VLT/VIMOS aiming at detecting supernovae at a redshift range of 0 to ~1.3. The pipeline consists of four main tasks: aligning images; subtracting images (using a slightly modified ISIS2.2 code, Alard 2000); detecting variable sources; and photometry of the detected sources. The detection efficiency and the photometric accuracy have been studied by placing artificial stars in the science images (within and outside galaxies) and running the simulated frames through the pipeline. We have investigated how these two observables are affected by: (i) variation in the input parameters to the four main tasks; and (ii) observational quality of the data. We find that many of the pipeline parameters are important. The most crucial factor is found to be how the PSF matching convolution kernels for the images are computed. In addition both the SN detection efficiency and the photometric accuracy are sensitive to the position of the SN within its host galaxy. The seeing of the SN search images is found to mainly affect the detection efficiency.
Fransson Claes
Mattila Seppo
Melinder Jens
Ostlin Goeran
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