Mathematics – Logic
Scientific paper
May 2009
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2009aas...21431602l&link_type=abstract
American Astronomical Society, AAS Meeting #214, #316.02; Bulletin of the American Astronomical Society, Vol. 41, p.761
Mathematics
Logic
Scientific paper
The robotic Lick Observatory Supernova Search (LOSS), conducted with the 0.76-m Katzman Automatic Imaging Telescope (KAIT), has been the world's most successful nearby supernova search engine over the past decade. For the over 1,000 supernovae (SNe) discovered in the LOSS sample galaxies until the end of the year 2008, we used an optimal subsample of 728 SNe to derive the SN rate in the local universe. The LOSS galaxy sample consists of about 14,000 fields, imaged with temporal frequencies that typically range from 2 to 10 days. Detailed logs of the observations and search parameters have allowed us to determine the most accurate nearby SN rates since the study of Cappellaro, Evans, & Turatto (1999, A&A, 351, 459).
We first selected 140 SNe, discovered in a distance-limited sample, to construct the observed luminosity functions for various types of SNe. Photometry for each of these 140 SNe was collected, their peak magnitudes were measured, and their completeness in the survey was calculated. The resulting luminosity functions are the first of their kind, and provide significant improvement to Zwicky's well-known control-time calculation for the SN rates.
We derived SN rates for various types of SNe, in galaxies of different Hubble types and B-K colors. Our rates agree well with previous measurements, but provide significant improvement in precision, more morphological and color bins, and fewer observational biases. We found that the SN rates, after linear normalization by the size of the galaxies, still have a significant correlation with the galaxy size, in the sense that smaller galaxies have a higher SN rate per unit luminosity or mass. The volumetric SN rates are as follows (in units of 10^-4 SN Mpc^-3 yr^-1): 0.28 +/- 0.03 for SNe Ia, 0.20 +/- 0.03 for SNe Ibc, and 0.40 +/- 0.05 for SNe II.
Filippenko Alexei
Leaman Jesse F.
Li Wangrong
LOSS
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