Steven Rodney with John Tonry (Univ. of Hawaii, IfA)
We present motivation and initial results from our HST archivalresearch program: searching for undetected supernovae in the GOODSfields. One extremely important constraint on theoretical models ofType Ia Supernova (SNIa) progenitors is the evolution of the SNIa rate(SNR) as a function of redshift. The SNR(z) can distinguish betweencompeting progenitor models and help to unveil the mystery of theseimportant objects. The most important (and difficult) component ofthis measurement is in the highest redshift bins, at z>1, whichrequires the unique observing tools of the Hubble Space Telescope(HST). We have revisited the Hubble Space Telescope's GreatObservatories Origins Deep Survey (GOODS) data to improve the accuracyand precision of the high-z SNIa rate measurement. The high redshiftSNe discovered in the GOODS fields were originally detected usingvisual inspection of difference images made using the traditional\"image - template\" search srategy (Riess et al, 2004,2006). Thesesearches revealed a dearth of faint, high-z SNIa - but left open thepossibility of objects that were missed due to the constraints ofearly detection and strong identification to direct the follow-upobservations. In revisiting the GOODS fields, we can now exploit thefull potential of this dataset by utilizing fully automated detectiontechniques that employ the NN2 difference photometry algorithm andlarge numbers of synthetic transients for error estimation.
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