Decelerating and Dustfree: Efficient Dark Energy Studies with Supernovae and Clusters

Details Decelerating and Dustfree: Efficient Dark Energy Studies with Supernovae and Clusters Decelerating and Dustfree: Efficient Dark Energy Studies with Supernovae and Clusters

Jul 2005

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2005hst..prop10496p&link_type=abstract

HST Proposal ID #10496

Physics

1

Hst Proposal Id #10496 Cosmology

Scientific paper

We propose a novel HST approach to obtain a dramatically more useful "dust free" Type Ia supernovae {SNe Ia} dataset than available with the previous GOODS searches. Moreover, this approach provides a strikingly more efficient search-and-follow-up that is primarily pre-scheduled. The resulting dark energy measurements do not share the major systematic uncertainty at these redshifts, that of the extinction correction with a prior. By targeting massive galaxy clusters at z > 1 we obtain a five-times higher efficiency in detection of Type Ia supernovae in ellipticals, providing a well-understood host galaxy environment. These same deep cluster images then also yield fundamental calibrations required for future weak lensing and Sunyaev-Zel'dovich measurements of dark energy, as well as an entire program of cluster studies. The data will make possible a factor of two improvement on supernova constraints on dark energy time variation, and much larger improvement in systematic uncertainty. They will provide both a cluster dataset and a SN Ia dataset that will be a longstanding scientific resource.

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