Utilizing Type Ia Supernovae in a Large, Fast, Imaging Survey to   Constrain Dark Energy
  We study the utility of a large sample of type Ia supernovae that might be observed in an imaging survey that rapidly scans a large fraction of the sky for constraining dark energy. We consider information from the traditional luminosity distance test as well as the spread in SNeIa fluxes at fixed redshift induced by gravitational lensing. We include a treatment of photometric redshift uncertainties in our analysis. Our primary result is that the information contained in the mean distance moduli of SNeIa and the dispersion among SNeIa distance moduli complement each other, breaking a degeneracy between the present dark energy equation of state and its time variation without the need for a high-redshift supernova sample. To address photometric redshift uncertainties, we present dark energy constraints as a function of the size of an external set of spectroscopically-observed SNeIa that may be used for redshift calibration, nspec. We find that an imaging survey can constrain the dark energy equation of state at the epoch where it is best constrained with a 1-sigma error of sigma(wpiv)~0.03-0.09$, depending upon various assumptions. In addition, the marginal improvement in the error sigma(wpiv) from an increase in the spectroscopic calibration sample drops once nspec ~ 10^3. This result is important because it is of the order of the size of calibration samples likely to be compiled in the coming decade and because, for samples of this size, the spectroscopic and imaging surveys individually place comparable constraints on the dark energy equation of state. In all cases, it is best to calibrate photometric redshifts with a set of spectroscopically-observed SNeIa with relatively more objects at high redshift than the parent sample of imaging SNeIa. 
Andrew R. Zentner and Suman Bhattacharya (University of Pittsburgh)