Cosmological Prediction of the CSST Ultra Deep Field Type Ia Supernova Photometric Survey

Abstract: Type Ia supernova (SN Ia) as a standard candle is an ideal tool to measure cosmic distance and expansion history of the Universe. Here we investigate the SN Ia photometric measurement in the China Space Station Telescope Ultra Deep Field (CSST-UDF) survey, and study the constraint power on the cosmological parameters, such as the equation of state of dark energy. The CSST-UDF survey is expected to cover a 9 deg$^2$ sky area in two years with 250 s $\times$ 60 exposures for each band. The magnitude limit can reach $i\simeq26$ AB mag for 5$\sigma$ point source detection with a single exposure. We generate light curve mock data for SNe Ia and different types of core-collapse supernovae (CCSNe). {\tt SNCosmo} is chosen as the framework by utilizing the SALT3 model to simulate SN Ia data. After selecting high-quality data and fitting the light curves, we derive the light curve parameters and identify CCSNe as contamination, resulting in $\sim2200$ SNe with a $\sim7\%$ CCSN contamination rate. We adopt a calibration method similar to Chauvenet's criterion, and apply it to the distance modulus data to further reduce the contamination. We find that this method is effective and can suppress the contamination fraction to $\sim3.5\%$ with 2012 SNe Ia and 73 CCSNe. In the cosmological fitting stage, we did not distinguish between SNe Ia and CCSNe. We find that the constraint accuracies on $\Omega_{\rm M}$, $\Omega_{\Lambda}$ and $w$ are about two times better than the current SN surveys, and it could be further improved by a factor of $\sim$1.4 if including the baryon acoustic oscillation (BAO) data from the CSST spectroscopic wide-field galaxy survey.