Kavli Affiliate: Hu Zhan
| First 5 Authors: Minglin Wang, Yan Gong, Furen Deng, Haitao Miao, Xuelei Chen
| Summary:
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 $isimeq26$ 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.
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