  The Legacy Survey of Space and Time (LSST) will revolutionize Time Domain
Astronomy by detecting millions of transients. In particular, it is expected to
increment the number of type Ia supernovae (SNIa) of a factor of 100 compared
to existing samples up to z~1.2. Such a high number of events will dramatically
reduce statistical uncertainties in the analysis of SNIa properties and rates.
However, the impact of all other sources of uncertainty on the measurement must
still be evaluated. The comprehension and reduction of such uncertainties will
be fundamental both for cosmology and stellar evolution studies, as measuring
the SNIa rate can put constraints on the evolutionary scenarios of different
SNIa progenitors. We use simulated data from the DESC Data Challenge 2 (DC2)
and LSST Data Preview 0 (DP0) to measure the SNIa rate on a 15 deg2 region of
the Wide-Fast-Deep area. We select a sample of SN candidates detected on
difference images, associate them to the host galaxy, and retrieve their
photometric redshifts (z-phot). Then, we test different light curves
classification methods, with and without redshift priors. We discuss how the
distribution in redshift measured for the SN candidates changes according to
the selected host galaxy and redshift estimate. We measure the SNIa rate
analyzing the impact of uncertainties due to z-phot, host galaxy association
and classification on the distribution in redshift of the starting sample. We
found a 17% average lost fraction of SNIa with respect to the simulated sample.
As 10% of the bias is due to the uncertainty on the z-phot alone (which also
affects classification when used as a prior), it results to be the major source
of uncertainty. We discuss possible reduction of the errors in the measurement
of the SNIa rate, including synergies with other surveys, which may help using
the rate to discriminate different progenitor models.
