Presentation #318.02 in the session Computation, Data Handling, Image Analysis II.
One of the Nancy Grace Roman Space Telescope’s objectives is to elucidate the nature of dark energy using Type Ia Supernovae (SNe Ia). Proposed surveys will use a combination of wide-field imaging and slitless spectroscopy, but since SNe Ia spectra will be contaminated by their host galaxies, removing the host galaxy spectrum accurately is important. A clean, uncontaminated SN Ia spectrum improves the accuracy of the determination of luminosity distances as well as the intrinsic brightness of the supernova, and hence, better determination of the dark energy equation of state parameters, w0 and wa.
To this end, we have developed a datacube reconstruction algorithm that uses the host galaxy spectra observed at various roll angles during the course of the survey. For a supernova in this galaxy, the reconstructed datacube can then be used for host galaxy subtraction of the SN+galaxy spectra. We generate simulated Roman data using SDSS images and redshift-dependent star formation models to create synthetic datacubes of plausible galaxies at various redshifts. These datacubes are then convolved with the Roman Space Telescope optical throughputs using the most current characterization of the optical system and detectors. We use a realistic noise model based on the known properties of the detector.
In this presentation we show results from our analysis of the resulting host-galaxy-subtracted noisy-spectra of SNe Ia and evaluate how well we can recover the SNe Ia spectra given the statistical and systematic uncertainties of different survey observing strategies.