Cosmology Requirements on Supernova Photometric Redshift Systematics for Rubin LSST and Roman Space Telescope
arXiv:2011.08206 · doi:10.1103/PhysRevD.103.023524
Abstract
Some million Type Ia supernovae (SN) will be discovered and monitored during upcoming wide area time domain surveys such as the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). For cosmological use, accurate redshifts are needed among other characteristics; however the vast majority of the SN will not have spectroscopic redshifts, even for their host galaxies, only photometric redshifts. We assess the redshift systematic control necessary for robust cosmology. Based on the photometric vs true redshift relation generated by machine learning applied to a simulation of 500,000 galaxies as observed with LSST quality, we quantify requirements on systematics in the mean relation and in the outlier fraction and deviance so as not to bias dark energy cosmological inference. Certain redshift ranges are particularly sensitive, motivating spectroscopic followup of SN at and around -0.6. Including Nancy Grace Roman Space Telescope near infrared bands in the simulation, we reanalyze the constraints, finding improvements at high redshift but little at the low redshifts where systematics lead to strong cosmology bias. We identify a complete spectroscopic survey of SN host galaxies for as a highly favored element for robust SN cosmology.
Accepted in PRD. 9 pages, 11 figures
References in corpus (7)
- The Zwicky Transient Facility: System Overview, Performance, and First Results
- Photometric Redshifts with the LSST: Evaluating Survey Observing Strategies
- Complementarity of Peculiar Velocity Surveys and Redshift Space Distortions for Testing Gravity
- WFIRST: The Essential Cosmology Space Observatory for the Coming Decade
- Photometric Redshifts with the LSST II: The Impact of Near-Infrared and Near-Ultraviolet Photometry
- Testing Gravity Using Type Ia Supernovae Discovered by Next-Generation Wide-Field Imaging Surveys
- Wide-field Multi-object Spectroscopy to Enhance Dark Energy Science from LSST