Simulating Photo-z Quality for Rubin Observatory Survey Strategies

Accurate photometric redshift (photo-z) estimates are essential to the cosmological science goals of the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). In this talk we will present the Color-Matched Nearest-Neighbors (CMNN) Estimator, which is publicly available via GitHub, and demonstrate how to use it to simulate and evaluate photo-z results for various Rubin Observatory survey strategies that yield different co-added depths in the six filters, ugrizy. We will also show results of such analyses for a set of proposed observing strategies, and for simulations that incorporate overlap with space-based near-ultraviolet and near-infrared sky surveys.