73 citations · 89 across the 12 of their papers we have counts for
4 papers · 1 filter
Optimizing Photometric Redshift Training Sets I: Efficient Compression of the Galaxy Color-Redshift Relation with UMAP
Finian Ashmead, Jeffrey A. Newman, Brett H. Andrews +4
Spectroscopic datasets are essential for training and calibrating photometric redshift (photo-) methods. However, spectroscopic redshifts (spec-'s) constitute a biased and sp…
Photometric Redshift Estimation for Rubin Observatory Data Preview 1 with Redshift Assessment Infrastructure Layers (RAIL)
T. Zhang, E. Charles, J. F. Crenshaw +87
We present the first systematic analysis of photometric redshifts (photo-z) estimated from the Rubin Observatory Data Preview 1 (DP1) data taken with the Legacy Survey of Space and…
Forecasting the Impact of Source Galaxy Photometric Redshift Uncertainties on the LSST pt Analysis
Tianqing Zhang, Husni Almoubayyed, Rachel Mandelbaum +7
Photometric redshifts of the source galaxies are a key source of systematic uncertainty in the Rubin Observatory Legacy Survey of Space and Time (LSST)'s galaxy clustering and weak…
Deep Learning Improves Photometric Redshifts in All Regions of Color Space
Emma R. Moran, Brett H. Andrews, Jeffrey A. Newman +1
Photometric redshifts (photo-'s) are crucial for the cosmology, galaxy evolution, and transient science drivers of next-generation imaging facilities like the Euclid Mission, th…