3 papers
astro-ph.IM2026
Diagnosing the Effects of Spectroscopic Training Set Imperfection on Photometric Redshift Performance
Alice Crafford, Alex I. Malz, Tianqing Zhang +11
Most LSST extragalactic science will rely on photometric redshifts (photo-) to extract distance information for the galaxies. However, an incomplete or non-representative traini…
astro-ph.IM2025
Variability-finding in Rubin Data Preview 1 with LSDB
Konstantin Malanchev, Melissa DeLucchi, Neven Caplar +56
The Vera C. Rubin Observatory recently released Data Preview 1 (DP1) in advance of the upcoming Legacy Survey of Space and Time (LSST), which will enable boundless discoveries in t…
astro-ph.IM2024
DeepDISC-photoz: Deep Learning-Based Photometric Redshift Estimation for Rubin LSST
Grant Merz, Xin Liu, Samuel Schmidt +11
Photometric redshifts will be a key data product for the Rubin Observatory Legacy Survey of Space and Time (LSST) as well as for future ground and space-based surveys. The need for…