8 papers
Propagating data-driven galaxy redshift distribution uncertainties in 32-pt analyses
Jaime Ruiz-Zapatero, Qianjun Hang, Yun-Hao Zhang +7
Uncertainties in the radial distribution of galaxies, , are one of the major contributions to the error budget of early Stage-IV galaxy survey analy…
Modeling of the diffuse background produced by the Vera C. Rubin Observatory M2 baffle scattered light
Alessio Taranto, Gabriele Rodeghiero, Luca Rosignoli +58
The Vera C. Rubin Observatory, with its unprecedented field of view and fast focal ratio, will survey the entire sky every 3.5 nights. This unique capacity requires dealing with of…
Redshift Assessment Infrastructure Layers (RAIL): Rubin-era photometric redshift stress-testing and at-scale production
The RAIL Team, Jan Luca van den Busch, Eric Charles +30
Virtually all extragalactic use cases of the Vera C. Rubin Observatory's Legacy Survey of Space and Time (LSST) require the use of galaxy redshift information, yet the vast majorit…
Calibrating redshift distributions at with Lyman- forest cross-correlations
Qianjun Hang, Laura Casas, William d'Assignies +3
We explore the feasibility of using Lyman- (Ly) forests to calibrate the ensemble redshift distribution of the high-redshift tail () of photometric galaxies. We use…
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…
Biasing from galaxy trough and peak profiles with the DES Y3 redMaGiC galaxies and the weak lensing mass map
Q. Hang, N. Jeffrey, L. Whiteway +83
We measure the correspondence between the distribution of galaxies and matter around troughs and peaks in the projected galaxy density, by comparing \texttt{redMaGiC} galaxies ($0.…