Forward modeling fluctuations in the DESI LRGs target sample using image simulations
Hui Kong, Ashley J. Ross, Klaus Honscheid, Dustin Lang, Anna Porredon,, Arnaud de Mattia, Mehdi Rezaie, Rongpu Zhou, Edward Schlafly, John Moustakas,, Alberto Rosado-Marin, Jessica Nicole Aguilar, Steven Ahlen, David Brooks,, Edmond Chaussidon, Todd Claybaugh, Shaun Cole

TL;DR
This study uses advanced image simulations to understand and predict the impact of imaging systematics on the DESI LRG sample, revealing key dependencies and discrepancies that inform future mitigation strategies.
Contribution
The paper extends the Obiwan simulation pipeline to include WISE infrared data, enabling comprehensive modeling of DESI LRG target selection and systematics.
Findings
Simulations predict trends with depth and brightness observed in data.
Faint LRGs significantly influence imaging systematics.
Galactic extinction trends suggest contamination from large-scale structure effects.
Abstract
We use the forward modeling pipeline, Obiwan, to study the imaging systematics of the Luminous Red Galaxies (LRGs) targeted by the Dark Energy Spectroscopic Instrument (DESI). We update the Obiwan pipeline, which had previously been developed to simulate the optical images used to target DESI data, to further simulate WISE images in the infrared. This addition makes it possible to simulate the DESI LRGs sample, which utilizes WISE data in the target selection. Deep DESI imaging data combined with a method to account for biases in their shapes is used to define a truth sample of potential LRG targets. We simulate a total of 15 million galaxies to obtain a simulated LRG sample (Obiwan LRGs) that predicts the variations in target density due to imaging properties. We find that the simulations predict the trends with depth observed in the data, including how they depend on the intrinsic…
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