Dark Energy Survey Year 3 results: measuring the survey transfer function with Balrog

Everett, S, Yanny, B, Kuropatkin, N, Huff, E M, Zhang, Y, Myles, J, Masegian, A, Elvin-Poole, J, Allam, S, Bernstein, G M, Sevilla-Noarbe, I, Splettstoesser, M, Bhargava, S, Romer, A K, Wilkinson, R D, DES Collaboration, and others, (2022) Dark Energy Survey Year 3 results: measuring the survey transfer function with Balrog. Astrophysical Journal, Supplement Series, 258 (1). a15 1-46. ISSN 0067-0049

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Abstract

We describe an updated calibration and diagnostic framework, Balrog, used to directly sample the selection and photometric biases of the Dark Energy Survey (DES) Year 3 (Y3) data set. We systematically inject onto the single-epoch images of a random 20% subset of the DES footprint an ensemble of nearly 30 million realistic galaxy models derived from DES Deep Field observations. These augmented images are analyzed in parallel with the original data to automatically inherit measurement systematics that are often too difficult to capture with generative models. The resulting object catalog is a Monte Carlo sampling of the DES transfer function and is used as a powerful diagnostic and calibration tool for a variety of DES Y3 science, particularly for the calibration of the photometric redshifts of distant "source"galaxies and magnification biases of nearer "lens"galaxies. The recovered Balrog injections are shown to closely match the photometric property distributions of the Y3 GOLD catalog, particularly in color, and capture the number density fluctuations from observing conditions of the real data within 1% for a typical galaxy sample. We find that Y3 colors are extremely well calibrated, typically within ∼1-8 mmag, but for a small subset of objects, we detect significant magnitude biases correlated with large overestimates of the injected object size due to proximity effects and blending. We discuss approaches to extend the current methodology to capture more aspects of the transfer function and reach full coverage of the survey footprint for future analyses.

Item Type: Article
Schools and Departments: School of Mathematical and Physical Sciences > Physics and Astronomy
SWORD Depositor: Mx Elements Account
Depositing User: Mx Elements Account
Date Deposited: 20 Apr 2022 08:53
Last Modified: 27 Apr 2023 09:47
URI: http://sro.sussex.ac.uk/id/eprint/105338

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