Dark Energy Survey Year 3 Results: Measuring the Survey Transfer Function with Balrog Academic Article uri icon

abstract

  • 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 18 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.

published proceedings

  • ASTROPHYSICAL JOURNAL SUPPLEMENT SERIES

altmetric score

  • 9.33

author list (cited authors)

  • Everett, S., Yanny, B., Kuropatkin, N., Huff, E. M., Zhang, Y., Myles, J., ... Wilkinson, R. D.

citation count

  • 16

complete list of authors

  • Everett, S||Yanny, B||Kuropatkin, N||Huff, EM||Zhang, Y||Myles, J||Masegian, A||Elvin-Poole, J||Allam, S||Bernstein, GM||Sevilla-Noarbe, I||Splettstoesser, M||Sheldon, E||Jarvis, M||Amon, A||Harrison, I||Choi, A||Hartley, WG||Alarcon, A||Sánchez, C||Gruen, D||Eckert, K||Prat, J||Tabbutt, M||Busti, V||Becker, MR||MacCrann, N||Diehl, HT||Tucker, DL||Bertin, E||Jeltema, T||Drlica-Wagner, A||Gruendl, RA||Bechtol, K||Rosell, A Carnero||Abbott, TMC||Aguena, M||Annis, J||Bacon, D||Bhargava, S||Brooks, D||Burke, DL||Kind, M Carrasco||Carretero, J||Castander, FJ||Conselice, C||Costanzi, M||da Costa, LN||Pereira, MES||De Vicente, J||DeRose, J||Desai, S||Eifler, TF||Evrard, AE||Ferrero, I||Fosalba, P||Frieman, J||García-Bellido, J||Gaztanaga, E||Gerdes, DW||Gutierrez, G||Hinton, SR||Hollowood, DL||Honscheid, K||Huterer, D||James, DJ||Kent, S||Krause, E||Kuehn, K||Lahav, O||Lima, M||Lin, H||Maia, MAG||Marshall, JL||Melchior, P||Menanteau, F||Miquel, R||Mohr, JJ||Morgan, R||Muir, J||Ogando, RLC||Palmese, A||Paz-Chinchón, F||Plazas, AA||Rodriguez-Monroy, M||Romer, AK||Roodman, A||Sanchez, E||Scarpine, V||Serrano, S||Smith, M||Soares-Santos, M||Suchyta, E||Swanson, MEC||Tarle, G||To, C||Troxel, MA||Varga, TN||Weller, J||Wilkinson, RD

publication date

  • January 2022