Dark Energy Survey Y3 results: blending shear and redshift biases in image simulations. Issue 3 (9th October 2021)
- Record Type:
- Journal Article
- Title:
- Dark Energy Survey Y3 results: blending shear and redshift biases in image simulations. Issue 3 (9th October 2021)
- Main Title:
- Dark Energy Survey Y3 results: blending shear and redshift biases in image simulations
- Authors:
- MacCrann, N
Becker, M R
McCullough, J
Amon, A
Gruen, D
Jarvis, M
Choi, A
Troxel, M A
Sheldon, E
Yanny, B
Herner, K
Dodelson, S
Zuntz, J
Eckert, K
Rollins, R P
Varga, T N
Bernstein, G M
Gruendl, R A
Harrison, I
Hartley, W G
Sevilla-Noarbe, I
Pieres, A
Bridle, S L
Myles, J
Alarcon, A
Everett, S
Sánchez, C
Huff, E M
Tarsitano, F
Gatti, M
Secco, L F
Abbott, T M C
Aguena, M
Allam, S
Annis, J
Bacon, D
Bertin, E
Brooks, D
Burke, D L
Carnero Rosell, A
Carrasco Kind, M
Carretero, J
Costanzi, M
Crocce, M
Pereira, M E S
De Vicente, J
Desai, S
Diehl, H T
Dietrich, J P
Doel, P
Eifler, T F
Ferrero, I
Ferté, A
Flaugher, B
Fosalba, P
Frieman, J
García-Bellido, J
Gaztanaga, E
Gerdes, D W
Giannantonio, T
Gschwend, J
Gutierrez, G
Hinton, S R
Hollowood, D L
Honscheid, K
James, D J
Lahav, O
Lima, M
Maia, M A G
March, M
Marshall, J L
Martini, P
Melchior, P
Menanteau, F
Miquel, R
Mohr, J J
Morgan, R
Muir, J
Ogando, R L C
Palmese, A
Paz-Chinchón, F
Plazas, A A
Rodriguez-Monroy, M
Roodman, A
Samuroff, S
Sanchez, E
Scarpine, V
Serrano, S
Smith, M
Soares-Santos, M
Suchyta, E
Swanson, M E C
Tarle, G
Thomas, D
To, C
Wilkinson, R D
… (more) - Abstract:
- ABSTRACT: As the statistical power of galaxy weak lensing reaches per cent level precision, large, realistic, and robust simulations are required to calibrate observational systematics, especially given the increased importance of object blending as survey depths increase. To capture the coupled effects of blending in both shear and photometric redshift calibration, we define the effective redshift distribution for lensing, n γ ( z ), and describe how to estimate it using image simulations. We use an extensive suite of tailored image simulations to characterize the performance of the shear estimation pipeline applied to the Dark Energy Survey (DES) Year 3 data set. We describe the multiband, multi-epoch simulations, and demonstrate their high level of realism through comparisons to the real DES data. We isolate the effects that generate shear calibration biases by running variations on our fiducial simulation, and find that blending-related effects are the dominant contribution to the mean multiplicative bias of approximately $-2{{\ \rm per\ cent}}$ . By generating simulations with input shear signals that vary with redshift, we calibrate biases in our estimation of the effective redshift distribution, and demonstrate the importance of this approach when blending is present. We provide corrected effective redshift distributions that incorporate statistical and systematic uncertainties, ready for use in DES Year 3 weak lensing analyses.
- Is Part Of:
- Monthly notices of the Royal Astronomical Society. Volume 509:Issue 3(2022)
- Journal:
- Monthly notices of the Royal Astronomical Society
- Issue:
- Volume 509:Issue 3(2022)
- Issue Display:
- Volume 509, Issue 3 (2022)
- Year:
- 2022
- Volume:
- 509
- Issue:
- 3
- Issue Sort Value:
- 2022-0509-0003-0000
- Page Start:
- 3371
- Page End:
- 3394
- Publication Date:
- 2021-10-09
- Subjects:
- gravitational lensing: weak -- large-scale structure of Universe
Astronomy -- Periodicals
Periodicals
520.5 - Journal URLs:
- http://mnras.oxfordjournals.org/ ↗
http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-2966 ↗
http://www.blackwell-synergy.com/issuelist.asp?journal=mnr ↗
http://www.blackwell-synergy.com/loi/mnr ↗
http://ukcatalogue.oup.com/ ↗ - DOI:
- 10.1093/mnras/stab2870 ↗
- Languages:
- English
- ISSNs:
- 0035-8711
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 5943.000000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 19941.xml