Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations

N. MacCrann; M. R. Becker; J. McCullough; A. Amon; D. Gruen; M. Jarvis; A. Choi; M. A. Troxel; E. Sheldon; B. Yanny; K. Herner; S. Dodelson; J. Zuntz; K. Eckert; R. P. Rollins; T. N. Varga; G. M. Bernstein; R. A. Gruendl; I. Harrison; W. G. Hartley; I. Sevilla-Noarbe; A. Pieres; S. L. Bridle; J. Myles; A. Alarcon; S. Everett; C. Sánchez; E. M. Huff; F. Tarsitano; M. Gatti; L. F. Secco; T. M.C. Abbott; M. Aguena; S. Allam; J. Annis; D. Bacon; E. Bertin; D. Brooks; D. L. Burke; A. Carnero Rosell; M. Carrasco Kind; J. Carretero; M. Costanzi; M. Crocce; M. E.S. Pereira; J. De Vicente; S. Desai; H. T. Diehl; J. P. Dietrich; P. Doel; T. F. Eifler; I. Ferrero; A. Ferté; B. Flaugher; P. Fosalba; J. Frieman; J. García-Bellido; E. Gaztanaga; D. W. Gerdes; T. Giannantonio; J. Gschwend; G. Gutierrez; S. R. Hinton; D. L. Hollowood; K. Honscheid; D. J. James; O. Lahav; M. Lima; M. A.G. Maia; M. March; J. L. Marshall; P. Martini; P. Melchior; F. Menanteau; R. Miquel; J. J. Mohr; R. Morgan; J. Muir; R. L.C. Ogando; A. Palmese; F. Paz-Chinchón; A. A. Plazas; M. Rodriguez-Monroy; A. Roodman; S. Samuroff; E. Sanchez; V. Scarpine; S. Serrano; M. Smith; M. Soares-Santos; E. Suchyta; M. E.C. Swanson; G. Tarle; D. Thomas; C. To; R. D. Wilkinson

doi:10.1093/mnras/stab2870

Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations

N. MacCrann, M. R. Becker, J. McCullough, A. Amon, D. Gruen, M. Jarvis, A. Choi, M. A. Troxel, E. Sheldon, B. Yanny, K. Herner, S. Dodelson, J. Zuntz, K. Eckert, R. P. Rollins, T. N. Varga, G. M. Bernstein, R. A. Gruendl, I. Harrison, W. G. HartleyI. Sevilla-Noarbe, A. Pieres, S. L. Bridle, J. Myles, A. Alarcon, S. Everett, C. Sánchez, E. M. Huff, F. Tarsitano, M. Gatti, L. F. Secco, T. M.C. Abbott, M. Aguena, S. Allam, J. Annis, D. Bacon, E. Bertin, D. Brooks, D. L. Burke, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, M. Costanzi, M. Crocce, M. E.S. Pereira, J. De Vicente, S. Desai, H. T. Diehl, J. P. Dietrich, P. Doel, T. F. Eifler, I. Ferrero, A. Ferté, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, E. Gaztanaga, D. W. Gerdes, T. Giannantonio, J. Gschwend, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, O. Lahav, M. Lima, M. A.G. Maia, M. March, J. L. Marshall, P. Martini, P. Melchior, F. Menanteau, R. Miquel, J. J. Mohr, R. Morgan, J. Muir, R. L.C. Ogando, A. Palmese, F. Paz-Chinchón, A. A. Plazas, M. Rodriguez-Monroy, A. Roodman, S. Samuroff, E. Sanchez, V. Scarpine, S. Serrano, M. Smith, M. Soares-Santos, E. Suchyta, M. E.C. Swanson, G. Tarle, D. Thomas, C. To, R. D. Wilkinson

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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, nγ(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.

Original language	English
Pages (from-to)	3371-3394
Number of pages	24
Journal	Monthly Notices of the Royal Astronomical Society
Volume	509
Issue number	3
DOIs	https://doi.org/10.1093/mnras/stab2870
State	Published - Jan 1 2022

Funding

Funders	Funder number
Seventh Framework Programme	681431, 1138766, 240672, 306478, 851274, 291329

Keywords

gravitational lensing: weak
large-scale structure of Universe

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10.1093/mnras/stab2870

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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., ... Wilkinson, R. D. (2022). Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations. Monthly Notices of the Royal Astronomical Society, 509(3), 3371-3394. https://doi.org/10.1093/mnras/stab2870

@article{b2124e289e0d4622913438e040f1534c,

title = "Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations",

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, nγ(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.",

keywords = "gravitational lensing: weak, large-scale structure of Universe",

author = "N. MacCrann and Becker, {M. R.} and J. McCullough and A. Amon and D. Gruen and M. Jarvis and A. Choi and Troxel, {M. A.} and E. Sheldon and B. Yanny and K. Herner and S. Dodelson and J. Zuntz and K. Eckert and Rollins, {R. P.} and Varga, {T. N.} and Bernstein, {G. M.} and Gruendl, {R. A.} and I. Harrison and Hartley, {W. G.} and I. Sevilla-Noarbe and A. Pieres and Bridle, {S. L.} and J. Myles and A. Alarcon and S. Everett and C. S{\'a}nchez and Huff, {E. M.} and F. Tarsitano and M. Gatti and Secco, {L. F.} and Abbott, {T. M.C.} and M. Aguena and S. Allam and J. Annis and D. Bacon and E. Bertin and D. Brooks and Burke, {D. L.} and {Carnero Rosell}, A. and {Carrasco Kind}, M. and J. Carretero and M. Costanzi and M. Crocce and Pereira, {M. E.S.} and {De Vicente}, J. and S. Desai and Diehl, {H. T.} and Dietrich, {J. P.} and P. Doel and Eifler, {T. F.} and I. Ferrero and A. Fert{\'e} and B. Flaugher and P. Fosalba and J. Frieman and J. Garc{\'i}a-Bellido and E. Gaztanaga and Gerdes, {D. W.} and T. Giannantonio and J. Gschwend and G. Gutierrez and Hinton, {S. R.} and Hollowood, {D. L.} and K. Honscheid and James, {D. J.} and O. Lahav and M. Lima and Maia, {M. A.G.} and M. March and Marshall, {J. L.} and P. Martini and P. Melchior and F. Menanteau and R. Miquel and Mohr, {J. J.} and R. Morgan and J. Muir and Ogando, {R. L.C.} and A. Palmese and F. Paz-Chinch{\'o}n and Plazas, {A. A.} and M. Rodriguez-Monroy and A. Roodman and S. Samuroff and E. Sanchez and V. Scarpine and S. Serrano and M. Smith and M. Soares-Santos and E. Suchyta and Swanson, {M. E.C.} and G. Tarle and D. Thomas and C. To and Wilkinson, {R. D.}",

note = "Publisher Copyright: {\textcopyright} 2021 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.",

year = "2022",

month = jan,

day = "1",

doi = "10.1093/mnras/stab2870",

language = "English",

volume = "509",

pages = "3371--3394",

journal = "Monthly Notices of the Royal Astronomical Society",

issn = "0035-8711",

publisher = "Oxford University Press",

number = "3",

}

MacCrann, N, Becker, MR, McCullough, J, Amon, A, Gruen, D, Jarvis, M, Choi, A, Troxel, MA, Sheldon, E, Yanny, B, Herner, K, Dodelson, S, Zuntz, J, Eckert, K, Rollins, RP, Varga, TN, Bernstein, GM, Gruendl, RA, Harrison, I, Hartley, WG, Sevilla-Noarbe, I, Pieres, A, Bridle, SL, Myles, J, Alarcon, A, Everett, S, Sánchez, C, Huff, EM, Tarsitano, F, Gatti, M, Secco, LF, Abbott, TMC, Aguena, M, Allam, S, Annis, J, Bacon, D, Bertin, E, Brooks, D, Burke, DL, Carnero Rosell, A, Carrasco Kind, M, Carretero, J, Costanzi, M, Crocce, M, Pereira, MES, De Vicente, J, Desai, S, Diehl, HT, Dietrich, JP, Doel, P, Eifler, TF, Ferrero, I, Ferté, A, Flaugher, B, Fosalba, P, Frieman, J, García-Bellido, J, Gaztanaga, E, Gerdes, DW, Giannantonio, T, Gschwend, J, Gutierrez, G, Hinton, SR, Hollowood, DL, Honscheid, K, James, DJ, Lahav, O, Lima, M, Maia, MAG, March, M, Marshall, JL, Martini, P, Melchior, P, Menanteau, F, Miquel, R, Mohr, JJ, Morgan, R, Muir, J, Ogando, RLC, Palmese, A, Paz-Chinchón, F, Plazas, AA, Rodriguez-Monroy, M, Roodman, A, Samuroff, S, Sanchez, E, Scarpine, V, Serrano, S, Smith, M, Soares-Santos, M, Suchyta, E, Swanson, MEC, Tarle, G, Thomas, D, To, C & Wilkinson, RD 2022, 'Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations', Monthly Notices of the Royal Astronomical Society, vol. 509, no. 3, pp. 3371-3394. https://doi.org/10.1093/mnras/stab2870

TY - JOUR

T1 - Dark Energy Survey Y3 results

T2 - Blending shear and redshift biases in image simulations

AU - MacCrann, N.

AU - Becker, M. R.

AU - McCullough, J.

AU - Amon, A.

AU - Gruen, D.

AU - Jarvis, M.

AU - Choi, A.

AU - Troxel, M. A.

AU - Sheldon, E.

AU - Yanny, B.

AU - Herner, K.

AU - Dodelson, S.

AU - Zuntz, J.

AU - Eckert, K.

AU - Rollins, R. P.

AU - Varga, T. N.

AU - Bernstein, G. M.

AU - Gruendl, R. A.

AU - Harrison, I.

AU - Hartley, W. G.

AU - Sevilla-Noarbe, I.

AU - Pieres, A.

AU - Bridle, S. L.

AU - Myles, J.

AU - Alarcon, A.

AU - Everett, S.

AU - Sánchez, C.

AU - Huff, E. M.

AU - Tarsitano, F.

AU - Gatti, M.

AU - Secco, L. F.

AU - Abbott, T. M.C.

AU - Aguena, M.

AU - Allam, S.

AU - Annis, J.

AU - Bacon, D.

AU - Bertin, E.

AU - Brooks, D.

AU - Burke, D. L.

AU - Carnero Rosell, A.

AU - Carrasco Kind, M.

AU - Carretero, J.

AU - Costanzi, M.

AU - Crocce, M.

AU - Pereira, M. E.S.

AU - De Vicente, J.

AU - Desai, S.

AU - Diehl, H. T.

AU - Dietrich, J. P.

AU - Doel, P.

AU - Eifler, T. F.

AU - Ferrero, I.

AU - Ferté, A.

AU - Flaugher, B.

AU - Fosalba, P.

AU - Frieman, J.

AU - García-Bellido, J.

AU - Gaztanaga, E.

AU - Gerdes, D. W.

AU - Giannantonio, T.

AU - Gschwend, J.

AU - Gutierrez, G.

AU - Hinton, S. R.

AU - Hollowood, D. L.

AU - Honscheid, K.

AU - James, D. J.

AU - Lahav, O.

AU - Lima, M.

AU - Maia, M. A.G.

AU - March, M.

AU - Marshall, J. L.

AU - Martini, P.

AU - Melchior, P.

AU - Menanteau, F.

AU - Miquel, R.

AU - Mohr, J. J.

AU - Morgan, R.

AU - Muir, J.

AU - Ogando, R. L.C.

AU - Palmese, A.

AU - Paz-Chinchón, F.

AU - Plazas, A. A.

AU - Rodriguez-Monroy, M.

AU - Roodman, A.

AU - Samuroff, S.

AU - Sanchez, E.

AU - Scarpine, V.

AU - Serrano, S.

AU - Smith, M.

AU - Soares-Santos, M.

AU - Suchyta, E.

AU - Swanson, M. E.C.

AU - Tarle, G.

AU - Thomas, D.

AU - To, C.

AU - Wilkinson, R. D.

PY - 2022/1/1

Y1 - 2022/1/1

N2 - 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, nγ(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.

AB - 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, nγ(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.

KW - gravitational lensing: weak

KW - large-scale structure of Universe

UR - http://www.scopus.com/inward/record.url?scp=85121633283&partnerID=8YFLogxK

U2 - 10.1093/mnras/stab2870

DO - 10.1093/mnras/stab2870

M3 - Article

AN - SCOPUS:85121633283

SN - 0035-8711

VL - 509

SP - 3371

EP - 3394

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

IS - 3

ER -

Dark Energy Survey Y3 results: Blending shear and redshift biases in image simulations

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