Dark Energy Survey year 3 results: Point spread function modelling

M. Jarvis; G. M. Bernstein; A. Amon; C. Davis; P. F. Léget; K. Bechtol; I. Harrison; M. Gatti; A. Roodman; C. Chang; R. Chen; A. Choi; S. Desai; A. Drlica-Wagner; D. Gruen; R. A. Gruendl; A. Hernandez; N. MacCrann; J. Meyers; A. Navarro-Alsina; S. Pandey; A. A. Plazas; L. F. Secco; E. Sheldon; M. A. Troxel; S. Vorperian; K. Wei; J. Zuntz; T. M.C. Abbott; M. Aguena; S. Allam; S. Avila; S. Bhargava; S. L. Bridle; D. Brooks; A. Carnero Rosell; M. Carrasco Kind; J. Carretero; M. Costanzi; L. N. Da Costa; J. De Vicente; H. T. Diehl; P. Doel; S. Everett; B. Flaugher; P. Fosalba; J. Frieman; J. García-Bellido; E. Gaztanaga; D. W. Gerdes; G. Gutierrez; S. R. Hinton; D. L. Hollowood; K. Honscheid; D. J. James; S. Kent; K. Kuehn; N. Kuropatkin; O. Lahav; M. A.G. Maia; M. March; J. L. Marshall; P. Melchior; F. Menanteau; R. Miquel; R. L.C. Ogando; F. Paz-Chinchón; E. S. Rykoff; E. Sanchez; V. Scarpine; M. Schubnell; S. Serrano; I. Sevilla-Noarbe; M. Smith; E. Suchyta; M. E.C. Swanson; G. Tarle; T. N. Varga; A. R. Walker; W. Wester; R. D. Wilkinson

doi:10.1093/mnras/staa3679

Dark Energy Survey year 3 results: Point spread function modelling

M. Jarvis, G. M. Bernstein, A. Amon, C. Davis, P. F. Léget, K. Bechtol, I. Harrison, M. Gatti, A. Roodman, C. Chang, R. Chen, A. Choi, S. Desai, A. Drlica-Wagner, D. Gruen, R. A. Gruendl, A. Hernandez, N. MacCrann, J. Meyers, A. Navarro-AlsinaS. Pandey, A. A. Plazas, L. F. Secco, E. Sheldon, M. A. Troxel, S. Vorperian, K. Wei, J. Zuntz, T. M.C. Abbott, M. Aguena, S. Allam, S. Avila, S. Bhargava, S. L. Bridle, D. Brooks, A. Carnero Rosell, M. Carrasco Kind, J. Carretero, M. Costanzi, L. N. Da Costa, J. De Vicente, H. T. Diehl, P. Doel, S. Everett, B. Flaugher, P. Fosalba, J. Frieman, J. García-Bellido, E. Gaztanaga, D. W. Gerdes, G. Gutierrez, S. R. Hinton, D. L. Hollowood, K. Honscheid, D. J. James, S. Kent, K. Kuehn, N. Kuropatkin, O. Lahav, M. A.G. Maia, M. March, J. L. Marshall, P. Melchior, F. Menanteau, R. Miquel, R. L.C. Ogando, F. Paz-Chinchón, E. S. Rykoff, E. Sanchez, V. Scarpine, M. Schubnell, S. Serrano, I. Sevilla-Noarbe, M. Smith, E. Suchyta, M. E.C. Swanson, G. Tarle, T. N. Varga, A. R. Walker, W. Wester, R. D. Wilkinson

Research output: Contribution to journal › Article › peer-review

Abstract

We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.

Original language	English (US)
Pages (from-to)	1282-1299
Number of pages	18
Journal	Monthly Notices of the Royal Astronomical Society
Volume	501
Issue number	1
DOIs	https://doi.org/10.1093/mnras/staa3679
State	Published - Feb 1 2021
Externally published	Yes

Keywords

catalogues
cosmology: observations
gravitational lensing: weak
software: data analysis
surveys
techniques: image processing

ASJC Scopus subject areas

Astronomy and Astrophysics
Space and Planetary Science

Online availability

10.1093/mnras/staa3679

Library availability

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Jarvis, M., Bernstein, G. M., Amon, A., Davis, C., Léget, P. F., Bechtol, K., Harrison, I., Gatti, M., Roodman, A., Chang, C., Chen, R., Choi, A., Desai, S., Drlica-Wagner, A., Gruen, D., Gruendl, R. A., Hernandez, A., MacCrann, N., Meyers, J., ... Wilkinson, R. D. (2021). Dark Energy Survey year 3 results: Point spread function modelling. Monthly Notices of the Royal Astronomical Society, 501(1), 1282-1299. https://doi.org/10.1093/mnras/staa3679

Jarvis, M, Bernstein, GM, Amon, A, Davis, C, Léget, PF, Bechtol, K, Harrison, I, Gatti, M, Roodman, A, Chang, C, Chen, R, Choi, A, Desai, S, Drlica-Wagner, A, Gruen, D, Gruendl, RA, Hernandez, A, MacCrann, N, Meyers, J, Navarro-Alsina, A, Pandey, S, Plazas, AA, Secco, LF, Sheldon, E, Troxel, MA, Vorperian, S, Wei, K, Zuntz, J, Abbott, TMC, Aguena, M, Allam, S, Avila, S, Bhargava, S, Bridle, SL, Brooks, D, Carnero Rosell, A, Carrasco Kind, M, Carretero, J, Costanzi, M, Da Costa, LN, De Vicente, J, Diehl, HT, Doel, P, Everett, S, Flaugher, B, Fosalba, P, Frieman, J, García-Bellido, J, Gaztanaga, E, Gerdes, DW, Gutierrez, G, Hinton, SR, Hollowood, DL, Honscheid, K, James, DJ, Kent, S, Kuehn, K, Kuropatkin, N, Lahav, O, Maia, MAG, March, M, Marshall, JL, Melchior, P, Menanteau, F, Miquel, R, Ogando, RLC, Paz-Chinchón, F, Rykoff, ES, Sanchez, E, Scarpine, V, Schubnell, M, Serrano, S, Sevilla-Noarbe, I, Smith, M, Suchyta, E, Swanson, MEC, Tarle, G, Varga, TN, Walker, AR, Wester, W & Wilkinson, RD 2021, 'Dark Energy Survey year 3 results: Point spread function modelling', Monthly Notices of the Royal Astronomical Society, vol. 501, no. 1, pp. 1282-1299. https://doi.org/10.1093/mnras/staa3679

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title = "Dark Energy Survey year 3 results: Point spread function modelling",

abstract = "We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.",

keywords = "catalogues, cosmology: observations, gravitational lensing: weak, software: data analysis, surveys, techniques: image processing",

author = "M. Jarvis and Bernstein, {G. M.} and A. Amon and C. Davis and L{\'e}get, {P. F.} and K. Bechtol and I. Harrison and M. Gatti and A. Roodman and C. Chang and R. Chen and A. Choi and S. Desai and A. Drlica-Wagner and D. Gruen and Gruendl, {R. A.} and A. Hernandez and N. MacCrann and J. Meyers and A. Navarro-Alsina and S. Pandey and Plazas, {A. A.} and Secco, {L. F.} and E. Sheldon and Troxel, {M. A.} and S. Vorperian and K. Wei and J. Zuntz and Abbott, {T. M.C.} and M. Aguena and S. Allam and S. Avila and S. Bhargava and Bridle, {S. L.} and D. Brooks and {Carnero Rosell}, A. and {Carrasco Kind}, M. and J. Carretero and M. Costanzi and {Da Costa}, {L. N.} and {De Vicente}, J. and Diehl, {H. T.} and P. Doel and S. Everett and B. Flaugher and P. Fosalba and J. Frieman and J. Garc{\'i}a-Bellido and E. Gaztanaga and Gerdes, {D. W.} and G. Gutierrez and Hinton, {S. R.} and Hollowood, {D. L.} and K. Honscheid and James, {D. J.} and S. Kent and K. Kuehn and N. Kuropatkin and O. Lahav and Maia, {M. A.G.} and M. March and Marshall, {J. L.} and P. Melchior and F. Menanteau and R. Miquel and Ogando, {R. L.C.} and F. Paz-Chinch{\'o}n and Rykoff, {E. S.} and E. Sanchez and V. Scarpine and M. Schubnell and S. Serrano and I. Sevilla-Noarbe and M. Smith and E. Suchyta and Swanson, {M. E.C.} and G. Tarle and Varga, {T. N.} and Walker, {A. R.} and W. Wester and Wilkinson, {R. D.}",

note = "Publisher Copyright: {\textcopyright} 2020 The Author(s) Published by Oxford University Press on behalf of Royal Astronomical Society.",

year = "2021",

month = feb,

day = "1",

doi = "10.1093/mnras/staa3679",

language = "English (US)",

volume = "501",

pages = "1282--1299",

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

issn = "0035-8711",

publisher = "Oxford University Press",

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TY - JOUR

T1 - Dark Energy Survey year 3 results

T2 - Point spread function modelling

AU - Jarvis, M.

AU - Bernstein, G. M.

AU - Amon, A.

AU - Davis, C.

AU - Léget, P. F.

AU - Bechtol, K.

AU - Harrison, I.

AU - Gatti, M.

AU - Roodman, A.

AU - Chang, C.

AU - Chen, R.

AU - Choi, A.

AU - Desai, S.

AU - Drlica-Wagner, A.

AU - Gruen, D.

AU - Gruendl, R. A.

AU - Hernandez, A.

AU - MacCrann, N.

AU - Meyers, J.

AU - Navarro-Alsina, A.

AU - Pandey, S.

AU - Plazas, A. A.

AU - Secco, L. F.

AU - Sheldon, E.

AU - Troxel, M. A.

AU - Vorperian, S.

AU - Wei, K.

AU - Zuntz, J.

AU - Abbott, T. M.C.

AU - Aguena, M.

AU - Allam, S.

AU - Avila, S.

AU - Bhargava, S.

AU - Bridle, S. L.

AU - Brooks, D.

AU - Carnero Rosell, A.

AU - Carrasco Kind, M.

AU - Carretero, J.

AU - Costanzi, M.

AU - Da Costa, L. N.

AU - De Vicente, J.

AU - Diehl, H. T.

AU - Doel, P.

AU - Everett, S.

AU - Flaugher, B.

AU - Fosalba, P.

AU - Frieman, J.

AU - García-Bellido, J.

AU - Gaztanaga, E.

AU - Gerdes, D. W.

AU - Gutierrez, G.

AU - Hinton, S. R.

AU - Hollowood, D. L.

AU - Honscheid, K.

AU - James, D. J.

AU - Kent, S.

AU - Kuehn, K.

AU - Kuropatkin, N.

AU - Lahav, O.

AU - Maia, M. A.G.

AU - March, M.

AU - Marshall, J. L.

AU - Melchior, P.

AU - Menanteau, F.

AU - Miquel, R.

AU - Ogando, R. L.C.

AU - Paz-Chinchón, F.

AU - Rykoff, E. S.

AU - Sanchez, E.

AU - Scarpine, V.

AU - Schubnell, M.

AU - Serrano, S.

AU - Sevilla-Noarbe, I.

AU - Smith, M.

AU - Suchyta, E.

AU - Swanson, M. E.C.

AU - Tarle, G.

AU - Varga, T. N.

AU - Walker, A. R.

AU - Wester, W.

AU - Wilkinson, R. D.

PY - 2021/2/1

Y1 - 2021/2/1

N2 - We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.

AB - We introduce a new software package for modelling the point spread function (PSF) of astronomical images, called piff (PSFs In the Full FOV), which we apply to the first three years (known as Y3) of the Dark Energy Survey (DES) data. We describe the relevant details about the algorithms used by piff to model the PSF, including how the PSF model varies across the field of view (FOV). Diagnostic results show that the systematic errors from the PSF modelling are very small over the range of scales that are important for the DES Y3 weak lensing analysis. In particular, the systematic errors from the PSF modelling are significantly smaller than the corresponding results from the DES year one (Y1) analysis. We also briefly describe some planned improvements to piff that we expect to further reduce the modelling errors in future analyses.

KW - catalogues

KW - cosmology: observations

KW - gravitational lensing: weak

KW - software: data analysis

KW - surveys

KW - techniques: image processing

UR - http://www.scopus.com/inward/record.url?scp=85100356476&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85100356476&partnerID=8YFLogxK

U2 - 10.1093/mnras/staa3679

DO - 10.1093/mnras/staa3679

M3 - Article

AN - SCOPUS:85100356476

SN - 0035-8711

VL - 501

SP - 1282

EP - 1299

JO - Monthly Notices of the Royal Astronomical Society

JF - Monthly Notices of the Royal Astronomical Society

IS - 1

ER -

Dark Energy Survey year 3 results: Point spread function modelling

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