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

Author:

MacCrann N1ORCID,Becker M R2ORCID,McCullough J345,Amon A345,Gruen D345,Jarvis M6,Choi A7,Troxel M A8,Sheldon E9,Yanny B10,Herner K10,Dodelson S11,Zuntz J12,Eckert K6,Rollins R P13,Varga T N1415,Bernstein G M6,Gruendl R A1617,Harrison I1318,Hartley W G19,Sevilla-Noarbe I20,Pieres A2122,Bridle S L13,Myles J4,Alarcon A2,Everett S23,Sánchez C6,Huff E M24,Tarsitano F25,Gatti M26,Secco L F6,Abbott T M C27,Aguena M2128,Allam S10,Annis J10,Bacon D29,Bertin E3031,Brooks D32,Burke D L35,Carnero Rosell A3334,Carrasco Kind M1617,Carretero J26,Costanzi M3536,Crocce M3738,Pereira M E S39,De Vicente J20,Desai S40,Diehl H T10,Dietrich J P41,Doel P32,Eifler T F2442,Ferrero I43,Ferté A24,Flaugher B10,Fosalba P3738,Frieman J1044,García-Bellido J45,Gaztanaga E3738,Gerdes D W3946,Giannantonio T4748,Gschwend J2122,Gutierrez G10,Hinton S R49,Hollowood D L23,Honscheid K750,James D J51,Lahav O32,Lima M2128,Maia M A G2122,March M6,Marshall J L52,Martini P75354,Melchior P55,Menanteau F1617,Miquel R2656,Mohr J J1441,Morgan R57,Muir J3,Ogando R L C2122,Palmese A1044,Paz-Chinchón F1747,Plazas A A55,Rodriguez-Monroy M20,Roodman A35,Samuroff S11,Sanchez E20,Scarpine V10,Serrano S3738,Smith M58,Soares-Santos M39,Suchyta E59,Swanson M E C17,Tarle G39,Thomas D29,To C345,Wilkinson R D60,

Affiliation:

1. Department of Applied Mathematics and Theoretical Physics, University of Cambridge, Cambridge CB3 0WA, UK

2. Argonne National Laboratory, 9700 South Cass Avenue, Lemont, IL 60439, USA

3. Kavli Institute for Particle Astrophysics & Cosmology, Stanford University, P. O. Box 2450, Stanford, CA 94305, USA

4. Department of Physics, Stanford University, 382 Via Pueblo Mall, Stanford, CA 94305, USA

5. SLAC National Accelerator Laboratory, Menlo Park, CA 94025, USA

6. Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA 19104, USA

7. Center for Cosmology and Astro-Particle Physics, The Ohio State University, Columbus, OH 43210, USA

8. Department of Physics, Duke University, Durham, NC 27708, USA

9. Brookhaven National Laboratory, Bldg 510, Upton, NY 11973, USA

10. Fermi National Accelerator Laboratory, P. O. Box 500, Batavia, IL 60510, USA

11. Department of Physics, Carnegie Mellon University, Pittsburgh, Pennsylvania 15312, USA

12. Institute for Astronomy, University of Edinburgh, Edinburgh EH9 3HJ, UK

13. Jodrell Bank Centre for Astrophysics, School of Physics and Astronomy, University of Manchester, Oxford Road, Manchester M13 9PL, UK

14. Max Planck Institute for Extraterrestrial Physics, Giessenbachstrasse, D-85748 Garching, Germany

15. Universitäts-Sternwarte, Fakultät für Physik, Ludwig-Maximilians Universität München, Scheinerstr 1, D-81679 München, Germany

16. Department of Astronomy, University of Illinois at Urbana-Champaign, 1002 W. Green Street, Urbana, IL 61801, USA

17. National Center for Supercomputing Applications, 1205 West Clark St, Urbana, IL 61801, USA

18. Department of Physics, University of Oxford, Denys Wilkinson Building, Keble Road, Oxford OX1 3RH, UK

19. Département de Physique Théorique and Center for Astroparticle Physics, Université de Genève, 24 quai Ernest Ansermet, CH-1211 Geneva, Switzerland

20. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Av. Complutense, 40, 28040 Madrid, Spain

21. Laboratório Interinstitucional de e-Astronomia - LIneA, Rua Gal. José Cristino 77, Rio de Janeiro, RJ - 20921-400, Brazil

22. Observatório Nacional, Rua Gal. José Cristino 77, Rio de Janeiro, RJ - 20921-400, Brazil

23. Santa Cruz Institute for Particle Physics, Santa Cruz, CA 95064, USA

24. Jet Propulsion Laboratory, California Institute of Technology, 4800 Oak Grove Dr., Pasadena, CA 91109, USA

25. Department of Physics, ETH Zurich, Wolfgang-Pauli-Strasse 16, CH-8093 Zurich, Switzerland

26. Institut de Física d’Altes Energies (IFAE), The Barcelona Institute of Science and Technology, Campus UAB, E-08193 Bellaterra (Barcelona), Spain

27. Cerro Tololo Inter-American Observatory, NSF’s National Optical-Infrared Astronomy Research Laboratory, Casilla 603, La Serena, Chile

28. Departamento de Física Matemática, Instituto de Física, Universidade de São Paulo, CP 66318, São Paulo, SP, 05314-970, Brazil

29. Institute of Cosmology and Gravitation, University of Portsmouth, Portsmouth PO1 3FX, UK

30. CNRS, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France

31. Sorbonne Universités, UPMC Univ Paris 06, UMR 7095, Institut d’Astrophysique de Paris, F-75014 Paris, France

32. Department of Physics & Astronomy, University College London, Gower Street, London WC1E 6BT, UK

33. Instituto de Astrofisica de Canarias, E-38205 La Laguna, Tenerife, Spain

34. Dpto. Astrofísica, Universidad de La Laguna, E-38206 La Laguna, Tenerife, Spain

35. INAF-Osservatorio Astronomico di Trieste, via G. B. Tiepolo 11, I-34143 Trieste, Italy

36. Institute for Fundamental Physics of the Universe, Via Beirut 2, I-34014 Trieste, Italy

37. Institut d’Estudis Espacials de Catalunya (IEEC), E-08034 Barcelona, Spain

38. Institute of Space Sciences (ICE, CSIC), Campus UAB, Carrer de Can Magrans, s/n, E-08193 Barcelona, Spain

39. Department of Physics, University of Michigan, Ann Arbor, MI 48109, USA

40. Department of Physics, IIT Hyderabad, Kandi, Telangana 502285, India

41. Faculty of Physics, Ludwig-Maximilians-Universität, Scheinerstr 1, D-81679 Munich, Germany

42. Department of Astronomy/Steward Observatory, University of Arizona, 933 North Cherry Avenue, Tucson, AZ 85721-0065, USA

43. Institute of Theoretical Astrophysics, University of Oslo, P.O. Box 1029 Blindern, NO-0315 Oslo, Norway

44. Kavli Institute for Cosmological Physics, University of Chicago, Chicago, IL 60637, USA

45. Instituto de Fisica Teorica UAM/CSIC, Universidad Autonoma de Madrid, E-28049 Madrid, Spain

46. Department of Astronomy, University of Michigan, Ann Arbor, MI 48109, USA

47. Institute of Astronomy, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK

48. Kavli Institute for Cosmology, University of Cambridge, Madingley Road, Cambridge CB3 0HA, UK

49. School of Mathematics and Physics, University of Queensland, Brisbane, QLD 4072, Australia

50. Department of Physics, The Ohio State University, Columbus, OH 43210, USA

51. Center for Astrophysics | Harvard & Smithsonian, 60 Garden Street, Cambridge, MA 02138, USA

52. George P. and Cynthia Woods Mitchell Institute for Fundamental Physics and Astronomy, and Department of Physics and Astronomy, Texas A&M University, College Station, TX 77843, USA

53. Department of Astronomy, The Ohio State University, Columbus, OH 43210, USA

54. Radcliffe Institute for Advanced Study, Harvard University, Cambridge, MA 02138, USA

55. Department of Astrophysical Sciences, Princeton University, Peyton Hall, Princeton, NJ 08544, USA

56. Institució Catalana de Recerca i Estudis Avançats, E-08010 Barcelona, Spain

57. Physics Department, 2320 Chamberlin Hall, University of Wisconsin-Madison, 1150 University Avenue Madison, WI 53706-1390, USA

58. School of Physics and Astronomy, University of Southampton, Southampton SO17 1BJ, UK

59. Computer Science and Mathematics Division, Oak Ridge National Laboratory, Oak Ridge, TN 37831, USA

60. Department of Physics and Astronomy, Pevensey Building, University of Sussex, Brighton BN1 9QH, UK

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, 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.

Funder

National Science Foundation

MICINN

Generalitat de Catalunya

ERC

CNPq

U.S. Department of Energy

Science and Technology Facilities Council

Higher Education Funding Council for England

University of Illinois at Urbana-Champaign

University of Chicago

Ohio State University

Ministério da Ciência, Tecnologia e Inovação

Deutsche Forschungsgemeinschaft

Argonne National Laboratory

Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas

University College London

Eidgenössische Technische Hochschule Zürich

Lawrence Berkeley National Laboratory

University of Nottingham

University of Portsmouth

SLAC National Accelerator Laboratory

Stanford University

University of Sussex

Texas A&M University

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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