The Dark Energy Survey supernova program: cosmological biases from supernova photometric classification-Reference-Cited by-同舟云学术

The Dark Energy Survey supernova program: cosmological biases from supernova photometric classification

Published:2022-06-03 Issue:1 Volume:518 Page:1106-1127
ISSN:0035-8711
Container-title:Monthly Notices of the Royal Astronomical Society
language:en
Short-container-title:

Author:

Vincenzi M¹²³^ORCID,Sullivan M¹^ORCID,Möller A⁴⁵^ORCID,Armstrong P⁶^ORCID,Bassett B A⁷⁸⁹,Brout D¹⁰^ORCID,Carollo D¹¹,Carr A¹²,Davis T M¹²^ORCID,Frohmaier C¹²^ORCID,Galbany L¹³¹⁴^ORCID,Glazebrook K⁴,Graur O²¹⁵^ORCID,Kelsey L¹²^ORCID,Kessler R¹⁶¹⁷,Kovacs E¹⁸,Lewis G F¹⁹^ORCID,Lidman C⁶²⁰^ORCID,Malik U⁶,Nichol R C²,Popovic B³,Sako M²¹,Scolnic D³^ORCID,Smith M¹^ORCID,Taylor G⁶^ORCID,Tucker B E⁶,Wiseman P¹^ORCID,Aguena M²²,Allam S²³,Annis J²³,Asorey J²⁴,Bacon D²,Bertin E²⁵²⁶,Brooks D²⁷,Burke D L²⁸²⁹,Rosell A Carnero²²,Carretero J³⁰,Castander F J¹³¹⁴,Costanzi M³¹³²³³,da Costa L N²²³⁴,Pereira M E S³⁵³⁶,De Vicente J²⁴,Desai S³⁷,Diehl H T²³,Doel P²⁷,Everett S³⁸,Ferrero I³⁹,Flaugher B²³,Fosalba P¹³¹⁴,Frieman J¹⁷²³,García-Bellido J⁴⁰,Gerdes D W³⁵⁴¹,Gruen D⁴²,Gutierrez G²³,Hinton S R¹²,Hollowood D L³⁸,Honscheid K⁴³⁴⁴,James D J¹⁰,Kuehn K⁴⁵⁴⁶,Kuropatkin N²³,Lahav O²⁷,Li T S⁴⁷⁴⁸,Lima M²²⁴⁹,Maia M A G²²³⁴,Marshall J L⁵⁰,Miquel R³⁰⁵¹,Morgan R⁵²,Ogando R L C³⁴,Palmese A⁵³,Paz-Chinchón F⁵⁴⁵⁵,Pieres A²²³⁴,Malagón A A Plazas⁵⁶,Reil K²⁹,Roodman A²⁸²⁹,Sanchez E²⁴,Schubnell M³⁵,Serrano S¹³¹⁴,Sevilla-Noarbe I²⁴,Suchyta E⁵⁷,Tarle G³⁵,To C²⁸²⁹⁵⁸,Varga T N⁵⁹⁶⁰,Weller J⁵⁹⁶⁰,Wilkinson R D⁶¹,

Affiliation:

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

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

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

4. Centre for Astrophysics & Supercomputing, Swinburne University of Technology , Victoria 3122, Australia

5. Université Clermont Auvergne , CNRS/IN2P3, LPC, F-63000 Clermont-Ferrand, France

6. The Research School of Astronomy and Astrophysics, Australian National University , ACT 2601, Australia

7. African Institute for Mathematical Sciences , 6 Melrose Road, Muizenberg 7945, South Africa

8. Department of Maths and Applied Maths, University of Cape Town , Cape Town, 7700, South Africa

9. South African Astronomical Observatory , Observatory, Cape Town, 7925, South Africa

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

11. INAF, Astrophysical Observatory of Turin , I-10025 Pino Torinese, Italy

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

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

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

15. Department of Astrophysics, American Museum of Natural History , New York, NY 10024, USA

16. Department of Astronomy and Astrophysics, University of Chicago , Chicago, IL 60637, USA

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

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

19. Sydney Institute for Astronomy, School of Physics , A28, The University of Sydney, NSW 2006, Australia

20. Centre for Gravitational Astrophysics, College of Science, The Australian National University , ACT 2601, Australia

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

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

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

24. Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT) , Madrid 28040, Spain

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

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

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

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

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

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

31. Astronomy Unit, Department of Physics, University of Trieste , via Tiepolo 11, I-34131 Trieste, Italy

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

33. Institute for Fundamental Physics of the Universe , Via Beirut 2, 34014 Trieste, Italy

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

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

36. Hamburger Sternwarte, Universität Hamburg , Gojenbergsweg 112, D-21029 Hamburg, Germany

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

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

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

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

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

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

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

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

45. Australian Astronomical Optics, Macquarie University , North Ryde, NSW 2113, Australia

46. Lowell Observatory , 1400 Mars Hill Rd, Flagstaff, AZ 86001, USA

47. Observatories of the Carnegie Institution for Science , 813 Santa Barbara St., Pasadena, CA 91101, USA

48. Department of Astrophysical Sciences, Princeton University , Princeton, NJ 08544, USA

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

50. 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

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

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

53. Department of Astronomy, University of California , Berkeley, 501 Campbell Hall, Berkeley, CA 94720, USA

54. Center for Astrophysical Surveys, National Center for Supercomputing Applications , 1205 West Clark St., Urbana, IL 61801, USA

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

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

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

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

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

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

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

Abstract

ABSTRACT Cosmological analyses of samples of photometrically identified type Ia supernovae (SNe Ia) depend on understanding the effects of ‘contamination’ from core-collapse and peculiar SN Ia events. We employ a rigorous analysis using the photometric classifier SuperNNova on state-of-the-art simulations of SN samples to determine cosmological biases due to such ‘non-Ia’ contamination in the Dark Energy Survey (DES) 5-yr SN sample. Depending on the non-Ia SN models used in the SuperNNova training and testing samples, contamination ranges from 0.8 to 3.5 per cent, with a classification efficiency of 97.7–99.5 per cent. Using the Bayesian Estimation Applied to Multiple Species (BEAMS) framework and its extension BBC (‘BEAMS with Bias Correction’), we produce a redshift-binned Hubble diagram marginalized over contamination and corrected for selection effects, and use it to constrain the dark energy equation-of-state, w. Assuming a flat universe with Gaussian ΩM prior of 0.311 ± 0.010, we show that biases on w are <0.008 when using SuperNNova, with systematic uncertainties associated with contamination around 10 per cent of the statistical uncertainty on w for the DES-SN sample. An alternative approach of discarding contaminants using outlier rejection techniques (e.g. Chauvenet’s criterion) in place of SuperNNova leads to biases on w that are larger but still modest (0.015–0.03). Finally, we measure biases due to contamination on w0 and wa (assuming a flat universe), and find these to be <0.009 in w0 and <0.108 in wa, 5 to 10 times smaller than the statistical uncertainties for the DES-SN sample.

Funder

Science and Technology Facilities Council

ARC

Ministry of Science, Innovation and Universities

U.S. Department of Energy

NASA

National Science Foundation

MICINN

European Research Council

CNPq

Publisher

Oxford University Press (OUP)