Time delay lens modelling challenge

Author:

Ding X12ORCID,Treu T1ORCID,Birrer S3,Chen G C-F4ORCID,Coles J5,Denzel P67ORCID,Frigo M8ORCID,Galan A9,Marshall P J10ORCID,Millon M9,More A2ORCID,Shajib A J111ORCID,Sluse D12,Tak H1314151617ORCID,Xu D18,Auger M W19,Bonvin V9,Chand H2021,Courbin F9ORCID,Despali G22,Fassnacht C D4,Gilman D1,Hilbert S2324,Kumar S R20,Lin J Y-Y25,Park J W10,Saha P76ORCID,Vegetti S8,Van de Vyvere L12,Williams L L R26ORCID

Affiliation:

1. Department of Physics and Astronomy, University of California, Los Angeles, CA 90095-1547, USA

2. Kavli IPMU (WPI), UTIAS, The University of Tokyo, Kashiwa, Chiba 277-8583, Japan

3. Kavli Institute for Particle Astrophysics and Cosmology and Department of Physics, Stanford University, Stanford, CA 94305, USA

4. Department of Physics, University of California, Davis, CA 95616, USA

5. Physik-Department T38, Technische Universität München, James-Franck-Str 1, D-85748 Garching, Germany

6. Institute for Computational Science, University of Zurich, CH-8057 Zurich, Switzerland

7. Physics Institute, University of Zurich, CH-8057 Zurich, Switzerland

8. Max Planck Institute for Astrophysics, Karl-Schwarzschild-Strasse 1, D-85740 Garching, Germany

9. Institute of Physics, Laboratory of Astrophysics, Ecole Polytechnique Fédérale de Lausanne (EPFL), Observatoire de Sauverny, CH-1290 Versoix, Switzerland

10. Kavli Institute for Particle Astrophysics and Cosmology, Stanford University, 452 Lomita Mall, Stanford, CA 94035, USA

11. Department of Astronomy & Astrophysics, University of Chicago, Chicago, IL 606374, USA

12. STAR Institute, Quartier Agora - Allée du six Août, 19c, B-4000 Liège, Belgium

13. International CHASC Astrostatistics Collaboration, Harvard University, Cambridge, MA 02138, USA

14. Center for Astrostatistics, The Pennsylvania State University, University Park, PA 16802, USA

15. Department of Statistics, The Pennsylvania State University, University Park, PA 16802, USA

16. Department of Astronomy and Astrophysics, The Pennsylvania State University, University Park, PA 16802, USA

17. Institute for Computational and Data Sciences, The Pennsylvania State University, University Park, PA 16802, USA

18. Department of Astronomy, Tsinghua University, Beijing 100084, China

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

20. Department of Astronomy, Aryabhatta Research Institute of observational sciencES (ARIES), Nainital 263002, India

21. Department of Physics and Astronomical Sciences, Central University of Himachal Pradesh, Dharamshala 176206, India

22. Zentrum für Astronomie der Universität Heidelberg, Institut für Theoretische Astrophysik, Albert-Ueberle-Str 2, D-69120 Heidelberg, Germany

23. Exzellenzcluster Universe, Boltzmannstr 2, D-85748 Garching, Germany

24. Ludwig-Maximilians-Universität, Universitäts-Sternwarte, Scheinerstr 1, D-81679 München, Germany

25. Department of Physics, University of Illinois at Urbana-Champaign, 1110 West Green Street, Urbana, IL 61801, USA

26. School of Physics and Astronomy, University of Minnesota, 116 Church Street SE, Minneapolis, MN 55455, USA

Abstract

ABSTRACT In recent years, breakthroughs in methods and data have enabled gravitational time delays to emerge as a very powerful tool to measure the Hubble constant H0. However, published state-of-the-art analyses require of order 1 yr of expert investigator time and up to a million hours of computing time per system. Furthermore, as precision improves, it is crucial to identify and mitigate systematic uncertainties. With this time delay lens modelling challenge, we aim to assess the level of precision and accuracy of the modelling techniques that are currently fast enough to handle of order 50 lenses, via the blind analysis of simulated data sets. The results in Rungs 1 and 2 show that methods that use only the point source positions tend to have lower precision ($10\!-\!20{{\ \rm per\ cent}}$) while remaining accurate. In Rung 2, the methods that exploit the full information of the imaging and kinematic data sets can recover H0 within the target accuracy (|A| < 2 per cent) and precision (<6 per cent per system), even in the presence of a poorly known point spread function and complex source morphology. A post-unblinding analysis of Rung 3 showed the numerical precision of the ray-traced cosmological simulations to be insufficient to test lens modelling methodology at the percent level, making the results difficult to interpret. A new challenge with improved simulations is needed to make further progress in the investigation of systematic uncertainties. For completeness, we present the Rung 3 results in an appendix and use them to discuss various approaches to mitigating against similar subtle data generation effects in future blind challenges.

Funder

David and Lucile Packard Foundation

National Science Foundation

H2020 European Research Council

National Aeronautics and Space Administration

Space Telescope Science Institute

U.S. Department of Energy

Publisher

Oxford University Press (OUP)

Subject

Space and Planetary Science,Astronomy and Astrophysics

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1. Essentials of Strong Gravitational Lensing;Space Science Reviews;2024-02

2. Determining cosmological-model-independent H0 and post-Newtonian parameter with time-delay lenses and supernovae;Monthly Notices of the Royal Astronomical Society;2024-01-11

3. Progress in direct measurements of the Hubble constant;Journal of Cosmology and Astroparticle Physics;2023-11-01

4. Accelerating galaxy dynamical modeling using a neural network for joint lensing and kinematic analyses;Astronomy & Astrophysics;2023-11

5. COOLEST: COde-independent Organized LEns STandard;Journal of Open Source Software;2023-08-09

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