Time delay lens modelling challenge

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 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.

This is a pre-copyedited, author-produced PDF of an article accepted for publication in Monthly Notices of the Royal Astronomical Society following peer review. The version of record [Time delay lens modelling challenge. Monthly Notices of the Royal Astronomical Society 503, 1 p1096-1123 (2021)] is available online at: https://doi.org/10.1093/mnras/stab484.

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Work Title Time delay lens modelling challenge
Access
Open Access
Creators
  1. X. Ding
  2. T. Treu
  3. S. Birrer
  4. G. C.F. Chen
  5. J. Coles
  6. P. Denzel
  7. M. Frigo
  8. A. Galan
  9. P. J. Marshall
  10. M. Millon
  11. A. More
  12. A. J. Shajib
  13. D. Sluse
  14. H. Tak
  15. D. Xu
  16. M. W. Auger
  17. V. Bonvin
  18. H. Chand
  19. F. Courbin
  20. G. Despali
  21. C. D. Fassnacht
  22. D. Gilman
  23. S. Hilbert
  24. S. R. Kumar
  25. J. Y.Y. Lin
  26. J. W. Park
  27. P. Saha
  28. S. Vegetti
  29. L. Van De Vyvere
  30. L. L.R. Williams
Keyword
  1. Gravitational lensing: strong
  2. Methods: data analysis
  3. Cosmology: observations
License In Copyright (Rights Reserved)
Work Type Article
Publisher
  1. Monthly Notices of the Royal Astronomical Society
Publication Date February 22, 2021
Publisher Identifier (DOI)
  1. https://doi.org/10.1093/mnras/stab484
Deposited February 03, 2024

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Version 1
published

  • Created
  • Added 2006.08619-1.pdf
  • Added Creator X. Ding
  • Added Creator T. Treu
  • Added Creator S. Birrer
  • Added Creator G. C.F. Chen
  • Added Creator J. Coles
  • Added Creator P. Denzel
  • Added Creator M. Frigo
  • Added Creator A. Galan
  • Added Creator P. J. Marshall
  • Added Creator M. Millon
  • Added Creator A. More
  • Added Creator A. J. Shajib
  • Added Creator D. Sluse
  • Added Creator H. Tak
  • Added Creator D. Xu
  • Added Creator M. W. Auger
  • Added Creator V. Bonvin
  • Added Creator H. Chand
  • Added Creator F. Courbin
  • Added Creator G. Despali
  • Added Creator C. D. Fassnacht
  • Added Creator D. Gilman
  • Added Creator S. Hilbert
  • Added Creator S. R. Kumar
  • Added Creator J. Y.Y. Lin
  • Added Creator J. W. Park
  • Added Creator P. Saha
  • Added Creator S. Vegetti
  • Added Creator L. Van De Vyvere
  • Added Creator L. L.R. Williams
  • Published
  • Updated Keyword, Description Show Changes
    Keyword
    • Gravitational lensing: strong, Methods: data analysis, Cosmology: observations
    Description
    • 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| &lt; 2 per cent) and precision (&lt;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.
    • 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 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| &lt; 2 per cent) and precision (&lt;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.
  • Updated