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Large data set of lensed quasars: higher accuracy on H0? The angular structures viewpoint

Published online by Cambridge University Press:  04 March 2024

Lyne Van de Vyvere Open the ORCID record for Lyne Van de Vyvere [Opens in a new window]
Lyne Van de Vyvere*
Affiliation:
Univerity of Liège STAR Institute, Quartier Agora - Allée du six Août, 19c B-4000 Liège, Belgium
*
email: [email protected]
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Abstract

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Thanks to forthcoming large-scale surveys, a tremendous number of strong lenses will be discovered in the coming years. The gain in accuracy on H0 from such a large population of lensed quasars is a key question for the future of time-delay cosmography. In such context, lensed systems will have to be modeled in an automated way, with models that are sufficiently generic to apply to every lens. I explore the biases that may arise from unaccounted-for azimuthal structures in mass models. The non-modeled twists in lensing galaxies are expected to bias the shear inference but not H0. Disregarded ellipticity gradients, boxyness and discyness may impact the cosmological inference on a lens-by-lens basis. Nevertheless, the diversity of azimuthal mass profile in lenses balances the bias at a population level and the H0 inference can thus benefits from such large surveys.

Keywords

gravitational lensinggalaxies: elliptical and lenticularcDgalaxies: statisticscosmological parametersmethods: numerical
Type
Contributed Paper
Information
Proceedings of the International Astronomical Union , Volume 18 , Symposium S381: Strong Gravitational Lensing in the Era of Big Data , December 2022 , pp. 120 - 124
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Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of International Astronomical Union

References

Birrer, S. & Amara, A. 2018, Physics of the Dark Universe, 22, 189 CrossRefGoogle Scholar
Birrer, S., Amara, A., & Refregier, A. 2015, ApJ, 813, 102 CrossRefGoogle Scholar
Birrer, S., Shajib, A. J., Gilman, D., et al. 2021, JOSS, 6, 3283 CrossRefGoogle Scholar
Cappellari, M. 2016, ARA&A, 54, 597 Google Scholar
Crain, R. A., Schaye, J., Bower, R. G., et al. 2015, MNRAS, 450, 1937 CrossRefGoogle Scholar
Dutton, A. A., Brewer, B. J., Marshall, P. J., et al. 2011, MNRAS, 417, 1621 CrossRefGoogle Scholar
Etherington, A., Nightingale, J. W., Massey, R., et al. 2023, arXiv e-prints, arXiv:2301.05244Google Scholar
Galan, A., Vernardos, G., Peel, A., Courbin, F., & Starck, J.-L. 2022, A&A, 668, A155 Google Scholar
Hao, C. N., Mao, S., Deng, Z. G., Xia, X. Y., & Wu, H. 2006, MNRAS, 370, 1339 CrossRefGoogle Scholar
Keeton, C. R., Falco, E. E., Impey, C. D., et al. 2000, ApJ, 542, 74 CrossRefGoogle Scholar
Khochfar, S. & Burkert, A. 2005, MNRAS, 359, 1379 CrossRefGoogle Scholar
Kormendy, J., Fisher, D. B., Cornell, M. E., & Bender, R. 2009, ApJS, 182, 216 CrossRefGoogle Scholar
McAlpine, S., Helly, J. C., Schaller, M., et al. 2016, Astronomy and Computing, 15, 72 CrossRefGoogle Scholar
Mitsuda, K., Doi, M., Morokuma, T., et al. 2017, ApJ, 834, 109 CrossRefGoogle Scholar
Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, ApJ, 462, 563 CrossRefGoogle Scholar
Pasquali, A., Ferreras, I., Panagia, N., et al. 2006, ApJ, 636, 115 CrossRefGoogle Scholar
Powell, D. M., Vegetti, S., McKean, J. P., et al. 2022, MNRAS, 516, 1808 CrossRefGoogle Scholar
Schaye, J., Crain, R. A., Bower, R. G., et al. 2015, MNRAS, 446, 521 CrossRefGoogle Scholar
Schramm, T. 1994, A&A, 284, 44 Google Scholar
Sonnenfeld, A., Li, S.-S., Despali, G., Shajib, A., & Taylor, E. 2023, arXiv e-prints, arXiv:2301.13230Google Scholar
Suyu, S. H., Treu, T., Hilbert, S., et al. 2014, ApJL, 788, L35 CrossRefGoogle Scholar
Van de Vyvere, L., Gomer, M. R., Sluse, D., et al. 2022 a, A&A, 659, A127 CrossRefGoogle Scholar
Van de Vyvere, L., Sluse, D., Gomer, M. R., & Mukherjee, S. 2022 b, A&A, 663, A179 CrossRefGoogle Scholar
Van de Vyvere, L., Sluse, D., Mukherjee, S., Xu, D., & Birrer, S. 2020, A&A, 644, A108 Google Scholar
Wong, K. C., Suyu, S. H., Chen, G. C. F., et al. 2020, MNRAS, 498, 1420 CrossRefGoogle Scholar