- Physical Review Journals
All JournalsPhysics Magazine
Access Provided by Xinjiang University

Physical Review D

Reuse & Permissions

It is not necessary to obtain permission to reuse this article or its components as it is available under the terms of the Creative Commons Attribution 4.0 International license. This license permits unrestricted use, distribution, and reproduction in any medium, provided attribution to the author(s) and the published article's title, journal citation, and DOI are maintained. Please note that some figures may have been included with permission from other third parties. It is your responsibility to obtain the proper permission from the rights holder directly for these figures.

Export citation

Export citation

Choose format for download:

Download Citation
  • Open Access
  • Access by Xinjiang University

Forward analytical model for the optical selection bias on galaxy cluster lensing profiles

M. Costanzi1,2,3, H.-Y. Wu4, J. H. Esteves5, S. Grandis6, C. To7,8,9, and M. Aguena2,3

PDF

Phys. Rev. D 113, 103508 – Published 5 May, 2026

DOI: https://doi.org/10.1103/b3qk-m2np

Abstract

Cluster catalogs selected by optical properties are subject to selection biases, primarily arising from unresolved systems along the line of sight. These biases affect key observables for cluster cosmology, such as the lensing signal and clustering statistics. In this work, we present a fully predictive forward analytical model to quantify the impact of optical-selection bias due to projection effects on cluster density profiles. This is achieved by introducing a scale-dependent parametrization of the optical cluster bias, whose small- and large-scale behavior is set by the amplitude of projection effects, and by expressing the two-halo component of the density profile in terms of the contributions from off-axis halos along the line of sight. As a case study, we consider a DES Y3-like cluster catalog and validate our model against simulated samples. Our model successfully captures the dependence of the two-halo component on richness boosts induced by projections, as well as its evolution with richness and redshift. It also recovers the overall bias in the projected density profile relative to a randomly selected sample with the same mass distribution. The framework presented here provides a consistent methodology for modeling the impact of line-of-sight structures on the observed richness and density profiles of optically selected clusters, directly linking selection biases to the underlying cosmology and survey specifications.

View figure in article

Physics Subject Headings (PhySH)

Article Text

References (42)

  1. A. Lee et al., Phys. Rev. D 111, 063502 (2025).
  2. H.-Y. Wu et al., Mon. Not. R. Astron. Soc. 515, 4471 (2022).
  3. Z. Zhang et al., Mon. Not. R. Astron. Soc. 523, 1994 (2023).
  4. A. N. Salcedo, H.-Y. Wu, E. Rozo, D. H. Weinberg, C.-H. To, T. Sunayama, and A. Lee, Phys. Rev. Lett. 133, 221002 (2024).
  5. T. Sunayama et al., Mon. Not. R. Astron. Soc. 496, 4468 (2020).
  6. T. Nyarko Nde, H.-Y. Wu, S. Cao, G. Muthoni Kamau, A. Tamosiunas, C.-H. To, and C. Zhou, Phys. Rev. D 113, 063559 (2026).
  7. DES Collaboration et al., Phys. Rev. D 102, 023509 (2020).
  8. T. Sunayama, Mon. Not. R. Astron. Soc. 521, 5064 (2023).
  9. C. Zhou et al., Phys. Rev. D 110, 103508 (2024).
  10. T. Sunayama et al., Phys. Rev. D 110, 083511 (2024).
  11. DES Collaboration et al., Phys. Rev. D 112, 083535 (2025).
  12. E. S. Rykoff et al., Astrophys. J. 785, 104 (2014).
  13. M. Costanzi et al., Mon. Not. R. Astron. Soc. 482, 490 (2019).
  14. A. Farahi, A. E. Evrard, E. Rozo, E. S. Rykoff, and R. H. Wechsler, Mon. Not. R. Astron. Soc. 460, 3900 (2016).
  15. R. Wojtak et al., Mon. Not. R. Astron. Soc. 481, 324 (2018).
  16. Y. Zu, R. Mandelbaum, M. Simet, E. Rozo, and E. S. Rykoff, Mon. Not. R. Astron. Soc. 470, 551 (2017).
  17. M. Maturi, F. Bellagamba, M. Radovich, M. Roncarelli, M. Sereno, L. Moscardini, S. Bardelli, and E. Puddu, Mon. Not. R. Astron. Soc. 485, 498 (2019).
  18. S. Grandis et al., Astron. Astrophys. 700, A15 (2025).
  19. S. Bocquet et al., Phys. Rev. D 110, 083510 (2024).
  20. G. F. Lesci et al., Astron. Astrophys. 703, A25 (2025).
  21. C.-H. To et al., Phys. Rev. D 112, 063537 (2025).
  22. C. Zeng, A. N. Salcedo, H.-Y. Wu, and C. M. Hirata, Mon. Not. R. Astron. Soc. 523, 4270 (2023).
  23. M. Oguri and T. Hamana, Mon. Not. R. Astron. Soc. 414, 1851 (2011).
  24. D. E. Johnston et al., arXiv:0709.1159.
  25. X. Yang, H. J. Mo, F. C. van den Bosch, Y. P. Jing, S. M. Weinmann, and M. Meneghetti, Mon. Not. R. Astron. Soc. 373, 1159 (2006).
  26. J. Tinker, A. V. Kravtsov, A. Klypin, K. Abazajian, M. Warren, G. Yepes, S. Gottlöber, and D. E. Holz, Astrophys. J. 688, 709 (2008).
  27. J. L. Tinker, B. E. Robertson, A. V. Kravtsov, A. Klypin, M. S. Warren, G. Yepes, and S. Gottlöber, Astrophys. J. 724, 878 (2010).
  28. J. F. Navarro, C. S. Frenk, and S. D. M. White, Astrophys. J. 490, 493 (1997).
  29. J. DeRose et al., arXiv:1901.02401.
  30. V. Springel, Mon. Not. R. Astron. Soc. 364, 1105 (2005).
  31. P. S. Behroozi, R. H. Wechsler, and H.-Y. Wu, Astrophys. J. 762, 109 (2013).
  32. DES Collaboration et al., Phys. Rev. D 98, 043526 (2018).
  33. Y. Zhang, S. Adhikari, M. Costanzi, J. Frieman, J. Annis, and C. Chang, Open J. Astrophys. 6, 46 (2023).
  34. J. H. Esteves et al., Mon. Not. R. Astron. Soc. 536, 931 (2025).
  35. M. Aguena et al., Mon. Not. R. Astron. Soc. 502, 4435 (2021).
  36. C. R. Harris et al., Nature (London) 585, 357 (2020).
  37. P. Virtanen, R. Gommers, T. E. Oliphant et al., Nat. Methods 17, 261 (2020).
  38. J. D. Hunter, Comput. Sci. Eng. 9, 90 (2007).
  39. A. Lewis, A. Challinor, and A. Lasenby, Astrophys. J. 538, 473 (2000).
  40. S. Bertocco et al., INAF Trieste Astronomical Observatory Information Technology Framework, in Astronomical Data Analysis Software and Systems XXIX, edited by R. Pizzo, E. R. Deul, J. D. Mol, J. de Plaa, and H. Verkouter, Astronomical Society of the Pacific Conference Series Vol. 527 (2020), p. 303, https://ui.adsabs.harvard.edu/abs/2020ASPC..527..303B.
  41. G. Taffoni, U. Becciani, B. Garilli, G. Maggio, F. Pasian, G. Umana, R. Smareglia, and F. Vitello, arXiv:2002.01283.
  42. M. Costanzi, SelectionBias (2026), https://github.com/MCostanzi/SelectionBias.

Outline

Information

Phys. Rev. D 113, 103508– Published 5 May, 2026
  • Received 22 December 2025
  • Accepted 6 April 2026
Crossmark - Check for updates button
Creative Commons Logo

Published by the American Physical Society under the terms of the Creative Commons Attribution 4.0 International license. Further distribution of this work must maintain attribution to the author(s) and the published article’s title, journal citation, and DOI.

Published by the American Physical Society

Sign In to Your Journals Account

Filter

Filter

Article Lookup

Enter a citation