Cited by 12Galaxies: Formation, Evolution, PhenomenaDark Matter and Cosmic PhenomenaCosmology and Gravitation Theories

Why weak lensing cluster shapes are insensitive to self-interacting dark matter

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Robertson, Andrew, Huff, Eric, Markovič, Katarina·2023·Monthly Notices of the Royal Astronomical Society

Abstract

We investigate whether the shapes of galaxy clusters inferred from weak gravitational lensing can be used as a test of the nature of dark matter. We analyse mock weak lensing data, with gravitational lenses extracted from cosmological simulations run with two different dark matter models: cold dark matter (CDM) and self-interacting dark matter (SIDM). We fit elliptical Navarro–Frenk–White profiles to the shear fields of the simulated clusters. Despite large differences in the distribution of 3D shapes between CDM and SIDM, we find that the distributions of weak-lensing-inferred cluster shapes are almost indistinguishable. We trace this information loss to two causes. First, weak lensing measures the shape of the projected mass distribution, not the underlying 3D shape, and projection effects wash out some of the difference. Secondly, weak lensing is most sensitive to the projected shape of clusters, on a scale approaching the virial radius ($\sim\! 1.5 \mathrm{\, Mpc}$), whereas SIDM shapes differ most from CDM in the inner halo. We introduce a model for the mass distribution of galaxy clusters where the ellipticity of the mass distribution can vary with distance to the centre of the cluster. While this mass distribution does not enable weak lensing data to distinguish between CDM and SIDM with cluster shapes (the ellipticity at small radii is poorly constrained by weak lensing), it could be useful when modelling combined strong and weak gravitational lensing of clusters.

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  • Weak lensing alone is unlikely to provide meaningful constraints on SIDM, but is highly useful in combination with the other probes here to ensure the inferred cluster mass is accurate on larger scales.

    “Weak lensing alone is unlikely to provide meaningful constraints on SIDM [28], but is highly useful in combination with the other probes here to ensure the inferred cluster mass is accurate on larger scales.”

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Research works printed but not linked: 59

  1. Agrawal P., Cyr-Racine F.-Y., Randall L., Scholtz J., 2017, J. Cosmol. Astropart. Phys. , 2017, 022 · DOI
  2. Allgood B., Flores R. A., Primack J. R., Kravtsov A. V., Wechsler R. H., Faltenbacher A., Bullock J. S., 2006, MNRAS , 367, 1781 · DOI
  3. Andrade K. E., Fuson J., Gad-Nasr S., Kong D., Minor Q., Roberts M. G., Kaplinghat M., 2022, MNRAS , 510, 54 · DOI · Paper page
  4. Astropy Collaboration, 2013, A&A , 558, A33 · DOI · Paper page
  5. Bett P., Eke V., Frenk C. S., Jenkins A., Helly J., Navarro J., 2007, MNRAS , 376, 215 · DOI
  6. Bondarenk o K., Sok olenk o A., Bo yarsk y A., Robertson A., Harv e y D., Re v az Y., 2021, J. Cosmol. Astropart. Phys. , 2021, 043 · DOI
  7. Booth C. M., Schaye J., 2009, MNRAS , 398, 53 · DOI
  8. Brinckmann T., Zavala J., Rapetti D., Hansen S. H., Vogelsberger M., 2018, MNRAS , 474, 746 · DOI
  9. Dalla Vecchia C., Schaye J., 2008, MNRAS , 387, 1431 · DOI
  10. Despali G., Giocoli C., Bonamigo M., Limousin M., Tormen G., 2017, MNRAS , 466, 181 · DOI
  11. Despali G., Walls L. G., Vegetti S., Sparre M., Vogelsberger M., Zavala J., 2022, MNRAS , 516, 4543 · DOI
  12. Duchi J. C., 2016, Deri v ations for Linear Algebra and Optimization. Semantic Scholar, p. 237012311, available at: ht tps://www.semant icscho lar.org/ paper/ Derivations-for-Linear-Algebra-and-Opt imizat ion-Duchi/ 13cea0b9cff9e77c2631000b7de2e85ad992130b D úmet-Montoya H. S., Caminha G. B., Makler M., 2012, A&A , 544, A83 · DOI
  13. Eckert D., Ettori S., Robertson A., Massey R., Pointecouteau E., Harv e y D., McCarthy I. G., 2022, A&A , 666, A41 · DOI
  14. F oreman-Macke y D., 2016, J. Open Source Softw. , 1, 24 · DOI
  15. F oreman-Macke y D., Hogg D. W., Lang D., Goodman J., 2013, PASP , 125, 306 · DOI
  16. Golse G., Kneib J. P., 2002, A&A , 390, 821 · DOI
  17. Harv e y D., Robertson A., Tam S.-I., Jauzac M., Massey R., Rhodes J., McCarthy I. G., 2021, MNRAS , 500, 2627 · DOI
  18. Hinshaw G. et al., 2013, ApJS , 208, 19 · DOI · Paper page
  19. Hunter J. D., 2007, Comput. Sci. Eng , 9, 90 · DOI · Paper page
  20. Jing Y. P., Suto Y., 2002, ApJ , 574, 538 · DOI
  21. Jullo E., Kneib J. P., Limousin M., El íasd óttir Á., Marshall P. J., Verdugo T., 2007, New J. Phys. , 9, 447 · DOI
  22. Kaplinghat M., Keeley R. E., Linden T., Yu H.-B., 2014, Phys. Rev. Lett. , 113, 021302 · DOI
  23. Kaplinghat M., Tulin S., Yu H.-B., 2016, Phys. Rev. Lett. , 116, 041302 · DOI · Paper page
  24. Kullback S., Leibler R. A., 1951, Ann. Math. Statist. , 22, 79 · DOI · Paper page
  25. Leauthaud A. et al., 2007, ApJS , 172, 219 · DOI
  26. Lotz J. M. et al., 2017, ApJ , 837, 97 · DOI
  27. Massey R., Goldberg D. M., 2008, ApJ , 673, L111 · DOI
  28. McCarthy I. G., Schaye J., Bird S., Le Brun A. M. C., 2017, MNRAS , 465, 2936 · DOI
  29. McCarthy I. G., Bird S., Schaye J., Harnois-Deraps J., Font A. S., van Waerbeke L., 2018, MNRAS , 476, 2999 · DOI
  30. McDaniel A., Jeltema T., Profumo S., 2021, J. Cosmol. Astropart. Phys. , 2021, 020 · DOI
  31. Miralda-Escud é J., 2002, ApJ , 564, 60 · DOI
  32. More S., Kravtsov A. V., Dalal N., Gottl öber S., 2011, ApJS , 195, 4 · DOI
  33. Navarro J. F., Frenk C. S., White S. D. M., 1997, ApJ , 490, 493 · DOI · Paper page
  34. Nesseris S., Garc ía-Bellido J., 2013, J. Cosmol. Astropart. Phys. , 2013, 036 · DOI
  35. Niemiec A., Jauzac M., Jullo E., Limousin M., Sharon K., Kneib J.-P., Natarajan P., Richard J., 2020, MNRAS , 493, 3331 · DOI
  36. Nightingale J. W. et al., 2021, J. Open Source Softw. , 6, 2825 · DOI
  37. Oguri M., 2021, PASP , 133, 074504 · DOI
  38. Oguri M., Takada M., Okabe N., Smith G. P., 2010, MNRAS , 405, 2215 · DOI
  39. Peter A. H. G., Rocha M., Bullock J. S., Kaplinghat M., 2013, MNRAS , 430, 105 · DOI
  40. Postman M. et al., 2012, ApJS , 199, 25 · DOI
  41. Price-Whelan A. M. et al., 2018, AJ , 156, 123 · DOI
  42. Ren T., Kwa A., Kaplinghat M., Yu H.-B., 2019, Phys. Rev. X , 9, 031020 · DOI · Paper page
  43. Robertson A., Massey R., Eke V., 2017, MNRAS , 465, 569 · DOI · Paper page
  44. Robertson A., Harv e y D., Masse y R., Eke V., McCarthy I. G., Jauzac M., Li B., Schaye J., 2019, MNRAS , 488, 3646 · DOI
  45. Rocha M., Peter A. H. G., Bullock J. S., Kaplinghat M., Garrison-Kimmel S., O ˜ norbe J., Moustakas L. A., 2013, MNRAS , 430, 81 · DOI
  46. Romualdez L. J. et al., 2018, in Evans C. J., Simard L., Takami H.eds, Proc. SPIE Conf. Ser. Vol. 10702, Ground-based and Airborne Instrumentation for Astronomy VII. SPIE, Bellingham, p. 107020R
  47. Sagunski L., Gad-Nasr S., Colquhoun B., Robertson A., Tulin S., 2021, J. Cosmol. Astropart. Phys. , 1, 024 · DOI · Paper page
  48. Schaye J., Dalla Vecchia C., 2008, MNRAS , 383, 1210 · DOI
  49. Schaye J. et al., 2010, MNRAS , 402, 1536 · DOI
  50. Schneider M. D., Frenk C. S., Cole S., 2012, J. Cosmol. Astropart. Phys. , 2012, 030 · DOI
  51. Shaaban M. M. et al., 2022, AJ , 165, 245 · DOI
  52. Shin T.-h., Clampitt J., Jain B., Bernstein G., Neil A., Rozo E., Rykoff E., 2018, MNRAS , 475, 2421 · DOI
  53. Springel V., 2005, MNRAS , 364, 1105 · DOI · Paper page
  54. Springel V., White S. D. M., Tormen G., Kauffmann G., 2001, MNRAS , 328, 726 · DOI
  55. Tam S.-I., Umetsu K., Robertson A., McCarthy I. G., 2022, preprint ( arXiv:2207.03506 ) · arXiv
  56. van der Walt S., Colbert S. C., Varoquaux G., 2011, Comput. Sci. Eng. , 13, 22 · DOI
  57. Wiersma R. P. C., Schaye J., Smith B. D., 2009a, MNRAS , 393, 99 · DOI
  58. Wiersma R. P. C., Schaye J., Theuns T., Dalla Vecchia C., Tornatore L., 2009b, MNRAS , 399, 574 · DOI
  59. Wyithe J. S. B., Turner E. L., Spergel D. N., 2001, ApJ , 555, 504 · DOI

Cited by

Sorted by citations

Authors
Robertson, A., Huff, E., & Markovič, K.
Affiliations
  • California Institute of Technology (US)
  • Jet Propulsion Laboratory, California Institute of Technology , 4800 Oak Grove Drive, Pasadena, CA 91109, USA
Corresponding author
Robertson, Andrew
Venue
Monthly Notices of the Royal Astronomical Society
Published
2023-03-14
Volume
521
Issue
2
Pages
3172-3185
ISSN
  • 0035-8711 (ISSN-L)
  • 1365-2966
OpenAlex
W4324317058
Cited by
12
References
0
Citations by year
2026: 3 · 2025: 5 · 2024: 4
FWCI
1.32
Type
journal article
Language
en
Open access
Locations
  • Monthly Notices of the Royal Astronomical Society (publishedVersion)
  • arXiv (Cornell University) (submittedVersion)
  • arXiv (Cornell University)
Funders
  • National Aeronautics and Space Administration (80NM0018D0004, 14-APRA14-0013)
  • JPL Information and Technology Solutions Directorate
  • STFC (ST/K00042X/1, ST/P002293/1, ST/R002371/1, ST/S002502/1, ST/R000832/1)
  • Durham University
Topics
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Galaxies: Formation, Evolution, Phenomena
  • Physical Sciences › Physics and Astronomy › Nuclear and High Energy Physics › Dark Matter and Cosmic Phenomena
  • Physical Sciences › Physics and Astronomy › Astronomy and Astrophysics › Cosmology and Gravitation Theories
Keywords
weak gravitational lensing, self-interacting dark matter, cold dark matter, nature of dark matter, Navarro-Frenk-White profile, projection effects, cluster ellipticity, strong gravitational lensing

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