Hostname: page-component-848d4c4894-nr4z6 Total loading time: 0 Render date: 2024-05-01T03:05:21.728Z Has data issue: false hasContentIssue false

Predicting the scaling relations between the dark matter halo mass and observables from generalised profiles II: Intracluster gas emission

Published online by Cambridge University Press:  26 March 2024

Andrew Sullivan*
Affiliation:
International Centre for Radio Astronomy Research, The University of Western Australia, Crawley, Western Australia, Australia ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
Chris Power
Affiliation:
International Centre for Radio Astronomy Research, The University of Western Australia, Crawley, Western Australia, Australia ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
Connor Bottrell
Affiliation:
International Centre for Radio Astronomy Research, The University of Western Australia, Crawley, Western Australia, Australia
Aaron Robotham
Affiliation:
International Centre for Radio Astronomy Research, The University of Western Australia, Crawley, Western Australia, Australia ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D)
Stanislav Shabala
Affiliation:
ARC Centre of Excellence for All Sky Astrophysics in 3 Dimensions (ASTRO 3D) School of Natural Sciences, University of Tasmania, Hobart, Tasmania, Australia
*
Corresponding author: Andrew Sullivan; Email: andrew.sullivan@icrar.org

Abstract

We investigate the connection between a cluster’s structural configuration and observable measures of its gas emission that can be obtained in X-ray and Sunyaev–Zeldovich (SZ) surveys. We present an analytic model for the intracluster gas density profile: parameterised by the dark matter halo’s inner logarithmic density slope, $\alpha$, the concentration, c, the gas profile’s inner logarithmic density slope, $\varepsilon$, the dilution, d, and the gas fraction, $\eta$, normalised to cosmological content. We predict four probes of the gas emission: the emission-weighted, $T_\mathrm{X}$, and mean gas mass-weighted, $T_\mathrm{m_g}$, temperatures, and the spherically, $Y_\mathrm{sph}$, and cylindrically, $Y_\mathrm{cyl}$, integrated Compton parameters. Over a parameter space of clusters, we constrain the X-ray temperature scaling relations, $M_{200} - T_\mathrm{X}$ and $M_{500} - T_\mathrm{X}$, within $57.3\%$ and $41.6\%$, and $M_{200} - T_\mathrm{m_g}$ and $M_{500} - T_\mathrm{m_g}$, within $25.7\%$ and $7.0\%$, all respectively. When excising the cluster’s core, the $M_{200} - T_\mathrm{X}$ and $M_{500} - T_\mathrm{X}$ relations are further constrained, to within $31.3\%$ and $17.1\%$, respectively. Similarly, we constrain the SZ scaling relations, $M_{200} - Y_\mathrm{sph}$ and $M_{500} - Y_\mathrm{sph}$, within $31.1\%$ and $17.7\%$, and $M_{200} - Y_\mathrm{cyl}$ and $M_{500} - Y_\mathrm{cyl}$, within $25.2\%$ and $22.0\%$, all respectively. The temperature observable $T_\mathrm{m_g}$ places the strongest constraint on the halo mass, whilst $T_\mathrm{X}$ is more sensitive to the parameter space. The SZ constraints are sensitive to the gas fraction, whilst insensitive to the form of the gas profile itself. In all cases, the halo mass is recovered with an uncertainty that suggests the cluster’s structural profiles only contribute a minor uncertainty in its scaling relations.

Type
Research Article
Copyright
© The Author(s), 2024. Published by Cambridge University Press on behalf of Astronomical Society of Australia

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Akino, D., Eckert, D., Okabe, N., et al. 2022, PASJ, 74, 175 Google Scholar
Allison, J. R., Taylor, A. C., Jones, M. E., Rawlings, S., & Kay, S. T. 2011, MNRAS, 410, 341 Google Scholar
Andersson, K., Benson, B. A., Ade, P. A. R., et al. 2011, ApJ, 738, 48 Google Scholar
Angelinelli, M., Vazza, F., Giocoli, C., et al. 2020, MNRAS, 495, 864 CrossRefGoogle Scholar
Arnaud, M., Pointecouteau, E., & Pratt, G. W. 2005, A&A, 441, 893 Google Scholar
Arnaud, M., Pratt, G. W., Piffaretti, R., et al. 2010, A&A, 517, A92 Google Scholar
Babyk, I. V., & McNamara, B. R. 2023, ApJ, 946, 54 CrossRefGoogle Scholar
Bleem, L. E., Stalder, B., de Haan, T., et al. 2015, ApJS, 216, 27 Google Scholar
Bode, P., Ostriker, J. P., & Vikhlinin, A. 2009, ApJ, 700, 989 CrossRefGoogle Scholar
Bullock, J. S., Kolatt, T. S., Sigad, Y., et al. 2001, MNRAS, 321, 559 CrossRefGoogle Scholar
Cavaliere, A., & Fusco-Femiano, R. 1978, A&A, 70, 677 Google Scholar
Choi, S. K., Hasselfield, M., Ho, S.-P. P., et al. 2020, J. Cosmology Astropart. Phys., 2020, 045 Google Scholar
Cole, S., & Lacey, C. 1996, MNRAS, 281, 716 Google Scholar
Correa, C. A., Wyithe, J. S. B., Schaye, J., & Duffy, A. R. 2015, MNRAS, 452, 1217 Google Scholar
Croston, J. H., Pratt, G. W., Böhringer, H., et al. 2008, A&A, 487, 431 Google Scholar
Czakon, N. G., Sayers, J., Mantz, A., et al. 2015, ApJ, 806, 18 Google Scholar
de Blok, W. J. G., & McGaugh, S. S. 1997, MNRAS, 290, 533 CrossRefGoogle Scholar
de Blok, W. J. G., McGaugh, S. S., Bosma, A., & Rubin, V. C. 2001, ApJ, 552, L23 CrossRefGoogle Scholar
De Grandi, S., & Molendi, S. 2002, ApJ, 567, 163 Google Scholar
Di Cintio, A., Brook, C. B., Dutton, A. A., et al. 2014 a, MNRAS, 441, 2986 Google Scholar
Di Cintio, A., Brook, C. B., Macciò, A. V., et al. 2014 b, MNRAS, 437, 415 CrossRefGoogle Scholar
Duffy, A. R., Schaye, J., Kay, S. T., & Dalla Vecchia, C. 2008, MNRAS, 390, L64 Google Scholar
Eckert, D., Ettori, S., Molendi, S., Vazza, F., & Paltani, S. 2013, A&A, 551, A23 Google Scholar
Eckert, D., Ghirardini, V., Ettori, S., et al. 2019, A&A, 621, A40 Google Scholar
Ettori, S. 2015, MNRAS, 446, 2629 Google Scholar
Ettori, S., & Eckert, D. 2022, A&A, 657, L1 Google Scholar
Ettori, S., Lovisari, L., & Eckert, D. 2023, A&A, 669, A133 Google Scholar
Ettori, S., Morandi, A., Tozzi, P., et al. 2009, A&A, 501, 61 CrossRefGoogle Scholar
Frenk, C. S., White, S. D. M., Bode, P., et al. 1999, ApJ, 525, 554 Google Scholar
Genel, S., Genzel, R., Bouché, N., Naab, T., & Sternberg, A. 2009, ApJ, 701, 2002 Google Scholar
Ghirardini, V., Ettori, S., Eckert, D., & Molendi, S. 2019a, A&A, 627, A19 Google Scholar
Ghirardini, V., Eckert, D., Ettori, S., et al. 2019b, A&A,621, A41 Google Scholar
Jansen, F., Lumb, D., Altieri, B., et al. 2001, A&A, 365, L1 Google Scholar
Komatsu, E., & Seljak, U. 2001, MNRAS, 327, 1353 Google Scholar
Kuzio de Naray, R., McGaugh, S. S., & de Blok, W. J. G. 2008, ApJ, 676, 920 Google Scholar
Lau, E. T., Nagai, D., Avestruz, C., Nelson, K., & Vikhlinin, A. 2015, ApJ, 806, 68 Google Scholar
Liu, J., Mohr, J., Saro, A., et al. 2015, MNRAS, 448, 2085 Google Scholar
Ludlow, A. D., Navarro, J. F., Angulo, R. E., et al. 2014, MNRAS, 441, 378 CrossRefGoogle Scholar
Ludlow, A. D., Navarro, J. F., Li, M., et al. 2012, MNRAS, 427, 1322 Google Scholar
Lyskova, N., Churazov, E., Khabibullin, I. I., et al. 2023, MNRAS, 525, 898 Google Scholar
Martizzi, D., & Agrusa, H. 2016, arXiv e-prints, arXiv:1608.04388Google Scholar
Maughan, B. J. 2014, MNRAS, 437, 1171 Google Scholar
McDonald, M., Allen, S. W., Bayliss, M., et al. 2017, ApJ, 843, 28 Google Scholar
Moore, B. 1994, Nature, 370, 629 Google Scholar
Morandi, A., Sun, M., Forman, W., & Jones, C. 2015, MNRAS, 450, 2261 Google Scholar
Navarro, J. F., Frenk, C. S., & White, S. D. M. 1995, MNRAS, 275, 720 CrossRefGoogle Scholar
Navarro, J. F., Frenk, C. S., & White, S. D. M. 1996, ApJ, 462, 563 Google Scholar
Navarro, J. F., Frenk, C. S., & White, S. D. M. 1997, ApJ, 490, 493 Google Scholar
Nelson, K., Lau, E. T., & Nagai, D. 2014, ApJ, 792, 25 Google Scholar
Ogiya, G., & Hahn, O. 2018, MNRAS, 473, 4339 Google Scholar
Oh, S.-H., Brook, C., Governato, F., et al. 2011, AJ, 142, 24 CrossRefGoogle Scholar
Osato, K., & Nagai, D. 2023, MNRAS, 519, 2069 Google Scholar
Patej, A., & Loeb, A. 2015, ApJ, 798, L20 Google Scholar
Pizzardo, M., Geller, M. J., Kenyon, S. J., Damjanov, I., & Diaferio, A. 2023, A&A, 680, A48 CrossRefGoogle Scholar
Collaboration, Planck, Ade, P. A. R., Aghanim, N., et al. 2016 a, A&A, 594, A13 Google Scholar
Collaboration, Planck, Aghanim, N., Arnaud, M., et al. 2016 b, A&A, 594, A22Google Scholar
Pontzen, A., & Governato, F. 2012, MNRAS, 421, 3464 Google Scholar
Power, C., Elahi, P. J., Welker, C., et al. 2020, MNRAS, 491, 3923 Google Scholar
Pratt, G. W., Arnaud, M., Maughan, B. J., & Melin, J. B. 2023, A&A, 669, C2 CrossRefGoogle Scholar
Predehl, P., Andritschke, R., Arefiev, V., et al. 2021, A&A, 647, A1 Google Scholar
Rasia, E., Mazzotta, P., Borgani, S., et al. 2005, ApJ, 618, L1 CrossRefGoogle Scholar
Sarazin, C. L. 1988, X-ray emission from clusters of galaxiesCrossRefGoogle Scholar
Sayers, J., Sereno, M., Ettori, S., et al. 2021, MNRAS, 505, 4338 CrossRefGoogle Scholar
Sun, M., Voit, G. M., Donahue, M., et al. 2009, ApJ, 693, 1142 CrossRefGoogle Scholar
Sunyaev, R. A., & Zeldovich, Y. B. 1970, Comments on Astrophysics and Space Physics, 2, 66 Google Scholar
Sunyaev, R. A., & Zeldovich, Y. B. 1972, Comments on Astrophysics and Space Physics, 4, 173 Google Scholar
Vanderlinde, K., Crawford, T. M., de Haan, T., et al. 2010, ApJ, 722, 1180 Google Scholar
Vikhlinin, A., Kravtsov, A., Forman, W., et al. 2006, ApJ, 640, 691 CrossRefGoogle Scholar
Vikhlinin, A., Burenin, R. A., Ebeling, H., et al. 2009, ApJ, 692, 1033 Google Scholar
Weisskopf, M. C., Tananbaum, H. D., Van Speybroeck, L. P., & O’Dell, S. L. 2000, in Society of Photo-Optical Instrumentation Engineers (SPIE) Conference Series, Vol. 4012, X-Ray Optics, Instruments, and Missions III, ed. Truemper, J. E. & Aschenbach, B., 2–16Google Scholar
White, M. 2001, A&A, 367, 27 CrossRefGoogle Scholar
White, S. D. M., & Frenk, C. S. 1991, ApJ, 379, 52 Google Scholar
White, S. D. M., & Rees, M. J. 1978, MNRAS, 183, 341 Google Scholar
Yoshikawa, K., Jing, Y. P., & Suto, Y. 2000, ApJ, 535, 593 CrossRefGoogle Scholar