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What Do Statistics Reveal About the MBHMbulge Correlation and Co-Evolution?

Published online by Cambridge University Press:  03 June 2010

Chien Y. Peng*
Affiliation:
Herzberg Institute of Astrophysics, National Research Council of Canada, 5071 West Saanich Road, Victoria, British Columbia, V9E 2E7, Canada Email: [email protected]
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Abstract

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Observational data show that the correlation between the masses of supermassive black holes MBH and galaxy bulge masses Mbulge follows a nearly linear trend, and that the correlation is strongest with the bulge rather than the total stellar mass Mgal. With increasing redshift, the ratio Γ=MBH/Mbulge relative to z = 0 also seems to be larger for MBH≳108.5M. This study looks more closely at statistics to see what effect it has on creating, and observing, the MBHMbulge correlation. It is possible to show that if galaxy merging statistics can drive the correlation, minor mergers are responsible for causing a convergence to linearity most evident at high masses, whereas major mergers have a central limit convergence that more strongly reduces the scatter. This statistical reasoning is agnostic about galaxy morphology. Therefore, combining statistical prediction (more major mergers ⟹ tighter correlation) with observations (bulges = tightest correlation), would lead one to conclude that more major mergers (throughout an entire merger tree, not just the primary branch) give rise to more prominent bulges. Lastly, with regard to controversial findings that Γ increases with redshift, this study shows why the luminosity function (LF) bias argument, taken correctly at face value, actually strengthens, rather than weakens, the findings. However, correcting for LF bias is unwarranted because the BH mass scale for quasars is bootstrapped to the MBH–σ* correlation in normal galaxies at z = 0, and quasar–quasar comparisons are mostly internally consistent. In Monte-Carlo simulations, high Γ galaxies are indeed present: they are statistical outliers (i.e., “under-merged”) that take longer to converge to linearity via minor mergers. Additional evidence that the galaxies are undermassive at z≳2 for their MBH is that the quasar hosts are very compact for their expected mass.

Type
Contributed Papers
Copyright
Copyright © International Astronomical Union 2010

References

Adelberger, K. L. & Steidel, C. C. 2005, ApJ, 627, L1Google Scholar
Alexander, D. M., et al. 2008, AJ, 135, 1968Google Scholar
Ciotti, L. & van Albada, T. S. 2001, ApJ, 552, L13Google Scholar
Di Matteo, T., Springel, V., & Hernquist, L. 2005, Nature, 433, 604Google Scholar
Ferrarese, L. & Merritt, D. 2000, ApJ, 539, L9CrossRefGoogle Scholar
Fine, S., et al. 2006, MNRAS, 373, 613Google Scholar
Gebhardt, K., et al. 2000, ApJ, 539, L13Google Scholar
Granato, G. L., De Zotti, G., Silva, L., Bressan, A., & Danese, L. 2004, ApJ, 600, 580Google Scholar
Häring, N. & Rix, H.-W. 2004, ApJ, 604, L89Google Scholar
Hopkins, P. F., Hernquist, L., Cox, T. J., Robertson, B., & Krause, E. 2007a, ApJ, 669, 67Google Scholar
Hopkins, P. F., Richards, G. T., & Hernquist, L. 2007b, ApJ, 654, 731CrossRefGoogle Scholar
Islam, R. R., Taylor, J. E., & Silk, J. 2003, MNRAS, 340, 647CrossRefGoogle Scholar
Kaspi, S., Smith, P. S., Netzer, H., Maoz, D., Jannuzi, B. T., & Giveon, U. 2000, ApJ, 533, 631Google Scholar
Kauffmann, G., & Haehnelt, M. 2000, MNRAS, 311, 576Google Scholar
Kim, M., et al. 2008, ApJ, 687, 767Google Scholar
Kollmeier, J. A., et al. 2006, ApJ, 648, 128Google Scholar
Kormendy, J. & Richstone, D. 1995, ARAA, 33, 581Google Scholar
Lauer, T. R., Tremaine, S., Richstone, D., & Faber, S. M. 2007, ApJ, 670, 249Google Scholar
Magorrian, J., et al. 1998, AJ, 115, 2285CrossRefGoogle Scholar
Marconi, A. & Hunt, L. K. 2003, ApJ, 589, L21CrossRefGoogle Scholar
McLure, R. J., et al. 2006, MNRAS, 368, 1395Google Scholar
Onken, C. A., et al. 2004, ApJ, 615, 645Google Scholar
Peng, C. Y. 2004, PhD thesis, The University of ArizonaGoogle Scholar
Peng, C. Y. 2007, ApJ, 671, 1098CrossRefGoogle Scholar
Peng, C. Y., Impey, C. D., Ho, L. C., Barton, E. J., & Rix, H.-W. 2006a, ApJ, 640, 114Google Scholar
Peng, C. Y., et al. 2006b, ApJ, 649, 616CrossRefGoogle Scholar
Robertson, B., et al. 2006, ApJ, 641, 90Google Scholar
Salviander, S., et al. 2006, New Astron. Revs., 50, 803Google Scholar
Stockton, A., McGrath, E., Canalizo, G., Iye, M., & Maihara, T. 2008, ApJ, 672, 146Google Scholar
Treu, T., Woo, J.-H., Malkan, M. A., & Blandford, R. D. 2007, ApJ, 667, 117Google Scholar
Trujillo, I., et al. 2006, ApJ, 650, 18Google Scholar
van Dokkum, P. G., et al. 2008, ApJ, 677, L5Google Scholar
Woo, J.-H., Treu, T., Malkan, M. A., & Blandford, R. D. 2006, ApJ, 645, 900Google Scholar