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| black hole mass–stellar mass relation | |
|---|---|
| Name | Black hole mass–stellar mass relation |
| Type | Astrophysical scaling relation |
| Field | Astronomy |
| Key people | John Kormendy, Luis C. Ho, Katherine Blundell, Martin Rees, Marta Volonteri |
| Discovered | 1990s |
| Related | M–sigma relation, Active galactic nucleus, Quasar, Galaxy merger |
black hole mass–stellar mass relation The black hole mass–stellar mass relation describes an empirical correlation between the mass of central supermassive black holes and the stellar mass of their host galaxy bulges or spheroids. First quantified in observational surveys of nearby galaxies, the relation links measurements from instruments on telescopes such as the Hubble Space Telescope and the Sloan Digital Sky Survey to theoretical work by groups at institutions like the Harvard–Smithsonian Center for Astrophysics and the Max Planck Institute for Astrophysics. It provides constraints used by researchers at the European Southern Observatory, Jet Propulsion Laboratory, and universities including Princeton University and Cambridge University to test models of coevolution between black holes and galaxies.
The relation ties supermassive black hole mass estimates from dynamical modeling and reverberation mapping to stellar mass determinations based on photometry and stellar population synthesis. Key observational programs led by teams at California Institute of Technology, University of California, Berkeley, University of Cambridge, and University of Oxford produced early versions, while theoretical interpretation has been driven by groups at Columbia University, Institute for Advanced Study, and ETH Zurich. The relation is often compared to the M–sigma relation and the Fundamental Plane of elliptical galaxies to place black hole growth in a broader galactic context.
Empirical determinations use stellar- and gas-dynamical modeling from facilities such as the Very Large Telescope, Keck Observatory, Chandra X-ray Observatory, and the Atacama Large Millimeter/submillimeter Array. Surveys like Sloan Digital Sky Survey, COSMOS Survey, and programs associated with the Hubble Space Telescope Treasury projects provide photometry and spectroscopy that teams at University of California, Santa Cruz and University of Arizona analyze. Dynamical masses from authors at University of Texas at Austin and reverberation mapping campaigns coordinated by researchers at Ohio State University and Pennsylvania State University yield black hole masses linked to stellar mass estimates produced by groups at Carnegie Institution for Science and Yale University.
Theoretical frameworks developed at Princeton University, University of Chicago, Harvard University, and Kavli Institute for Cosmology interpret the relation via models invoking active galactic nucleus feedback, merger-driven growth, and secular processes. Semi-analytic models from teams at Durham University and Max Planck Institute for Astrophysics and hydrodynamic cosmological simulations conducted by consortia including the Illustris Project and groups at Flatiron Institute or Lawrence Berkeley National Laboratory explore mechanisms that could produce the observed scaling. Researchers at Columbia University and University of California, Santa Barbara test whether models with momentum-driven or energy-driven feedback reproduce normalization and slope.
Studies using deep surveys from Hubble Space Telescope, James Webb Space Telescope, and ground-based programs at Subaru Telescope and European Southern Observatory examine the relation at higher redshift. Teams at Max Planck Institute for Astronomy, University of Edinburgh, University of Toronto, and Observatoire de Paris compare local calibrations to samples of quasars and bulge-dominated galaxies to assess evolution. Work by researchers at Space Telescope Science Institute and Carnegie Observatories evaluates cosmic assembly histories and the role of early black hole seeding scenarios studied at Institute for Theory and Computation.
Analyses by groups at Yale University, University of Michigan, University of Illinois Urbana–Champaign, and Rutgers University quantify intrinsic scatter and biases introduced by sample selection, measurement errors, and host decomposition. Systematics arise in bulge–disk separation methods developed by teams at University of Hawaii and in black hole mass calibration techniques refined by investigators at Ohio State University and University of California, Riverside. Cross-comparisons by collaborative groups involving Harvard–Smithsonian Center for Astrophysics highlight how censored samples, luminosity thresholds, and active nucleus contamination affect inferred slope and normalization.
The relation informs models of galaxy quenching, morphological transformation, and feedback processes investigated at Princeton University, Rutgers University, University of Cambridge, and Max Planck Institute for Extraterrestrial Physics. Studies connecting black hole growth to star formation histories utilize data from Spitzer Space Telescope, Herschel Space Observatory, and surveys run by the European Southern Observatory and National Radio Astronomy Observatory. Implications extend to cosmological modeling efforts by teams at Institute for Computational Cosmology, Flatiron Institute, and Lawrence Livermore National Laboratory that implement subgrid prescriptions calibrated to the observed scaling.
Unresolved questions addressed by international consortia at Space Telescope Science Institute, European Southern Observatory, Max Planck Society, and university groups at Columbia University and Stanford University include the role of black hole seeding, low-mass galaxy behavior, and redshift dependence. Planned observations with the James Webb Space Telescope, next-generation extremely large telescopes such as the Extremely Large Telescope and the Thirty Meter Telescope, and survey instruments coordinated by National Science Foundation-funded teams will refine measurements. Continued collaboration among theorists at Institute for Advanced Study, Princeton University, and simulation projects like IllustrisTNG aims to converge on a predictive physical model.