Supermassive black hole ancestors

Astronomy and Astrophysics – Astrophysics – Cosmology and Extragalactic Astrophysics

Scientific paper

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12 pages, 9 figures, 1 table, MNRAS in press

Scientific paper

We study a model in which supermassive black holes (SMBHs) can grow by the combined action of gas accretion on heavy seeds and mergers of both heavy (m_s^h=10^5 Msol) and light (m_s^l = 10^2 Msol) seeds. The former result from the direct collapse of gas in T_s^h >1.5x10^4K, H_2-free halos; the latter are the endproduct of a standard H_2-based star formation process. The H_2-free condition is attained by exposing halos to a strong (J_21 > 10^3) Lyman-Werner UV background produced by both accreting BHs and stars, thus establishing a self-regulated growth regime. We find that this condition is met already at z close to 18 in the highly biased regions in which quasars are born. The key parameter allowing the formation of SMBHs by z=6-7 is the fraction of halos that can form heavy seeds: the minimum requirement is that f_heavy>0.001; SMBH as large as 2x10^10 Msol can be obtained when f_heavy approaches unity. Independently of f_heavy, the model produces a high-z stellar bulge-black hole mass relation which is steeper than the local one, implying that SMBHs formed before their bulge was in place. The formation of heavy seeds, allowed by the Lyman-Werner radiative feedback in the quasar-forming environment, is crucial to achieve a fast growth of the SMBH by merger events in the early phases of its evolution, i.e. z>7. The UV photon production is largely dominated by stars in galaxies, i.e. black hole accretion radiation is sub-dominant. Interestingly, we find that the final mass of light BHs and of the SMBH in the quasar is roughly equal by z=6; by the same time only 19% of the initial baryon content has been converted into stars. The SMBH growth is dominated at all epochs z > 7.2 by mergers (exceeding accretion by a factor 2-50); at later times accretion becomes by far the most important growth channel. We finally discuss possible shortcomings of the model.

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