Dark halo microphysics and massive black hole scaling relations in galaxies

Saxton, C. J.; Soria, Roberto; Wu, Kinwah

doi:10.1093/mnras/stu1984

Cited by 7 publications

(6 citation statements)

References 324 publications

(400 reference statements)

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“…Power-law fits to these correlations provide efficient means to estimate black hole masses in a statistically significant sample (Beifiori et al 2012;McConnell & Ma 2013). Several authors have argued the empirical scaling relations are rooted in a more fundamental relation between M BH and properties of the host galaxy dark matter halo, such as the halo virial mass (M vir DM ) or v max circ = GM (<r) r | max , the maximum circular velocity achieved beyond the bulge (e.g., Ferrarese 2002;Saxton et al 2014;Larkin & McLaughlin 2016). In this work we use v max circ as provided by numerical simulations that trace DM halo evolution from primordial density fluctuations in combination with the correlation found between M BH and the stellar velocity dispersion of the bulge σ.…”

Section: A Redshift Dependent M Bh − σ Relationmentioning

confidence: 99%

SMBH Seeds: Model Discrimination with High-energy Emission Based on Scaling Relation Evolution

Ben-Ami

Vikhlinin

Loeb

2018

ApJ

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We explore the expected X-ray (0.5-2keV) signatures from super massive black holes (SMBHs) at high redshifts (z ∼ 5 − 12) assuming various models for their seeding mechanism and evolution. The seeding models are approximated through deviations from the M BH − σ relation observed in the local universe. We use results from N-body simulations of the large-scale structure to estimate the density of observable SMBHs. We focus on two families of seeding models: (i ) light seed BHs from remnants of Pop-III stars; and (ii ) heavy seeds from the direct collapse of gas clouds. We investigate several models for the accretion history, such as sub-Eddington accretion, slim disk models allowing mild super-Eddington accretion and torque-limited growth models. We consider observations with two instruments: (i ) the Chandra X-ray observatory, and (ii ) the proposed Lynx. We find that all the simulated models are in agreement with the current results from Chandra Deep Field South (CDFS) -i.e., consistent with zero to a few observed SMBHs in the field of view. In deep Lynx exposures, the number of observed objects is expected to become statistically significant. We demonstrate the capability to limit the phase space of plausible scenarios of the birth and evolution of SMBHs by performing deep observations at a flux limit of 1 × 10 −19 erg cm −2 s −1 . Finally, we estimate the expected contribution from each model to the unresolved cosmic X-ray background (CXRB), and show that our models are in agreement with current limits on the CXRB and the expected contribution from unresolved quasars. We find that an analysis of CXRB contributions down to the Lynx confusion limit yields valuable information that can help identify the correct scenario for the birth and evolution of SMBHs.

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Section: A Redshift Dependent M Bh − σ Relationmentioning

confidence: 99%

SMBH Seeds: Model Discrimination with High-energy Emission Based on Scaling Relation Evolution

Ben-Ami

Vikhlinin

Loeb

2018

ApJ

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“…The goal of the present study is to strengthen the case for a very early feedback process between the growth of the total stellar population mass of a bulge (or a galaxy) and the growth of its central massive body. The mo-tivation to consider a very early feedback comes from the correlation between the mass of the SMBH and the properties of its host galaxy (bulge; e.g., Benedetto et al 2013;Graham, & Scott 2013;Saxton et al 2014), in particular the total stellar mass. The properties of the bulge-SMBH masses correlation itself shows that this correlation cannot be driven by many mergers of low mass galaxies (Ginat et al 2016).…”

Section: Discussion and Summarymentioning

confidence: 99%

Jet-driven active galactic nucleus feedback in galaxy formation before black hole formation

Bear,

Soker

2019

Preprint

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We propose a scenario where during galaxy formation an active galactic nucleus (AGN) feedback mechanism starts before the formation of a supermassive black hole (SMBH). The supermassive star (SMS) progenitor of the SMBH accretes mass as it grows and launches jets. We simulate the evolution of SMSs and show that the escape velocity from their surface is ≈ several × 10 3 km s −1 , with large uncertainties. We could not converge with the parameters of the evolutionary numerical code mesa to resolve the uncertainties for SMS evolution. Under the assumption that the jets carry about ten percent of the mass of the SMS, we show that the energy in the jets is a substantial fraction of the binding energy of the gas in the galaxy/bulge. Therefore, the jets that the SMS progenitor of the SMBH launches carry sufficient energy to establish a feedback cycle with the gas in the inner zone of the galaxy/bulge, and hence, set a relation between the total stellar mass and the mass of the SMS. As the SMS collapses to form the SMBH at the center, there is already a relation (correlation) between the newly born SMBH mass and the stellar mass of the galaxy/bulge. During the formation of the SMBH it rapidly accretes mass from the collapsing SMS and launches very energetic jets that might unbind most of the gas in the galaxy/bulge.

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“…One possible explanation is that both properties are associated with a common event such as major mergers, thus galaxies experimenting a recent major merger should have a large MBH mass and GC populations (e.g., Jahnke & Macciò 2011). The total mass of GCs and the central black hole mass can also correlate with the bulge binding energy in elliptical galaxies (e.g., Snyder et al 2011;Saxton et al 2014). Rapid growth of the nuclear black hole of a galaxy might be fuelled by a massive inflow of cold gas towards the centre of the galaxy.…”

Section: Irrmentioning

confidence: 99%

The overlooked potential of generalized linear models in astronomy – III. Bayesian negative binomial regression and globular cluster populations

Hilbe

Buelens²,

Riggs

et al. 2015

Mon. Not. R. Astron. Soc.

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In this paper, the third in a series illustrating the power of generalized linear models (GLMs) for the astronomical community, we elucidate the potential of the class of GLMs which handles count data. The size of a galaxy's globular cluster population (N GC ) is a prolonged puzzle in the astronomical literature. It falls in the category of count data analysis, yet it is usually modelled as if it were a continuous response variable. We have developed a Bayesian negative binomial regression model to study the connection between N GC and the following galaxy properties: central black hole mass, dynamical bulge mass, bulge velocity dispersion, and absolute visual magnitude. The methodology introduced herein naturally accounts for heteroscedasticity, intrinsic scatter, errors in measurements in both axes (either discrete or continuous), and allows modelling the population of globular clusters on their natural scale as a non-negative integer variable. Prediction intervals of 99 per cent around the trend for expected N GC comfortably envelope the data, notably including the Milky Way, which has hitherto been considered a problematic outlier. Finally, we demonstrate how random intercept models can incorporate information of each particular galaxy morphological type. Bayesian variable selection methodology allows for automatically identifying galaxy types with different productions of GCs, suggesting that on average S0 galaxies have a GC population 35 per cent smaller than other types with similar brightness.

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Dark halo microphysics and massive black hole scaling relations in galaxies

Cited by 7 publications

References 324 publications

SMBH Seeds: Model Discrimination with High-energy Emission Based on Scaling Relation Evolution

SMBH Seeds: Model Discrimination with High-energy Emission Based on Scaling Relation Evolution

Jet-driven active galactic nucleus feedback in galaxy formation before black hole formation

The overlooked potential of generalized linear models in astronomy – III. Bayesian negative binomial regression and globular cluster populations

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