The cosmic growth of the active black hole population at 1<z<2 in zCOSMOS, VVDS and SDSS

TL;DR

This study analyzes the evolution of active black holes at redshifts 1 to 2 by constructing their mass and accretion rate distributions, revealing downsizing phenomena and phase of intense growth, with implications for models of black hole evolution.

Contribution

It provides the first detailed census of active black hole populations at 1<z<2 using a novel maximum likelihood approach to disentangle mass and accretion rate evolution.

Findings

Black hole mass function shows downsizing at z~1.5 compared to z=0.

Active fraction of AGN is nearly flat across black hole masses at z~1.5.

Results agree with some models but highlight the need for refinement.

Abstract

We present a census of the active black hole population at 1<z<2, by constructing the bivariate distribution function of black hole mass and Eddington ratio, employing a maximum likelihood fitting technique. The study of the active black hole mass function (BHMF) and the Eddington ratio distribution function (ERDF) allows us to clearly disentangle the active galactic nuclei (AGN) downsizing phenomenon, present in the AGN luminosity function, into its physical processes of black hole mass downsizing and accretion rate evolution. We are utilizing type-1 AGN samples from three optical surveys (VVDS, zCOSMOS and SDSS), that cover a wide range of 3 dex in luminosity over our redshift interval of interest. We investigate the cosmic evolution of the AGN population as a function of AGN luminosity, black hole mass and accretion rate. Compared to z = 0, we find a distinct change in the shape of the BHMF and the ERDF, consistent with downsizing in black hole mass. The active fraction or duty cycle of type-1 AGN at z~1.5 is almost flat as a function of black hole mass, while it shows a strong decrease with increasing mass at z=0. We are witnessing a phase of intense black hole growth, which is largely driven by the onset of AGN activity in massive black holes towards z=2. We finally compare our results to numerical simulations and semi-empirical models and while we find reasonable agreement over certain parameter ranges, we highlight the need to refine these models in order to match our observations.