Massive, red galaxies in a hierarchical universe I. Counts of Extremely Red Objects and basic properties

TL;DR

This paper compares two galaxy formation models to observations of Extremely Red Objects (EROs), finding that AGN feedback models match observed counts but may quench star formation too effectively.

Contribution

It evaluates the effectiveness of superwind and AGN feedback models in predicting ERO properties within a hierarchical universe framework.

Findings

AGN feedback model matches ERO counts and redshift distribution

Superwind model underestimates ERO numbers by an order of magnitude

Model predicts too many passive galaxies at high redshift

Abstract

We present predictions for the abundance and nature of Extremely Red Objects (EROs) in the Lambda cold dark matter model. EROs are red, massive galaxies observed at z>= 1 and their numbers and properties pose a challenge to hierarchical galaxy formation models. We compare the predictions from two published models, one of which invokes a "superwind" to regulate star formation in massive haloes and the other which suppresses gas cooling in haloes through "radio-mode" AGN feedback. The superwind model underestimates the number counts of EROs by an order of magnitude, whereas the radio-mode AGN feedback model gives excellent agreement with the number counts and redshift distribution of EROs. In the AGN feedback model the ERO population is dominated by old, passively evolving galaxies, whereas observations favour an equal split between old galaxies and dusty starbursts. Also, the model predicts a more extended redshift distribution of passive galaxies than is observed. These comparisons suggest that star formation may be quenched too efficiently in this model.