On the quenching of star formation in observed and simulated central galaxies: Evidence for the role of integrated AGN feedback

Understand

In this paper we investigate how massive central galaxies cease their star formation by comparing theoretical predictions from cosmological simulations: EAGLE, Illustris and IllustrisTNG with observations of the local Universe from the Sloan Digital Sky Survey (SDSS).

• Our machine learning (ML) classification reveals supermassive black hole mass ($M_{\rm BH}$) as the most predictive parameter in determining whether a galaxy is star forming or quenched at redshift $z=0$ in all three simulations.
• This predicted consequence of active galactic nucleus (AGN) quenching is reflected in the observations, where it is true for a range of indirect estimates of $M_{\rm BH}$ via proxies as well as its dynamical measurements.
• Our partial correlation analysis shows that other galactic parameters lose their strong association with quiescence, once their correlations with $M_{\rm BH}$ are accounted for.