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Putting brakes on star formation in central galaxies

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Understanding the physical processes responsible for ceasing star formation in galaxies is one of the most important unresolved questions in the field of galaxy evolution. The past two decades of both observations and simulations showed that there potentially exist many a reason for which galaxies can experience a slowdown in their star formation activity, i.e., ‘quench’ their star formation. In the complex landscape of correlated data, varying timescales, and limited observables, identifying key physical drivers of quenching becomes a non-trivial problem. In this talk I will investigate how star formation is brought to a halt in local, massive, central galaxies by comparing Sloan Digital Sky Survey (SDSS) observations with three state-of-the-art hydrodynamical cosmological simulations – EAGLE , Illustris and IllustrisTNG. In this work we address the complex nature of quenching by combining machine learning techniques with partial correlation analysis to determine which galactic property is the most predictive of galaxy quiescence. We find that the supermassive black hole mass (MBH) is the most powerful parameter in determining whether a galaxy is star-forming or quenched – a statement which is true for all three implementations of AGN feedback in the simulations. Remarkably, this prediction is precisely confirmed in the SDSS observations, where we infer MBH from a variety of calibrations for ~230 000 local galaxies.

This talk is part of the Institute of Astronomy Seminars series.

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