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SUMMARY:On the quenching of star formation in observed and simulated centr
 al galaxies: Evidence for the role of integrated AGN feedback - Joanna Pio
 trowska (Cavendish)
DTSTART:20220513T103000Z
DTEND:20220513T113000Z
UID:TALK171251@talks.cam.ac.uk
CONTACT:Martin Haehnelt
DESCRIPTION:Understanding the physical processes responsible for ceasing s
 tar formation in galaxies is one of the most important unresolved question
 s in the field of galaxy evolution. Over the past two decades multiple mec
 hanisms were suggested as potential drivers of the transition between the 
 star-forming and quiescent galaxy categories\, referred to as galaxy ‘qu
 enching’. \n\n\nIn this talk I will present the results of our recent st
 udy\, in which we combine machine learning with partial correlation analys
 is to determine which among the three potential quenching mechanisms: supe
 rnova feedback\, halo shock heating or AGN feedback are most likely respon
 sible for bringing star formation to a halt in massive\, central galaxies.
  To this end we bridge the gap between theory and observation by extractin
 g theoretical predictions from three state-of-the-art cosmological simulat
 ions – EAGLE\, Illustris and IllustrisTNG and comparing them with the Sl
 oan Digital Sky Survey (SDSS) observations. We find that the supermassive 
 black hole mass (MBH) is the most powerful parameter in determining whethe
 r a galaxy is star-forming or quenched across all datasets. Remarkably\, t
 his result is true for all different implementations of AGN feedback in th
 e simulations and is met overwhelmingly well in the SDSS\, where we infer 
 MBH from a variety of calibrations for ~230 000 local galaxies. \n\n\n\nIn
  my brief talk I will share our results together with our methodology to m
 ake a convincing case for star formation being quenched by AGN in massive\
 , central galaxies. If you would like to learn more about this study\, you
  can now read it on arXiv/MNRAS at the following link: https://arxiv.org/a
 bs/2112.07672
LOCATION:in person &amp\; via zoom 
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