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SUMMARY:Augmenting Galaxy Catalogues in FLAMINGO using Machine Learning
DTSTART;VALUE=DATE-TIME:20260917T074000Z
DTEND;VALUE=DATE-TIME:20260917T080500Z
DTSTAMP;VALUE=DATE-TIME:20261023T231413Z
UID:indico-contribution-31303@indico.ific.uv.es
DESCRIPTION:Speakers: Elliot Scott (Newcastle University)\nRobust hydrodyn
 amic simulations are necessary for placing strong constraints on cosmologi
 cal parameters through the analysis pipelines of observations of statistic
 s such as galaxy clustering. However\, for these purposes\, the simulation
 s need both large box size and high resolution\, which is computationally 
 prohibitive. In this work we use the connection between galaxies and their
  host dark matter halos to populate dark-matter-only simulations\, using d
 ata from the FLAMINGO simulations suite. We employ the Extremely Randomize
 d Trees algorithm to model the connection between the mass profile\, histo
 ry and environment of dark matter halos and the probability distribution o
 f the stellar mass of the galaxy contained in the halo. However\, we also 
 demonstrate that dark matter properties which probe the centre of the dark
  matter profile are highly predictive when applied to data from hydrodynam
 ic simulations but are also sensitive to the baryonic feedback missing fro
 m dark-matter-only simulations. We use a Gaussian Processes emulator that 
 simultaneously optimises the hyperparameters of our model and selects for 
 the dark matter features which are predictive of the stellar mass while be
 ing insensitive to the differences between the hydrodynamic and dark-matte
 r-only simulations. Using this combination of features\, we produce novel 
 catalogues from large box dark-matter-only simulations in FLAMINGO. Our ca
 talogue from the FLAMINGO-10k simulation reproduces the galaxy stellar mas
 s function in the hydrodynamic simulations to within 0.1 dex in the range 
 of stellar masses to which the FLAMINGO stellar mass function was calibrat
 ed. We also reproduce the mean and scatter of the stellar mass-halo mass r
 elation to within 0.2 dex over a large range of halo masses. Furthermore w
 e find agreement in the two-point correlation function within several stel
 lar mass ranges to match to within 0.1 dex over a large range of length sc
 ales.\n\nhttps://indico.ific.uv.es/event/8160/contributions/31303/
LOCATION:
URL:https://indico.ific.uv.es/event/8160/contributions/31303/
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