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SUMMARY:Finding the boundary: Using galaxy membership to inform galaxy clu
 ster extent through machine learning
DTSTART;VALUE=DATE-TIME:20261028T175500Z
DTEND;VALUE=DATE-TIME:20261028T180500Z
DTSTAMP;VALUE=DATE-TIME:20261027T104411Z
UID:indico-contribution-3665@nyx.physics.mcgill.ca
DESCRIPTION:Speakers: Christine Hao (University of Toronto)\nThe spatial e
 xtent of the environment's impact on galaxies marks a transitional region 
 between cluster and field galaxies. We present a data‐driven method to i
 dentify this region in galaxy clusters with masses $M_{200\\rm \,mean}>10^
 {13} {\\rm M}_{\\odot}$ at $z = 0$. Using resolved galaxy samples from the
  largest simulation volume of IllustrisTNG (TNG300-1)\, we examine how gal
 axy properties vary as a function of distance to the closest cluster. We t
 rain neural networks to classify galaxies into cluster and field galaxies 
 based on their intrinsic properties. Using this classifier\, we present th
 e first quantitative and probabilistic map of the transition region. It is
  represented as a broad and intrinsically scattered region near cluster ou
 tskirts\, rather than a sharp physical boundary. This is the physical dete
 ction of a mixed population. In order to determine transition regions of d
 ifferent physical processes by training property-specific models\, we cate
 gorise galaxy properties based on their underlying physics\, i.e. gas\, st
 ellar\, and dynamical. Changes to the dynamical properties dominate the in
 nermost regions of the clusters of all masses. Stellar properties and gas 
 properties\, on the other hand\, exhibit transitions at similar locations 
 for low mass clusters\, yet gas properties have transitions in the outermo
 st regions for high mass clusters. These results have implications for clu
 ster environmental studies in both simulations and observations\, particul
 arly in refining the definition of cluster boundaries while considering en
 vironmental preprocessing and how galaxies evolve under the effect of the 
 cluster environment.\n\nhttps://nyx.physics.mcgill.ca/event/587/contributi
 ons/3665/
LOCATION:Online 
URL:https://nyx.physics.mcgill.ca/event/587/contributions/3665/
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