The SAMI galaxy survey: predicting kinematic morphology with logistic regression
arxiv(2024)
摘要
We use the SAMI galaxy survey to study the the kinematic morphology-density
relation: the observation that the fraction of slow rotator galaxies increases
towards dense environments. We build a logistic regression model to
quantitatively study the dependence of kinematic morphology (whether a galaxy
is a fast rotator or slow rotator) on a wide range of parameters, without
resorting to binning the data. Our model uses a combination of stellar mass,
star-formation rate (SFR), r-band half-light radius and a binary variable
based on whether the galaxy's observed ellipticity (ϵ) is less than
0.4. We show that, at fixed mass, size, SFR and ϵ, a galaxy's local
environmental surface density (log_10(Σ_5/Mpc^-2)) gives
no further information about whether a galaxy is a slow rotator, i.e. the
observed kinematic-morphology density relation can be entirely explained by the
well-known correlations between environment and other quantities. We show how
our model can be applied to different galaxy surveys to predict the fraction of
slow rotators which would be observed and discuss its implications for the
formation pathways of slow rotators.
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