How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data
arxiv(2024)
摘要
Galaxies are complex objects, yet the number of independent parameters to
describe them remains unknown. We present here a non-parametric method to
estimate the intrinsic dimensionality of large datasets. We apply it to
wide-band photometric data drawn from the COSMOS2020 catalogue and a comparable
mock catalogue from the Horizon-AGN simulation. Our galaxy catalogues are
limited in signal-to-noise ratio in all optical and NIR bands. Our results
reveal that most of the variance in the wide-band photometry of this galaxy
sample can be described with at most 4.3±0.5 independent parameters for
star-forming galaxies and 2.9±0.2 for passive ones, both in the observed
and simulated catalogues. We identify one of these parameters to be
noise-driven, and recover that stellar mass and redshift are two key
independent parameters driving the magnitudes. Our findings support the idea
that wide-band photometry does not provide more than one additional independent
parameter for star-forming galaxies. Although our sample is not mass-limited
and may miss some passive galaxies due to our cut in SNR, our work suggests
that dimensionality reduction techniques may be effectively used to explore and
analyse wide-band photometric data, provided the used latent space is at least
four-dimensional.
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