Skip to main content

Lund University Publications

LUND UNIVERSITY LIBRARIES

How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data

Cadiou, Corentin LU orcid ; Laigle, Clotilde and Agertz, Oscar LU (2025) In Monthly Notices of the Royal Astronomical Society 537(2). p.1869-1878
Abstract

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 data sets. 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 (SNR) in all optical and near-infrared 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... (More)

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 data sets. 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 (SNR) in all optical and near-infrared 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.

(Less)
Please use this url to cite or link to this publication:
author
; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
galaxies: formation, galaxies: fundamental parameters, methods: data analysis
in
Monthly Notices of the Royal Astronomical Society
volume
537
issue
2
pages
10 pages
publisher
Oxford University Press
external identifiers
  • scopus:85217079370
ISSN
0035-8711
DOI
10.1093/mnras/staf139
language
English
LU publication?
yes
id
665e6e87-31a6-4f9c-8f8d-285a0bfab6f7
date added to LUP
2025-04-01 15:36:25
date last changed
2025-04-04 14:56:19
@article{665e6e87-31a6-4f9c-8f8d-285a0bfab6f7,
  abstract     = {{<p>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 data sets. 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 (SNR) in all optical and near-infrared 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.</p>}},
  author       = {{Cadiou, Corentin and Laigle, Clotilde and Agertz, Oscar}},
  issn         = {{0035-8711}},
  keywords     = {{galaxies: formation; galaxies: fundamental parameters; methods: data analysis}},
  language     = {{eng}},
  number       = {{2}},
  pages        = {{1869--1878}},
  publisher    = {{Oxford University Press}},
  series       = {{Monthly Notices of the Royal Astronomical Society}},
  title        = {{How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data}},
  url          = {{http://dx.doi.org/10.1093/mnras/staf139}},
  doi          = {{10.1093/mnras/staf139}},
  volume       = {{537}},
  year         = {{2025}},
}