How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data
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arXiv
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| Autori principali: | , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| author | Cadiou, Corentin Laigle, Clotilde Agertz, Oscar |
| author_facet | Cadiou, Corentin Laigle, Clotilde Agertz, Oscar |
| contents | 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 $4.3\pm0.5$ independent parameters for star-forming galaxies and $2.9\pm0.2$ 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. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2404_02962 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data Cadiou, Corentin Laigle, Clotilde Agertz, Oscar Astrophysics of Galaxies Instrumentation and Methods for Astrophysics 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 $4.3\pm0.5$ independent parameters for star-forming galaxies and $2.9\pm0.2$ 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. |
| title | How complex are galaxies? A non-parametric estimation of the intrinsic dimensionality of wide-band photometric data |
| topic | Astrophysics of Galaxies Instrumentation and Methods for Astrophysics |
| url | https://arxiv.org/abs/2404.02962 |