horizon-AGN virtual observatory – 2. Template-free estimates of galaxy properties from colours

Davidzon, I.; Laigle, C.; Capak, P.; Ilbert, O.; Masters, D. C.; Hemmati, Shoubaneh; Apostolakos, N.; Coupon, J.; Torre, S. de la; Devriendt, Julien; Dubois, Yohan; Kashino, Daichi; Paltani, S.; Pichon, Christophe

doi:10.1093/mnras/stz2486

Cited by 37 publications

(45 citation statements)

References 104 publications

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“…Future large-field photometric surveys, such as Euclid (Laureijs et al 2011), HSC (Aihara et al 2018) and LSST (LSST Dark Energy Science Collaboration 2012) will be able to confirm and extend these results by probing a wider group mass range and a larger variety of environment (though in 2D) while relying on state-of-the art photometric redshift extraction techniques (e.g. Davidzon et al 2019;Pasquet et al 2019).…”

Section: Resultsmentioning

confidence: 98%

The impact of the connectivity of the cosmic web on the physical properties of galaxies at its nodes

Kraljic

Pichon

Codis

et al. 2019

Monthly Notices of the Royal Astronomical Society

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We investigate the impact of the number of filaments connected to the nodes of the cosmic web on the physical properties of their galaxies using the Sloan Digital Sky Survey. We compare these measurements to the cosmological hydrodynamical simulations Horizon-(no)AGN and SIMBA. We find that more massive galaxies are more connected, in qualitative agreement with theoretical predictions and measurements in dark matter only simulation. The star formation activity and morphology of observed galaxies both display some dependence on the connectivity of the cosmic web at fixed stellar mass: less star forming and less rotation supported galaxies also tend to have higher connectivity. These results qualitatively hold both for observed and virtual galaxies, and can be understood given that the cosmic web is the main source of fuel for galaxy growth. The simulations show the same trends at fixed halo mass, suggesting that the geometry of filamentary infall impacts galaxy properties beyond the depth of the local potential well. Based on simulations, it is also found that AGN feedback is key in reversing the relationship between stellar mass and connectivity at fixed halo mass. Technically, connectivity is a practical observational proxy for past and present accretion (minor mergers or diffuse infall).

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Section: Resultsmentioning

confidence: 98%

The impact of the connectivity of the cosmic web on the physical properties of galaxies at its nodes

Kraljic

Pichon

Codis

et al. 2019

Monthly Notices of the Royal Astronomical Society

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“…Clustering has been used, for example, to partition galaxies on the basis of their pixel data (Hocking et al 2017(Hocking et al , 2018Martin et al 2020), their spectra (Sánchez Almeida et al 2010;de Souza et al 2017), their SEDs (Siudek et al 2018b,a), and their derived astrophysical features (Barchi et al 2016;Turner et al 2019). Dimensionality reduction, which can extract important or discriminative information from large ensembles of input features, has been used, for example, to produce simplified projections of galaxy samples based on their multi-wavelength photometry (Steinhardt et al 2020) and their estimated SEDs (Davidzon et al 2019;Hemmati et al 2019), and to classify their spectra (Yip et al 2004;Marchetti et al 2013).…”

Section: Introductionmentioning

confidence: 99%

Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning

Turner

Siudek

Salim

et al. 2021

Monthly Notices of the Royal Astronomical Society

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The colour bimodality of galaxies provides an empirical basis for theories of galaxy evolution. However, the balance of processes that begets this bimodality has not yet been constrained. A more detailed view of the galaxy population is needed, which we achieve in this paper by using unsupervised machine learning to combine multi-dimensional data at two different epochs. We aim to understand the cosmic evolution of galaxy subpopulations by uncovering substructures within the colour bimodality. We choose a clustering algorithm that models clusters using only the most discriminative data available, and apply it to two galaxy samples: one from the second edition of the GALEX-SDSS-WISE Legacy Catalogue (GSWLC-2; z ∼ 0.06), and the other from the VIMOS Public Extragalactic Redshift Survey (VIPERS; z ∼ 0.65). We cluster within a nine-dimensional feature space defined purely by rest-frame ultraviolet-through-near-infrared colours. Both samples are similarly partitioned into seven clusters, breaking down into four of mostly star-forming galaxies (including the vast majority of green valley galaxies) and three of mostly passive galaxies. The separation between these two families of clusters suggests differences in the evolution of their galaxies, and that these differences are strongly expressed in their colours alone. The samples are closely related, with star-forming/green-valley clusters at both epochs forming morphological sequences, capturing the gradual internally-driven growth of galaxy bulges. At high stellar masses, this growth is linked with quenching. However, it is only in our low-redshift sample that additional, environmental processes appear to be involved in the evolution of low-mass passive galaxies.

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“…The choice of grid size is not well-defined and depends mostly on the size and variations of the training sample. A grid axis ratio of 1:1 has been shown in [Davidzon et al 2019] to slightly outperform the non-square choices, we hence choose a 6 × 6 cells grid here, which satisfies the needs of this study (we tested that a larger grid led to a large fraction of empty cells and a smaller grid didn't allow to show the differences between theories).…”

Section: Self-organizing Map Of Modified Gravity Probed By Cosmic Shearmentioning

confidence: 99%

Categorizing models using Self-Organizing Maps: an application to modified gravity theories probed by cosmic shear

Ferté¹,

Hemmati²,

Masters³

et al. 2021

Preprint

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We propose to use Self-Organizing Maps (SOM) to map the impact of physical models onto observables. Using this approach, we are able to determine how theories relate to each other given their signatures. In cosmology this will be particularly useful to determine cosmological models (such as dark energy, modified gravity or inflationary models) that should be tested by the new generation of experiments. As a first example, we apply this approach to the representation of a subset of the space of modified gravity theories probed by cosmic shear. We therefore train a SOM on shear correlation functions in the f (R), dilaton and symmetron models. The results indicate these three theories have similar signatures on shear for small values of their parameters but the dilaton has different signature for higher values. We also show that modified gravity (especially the dilaton model) has a different impact on cosmic shear compared to a dynamical dark energy so both need to be tested by galaxy surveys.

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horizon-AGN virtual observatory – 2. Template-free estimates of galaxy properties from colours

Cited by 37 publications

References 104 publications

The impact of the connectivity of the cosmic web on the physical properties of galaxies at its nodes

The impact of the connectivity of the cosmic web on the physical properties of galaxies at its nodes

Synergies between low- and intermediate-redshift galaxy populations revealed with unsupervised machine learning

Categorizing models using Self-Organizing Maps: an application to modified gravity theories probed by cosmic shear

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