Spectro-imaging forward model of red and blue galaxies

Martina Fagioli*, Luca Tortorelli, Jörg Herbel, Dominik Zürcher, Alexandre Refregier, Adam Amara

*Corresponding author for this work

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Abstract

For the next generation of spectroscopic galaxy surveys, it is important to forecast their performances and to accurately interpret their large data sets. For this purpose, it is necessary to consistently simulate different populations of galaxies, in particular Emission Line Galaxies (ELGs), less used in the past for cosmological purposes. In this work, we further the forward modeling approach presented in Fagioli et al. 2018, by extending the spectra simulator USPEC to model galaxies of different kinds with improved parameters from Tortorelli et al. 2020. Furthermore, we improve the modeling of the selection function by using the image simulator UFIG. We apply this to the Sloan Digital Sky Survey (SDSS), and simulate ∼157,000 multi-band images. We pre-process and analyse them to apply cuts for target selection, and finally simulate SDSS/BOSS DR14 galaxy spectra. We compute photometric, astrometric and spectroscopic properties for red and blue, real and simulated galaxies, finding very good agreement. We compare the statistical properties of the samples by decomposing them with Principal Component Analysis (PCA). We find very good agreement for red galaxies and a good, but less pronounced one, for blue galaxies, as expected given the known difficulty of simulating those. Finally, we derive stellar population properties, mass-to-light ratios, ages and metallicities, for all samples, finding again very good agreement. This shows how this method can be used not only to forecast cosmology surveys, but it is also able to provide insights into studies of galaxy formation and evolution.

Original languageEnglish
Article number050
Number of pages26
JournalJournal of Cosmology and Astroparticle Physics
Volume2020
Issue number6
DOIs
Publication statusPublished - 24 Jun 2020

Keywords

  • galaxy surveys
  • redshift surveys

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