Publications by Julien Devriendt


Horizon-AGN virtual observatory – 1. SED-fitting performance and forecasts for future imaging surveys

Monthly Notices of the Royal Astronomical Society Oxford University Press 486 (2019) 5104-5123

C Laigle, I Davidzon, O Ilbert, J Devriendt, D Kashino, C Pichon, P Capak, S Arnouts, SDL Torre, Y Dubois, G Gozaliasl, DL Borgne, S Lilly, HJ McCracken, M Salvato, A Slyz

Using the light-cone from the cosmological hydrodynamical simulation HORIZON-AGN, we produced a photometric catalogue over 0 < z < 4 with apparent magnitudes in COSMOS, Dark Energy Survey, Large Synoptic Survey Telescope (LSST)-like, and Euclid-like filters at depths comparable to these surveys. The virtual photometry accounts for the complex star formation history (SFH) and metal enrichment of HORIZON-AGN galaxies, and consistently includes magnitude errors, dust attenuation, and absorption by intergalactic medium. The COSMOS-like photometry is fitted in the same configuration as the COSMOS2015 catalogue. We then quantify random and systematic errors of photometric redshifts, stellar masses, and star formation rates (SFR). Photometric redshifts and redshift errors capture the same dependencies on magnitude and redshift as found in COSMOS2015, excluding the impact of source extraction. COSMOS-like stellar masses are well recovered with a dispersion typically lower than 0.1 dex. The simple SFHs and metallicities of the templates induce a systematic underestimation of stellar masses at z < 1.5 by at most 0.12 dex. SFR estimates exhibit a dust-induced bimodality combined with a larger scatter (typically between 0.2 and 0.6 dex). We also use our mock catalogue to predict photometric redshifts and stellar masses in future imaging surveys. We stress that adding Euclid near-infrared photometry to the LSST-like baseline improves redshift accuracy especially at the faint end and decreases the outlier fraction by a factor ∼2. It also considerably improves stellar masses, reducing the scatter up to a factor 3. It would therefore be mutually beneficial for LSST and Euclid to work in synergy.


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