Identifying high-quality local analogues to high-redshift (LAHz) galaxies using the <scp>cigale</scp> stellar population synthesis modelling code

ABSTRACT Local analogues to high-redshift (LAHz) galaxies provide a means to study the spatially resolved physical characteristics of early-Universe galaxies, thus informing the analysis of true early-Universe galaxies and improving our understanding of galaxy formation. This study explores how modern population synthesis codes can be used to identify LAHz galaxies. In particular, we illustrate that a high-quality LAHz galaxy classification requires both modelling a galaxy’s star formation history (SFH) and determining relevant physical properties (e.g. metallicity, dust content, etc.). We obtained new far-ultraviolet to far-infrared photometry to create spectral energy distributions (SEDs) of six galaxies. Five of the galaxies had been identified as potential LAHz galaxies in a prior study, and a non-LAHz galaxy was included as a control. The SEDs were fitted using cigale (Code Investigating GALaxy Emission). cigale uses a smooth functional form for the SFH model with very high time resolution and also provides best-fitting and likelihood-weighted estimates of physical parameters. We find that LAHz galaxies form distinct groupings in plots of galaxy age, specific star formation rate, metallicity, and dust luminosity. We contrast our results with the prior LAHz classifications, which were based on results from a different population synthesis code that used a piecewise constant SFH model and a fixed metallicity. We find cases where the two codes agree, and also cases where the cigale-based modelling changes and strengthens prior LAHz classifications. We conclude that the multidimensional analysis of galaxy properties returned by cigale provides an effective means to obtain high-quality LAHz candidates.