iMaNGA: mock MaNGA galaxies based on IllustrisTNG and MaStar SSPs - I. Construction and analysis of the mock data cubes

Galaxy formation and evolution simulations are essential tools to probe poorly known astrophysics processes, but particular care is needed to compare simulations with galaxy observations, as observed data need to be modelled as well. We present a method to generate mock galaxies from the hydro-dynamical IllustrisTNG simulations which are suited to compare with integral field spectroscopic observation of galaxies from the SDSS-IV/Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. First, we include the same instrumental effects and procedures as adopted in the acquisition and analysis of real data. Furthermore, we generate the galaxy spectra from the simulations using new stellar population models based on the MaNGA stellar library (MaStar). In this way, our mock data cubes have the same spatial sampling, cover the same wavelength range (3600-10 300 angstrom), and share the same spectral resolution (R approximate to 1800) and flux calibration of real MaNGA galaxy spectra. In this first paper, we demonstrate the method over an early- and a late-type simulated galaxy from TNG50. We analyse the correspondent mock MaNGA-like data cubes with the same full spectral fitting code, FIREFLY, which was used for the observed spectra. We find that the intrinsic and recovered age and metallicity gradients are consistent within 1 sigma, with residuals over all tassels consistent with 0 at the 68 per cent confidence level. We also perform the challenging test at comparing intrinsic and recovered star formation histories, finding a close resemblance between input and output. In follow-up papers, we will present a full simulated MaNGA-like catalogue (approximate to 10 000 galaxies) with a comprehensive comparison of TNG50 simulations to MaNGA observational results.

Automated summary

This study presents a method to generate mock galaxies from the hydro-dynamical IllustrisTNG simulations and compare them with real observational data. By including the same instrumental effects and procedures as in the acquisition and analysis of real data, and using new stellar population models based on the MaNGA stellar library, the mock data has similar characteristics to the real data. The results show that the recovered age and metallicity gradients are consistent with the real data, and the simulated star formation histories closely resemble the observed ones.