The catalogue of virtual early-type galaxies from IllustrisTNG: validation and real observation consistency

TL;DR

This paper creates a realistic simulated catalog of early-type galaxies from the IllustrisTNG simulation, validating their properties against real observations to aid future galaxy formation research.

Contribution

It introduces a new, observation-like sample of virtual early-type galaxies from IllustrisTNG and compares their properties with real data, demonstrating their consistency.

Findings

Virtual-ETGs match observed scaling relations.

The catalog includes over 10,000 galaxies at low redshift.

Results support the use of simulations for galaxy studies.

Abstract

Early-type galaxies (ETGs) are reference systems to understand galaxy formation and evolution processes. The physics of their formation and internal dynamics are codified in well-known scaling relations. In this context, cosmological hydrodynamical simulations play an important role in probing the physical origins of scaling relations by providing a controlled environment to study the formation and evolution of galaxies, linking their internal dynamics to underlying physical processes, and testing the robustness of observational inference methods. In this work, we present the closest-to-reality sample of ETGs from the IllustrisTNG100-1 simulation, dubbed "virtual-ETGs", based on an observational-like algorithm that combines standard projected and three-dimensional galaxy structural parameters. We extract 2D photometric information by projecting the galaxies' light into three planes and modelling them via S\'ersic profiles. Aperture velocity dispersions, corrected for softened central dynamics, are calculated along the line-of-sight orthogonal to the photometric projection plane. Central mass density profiles assume a power-law model, while 3D masses remain unmodified from the IllustrisTNG catalogue. The final catalogue includes $10121$ galaxies at redshifts $z \leq 0.1$. By comparing the virtual properties with observations, we find that the virtual-ETG scaling relations (e.g., size-mass, size-central surface brightness, and Faber-Jackson), central density slopes, and scaling relations among total density slopes and galaxy structural parameters are generally consistent with observations. We make the virtual-ETG publicly available for galaxy formation studies and plan to use this sample as a training set for machine learning tools to infer galaxy properties in future imaging and spectroscopic surveys.