Evaluating quenching in cosmological simulations of galaxy formation with spectral covariance in the optical window

TL;DR

This paper introduces a spectral covariance-based method to evaluate how well cosmological simulations replicate real galaxy spectra, revealing subtle differences in physical processes like AGN feedback.

Contribution

It applies spectral covariance analysis to synthetic galaxy spectra from simulations, providing a model-independent way to compare simulations with observations.

Findings

Spectral covariance is consistent between real and simulated spectra.

Principal component analysis links PC1 to stellar age distribution.

Discrepancies in AGN feedback implementation affect galaxy quenching predictions.

Abstract

Cosmological hydrodynamical simulations provide valuable insights on galaxy evolution when coupled with observational data. Comparisons with real galaxies are typically performed via scaling relations of the observables. Here we follow an alternative approach based on the spectral covariance in a model-independent way. We build upon previous work by Sharbaf et al. that studied the covariance of high quality SDSS continuum-subtracted spectra in a relatively narrow range of velocity dispersion ($\sigma\in [100,150]$\,km\,s$^{-1}$). Here the same analysis is applied to synthetic data from the EAGLE and Illustris TNG100 simulations, to assess the ability of these runs to mimic real galaxies. The real and simulated spectra are consistent regarding spectral covariance, although with subtle differences that can inform the implementation of subgrid physics. Spectral fitting done a posteriori on stacks segregated with respect to latent space reveals that the first principal component (PC1) is predominantly influenced by the stellar age distribution, with an underlying age-metallicity degeneracy. Good agreement is found regarding star formation prescriptions but there is disagreement with AGN feedback, that also affects the subset of quiescent galaxies. We show a substantial difference in the implementation of the AGN subgrid prescriptions, regarding central black hole seeding, that could lead to the mismatch. Differences are manifest between these two simulations in the star formation histories stacked with respect to latent space. We emphasise that this methodology only relies on the spectral covariance to assess whether simulations provide a true representation of galaxy formation.