Biases and systematics in the observational derivation of galaxy properties: comparing different techniques on synthetic observations of simulated galaxies

TL;DR

This study investigates biases and systematic errors in deriving galaxy properties from observations by comparing synthetic observations of simulated galaxies with known true values, highlighting the impact of various observational techniques.

Contribution

It provides a comprehensive analysis of how different observational methods introduce biases in galaxy property measurements using simulated data.

Findings

Systematic differences arise from observational biases and methodological choices.

Different techniques yield significantly varying estimates of galaxy properties.

Understanding these biases improves interpretation of observational data and simulation comparisons.

Abstract

We study the sources of biases and systematics in the derivation of galaxy properties of observational studies, focusing on stellar masses, star formation rates, gas/stellar metallicities, stellar ages and magnitudes/colors. We use hydrodynamical cosmological simulations of galaxy formation, for which the real quantities are known, and apply observational techniques to derive the observables. We also make an analysis of biases that are relevant for a proper comparison between simulations and observations. For our study, we post-process the simulation outputs to calculate the galaxies' spectral energy distributions (SEDs) using Stellar Population Synthesis models and also generating the fully-consistent far UV-submillimeter wavelength SEDs with the radiative transfer code SUNRISE. We compared the direct results of simulations with the observationally-derived quantities obtained in various ways, and found that systematic differences in all studied galaxy properties appear, which are caused by: (1) purely observational biases, (2) the use of mass-weighted/luminosity-weighted quantities, with preferential sampling of more massive/luminous regions, (3) the different ways to construct the template of models when a fit to the spectra is performed, and (4) variations due to the use of different calibrations, most notably in the cases of the gas metallicities and star formation rates. Our results show that large differences can appear depending on the technique used to derive galaxy properties. Understanding these differences is of primary importance both for simulators, to allow a better judgement on similarities/differences with observations, and for observers, to allow a proper interpretation of the data.