The SELGIFS data challenge: generating synthetic observations of CALIFA galaxies from hydrodynamical simulations

TL;DR

This paper presents a set of synthetic IFS observations of CALIFA-like galaxies generated from hydrodynamical simulations, including realistic observational effects, to serve as benchmarks for analysis algorithms.

Contribution

The work introduces a comprehensive method to produce realistic synthetic IFS data from simulations, mimicking CALIFA observations for benchmarking and testing analysis tools.

Findings

Synthetic datacubes include stellar, nebular emission, and dust effects.

Data is processed to match CALIFA observational setups.

Publicly available datasets enable benchmarking of analysis algorithms.

Abstract

In this work we present a set of synthetic observations that mimic the properties of the Integral Field Spectroscopy (IFS) survey CALIFA, generated using radiative transfer techniques applied to hydrodynamical simulations of galaxies in a cosmological context. The simulated spatially-resolved spectra include stellar and nebular emission, kinematic broadening of the lines, and dust extinction and scattering. The results of the radiative transfer simulations have been post-processed to reproduce the main properties of the CALIFA V500 and V1200 observational setups. The data has been further formatted to mimic the CALIFA survey in terms of field of view size, spectral range and sampling. We have included the effect of the spatial and spectral Point Spread Functions affecting CALIFA observations, and added detector noise after characterizing it on a sample of 20 galaxies. The simulated datacubes are suited to be analyzed by the same algorithms used on real IFS data. In order to provide a benchmark to compare the results obtained applying IFS observational techniques to our synthetic datacubes, and test the calibration and accuracy of the analysis tools, we have computed the spatially-resolved properties of the simulations. Hence, we provide maps derived directly from the hydrodynamical snapshots or the noiseless spectra, in a way that is consistent with the values recovered by the observational analysis algorithms. Both the synthetic observations and the product datacubes are public and can be found in the collaboration website http://astro.ft.uam.es/selgifs/data_challenge/.