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arXiv · 2506.00460

Mocking IFU observations and metallicity diagnostics from cosmological simulations

Abstract

Hydrodynamic simulations are powerful tools for studying galaxy formation. However, it is crucial to test and improve the sub-grid physics underlying these simulations by comparing their predictions with observations. To this aim, observable quantities can be derived for simulated galaxies, enabling the analysis of simulated properties through an observational approach. Our goal is to develop a new numerical tool capable of generating synthetic emission line spectra from spatially resolved regions in simulated galaxies, mocking Integral Field Unit (IFU) observations. Synthetic spectra of simulated galaxies are produced by integrating the software CIGALE with the outcomes of hydrodynamical simulations. We consider contributions of both stellar populations and nebular emission. The nebular emission lines in the spectra are modeled by considering only the contributions from the simulated star-forming regions. Our model considers the properties of the surrounding interstellar medium to estimate the ionizing parameters, the metallicity, the velocity dispersion and the electron density. We present the new numerical tool PRISMA. Leveraging synthetic spectra generated by our model, PRISMA successfully computed and recovered the intrinsic values of the star formation rate and gas-phase metallicity in local regions of simulated galaxies. Additionally, we examine the behavior of metallicity tracers such as N2, R23, O3N2, N2O2, recovered by PRISMA and propose new calibrations based on our simulated result. These findings show the robustness of our tool in recovering the intrinsic properties of simulated galaxies through their synthetic spectra, thereby becoming a powerful tool to confront simulations and observational data.

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BibTeXRIS

A. Cornejo-Cárdenas, E. Sillero, P. B. Tissera, M. Boquien, J. Vilchez, G. Bruzual, P. Jofré. 2025-05-31. Mocking IFU observations and metallicity diagnostics from cosmological simulations. https://doi.org/10.1051/0004-6361%2F202452226

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