Synthetic Galaxy Images and Spectra from the Illustris Simulation
Paul Torrey, Gregory F. Snyder, Mark Vogelsberger, Christopher C., Hayward, Shy Genel, Debora Sijacki, Volker Springel, Lars Hernquist, Dylan, Nelson, Mariska Kriek, Annalisa Pillepich, Laura V. Sales, Cameron K., McBride

TL;DR
This paper details the creation of a comprehensive catalog of synthetic galaxy images and spectra from the Illustris Simulation, enabling various analyses like morphology classification and stellar mass estimation.
Contribution
It introduces a new large-scale synthetic galaxy dataset with detailed spectral and imaging data, and demonstrates its use in deriving galaxy properties.
Findings
Systematic biases in photometric stellar mass estimates can be mitigated.
The synthetic data accurately reflect galaxy properties like metallicity and star formation history.
The catalog facilitates diverse galaxy analyses and comparisons with real observations.
Abstract
We present our methods for generating a catalog of 7,000 synthetic images and 40,000 integrated spectra of redshift z = 0 galaxies from the Illustris Simulation. The mock data products are produced by using stellar population synthesis models to assign spectral energy distributions (SED) to each star particle in the galaxies. The resulting synthetic images and integrated SEDs therefore properly reflect the spatial distribution, stellar metallicity distribution, and star formation history of the galaxies. From the synthetic data products it is possible to produce monochromatic or color-composite images, perform SED fitting, classify morphology, determine galaxy structural properties, and evaluate the impacts of galaxy viewing angle. The main contribution of this paper is to describe the production, format, and composition of the image catalog that makes up the Illustris Simulation…
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