The Galaxy Luminosity Functions in ASTRID: Predictions for LSST
Fatemeh Hafezianzadeh, Tianqing Zhang, Paul Rogozenski, Patrick Lachance, Yihao Zhou + 4 more
TLDR
This paper uses the ASTRID simulation to predict galaxy luminosity functions and photometric catalogs for the LSST survey, validated with observed data.
Key contributions
- Developed a physically motivated dust attenuation model calibrated with SDSS data.
- Generated LSST-ready mock photometric catalogs with ~378 million galaxies across 0 < z < 2.
- Provided predicted LSST ugrizy apparent-magnitude luminosity functions and Schechter parameters.
- Computed differential and cumulative galaxy number counts for LSST survey depths (Year 1-10).
Why it matters
This research provides crucial predictions and mock catalogs for the upcoming Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). By validating their models against existing observations, the authors offer a robust framework to interpret LSST data, enabling better understanding of galaxy evolution.
Original Abstract
We present validated and forward-modelled galaxy luminosity functions and photometric predictions for the Vera C. Rubin Observatory Legacy Survey of Space and Time using the ASTRID cosmological hydrodynamical simulation. Galaxy magnitudes are computed by combining stellar population synthesis modeling with a physically motivated dust attenuation prescription in which the optical depth scales with metal surface density. The dust model is calibrated at z = 0 using SDSS luminosity functions and tested at intermediate redshifts (z = 0.5, 1.0, and 1.5) in rest-frame B, V , R, and I bands. We find that the attenuated luminosity functions reproduce observed galaxy statistics across multiple wavelengths and redshifts. Using this calibrated framework, we construct LSST-ready mock photometric catalogs over 0 <= z <= 2 in steps of Delta z = 0.1, containing ~378 million galaxies. We provide predicted apparent-magnitude luminosity functions in the LSST ugrizy bands, derive best-fit Schechter parameters as a compact analytic representation, and compute differential and cumulative galaxy number counts as a function of survey depth from Year 1 to Year 10.
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