TY - JOUR
T1 - Synthetic Gaia Surveys from the FIRE Cosmological Simulations of Milky Way-mass Galaxies
AU - Sanderson, Robyn E.
AU - Wetzel, Andrew
AU - Loebman, Sarah
AU - Sharma, Sanjib
AU - Hopkins, Philip F.
AU - Garrison-Kimmel, Shea
AU - Faucher-Gigu re, Claude André
AU - Kereš, Dušan
AU - Quataert, Eliot
N1 - Publisher Copyright:
© 2020. The American Astronomical Society. All rights reserved.
PY - 2020/1
Y1 - 2020/1
N2 - With Gaia Data Release 2, the astronomical community is entering a new era of multidimensional surveys of the Milky Way. This new phase-space view of our Galaxy demands new tools for comparing observations to simulations of Milky Way-mass galaxies in a cosmological context, to test the physics of both dark matter and galaxy formation. We present ananke, a framework for generating synthetic phase-space surveys from high-resolution baryonic simulations, and use it to generate a suite of synthetic surveys resembling Gaia DR2 in data structure, magnitude limits, and observational errors. We use three cosmological simulations of Milky Way-mass galaxies from the Latte suite of the Feedback In Realistic Environments project, which feature self-consistent clustering of star formation in dense molecular clouds and thin stellar/gaseous disks in live cosmological halos with satellite dwarf galaxies and stellar halos. We select three solar viewpoints from each simulation to generate nine synthetic Gaia-like surveys. We sample synthetic stars by assuming each star particle (of mass 7070 M o˙) represents a single stellar population. At each viewpoint, we compute dust extinction from the simulated gas metallicity distribution and apply a simple error model to produce a synthetic Gaia-like survey that includes both observational properties and a pointer to the generating star particle. We provide the complete simulation snapshot at z = 0 for each simulated galaxy. We describe data access points, the data model, and plans for future upgrades. These synthetic surveys provide a tool for the scientific community to test analysis methods and interpret Gaia data.
AB - With Gaia Data Release 2, the astronomical community is entering a new era of multidimensional surveys of the Milky Way. This new phase-space view of our Galaxy demands new tools for comparing observations to simulations of Milky Way-mass galaxies in a cosmological context, to test the physics of both dark matter and galaxy formation. We present ananke, a framework for generating synthetic phase-space surveys from high-resolution baryonic simulations, and use it to generate a suite of synthetic surveys resembling Gaia DR2 in data structure, magnitude limits, and observational errors. We use three cosmological simulations of Milky Way-mass galaxies from the Latte suite of the Feedback In Realistic Environments project, which feature self-consistent clustering of star formation in dense molecular clouds and thin stellar/gaseous disks in live cosmological halos with satellite dwarf galaxies and stellar halos. We select three solar viewpoints from each simulation to generate nine synthetic Gaia-like surveys. We sample synthetic stars by assuming each star particle (of mass 7070 M o˙) represents a single stellar population. At each viewpoint, we compute dust extinction from the simulated gas metallicity distribution and apply a simple error model to produce a synthetic Gaia-like survey that includes both observational properties and a pointer to the generating star particle. We provide the complete simulation snapshot at z = 0 for each simulated galaxy. We describe data access points, the data model, and plans for future upgrades. These synthetic surveys provide a tool for the scientific community to test analysis methods and interpret Gaia data.
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U2 - 10.3847/1538-4365/ab5b9d
DO - 10.3847/1538-4365/ab5b9d
M3 - Article
AN - SCOPUS:85084129314
SN - 0067-0049
VL - 246
JO - Astrophysical Journal, Supplement Series
JF - Astrophysical Journal, Supplement Series
IS - 1
M1 - 6
ER -