Synthetic Gaia surveys from the FIRE cosmological simulations of Milky Way-mass galaxies

TL;DR

This paper introduces 'ananke', a framework for creating synthetic Gaia-like surveys from FIRE cosmological simulations, enabling better comparison between observations and models of Milky Way-like galaxies.

Contribution

The paper presents a novel framework 'ananke' for generating realistic synthetic Gaia surveys from high-resolution cosmological simulations of Milky Way-mass galaxies.

Findings

Generated nine Gaia-like synthetic surveys from three simulations.

Included dust extinction and observational errors in the synthetic data.

Provided complete simulation snapshots and data access plans.

Abstract

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 (FIRE) 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 $M_{\odot}$) 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.