Galaxia: a code to generate a synthetic survey of the Milky Way

TL;DR

Galaxia is a fast, flexible code that generates synthetic Milky Way star catalogs based on various models, aiding the analysis of upcoming wide-area surveys like GAIA and LSST.

Contribution

It introduces a novel, efficient sampling scheme for both analytic and N-body Milky Way models, enabling realistic, continuous star distributions over large volumes.

Findings

Supports multiple photometric bands and complex stellar population models

Successfully simulates Gaia-like survey data for halo structure analysis

Provides a publicly available tool for synthetic Milky Way surveys

Abstract

We present here a fast code for creating a synthetic survey of the Milky Way. Given one or more color-magnitude bounds, a survey size and geometry, the code returns a catalog of stars in accordance with a given model of the Milky Way. The model can be specified by a set of density distributions or as an N-body realization. We provide fast and efficient algorithms for sampling both types of models. As compared to earlier sampling schemes which generate stars at specified locations along a line of sight, our scheme can generate a continuous and smooth distribution of stars over any given volume. The code is quite general and flexible and can accept input in the form of a star formation rate, age metallicity relation, age velocity dispersion relation and analytic density distribution functions. Theoretical isochrones are then used to generate a catalog of stars and support is available for a wide range of photometric bands. As a concrete example we implement the Besancon Milky Way model for the disc. For the stellar halo we employ the simulated stellar halo N-body models of Bullock & Johnston (2005). In order to sample N-body models, we present a scheme that disperses the stars spawned by an N-body particle, in such a way that the phase space density of the spawned stars is consistent with that of the N-body particles. The code is ideally suited to generating synthetic data sets that mimic near future wide area surveys such as GAIA, LSST and HERMES. As an application we study the prospect of identifying structures in the stellar halo with a simulated GAIA survey. We plan to make the code publicly available at http://galaxia.sourceforge.net.