Abstract

With the advent of large scale observational surveys to map out the stars in our galaxy, there is a need for an efficient tool to compare theoretical models of our galaxy with observations. To this end, we describe here the code Galaxia, which uses efficient and fast algorithms for creating a synthetic survey of the Milky Way, and discuss its uses. Given one or more observational constraints like the color-magnitude bounds, a survey size and geometry, Galaxia returns a catalog of stars in accordance with a given theoretical model of the Milky Way. Both analytic and N-body models can be sampled by Galaxia. For 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. In future, we plan to release the code publicly at http://galaxia.sourceforge.net. As an application of the code, we study the prospect of identifying structures in the stellar halo with future surveys that will have velocity information about the stars.

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