Speaker
Description
We present an application of the SPACIOUS platform (https://spacious.ub.edu) to run the Besançon Galaxy Model Fast Approximate Simulations, a tool aimed at deriving Galactic parameters by comparing observed and simulated catalogs. SPACIOUS allows us to work efficiently with both large observational datasets and our own simulated catalogs. In particular, we can retrieve and handle a Gaia sample of more than 16 million stars, and upload and process our BGM synthetic catalog within the same environment. By iteratively comparing observed color-magnitude diagrams with those generated using BGM FASt following a set of input parameters, we can derive the star formation history and the initial mass function of the Milky Way in the Solar neighbourhood and beyond, two fundamental magnitudes for the description and understanding of the origin and evolution of our Galaxy. The platform is prepared for parallelization through Apache Spark. This enables us to distribute our computations across multiple CPUs, including user-defined functions, without having to implement parallelization manually. As a result, the full workflow—from data access to model evaluation—runs in a scalable and reproducible way.
