To understand the evolution of the Milky Way Galaxy requires detailed knowledge of the star formation history of various populations. The vast amounts of photometric and astrometric data provided by the Gaia mission give unprecedented opportunities in this area. The relationships between the observed data and the ages of stars are however complex and highly non-linear and great care must be taken in analyzing the data. We describe a Bayesian approach to calculate the star formation rate (SFR) from astrophysical data, using a genetic algorithm to solve the basic integral equation. We present simulations showing that the method is capable of resolving structures in the SFR that cannot be seen from a distribution of the individually estimated stellar ages.
|Conference||Symposium - The Three-Dimensional Universe with Gaia|
|Period||2004/10/04 → 2004/10/07|
- Astronomy, Astrophysics and Cosmology
- Stellar ages