Improving mass and age estimates of unresolved Stellar Clusters
Stellar clusters provide astronomers with powerful diagnostics to derive the history and evolution of the galaxies they reside in. Even with the Hubble Space Telescope, galaxies beyond our Local Group are too distant for the individual stars within these clusters to be resolved. Interpreting the integrated photometry of stellar clusters relies entirely on models to generate predicted colors of unresolved stellar systems. However, previous methods can lead to inaccurate estimates of cluster age because of the statistical fluctuations in the cluster's stellar mass function that leads to real and large ranges in integrated stellar cluster photometry. I will introduce a new stellar cluster modeling program we have designed that populates and evolves a realistic sample of stars and derives integrated properties as a function of age and total cluster mass. We have used our model to generate a Monte Carlo database of 100 million stellar clusters to derive likelihood photometric properties as a function of cluster age and mass. This allows the user to work back, through statistical inference, to find the most probable age and mass of their stellar cluster based on integrated photometry alone.