A Self-Consistent Bayesian Investigation of Star Cluster Binary Populations

We propose to self-consistently characterize the binary populations in >500 open star clusters, across a wide range of cluster properties, using the state-of-the-art Bayesian Analysis of Stellar Evolution (BASE-9) tool. For each cluster we will compile available photometry from Gaia, 2MASS and Pan-STARRS, and use these data within the BASE-9 software to (a) identify photo-metric binaries and determine their masses and mass ratios, (b) establish the cluster age, distance, reddening and metallicity, and (c) derive star-by-star photometric membership probabilities and masses. We will use these products to investigate long-standing theoretical predictions resulting from the dynamical processing of binaries in N-body star cluster models that largely remain empirically untested, and to better understand the star formation process. This database of cluster parameters and binarity will be made publicly available through a custom online interactive table and plotting utility.