A Bayesian Approach Accounting for Stochastic Fluctuations in Stellar
  Cluster Properties
  The integrated spectro-photometric properties of star clusters are subject to
large cluster-to-cluster variations. They are distributed in non trivial ways
around the average properties predicted by standard population synthesis
models. This results from the stochastic mass distribution of the finite
(small) number of luminous stars in each cluster, stars which may be either
particularly blue or particularly red. The color distributions are broad and
usually far from Gaussian, especially for young and intermediate age clusters,
as found in interacting galaxies. When photometric measurements of clusters are
used to estimate ages and masses in conjunction with standard models, biases
are to be expected. We present a Bayesian approach that explicitly accounts for
stochasticity when estimating ages and masses of star clusters that cannot be
resolved into stars. Based on Monte-Carlo simulations, we are starting to
explore the probability distributions of star cluster properties obtained given
a set of multi-wavelength photometric data.
