Subject: dynamic MCMC | Statistics - Applications | Color-Magnitude Diagram | Markov chain Monte Carlo | informative prior distributions | contaminated data | Astronomy | mixture models
arxiv: Astrophysics::Galaxy Astrophysics | Astrophysics::Cosmology and Extragalactic Astrophysics | Astrophysics::Earth and Planetary Astrophysics | Astrophysics::Solar and Stellar Astrophysics
Color-Magnitude Diagrams (CMDs) are plots that compare the
magnitudes (luminosities) of stars in different wavelengths of
light (colors). High nonlinear correlations among the mass,
color, and surface temperature of newly formed stars induce a
long narrow curved point cloud in a CMD known as the main
sequence. Aging stars form new CMD groups of red giants and
white dwarfs. The physical processes that govern this evolution
can be described with mathematical models and explored using
complex computer models. These calculations are designed to
predict the plotted magnitudes as a function of parameters of
scientific interest, such as stellar age, mass, and metallicity.
Here, we describe how we use the computer models as a component
of a complex likelihood function in a Bayesian analysis that
requires sophisticated computing, corrects for contamination of
the data by field stars, accounts for complications caused by
unresolved binary-star systems, and aims to compare competing
physics-based computer models of stellar evolution.