Stellar Population Inference with Prospector
  Inference of the physical properties of stellar populations from observed
photometry and spectroscopy is a key goal in the study of galaxy evolution. In
recent years the quality and quantity of the available data has increased, and
there have been corresponding efforts to increase the realism of the stellar
population models used to interpret these observations. Describing the observed
galaxy spectral energy distributions in detail now requires physical models
with a large number of highly correlated parameters. These models do not fit
easily on grids and necessitate a full exploration of the available parameter
space. We present prospector, a flexible code for inferring stellar population
parameters from photometry and spectroscopy spanning UV through IR wavelengths.
This code is based on forward modeling the data and Monte Carlo sampling the
posterior parameter distribution, enabling complex models and exploration of
moderate dimensional parameter spaces. We describe the key ingredients of the
code and discuss the general philosophy driving the design of these
ingredients. We demonstrate some capabilities of the code on several datasets,
including mock and real data.
