Next generation statistical methods for studying galaxy populations

Advisor: V. Wild (St. Andrews)
Summary: Bayesian statistics have revolutionized our understanding of galaxy evolution by allowing us to robustly estimate the physical properties of galaxies, together with the associated errors and, crucially, the degeneracies between fitted parameters. The goal of this project is to develop this idea one step further, to use Empirical Bayes techniques, in which the population itself is used to define the priors. This will lead to a substantial increase in our ability to break degeneracies between parameters. Applied to new and upcoming surveys, this will lead to important new insights into the physical processes driving galaxy formation and evolution.
Gran information: IAC international grants
Contact: Jesús Falcón-Barroso (

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