Statistics Seminar

Estimation of distances of galaxies is one essential component to determine the age and composition of our Universe. The Triangulum Galaxy (catalogued as M33) is the third-largest member of the Local Group of galaxies, and one of the most distant permanent objects that can be viewed with the naked eyes. Mira variable stars are a class of pulsating stars characterized by very red colors. In an interdisciplinary project, we used available light curve data to infer the periods and period-luminosity relations (PLR) of Miras in M33, and then infer the distance of M33 by referencing to the known distance of the LMC, a satellite galaxy of the Milky Way. In this talk, I shall discuss various challenges we faced in this project, including dealing with data sparsity, conducting genuine simulation, reducing computational cost, and quantifying uncertainty. I shall also show how statistical ideas were brought into play in dealing with these challenges. The statistical concepts or methods used include Gaussian process regression, semi-parametric inference, Bayesian hierarchical models, and stochastic variational inference.