Astrostatistics: The Final Frontier

How did the universe form? What is it made of, and how do its constituents evolve? How old is it? And, will it continue to expand? These are questions cosmologists have long sought to answer by comparing data from myriad astronomical objects to theories of the universe’s formation and evolution. But, until recently, cosmology was a data-starved science. For instance, before the 1990 launch of the Hubble Space Telescope, the Hubble constant— a number representing the current expansion rate of the universe—could only be inferred to within a factor of two, and cosmologists had to make do performing simple statistical analyses. Since that time, technological advances have led to a flood of new data, ushering in the era of precision cosmology. (The Sloan Digital Sky Survey alone has collected basic data for more than 200 million objects.) To help make sense of all this data, cosmologists have increasingly turned to statisticians, and a new interdisciplinary field has arisen: astrostatistics. Work in astrostatistics uses a wide range of statistical methods, but there are a few particular statistical issues that are prevalent. Here, we focus on two broad challenges: parameter estimation using complex models and data analysis using noisy, nonstandard data types. Parameter Estimation Using Type Ia Supernovae