An Efficient Method for Computing the Likelihood of Cosmological Parameters
by Peter Klinge
supervisor: Dr. Lado Samushia and Dr. Larry Weaver
This program is funded by the National Science Foundation through grant number PHYS-1461251. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
Project Overview: The study of cosmology involves many parameters such as dark energy and dark matter. These parameters describe the Universe and how it is changing. The calculations of these parameters often require large amounts of computational resources. This was a mathematical project whose purpose was to test a method that reduced the computational power needed to calculate the values of these parameters. It assumes the Gaussian shape that cosmological parameters often have with respect to a likelihood function to find the values and margins of error of the parameters. This method is very fast and worked well for data sets with a small number of parameters, but when more parameters were used the percent errors became very large.
I have found the following links particularly informative or useful: