Galaxy redshift surveys produce three-dimensional maps of the galaxy distribution. On large scales these maps trace the underlying matter fluctuations in a relatively simple manner, so that the…

This award is a $395,953.31 grant for research provided by the National Aeronautics and Space Administration (NASA) to the University of California, Berkeley to develop an open-source computational toolbox for modeling and analyzing data from galaxy redshift surveys. The goal is to enable more robust extraction of cosmological information, such as the expansion history of the universe and growth of large-scale structure, from these surveys, including those planned for the upcoming Wide-Field Infrared Survey Telescope (WFIRST) mission. The award does not have a set-aside designation. As a public research university, the University of California, Berkeley has received numerous prime federal contracts and grants from agencies like NASA, the Department of Defense, and the National Institutes of Health to conduct research across a range of scientific domains.

Galaxy redshift surveys produce three-dimensional maps of the galaxy distribution. On large scales these maps trace the underlying matter fluctuations in a relatively simple manner, so that the properties of the primordial fluctuations along with the overall expansion history and growth of perturbations can be extracted. The BAO standard ruler method to measure the expansion history of the universe using galaxy redshift surveys is thought to be robust to observational artifacts and understood theoretically with high precision. These same surveys can offer a host of additional information, including a measurement of the growth rate of large scale structure through redshift space distortions, the possibility of measuring the SUM of neutrino masses, tighter constraints on the expansion history through the alcock-paczynski effect, and constraints on the scale-dependence and non-gaussianity of the primordial fluctuations. Extracting this broadband clustering information hinges on both our ability to minimize and subtract observational systematics to the observed galaxy power spectrum, and our ability to model the broadband behavior of the observed galaxy power spectrum with exquisite precision. Rapid development on both fronts is required to capitalize on wfirst's data set. We propose to develop an open-source computational toolbox that will propel development in both areas by connecting large scale structure modeling and instrument and survey modeling with the statistical inference process.