This project will develop, and apply to available data, the analysis algorithms necessary to reach confident conclusions about dark energy and cosmological parameters, from optical imaging surveys. Such surveys have great potential for addressing what may be the most intriguing question in fundamental physics, the origin of the observed acceleration of the cosmological expansion rate. Focusing initially on the Deep Lens Survey will ground the algorithm development in practical needs. The analysis will start with the two-point function of the shear and then extend to the highly significant information in higher-order correlations. Sources of uncertainty in inferences from imaging data are complex and can only be taken fully into account with numerical simulation. This challenge will be met by developing a Monte Carlo analysis framework, using cosmological simulations from collaboration with the Los Alamos National Laboratory.
The developed analysis framework will be directly useful for future ground- and space-based surveys, both underway and being planned, and may be applicable to a diversity of other experiments where numerical simulation plays a key role in the interpretation of data. In addition the training of junior researchers, the research will inform work with K-12 teachers through the Sacramento-based 'Science in the River City' program.
