Analyzing Deep Imaging Data: State of the art algorithms for weak lensing and galaxy formation

Princeton University, Princeton NJ

Investigators

Abstract

This award is funded under the American Recovery and Reinvestment Act of 2009 (Public Law 111-5). Dr Strauss and his team will develop a software pipeline to analyze images from large sky surveys in a systematic way to optimize their use for weak-lensing measurements: light from a distant galaxy is bent by the gravity of all the matter that it passes by on its way to our telescopes, distorting the shape of the galaxy as we see it. The software will characterize the point spread function of the telescope and its variation across the observed field, and analyze multiple exposures of a given field in a self-consistent and statistically rigorous way. The team will both improve measurements of the observed shapes of the 'lensed' galaxies, and experiment with methods to characterize their intrinsic shapes. They will apply their code to raw data from the Canada-France-Hawaii Legacy Survey, which is now public. Their measurement of the weak-lensing signal (an indication of how strongly mass is clumped on the largest scales) will give results completely independent from those of that survey team. These data will enable the study of galaxy properties at redshifts around one, which are seen as they were when the cosmos had expanded to only half its present size, with roughly the same precision as that available at redshifts of only a tenth from the Sloan Digital Sky Survey. A postdoctoral scholar will be trained by participating in the research. The calibrated photometric catalogs will be made public, with the detailed shape measurements and photometric redshifts. The software tools will also be made public. Both those and the insights gained will be applicable to the next generation of wide-angle surveys, which also aim to measure weak-lensing signals.