Date of Award
Doctor of Philosophy (PhD)
Weak gravitational lensing measurements from the large-scale structure of the Universe probe the growth of structures at different epochs, thereby providing information about the mysterious dark energy component. Wide-field redshift surveys such as WFIRST, Euclid and LSST will image the sky and collect an unprecedented amount of data. The decrease in the statistical errors must necessarily be accompanied by an increase in our understanding of systematic errors. The sources of the systematic errors could be i) astrophysical, such as intrinsic alignments, failure to account for the complex morphology of the galaxies when estimating lensing distortions, or could be ii) foreground effects such as the Point Spread Function (PSF) or imperfections from the detectors etc. The systematic errors are estimated by testing the shear estimation pipeline on mock galaxy images that are forward-simulated from first principles. The simulated galaxy images must have realistic properties for the estimates of the systematic biases to be accurate. In this thesis, I describe in detail the work done towards incorporating in the image simulations some of the detector effects relevant for WFIRST and understanding the limitations of using images from narrow surveys, such as COSMOS, as input into image simulations for wide field surveys.
Kannawadi, Arun, "Systematic Effects in Realistic Image Simulations for Future Weak Lensing Surveys" (2016). Dissertations. 986.