Weak gravitational lensing systematic errors in the dark energy survey

Dark energy is one of the most important unsolved problems in modern Physics, and weak gravitational lensing (WL) by mass structures along the line of sight ("cosmic shear") is a promising technique to learn more about its nature. However, WL is subject to numerous systematic errors which induce biases in measured cosmological parameters and prevent the development of its full potential. In this thesis, we advance the understanding of WL systematics in the context of the Dark Energy Survey (DES). We develop a testing suite to assess the performance of the shapelet-based DES WL measurement pipeline. We determine that the measurement bias of the parameters of our Point Spread Function (PSF) model scales as (S/N )−2, implying that a PSF S/N > 75 is needed to satisfy DES requirements. PSF anisotropy suppression also satisfies the requirements for source galaxies with S/N [special characters omitted] 45. For low-noise, marginally-resolved exponential galaxies, the shear calibration errors are up to about 0.06% (for shear values [special characters omitted] 0.075). Galaxies with S/N [special characters omitted] 75 present about 1% errors, sufficient for first-year DES data. However, more work is needed to satisfy full-area DES requirements, especially in the high-noise regime. We then implement tests to validate the high accuracy of the map between pixel coordinates and sky coordinates (astrometric solution), which is crucial to detect the required number of galaxies for WL in stacked images. We also study the effect of atmospheric dispersion on cosmic shear experiments such as DES and the Large Synoptic Survey Telescope (LSST) in the four griz bands. For DES (LSST), we find systematics in the g and r (g, r, and i) bands that are larger than required. We find that a simple linear correction in galaxy color is accurate enough to reduce dispersion shear systematics to insignificant levels in the r ( i) band for DES (LSST). More complex corrections will likely reduce the sys