Cosmic Shear Systematics: Software-Hardware Balance
arXiv:0905.3176 · doi:10.1111/j.1365-2966.2010.16326.x
Abstract
Cosmic shear measurements rely on our ability to measure and correct the Point Spread Function (PSF) of the observations. This PSF is measured using stars in the field, which give a noisy measure at random points in the field. Using Wiener filtering, we show how errors in this PSF correction process propagate into shear power spectrum errors. This allows us to test future space-based missions, such as Euclid or JDEM, thereby allowing us to set clear engineering specifications on PSF variability. For ground-based surveys, where the variability of the PSF is dominated by the environment, we briefly discuss how our approach can also be used to study the potential of mitigation techniques such as correlating galaxy shapes in different exposures. To illustrate our approach we show that for a Euclid-like survey to be statistics limited, an initial pre-correction PSF ellipticity power spectrum, with a power-law slope of -3 must have an amplitude at l =1000 of less than 2 x 10^{-13}. This is 1500 times smaller than the typical lensing signal at this scale. We also find that the power spectrum of PSF size \dR^2) at this scale must be below 2 x 10^{-12}. Public code available as part of iCosmo at http://www.icosmo.org
5 pages, 3 figures. Submitted to MNRAS
References in corpus (5)
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- Fast Point Spread Function Modeling with Deep Learning
- The impact of galaxy colour gradients on cosmic shear measurement
- On Point Spread Function modelling: towards optimal interpolation
- The power spectrum of systematics in cosmic shear tomography and the bias on cosmological parameters
- An Algorithm to Mitigate Charge Migration Effects in Data from the Near Infrared Imager and Slitless Spectrograph on the James Webb Space Telescope