Barnaby Rowe, David Bacon, Richard Massey, Catherine Heymans, Boris Haeussler, Andy Taylor, Jason Rhodes, Yannick Mellier
We present a simulation analysis of flexion and shear measurement using shapelet decomposition, and identify apparent qualitative differences between flexion and shear measurement noise in deep survey data. Taking models of galaxies from the Hubble Space Telescope Ultra Deep Field (HUDF) as a basis set and applying a correction for the HUDF PSF we generate lensed simulations of deep, optical imaging data from Hubble's Advanced Camera for Surveys (ACS) with realistic galaxy morphologies. We find that flexion and shear estimates differ in our measurement pipeline: whereas intrinsic galaxy shape is the largest contribution to noise in shear estimates, noise in flexion estimates is dominated by pixel noise due to finite photon counts and detector read noise. This pixel noise also increases more rapidly as galaxy signal-to-noise decreases than is found for shear estimates. We provide simple power law fitting functions for this behaviour, for both flexion and shear, allowing the effect to be properly accounted for in future forecasts for flexion measurement. Using the simulations we also quantify the systematic biases of our shapelet flexion and shear measurement pipeline for deep Hubble datasets such as GEMS, STAGES or COSMOS. Flexion measurement biases are found to be significant, but consistent with previous studies.
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http://arxiv.org/abs/1211.0966
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