Cosmic shear bias and calibration in dark energy studies

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Abstract

With the advent of large-scale weak lensing surveys there is a need to understand how realistic, scale-dependent systematics bias cosmic shear and dark energy measurements, and how they can be removed. Here, we show how spatially varying image distortions are convolved with the shear field, mixing convergence E and B modes, and bias the observed shear power spectrum. In practise, many of these biases can be removed by calibration to data or simulations. The uncertainty in this calibration is marginalized over, and we calculate how this propagates into parameter estimation and degrades the dark energy Figure-of-Merit. We find that noise-like biases affect dark energy measurements the most, while spikes in the bias power have the least impact. We argue that, in order to remove systematic biases in cosmic shear surveys and maintain statistical power, effort should be put into improving the accuracy of the bias calibration rather than minimizing the size of the bias. In general, this appears to be a weaker condition for bias removal. We also investigate how to minimize the size of the calibration set for a fixed reduction in the Figure-of-Merit. Our results can be used to correctly model the effect of biases and calibration on a cosmic shear survey, assess their impact on the measurement of modified gravity and dark energy models, and to optimize survey and calibration requirements.

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