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Register a new userThe systematic error test for PSF correction in weak gravitational lensing shear measurement by The ERA Method by Idealizing PSF
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We improve the ERA(Ellipticity of Re-smeared Artificial image) method of PSF(Point Spread Function) correction in weak lensing shear analysis in order to treat realistic shape of galaxies and PSF. This is done by re-smearing PSF and the observed galaxy image smeared by a RSF(Re-Smearing Function), and allows us to use a new PSF with a simple shape and to correct PSF effect without any approximations and assumptions. We perform numerical test to show that the method applied for galaxies and PSF with some complicated shapes can correct PSF effect with systematic error less than 0.1%. We also apply ERA method for real data of Abell 1689 cluster to confirm that it is able to detect the systematic weak lensing shear pattern. The ERA method requires less than 0.1 or 1 second to correct PSF for each object in numerical test and real data analysis, respectively.
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We generalize ERA method of PSF correction for more realistic situations. The method re-smears the observed galaxy image(galaxy image smeared by PSF) and PSF image by an appropriate function called Re-Smearing Function(RSF) to make new images which have the same ellipticity with the lensed (before smeared by PSF) galaxy image. It has been shown that the method avoids a systematic error arising from an approximation in the usual PSF correction in moment method such as KSB for simple PSF shape. By adopting an idealized PSF we generalize ERA method applicable for arbitrary PSF. This is confirmed with simulated complex PSF shapes. We also consider the effect of pixel noise and found that the effect causes systematic overestimation.
Highly precise weak lensing shear measurement is required for statistical weak gravitational lensing analysis such as cosmic shear measurement to achieve severe constrain on the cosmological parameters. For this purpose any systematic error in the measurement should be corrected. One of the main systematic error comes from Pixel noise which is Poisson noise of flux from atmosphere. We investigate how the pixel noise makes systematic error in shear measurement based on ERA method and develop the correction method. This method is tested by simulations with various conditions and it is confirmed that the correction method can correct $80 sim 90%$ of the systematic error except very low signal to noise ratio galaxies.
We propose a new method for Point Spread Function (PSF) correction in weak gravitational lensing shear analysis using an artificial image with the same ellipticity as the lensed image. This avoids the systematic error associated with the approximation in PSF correction used in previous approaches. We test the new method with simulated objects which have Gaussian or Cersic profiles smeared by a Gaussian PSF, and confirm that there is no systematic error.
Accurate reconstruction of the spatial distributions of the Point Spread Function (PSF) is crucial for high precision cosmic shear measurements. Nevertheless, current methods are not good at recovering the PSF fluctuations of high spatial frequencies. In general, the residual PSF fluctuations are spatially correlated, therefore can significantly contaminate the correlation functions of the weak lensing signals. We propose a method to correct for this contamination statistically, without any assumptions on the PSF and galaxy morphologies or their spatial distribution. We demonstrate our idea with the data from the W2 field of CFHTLenS.
Reconstruction of the point spread function (PSF) is a critical process in weak lensing measurement. We develop a real-data based and galaxy-oriented pipeline to compare the performances of various PSF reconstruction schemes. Making use of a large amount of the CFHTLenS data, the performances of three classes of interpolating schemes - polynomial, Kriging, and Shepard - are evaluated. We find that polynomial interpolations with optimal orders and domains perform the best. We quantify the effect of the residual PSF reconstruction error on shear recovery in terms of the multiplicative and additive biases, and their spatial correlations using the shear measurement method of Zhang et al. (2015). We find that the impact of PSF reconstruction uncertainty on the shear-shear correlation can be significantly reduced by cross correlating the shear estimators from different exposures. It takes only 0.2 stars (SNR > 100) per square arcmin on each exposure to reach the best performance of PSF interpolation, a requirement that is generally satisfied in the CFHTlenS data.
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