Examinando por Autor "Wang, Chao"

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    Weak lensing study in VOICE survey - II. Shear bias calibrations
    (Oxford University Press, 2018-08) Liu, Dezi; Fu, Liping; Liu, Xiangkun; Radovich, Mario; Wang, Chao; Pan, Chuzhong; Fan, Zuhui; Covone, Giovanni; Vaccari, Mattia; Botticella, Maria Teresa; Capaccioli, Massimo; De Cicco, Demetrae Grado, Aniello; Miller, Lance; Napolitano, Nicola; Paolillo, Maurizio; Pignata, Giuliano
    The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is proposed to obtain deep optical ugri imaging of the CDFS and ES1 fields using the VLT Survey Telescope (VST). At present, the observations for the CDFS field have been completed, and comprise in total about 4.9 deg2 down to rAB~26 mag. In the companion paper by Fu et al., we present the weak lensing shear measurements for r-band images with seeing ≤0.9 arcsec. In this paper, we perform image simulations to calibrate possible biases of the measured shear signals. Statistically, the properties of the simulated point spread function and galaxies show good agreements with those of observations. The multiplicative bias is calibrated to reach an accuracy of ~3.0 per cent. We study the bias sensitivities to the undetected faint galaxies and to the neighbouring galaxies. We find that undetected galaxies contribute to the multiplicative bias at the level of ~0.3 per cent. Further analysis shows that galaxies with lower signal-to-noise ratio are impacted more significantly because the undetected galaxies skew the background noise distribution. For the neighbouring galaxies, we find that although most have been rejected in the shape measurement procedure, about one-third of them still remain in the final shear sample. They show a larger ellipticity dispersion and contribute to ~0.2 per cent of the multiplicative bias. Such a bias can be removed by further eliminating these neighbouring galaxies. But the effective number density of the galaxies can be reduced considerably. Therefore efficient methods should be developed for future weak lensing deep surveys. © 2018 The Author(s).