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arXiv · 1802.10282

Weak Lensing Study in VOICE Survey I: Shear Measurement

Abstract

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is a Guaranteed Time program carried out with the ESO/VST telescope to provide deep optical imaging over two 4 deg$^2$ patches of the sky centred on the CDFS and ES1 pointings. We present the cosmic shear measurement over the 4 deg$^2$ covering the CDFS region in the $r$-band using LensFit. Each of the four tiles of 1 deg$^2$ has more than one hundred exposures, of which more than 50 exposures passed a series of image quality selection criteria for weak lensing study. The $5\sigma$ limiting magnitude in $r$- band is 26.1 for point sources, which is $\sim$1 mag deeper than other weak lensing survey in the literature (e.g. the Kilo Degree Survey, KiDS, at VST). The photometric redshifts are estimated using the VOICE $u,g,r,i$ together with near-infrared VIDEO data $Y,J,H,K_s$. The mean redshift of the shear catalogue is 0.87, considering the shear weight. The effective galaxy number density is 16.35 gal/arcmin$^2$, which is nearly twice the one of KiDS. The performance of LensFit on such a deep dataset was calibrated using VOICE-like mock image simulations. Furthermore, we have analyzed the reliability of the shear catalogue by calculating the star-galaxy cross-correlations, the tomographic shear correlations of two redshift bins and the contaminations of the blended galaxies. As a further sanity check, we have constrained cosmological parameters by exploring the parameter space with Population Monte Carlo sampling. For a flat $\Lambda$CDM model we have obtained $\Sigma_8$ = $\sigma_8(\Omega_m/0.3)^{0.5}$ = $0.68^{+0.11}_{-0.15}$.

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Liping Fu, Dezi Liu, Mario Radovich, Xiangkun Liu, Chuzhong Pan, Zuhui Fan, Giovanni Covone, Mattia Vaccari, Valeria Amaro, Massimo Brescia, Massimo Capaccioli, Demetra De Cicco, Aniello Grado, Luca Limatola, Lance Miller, Nicola R. Napolitano, Maurizio Paolillo, Giuliano Pignata. 2018-02-28. Weak Lensing Study in VOICE Survey I: Shear Measurement. https://doi.org/10.1093/mnras/sty1579

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