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Accurate photometric redshift (photo- z) estimation requires support from multiband observational data. However, in the actual process of astronomical observations and data processing, some sources may have missing observational data in certain bands for various reasons. This could greatly affect the accuracy and reliability of photo- z estimation for these sources, and even render some estimation methods unusable. The same situation may exist for the upcoming Chinese Space Station Telescope (CSST). In this study, we employ a deep learning method called generative adversarial imputation networks (GAIN) to impute the missing photometric data in CSST , aiming to reduce the impact of data missing on photo- z estimation and improve estimation accuracy. Our results demonstrate that using the GAIN technique can effectively fill in the missing photometric data in CSST. Particularly, when the data missing rate is below 30 per cent, the imputation of photometric data exhibits high accuracy, with higher accuracy in the g, r, i, z , and y bands compared to the NUV and u bands. After filling in the missing values, the quality of photo- z estimation obtained by the widely used easy and accurate Zphot from Yale (eazy) software is notably enhanced. Evaluation metrics for assessing the quality of photo- z estimation, including the catastrophic outlier fraction (f out), the normalized median absolute deviation (⁠|$\rm {\sigma _{NMAD}}$|⁠), and the bias of photometric redshift (bias), all show some degree of improvement. Our research will help maximize the utilization of observational data and provide a new method for handling sample missing values for applications that require complete photometry data to produce results. [ABSTRACT FROM AUTHOR]

The VST Optical Imaging of the CDFS and ES1 Fields (VOICE) Survey is a Guaranteed Time programme carried out with the European Southern Observatory (ESO) VLT Survey Telescope (VST) telescope to provide deep optical imaging over two 4 deg2 patches of the sky centred on the Chandra Deep Field South (CDFS) and ES1 as part of the ESO-Spitzer Imaging Extragalactic Survey. We present the cosmic shear measurement over the 4 deg2 covering the CDFS region in the r band using LensFit. Each of the four tiles of 1 deg2 has more than 100 exposures, of which more than 50 exposures passed a series of image quality selection criteria for weak-lensing study. The 5σ limiting magnitude in r band is 26.1 for point sources, which is ≳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, Ks. 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 data set was calibrated using VOICE-like mock image simulations. Furthermore, we have analysed 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 Λ cold dark matter model, we have obtained $$\Sigma_8=\sigma_8(\Omega_{\rm m}/0.3)^{0.5}=0.68^{+0.11}_{-0.15}$$. [ABSTRACT FROM AUTHOR]

Dark energy may be the first sign of new fundamental physics in the Universe, taking either a physical form or revealing a correction to Einsteinian gravity. Weak gravitational lensing and galaxy peculiar velocities provide complementary probes of general relativity, and in combination allow us to test modified theories of gravity in a unique way. We perform such an analysis by combining measurements of cosmic shear tomography from the Canada–France–Hawaii Telescope Lensing Survey (CFHTLenS) with the growth of structure from the WiggleZ Dark Energy Survey and the Six-degree-Field Galaxy Survey, producing the strongest existing joint constraints on the metric potentials that describe general theories of gravity. For scale-independent modifications to the metric potentials which evolve linearly with the effective dark energy density, we find present-day cosmological deviations in the Newtonian potential and curvature potential from the prediction of general relativity to be ΔΨ/Ψ = 0.05 ± 0.25 and ΔΦ/Φ = −0.05 ± 0.3, respectively (68 per cent confidence limits). [ABSTRACT FROM PUBLISHER]

ABSTRACT We present the Canada-France-Hawaii Telescope Lensing Survey (CFHTLenS) that accurately determines a weak gravitational lensing signal from the full 154 deg2 of deep multicolour data obtained by the CFHT Legacy Survey. Weak gravitational lensing by large-scale structure is widely recognized as one of the most powerful but technically challenging probes of cosmology. We outline the CFHTLenS analysis pipeline, describing how and why every step of the chain from the raw pixel data to the lensing shear and photometric redshift measurement has been revised and improved compared to previous analyses of a subset of the same data. We present a novel method to identify data which contributes a non-negligible contamination to our sample and quantify the required level of calibration for the survey. Through a series of cosmology-insensitive tests we demonstrate the robustness of the resulting cosmic shear signal, presenting a science-ready shear and photometric redshift catalogue for future exploitation. [ABSTRACT FROM AUTHOR]