scholarly journals Atmospheric point spread function interpolation for weak lensing in short exposure imaging data

2012 ◽  
Vol 427 (3) ◽  
pp. 2572-2587 ◽  
Author(s):  
C. Chang ◽  
P. J. Marshall ◽  
J. G. Jernigan ◽  
J. R. Peterson ◽  
S. M. Kahn ◽  
...  
2020 ◽  
Vol 636 ◽  
pp. A78 ◽  
Author(s):  
M. A. Schmitz ◽  
J.-L. Starck ◽  
F. Ngole Mboula ◽  
N. Auricchio ◽  
J. Brinchmann ◽  
...  

Context. Future weak lensing surveys, such as the Euclid mission, will attempt to measure the shapes of billions of galaxies in order to derive cosmological information. These surveys will attain very low levels of statistical error, and systematic errors must be extremely well controlled. In particular, the point spread function (PSF) must be estimated using stars in the field, and recovered with high accuracy. Aims. The aims of this paper are twofold. Firstly, we took steps toward a nonparametric method to address the issue of recovering the PSF field, namely that of finding the correct PSF at the position of any galaxy in the field, applicable to Euclid. Our approach relies solely on the data, as opposed to parametric methods that make use of our knowledge of the instrument. Secondly, we studied the impact of imperfect PSF models on the shape measurement of galaxies themselves, and whether common assumptions about this impact hold true in an Euclid scenario. Methods. We extended the recently proposed resolved components analysis approach, which performs super-resolution on a field of under-sampled observations of a spatially varying, image-valued function. We added a spatial interpolation component to the method, making it a true 2-dimensional PSF model. We compared our approach to PSFEx, then quantified the impact of PSF recovery errors on galaxy shape measurements through image simulations. Results. Our approach yields an improvement over PSFEx in terms of the PSF model and on observed galaxy shape errors, though it is at present far from reaching the required Euclid accuracy. We also find that the usual formalism used for the propagation of PSF model errors to weak lensing quantities no longer holds in the case of an Euclid-like PSF. In particular, different shape measurement approaches can react differently to the same PSF modeling errors.


2020 ◽  
Vol 493 (3) ◽  
pp. 3825-3837
Author(s):  
Dezi Liu ◽  
Wenqiang Deng ◽  
Zuhui Fan ◽  
Liping Fu ◽  
Giovanni Covone ◽  
...  

ABSTRACT The VLT Survey Telescope (VST) Optical Imaging of the CDFS and ES1 Fields Survey, in synergy with the SUDARE survey, is a deep optical ugri imaging of the CDFS and ES1 fields using the VST. The observations for the CDFS field comprise about 4.38 deg2 down to r ∼ 26 mag. The total on-sky time spans over 4 yr in this field, distributed over four adjacent sub-fields. In this paper, we use the multiepoch r-band imaging data to measure the variability of the detected objects and search for transients. We perform careful astrometric and photometric calibrations and point spread function modelling. A new method, referring to as differential running-average photometry, is proposed to measure the light curves of the detected objects. With the method, the difference of PSFs between different epochs can be reduced, and the background fluctuations are also suppressed. Detailed uncertainty analysis and detrending corrections on the light curves are performed. We visually inspect the light curves to select variable objects, and present some objects with interesting light curves. Further investigation of these objects in combination with multiband data will be presented in our forthcoming paper.


Author(s):  
Lin Nie ◽  
Guoliang Li ◽  
John R Peterson ◽  
Chengliang Wei

Abstract Accurate shear measurement is a key topic in weak lensing community. Point Spread Function (PSF), which smears the observed galaxy image, plays one of the main roles in the systematic errors in shear measurement and must be treated carefully to avoid bias and errors in cosmological parameters. In this paper, we present new PSF measurement methods, Smooth-PCA (SPCA) and Improved-SPCA (iSPCA), which can reconstruct smooth PSFs with high efficiency. Our methods decompose the star images into smooth principal components by using the Expectation-Maximization-PCA (EMPCA) method, and the smooth principal components are composed by Moffatlets basis functions, which are derived from the Moffat function. We demonstrate our approaches based on simulated Moffat PSFs and PhoSim star images. The constructed smooth principal components show flexible and efficient as the same as EMPCA, and have more stable patterns than EMPCA under noises contamination. We then check the reconstruction accuracy on the shape of PSFs. We find that our methods are able to reconstruct the PSFs at the same precision as the EMPCA method which indicates and iSPCA are promising for weak lensing shear measurement.


2021 ◽  
Vol 502 (3) ◽  
pp. 4048-4063
Author(s):  
Arun Kannawadi ◽  
Erik Rosenberg ◽  
Henk Hoekstra

ABSTRACT metacalibration is a state-of-the-art technique for measuring weak gravitational lensing shear from well-sampled galaxy images. We investigate the accuracy of shear measured with metacalibration from fitting elliptical Gaussians to undersampled galaxy images. In this case, metacalibration introduces aliasing effects leading to an ensemble multiplicative shear bias about 0.01 for Euclid  and even larger for the Roman Space Telescope, well exceeding the missions’ requirements. We find that this aliasing bias can be mitigated by computing shapes from weighted moments with wider Gaussians as weight functions, thereby trading bias for a slight increase in variance of the measurements. We show that this approach is robust to the point-spread function in consideration and meets the stringent requirements of Euclid for galaxies with moderate to high signal-to-noise ratios. We therefore advocate metacalibration as a viable shear measurement option for weak lensing from upcoming space missions.


2009 ◽  
Vol 500 (2) ◽  
pp. 647-655 ◽  
Author(s):  
S. Paulin-Henriksson ◽  
A. Refregier ◽  
A. Amara

2014 ◽  
Vol 543-547 ◽  
pp. 2391-2394
Author(s):  
Feng Wang ◽  
Kun Fan Zhang ◽  
Fan Kun Meng ◽  
Yong Jun Zhao

The RL(Richardson-Lucy) algorithm is an important method for restoration of turbulence-degraded images. However, the shortcoming of this method is that it tends to amplify the noise and exsits excessive smoothing in the iterative procedure. This paper discusses the RL algorithm and its improving methods focusing on turbulence-degraded images restoration.Firstly, a short exposure atmospheric turbulence-degraded model is established and a numerical computing method is proposed for random phase screen. Secondly, the essential principle and computational formula are deduced. To restore the object image effectively from the turbulence-degraded image, a new double-circulation iterative Richardson-Lucy restoration algorithm using TV-regularized method is proposed. This new algorithm introduces the total variation restraint and estimates the object image and the point spread function based on the inner and outer double-circulation iteration, which can use the inherent relation between the object image and the point spread function adequately. Simulation experiments show that the proposed algorithm can effectively preserve the details and edges of the image and its restoration effect is obviously better than the traditional RL algorithm.


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