Testing Shear Recovery with Field Distortion

Abstract

The tilt, rotation, or offset of each CCD with respect to the focal plane, as well as the distortion of the focal plane itself, cause shape distortions to the observed objects, an effect typically known as field distortion (FD). We point out that FD provides a unique way of quantifying the accuracy of cosmic shear measurement. The idea is to stack the shear estimators from galaxies that share similar FD-induced shape distortions. Given that the latter can be calculated with parameters from astrometric calibrations, the accuracy of the shear estimator can be directly tested on real images. It provides a way to calibrate the multiplicative and additive shear recovery biases within the scientific data itself, without requiring simulations or any external data sets. We use the CFHTLenS images to test the Fourier Quad shear recovery method. We highlight some details in our image processing pipeline, including background removal, source identification and deblending, astrometric calibration, star selection for PSF reconstruction, noise reduction, etc.. We show that in the shear ranges of −0.005 ∼ < g 1 ∼ < 0.005 and −0.008 ∼ < g 2 ∼ < 0.008, the multiplicative biases are at the level of ∼ < 0.04. Slight additive biases on the order of ∼ 5 × 10 −4 (6σ) are identified for sources provided by the official CFHTLenS catalog (not using its shear catalog), but are minor (4σ) for source catalog generated by our Fourier Quad pipeline.

First measurement of the characteristic depletion radius of dark matter haloes from weak lensing

“…In this method, the effects due to the Point Spread Function, the background noise, and the source Poisson noise are all corrected in model-independent ways, and tested under general observing conditions to a very low Signalto-Noise Ratio (SNR) of the source image (SNR < 10) (Zhang et al 2015). More recently, it has been shown using both the CFHTLenS (Heymans et al 2012;Erben et al 2013) and DECaLS data that the FQ shear estimators of the galaxies can faithfully recover the small (∼ 10 −3 ) field distortion signals caused by the optics of the telescope (Zhang et al 2019;Wang et al 2021). In doing so, we caution that inappropriate selection of sources due to either the selection function itself or the presence of the geometric boundaries (CCD edges, bad pixels, etc.)…”

Avoiding the Geometric Boundary Effect in Shear Measurement

“…We use simulations to show that this simple procedure can indeed remove the additive shear bias related to the boundaries. We further demonstrate the existence of the boundary effect in real data, the DECaLS z-band imaging data, using the field-distortion test method proposed in Zhang et al (2019). The results also show that our treatment can accurately remove the bias from the boundary effect.…”

“…We use the Fourier Quad pipeline for shear measurement (Zhang et al 2015(Zhang et al , 2016(Zhang et al , 2019. The results for the RW galaxies are shown in fig.…”

“…The validity of this solution can also be tested in real data. A direct way to do so is to adopt the idea recently proposed by Zhang et al (2019), which shows that one can use the galaxy shear estimators to restore the field distortion signal as a way of testing the shear recovery accuracy. It can be done within the observational data itself, without requiring simulations.…”

Massive Star-Forming Galaxies Have Converted Most of Their Halo Gas into Stars

“…The shear catalog 4 used here to measure galaxy-galaxy lensing signals is based on the Dark Energy Camera Legacy Survey (DECaLS) DR8 imaging data (Dey et al 2019;Zou et al 2019). The shape of each galaxy is measured using the FOURIER_QUAD pipeline, which has been shown to yield accurate shear measurements even for extremely faint galaxy images (SNR < 10) when applied to both simulations (Zhang et al 2015) and real data (Zhang et al (2019) for the CFHTLenS data, and Wang et al (2021) for the DECaLS data). The whole shear catalog covers about 9,000 square degrees in g/r/z bands, containing shear estimators from 190/246/300 million galaxy images, respectively.…”