GREAT3 results I: systematic errors in shear estimation and the impact of real galaxy morphology

We present first results from the third GRavitational lEnsing Accuracy Testing (GREAT3) challenge, the third in a sequence of challenges for testing methods of inferring weak gravitational lensing shear distortions from simulated galaxy images. GREAT3 was divided into experiments to test three specific questions, and included simulated space- and ground-based data with constant or cosmologically-varying shear fields. The simplest (control) experiment included parametric galaxies with a realistic distribution of signal-to-noise, size, and ellipticity, and a complex point spread function (PSF). The other experiments tested the additional impact of realistic galaxy morphology, multiple exposure imaging, and the uncertainty about a spatially-varying PSF; the last two questions will be explored in Paper II. The 24 participating teams competed to estimate lensing shears to within systematic error tolerances for upcoming Stage-IV dark energy surveys, making 1525 submissions overall. GREAT3 saw considerable variety and innovation in the types of methods applied. Several teams now meet or exceed the targets in many of the tests conducted (to within the statistical errors). We conclude that the presence of realistic galaxy morphology in simulations changes shear calibration biases by $sim 1$ per cent for a wide range of methods. Other effects such as truncation biases due to finite galaxy postage stamps, and the impact of galaxy type as measured by the S{e}rsic index, are quantified for the first time. Our results generalize previous studies regarding sensitivities to galaxy size and signal-to-noise, and to PSF properties such as seeing and defocus. Almost all methods results support the simple model in which additive shear biases depend linearly on PSF ellipticity.

The GREAT3 Challenge

The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is an image analysis competition that aims to test algorithms to measure weak gravitational lensing from astronomical images. The challenge started in October 2013 and ends 30 April 2014. The challenge focuses on testing the impact on weak lensing measurements of realistically complex galaxy morphologies, realistic point spread function, and combination of multiple different exposures. It includes simulated ground- and space-based data. The details of the challenge are described in [15], and the challenge website and its leader board can be found at http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/, respectively.

The Third Gravitational Lensing Accuracy Testing (GREAT3) Challenge Handbook

The GRavitational lEnsing Accuracy Testing 3 (GREAT3) challenge is the third in a series of image analysis challenges, with a goal of testing and facilitating the development of methods for analyzing astronomical images that will be used to measure weak gravitational lensing. This measurement requires extremely precise estimation of very small galaxy shape distortions, in the presence of far larger intrinsic galaxy shapes and distortions due to the blurring kernel caused by the atmosphere, telescope optics, and instrumental effects. The GREAT3 challenge is posed to the astronomy, machine learning, and statistics communities, and includes tests of three specific effects that are of immediate relevance to upcoming weak lensing surveys, two of which have never been tested in a community challenge before. These effects include realistically complex galaxy models based on high-resolution imaging from space; spatially varying, physically-motivated blurring kernel; and combination of multiple different exposures. To facilitate entry by people new to the field, and for use as a diagnostic tool, the simulation software for the challenge is publicly available, though the exact parameters used for the challenge are blinded. Sample scripts to analyze the challenge data using existing methods will also be provided. See http://great3challenge.info and http://great3.projects.phys.ucl.ac.uk/leaderboard/ for more information.

Flexion measurement in simulations of Hubble Space Telescope data

We present a simulation analysis of weak gravitational lensing flexion and shear measurement using shapelet decomposition, and identify differences between flexion and shear measurement noise in deep survey data. Taking models of galaxies from the Hubble Space Telescope Ultra Deep Field (HUDF) and applying a correction for the HUDF point spread function we generate lensed simulations of deep, optical imaging data from Hubbles Advanced Camera for Surveys (ACS), with realistic galaxy morphologies. We find that flexion and shear estimates differ in our measurement pipeline: whereas intrinsic galaxy shape is typically the dominant contribution to noise in shear estimates, pixel noise due to finite photon counts and detector read noise is a major contributor to uncertainty in flexion estimates, across a broad range of galaxy signal-to-noise. This pixel noise also increases more rapidly as galaxy signal-to-noise decreases than is found for shear estimates. We provide simple power law fitting functions for this behaviour, for both flexion and shear, allowing the effect to be properly accounted for in future forecasts for flexion measurement. Using the simulations we also quantify the systematic biases of our shapelet flexion and shear measurement pipeline for deep Hubble data sets such as Galaxy Evolution from Morphology and SEDs, Space Telescope A901/902 Galaxy Evolution Survey or the Cosmic Evolution Survey. Flexion measurement biases are found to be significant but consistent with previous studies.