Bayesian Galaxy Shape Measurement for Weak Lensing Surveys -II. Application to Simulations

By Thomas D. Kitching, L. Miller, Catherine Heymans, L. Waerbeke, Alan Heavens. 2008

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In this paper, we extend the Bayesian model fitting shape measurement method presented in Miller et al., and use the method to estimate the shear from the Shear TEsting Programme simulations (STEP). The method uses a fast model fitting algorithm that uses realistic galaxy profiles and analytically marginalizes over the position and amplitude of the model by doing the model fitting in Fourier space. This is used to find the full posterior probability in ellipticity. The shear is then estimated in a Bayesian way from this posterior probability surface. The Bayesian estimation allows measurement bias arising from the presence of random noise to be removed. In this paper, we introduce an iterative algorithm that can be used to estimate the intrinsic ellipticity prior and show that this is accurate and stable. We present results using the STEP parametrization that relates the input shear γ T to the estimated shear γ M by introducing a bias m and an offset c: γ M - γ T = my T + c. The average number density of galaxies used in the STEP1 analysis was 9 per square arcminute, for STEP2 the number density was 30 per square arcminute. By using the method to estimate the shear from the STEP1 simulations we find the method to have a shear bias of m = 0.006 ± 0.005 and a variation in shear offset with point spread function type of σ = 0.0002. Using the method to estimate the shear from the STEP2 simulations we find that the shear bias and offset are m = 0.002 ± 0.016 and c = -0.0007 ± 0.0006, respectively. In addition, we find that the bias and offset are stable to changes in the magnitude and size of the galaxies. Such biases should yield any cosmological constraints from future weak lensing surveys robust to systematic effects in shape measurement. Finally, we present an alternative to the STEP parametrization by using a quality factor that relates the intrinsic shear variance in a simulation to the variance in shear that is measured and show that the method presented has an average of Q ≥ 100 which is at least a factor of 10 times better than other shape measurement methods.

Subfields: Astronomy and Astrophysics, Computer Vision and Pattern Recognition

View Paper: https://www.semanticscholar.org/paper/bddf0882575374af0796ed87a8af1f0d29c41032

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Citations in the corpus

Results of the GREAT08 Challenge?: an image analysis competition for cosmological lensing: Results o (2009, methodology): “For more details, see Appendix F of the GREAT08 Handbook and also Miller et al. (2007) and Kitching et al. (2008b).”
The Kilo-Degree Survey (2012, unknown): “THELI/Lensfit [9, 23] for weak lensing applications).”
CFHTLenS: the Canada–France–Hawaii Telescope Lensing Survey – imaging data and catalogue products (2012, background): “…two different versions of KSB+ (most recently used in Schrabback et al. 2010; Fu et al. 2008), three different versions of SHAPELETS (Kuijken 2006; Massey et al. 2007c; Velander et al. 2011) and the model fitting method lensfit (Miller et al. 2007; Kitching et al. 2008; Miller et al. 2012).”
Masses of Galaxy Clusters from Gravitational Lensing (2013, methodology): “Finally we mention lensfit (Miller et al. 2007, 2012), which is a Bayesian algorithm that fits galaxies with a bulge+disk model and has been used recently to analyse data from the CFHT Legacy Survey (Heymans et al. 2012).”
The DES Science Verification weak lensing shear catalogues (2015, methodology): “Multiple methods are supported for shear measurement, but for this study we adopted the “LENSFIT”-style method, based on the work of Miller et al. (2007).”
KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data (2018, methodology): “Shape measurements with lensfit The shapes of galaxies, described by the two ellipticity components 1 and 2, were measured from THELI-reduced individual r-band exposures with the self-calibrating version of the lensfit algorithm (Miller et al. 2007, 2013).”
Weak Gravitational Lensing (2012, methodology): “Following a similar approach, the lensﬁt method [62, 47] measures the shear by ﬁtting realistic galaxy proﬁles in a fully Bayesian way.”
Gravitational lensing analysis of the Kilo-Degree Survey (2015, methodology): “We use the lensfit code4 (Miller et al. 2007; Kitching et al. 2008; M+13) which performs a seven-parameter galaxy model fit (x, y position, flux, scalelength rd, bulge-to-disc ratio and ellipticity 1, 2), simultaneously to all subexposures of a given galaxy, taking into account the different PSFs…”
KiDS-450: cosmological parameter constraints from tomographic weak gravitational lensing (2016, methodology): “In this work, we use the lensFIT likelihood-based model-fitting method to estimate the shear from the shape of a galaxy (Miller et al. 2007, 2013; Kitching et al. 2008; Fenech Conti et al. 2016).”
Observational probes of cosmic acceleration (2012, background): “Propagating instrument noise through the elliptical Gaussian fitting method, Bernstein and Jarvis (2002) find, in the absence of a PSF, σ(e+[f ]) = σ(e×[f ]) = √ 16πnσf F = 2 ν , (122) where n is the flux noise variance per unit area, F is the galaxy flux, σf is the 1σ width of the galaxy (note: the”
Origins of weak lensing systematics, and requirements on future instrumentation (or knowledge of instrumentation) (2012, methodology): “This is naturally done by methods that fit parametric shape models to the data (e.g. Bridle et al. 2001; Miller et al. 2007; Kitching et al. 2008).”