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FPFS Shear Estimator: Systematic Tests on the Hyper Suprime-Cam Survey First Year Data
- Publication Year :
- 2019
-
Abstract
- We apply the Fourier Power Function Shapelets (FPFS) shear estimator to the first year data of the Hyper Suprime-Cam survey to construct a shape catalog. The FPFS shear estimator has been demonstrated to have multiplicative bias less than $1\%$ in the absence of blending, regardless of complexities of galaxy shapes, smears of point spread functions (PSFs) and contamination from noise. The blending bias is calibrated with realistic image simulations, which include the impact of neighboring objects, using the COSMOS Hubble Space Telescope images. Here we carefully test the influence of PSF model residual on the FPFS shear estimation and the uncertainties in the shear calibration. Internal null tests are conducted to characterize potential systematics in the FPFS shape catalog and the results are compared with those measured using a catalog where the shapes were estimated using the re-Gaussianization algorithms. Furthermore, we compare various weak lensing measurements between the FPFS shape catalog and the re-Gaussianization shape catalog and conclude that the weak lensing measurements between these two shape catalogs are consistent with each other within the statistical uncertainty.<br />24 pages, 19 figures, accepted by ApJS
- Subjects :
- Physics
Cosmology and Nongalactic Astrophysics (astro-ph.CO)
010308 nuclear & particles physics
Multiplicative function
Astrophysics::Instrumentation and Methods for Astrophysics
Estimator
FOS: Physical sciences
Astronomy and Astrophysics
Astrophysics::Cosmology and Extragalactic Astrophysics
Residual
01 natural sciences
Galaxy
symbols.namesake
Fourier transform
Space and Planetary Science
Observational cosmology
0103 physical sciences
symbols
Power function
010303 astronomy & astrophysics
Algorithm
Weak gravitational lensing
Astrophysics - Cosmology and Nongalactic Astrophysics
Subjects
Details
- Language :
- English
- Database :
- OpenAIRE
- Accession number :
- edsair.doi.dedup.....59d488c049bbeeae6185f4ce6ceeb61d