Separating the intrinsic alignment signal and the lensing signal using self-calibration in photo- z surveys with KiDS450 and KV450 Data
Year: 2020
Type: article
Abstract: ABSTRACT To reach the full potential for the next generation of weak lensing surveys, it is necessary to mitigate the contamination of intrinsic alignments (IAs) of galaxies in the observed cosmic shear signal. The self-calibration (SC) of IAs provides an independent method to measure the IA signal from the survey data and the photometric redshift information. It operates differently from the marginalization method based on the IA modelling. In this work, we present the first application of SC to the KiDS450 data and the KV450 data, to split directly the intrinsic shape–galaxy density (Ig) correlation signal and the gravitational shear–galaxy density (Gg) correlation signal, using the information from photometric redshift (photo-z). We achieved a clear separation of the two signals and performed several validation tests. Our measured signals are found to be in general agreement with the KiDS450 cosmic shear best-fitting cosmology, for both lensing and IA measurements. For KV450, we use partial (high-z) data, and our lensing measurements are also in good agreement with KV450 cosmic shear best fit, while our IA signal suggests a larger IA amplitude for the high-z sample. We discussed the impact of photo-z quality on IA detection and several other potential systematic biases. Finally, we discuss the potential application of the information extracted for both the lensing signal and the IA signal in future surveys.
Language: English
Subfield: Astronomy and Astrophysics
Field: Physics and Astronomy
Domain: Physical Sciences
Open Access status: green
Awards: NUMERICAL CODES FOR THE DESC-LSST ANALYSIS PIPELINE: CORE COSMOLOGY LIBRARY STANDARD MODULES AND BEYOND WCDM MODULES, G2736705176, Investigations of 2- and 3- point Intrinsic Alignments of Galaxies (II, GI, III, GGI, GII) and their Isolation in Current and Future Lensing Surveys, G5101662785, G8075452111
OpenAlex ID: W2987403365
