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RCSLenS: the Red Cluster Sequence Lensing Survey

Abstract:
We present the Red-sequence Cluster Lensing Survey (RCSLenS), an application of the methods developed for the Canada France Hawaii Telescope Lensing Survey (CFHTLenS) to the ~785deg$^2$, multi-band imaging data of the Red-sequence Cluster Survey 2 (RCS2). This project represents the largest public, sub-arcsecond seeing, multi-band survey to date that is suited for weak gravitational lensing measurements. With a careful assessment of systematic errors in shape measurements and photometric redshifts we extend the use of this data set to allow cross-correlation analyses between weak lensing observables and other data sets. We describe the imaging data, the data reduction, masking, multi-colour photometry, photometric redshifts, shape measurements, tests for systematic errors, and a blinding scheme to allow for more objective measurements. In total we analyse 761 pointings with r-band coverage, which constitutes our lensing sample. Residual large-scale B-mode systematics prevent the use of this shear catalogue for cosmic shear science. The effective number density of lensing sources over an unmasked area of 571.7deg$^2$ and down to a magnitude limit of r~24.5 is 8.1 galaxies per arcmin$^2$ (weighted: 5.5 arcmin$^{-2}$) distributed over 14 patches on the sky. Photometric redshifts based on 4-band griz data are available for 513 pointings covering an unmasked area of 383.5 deg$^2$ We present weak lensing mass reconstructions of some example clusters as well as the full survey representing the largest areas that have been mapped in this way. All our data products are publicly available through CADC at http://www.cadc-ccda.hia-iha.nrc-cnrc.gc.ca/en/community/rcslens/query.html in a format very similar to the CFHTLenS data release.
Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1093/mnras/stw2013

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Publisher:
Oxford University Press
Journal:
Monthly Notices of the Royal Astronomical Society More from this journal
Volume:
463
Issue:
1
Pages:
635-654
Publication date:
2016-11-21
Acceptance date:
2016-08-09
DOI:
EISSN:
1365-2966
ISSN:
0035-8711


Keywords:
Pubs id:
pubs:656768
UUID:
uuid:46c01860-cc07-485a-aa6b-e5c1df49a3ce
Local pid:
pubs:656768
Source identifiers:
656768
Deposit date:
2017-02-28

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