Galaxy-Galaxy lensing in HSC: Validation tests and the impact of heterogeneous spectroscopic training sets

December 2019 • 2019MNRAS.490.5658S

Authors • Speagle, Joshua S. • Leauthaud, Alexie • Huang, Song • Bradshaw, Christopher P. • Ardila, Felipe • Capak, Peter L. • Eisenstein, Daniel J. • Masters, Daniel C. • Mandelbaum, Rachel • More, Surhud • Simet, Melanie • Sifón, Cristóbal

Abstract • Although photometric redshifts (photo-z's) are crucial ingredients for current and upcoming large-scale surveys, the high-quality spectroscopic redshifts currently available to train, validate, and test them are substantially non-representative in both magnitude and colour. We investigate the nature and structure of this bias by tracking how objects from a heterogeneous training sample contribute to photo-z predictions as a function of magnitude and colour, and illustrate that the underlying redshift distribution at fixed colour can evolve strongly as a function of magnitude. We then test the robustness of the galaxy-galaxy lensing signal in 120 deg² of HSC-SSP DR1 data to spectroscopic completeness and photo-z biases, and find that their impacts are sub-dominant to current statistical uncertainties. Our methodology provides a framework to investigate how spectroscopic incompleteness can impact photo-z-based weak lensing predictions in future surveys such as LSST and WFIRST.

Links

• SIMBAD http://simbad.u-strasbg.fr/simbo.pl?bibcode=2019MNRAS.490.5658S
• PDF http://academic.oup.com/mnras/pdf-lookup/doi/10.1093/mnras/stz2968
• PREPRINT http://arxiv.org/abs/1906.05876
• DATA https://archive.stsci.edu/mastbibref.php?bibcode=2019MNRAS.490.5658S
• DATA https://hst.esac.esa.int/ehst/#/pages/search;bibcode=2019MNRAS.490.5658S
• DATA https://irsa.ipac.caltech.edu/bibdata/2019/S/2019MNRAS.490.5658S.html
• ELECTR https://doi.org/10.1093%2Fmnras%2Fstz2968