Dark Energy Survey Year 1 Results: redshift distributions of the weak-lensing source galaxies

By Ben Hoyle, Daniel Gruen, G. Bernstein, M. Rau, J. Vicente, William G. Hartley, Enrique Gaztañaga, J. DeRose, M. Troxel, C. Davis and 128 more. Monthly notices of the Royal Astronomical Society, 2017

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We describe the derivation and validation of redshift distribution estimates and their uncertainties for the populations of galaxies used as weak-lensing sources in the Dark Energy Survey (DES) Year 1 cosmological analyses. The Bayesian Photometric Redshift (BPZ) code is used to assign galaxies to four redshift bins between z ≈ 0.2 and ≈1.3, and to produce initial estimates of the lensing-weighted redshift distributions ni PZ(z) ∝ dni/dz for members of bin i. Accurate determination of cosmological parameters depends critically on knowledge of ni , but is insensitive to bin assignments or redshift errors for individual galaxies. The cosmological analyses allow for shifts ni(z) = niPZ(z − zi) to correct the mean redshift of ni(z) for biases in niPZ. The zi are constrained by comparison of independently estimated 30-band photometric redshifts of galaxies in the Cosmic Evolution Survey (COSMOS) field to BPZ estimates made from the DES griz fluxes, for a sample matched in fluxes, pre-seeing size, and lensing weight to the DES weak-lensing sources. In companion papers, the zi of the three lowest redshift bins are further constrained by the angular clustering of the source galaxies around red galaxies with secure photometric redshifts at 0.15 < z < 0.9. This paper details the BPZ and COSMOS procedures, and demonstrates that the cosmological inference is insensitive to details of the ni(z) beyond the choice of zi . The clustering and COSMOS validation methods produce consistent estimates of zi in the bins where both can be applied, with combined uncertainties of σzi = 0.015, 0.013, 0.011, and 0.022 in the four bins. Repeating the photo-z procedure instead using the Directional Neighbourhood Fitting algorithm, or using the ni(z) estimated from the matched sample in COSMOS, yields no discernible difference in cosmological inferences.

Subfields: Astronomy and Astrophysics, Electrical and Electronic Engineering

View Paper: https://www.semanticscholar.org/paper/a9b679117190bf6eb6143aed461ab54b694a85b0

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Citations in the corpus

Dark Energy Survey Year 1 results: weak lensing shape catalogues (2017, methodology): “As our source sample, we use galaxies with a BPZ photometric redshift estimate (Hoyle et al. 2018) based on their MOF photometry of 〈z〉 of 0.4 and above.”
KiDS+VIKING-450 and DES-Y1 combined: Cosmology with cosmic shear (2019, methodology): “However, we note that Hoyle et al. (2018) and Hartley et al. (2020) have moreover argued that the 4-band DES data may be inherently less suitable to our re-weighting scheme than the 9-band KiDS+VIKING data, which is a hypothesis that we assess in Appendix A (see also Buchs et al. 2019 for a way to…”
Dark Energy Survey Year 1 results: weak lensing mass calibration of redMaPPer galaxy clusters (2018, methodology): “For this work, we adapt the COSMOS calibration of Hoyle et al. (2018) to estimate the bias of our measurements, and the uncertainty in that bias.”
Cosmology from cosmic shear power spectra with Subaru Hyper Suprime-Cam first-year data (2018, background): “The other way to estimate the cosmic variance would be to populate mock simulation catalogs with galaxies with appropriate spectral energy distributions (Hoyle et al. 2018).”
KiDS+VIKING-450: Cosmic shear tomography with optical and infrared data (2018, methodology): “A69, page 6 of 30 Using COSMOS-2015 for the DIR method is very similar to the redshift calibration chosen for the DESy1 cosmological analysis (Hoyle et al. 2018) and the HSC-DR1 cosmic shear analysis (Hikage et al. 2019).”