Dark Energy Survey Year 3 results: calibration of lens sample redshift distributions using clustering redshifts with BOSS/eBOSS Get access Arrow
We present clustering redshift measurements for Dark Energy Survey (DES) lens sample galaxies to be used in weak gravitational lensing and galaxy clustering studies. To perform this measurement, we cross-correlate with spectroscopic galaxies from the Baryon Acoustic Oscillation Survey (BOSS) and its extension, eBOSS. We validate our methodology in simulations, including a new technique to calibrate systematic errors due to the galaxy clustering bias, finding our method to be generally unbiased in calibrating the mean redshift. We apply our method to the data, and estimate the redshift distribution for eleven different photometrically-selected bins. We find general agreement between clustering redshift and photometric redshift estimates, with differences on the inferred mean redshift to be below $$|\Delta z|=0.01$$ in most of the bins. We also test a method to calibrate a width parameter for redshift distributions, which we found necessary to use for some of our samples. Our typical uncertainties on the mean redshift ranged from 0.003 to 0.008, while our uncertainties on the width ranged from 4 to 9%. Finally, we discuss how these results calibrate the photometric redshift distributions used in companion DES Year 3 Results papers.
- Research Organization:
- Fermi National Accelerator Lab. (FNAL), Batavia, IL (United States); SLAC National Accelerator Lab., Menlo Park, CA (United States)
- Sponsoring Organization:
- USDOE Office of Science (SC), High Energy Physics (HEP)
- Contributing Organization:
- DES Collaboration
- DOE Contract Number:
- AC02-07CH11359
- OSTI ID:
- 1824823
- Report Number(s):
- FERMILAB-PUB-20-664-AE; arXiv:2012.12826; oai:inspirehep.net:1838121
- Journal Information:
- Monthly Notices of the Royal Astronomical Society, Vol. 513, Issue 4; ISSN 0035-8711
- Publisher:
- Oxford University Press
- Country of Publication:
- United States
- Language:
- English
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