2020
DOI: 10.1103/physrevd.101.063509
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Effects of redshift uncertainty on cross-correlations of CMB lensing and galaxy surveys

Abstract: We explore the effects of incorporating redshift uncertainty into measurements of galaxy clustering and crosscorrelations of galaxy positions and CMB lensing maps. We use a simple Gaussian model for a redshift distribution in a redshift bin with two parameters, the mean, z0, and the width, σz. We vary these parameters, as well as the galaxy bias, bg(z), and cosmological parameters σ8(z) and Ωm in a Fisher analysis across 12 redshift bins from z = 0 − 7. We find that incorporating redshift uncertainties degrade… Show more

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Cited by 9 publications
(8 citation statements)
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“…where 𝜎 𝑗 is the standard deviation of the redshift distribution. We note that photometric redshift scatter is often approximated as a Gaussian function (Cawthon 2020, LSST Science Collaboration 2009. If 𝑛(𝑧) is a Gaussian (i.e., 𝑛(𝑧)…”
Section: Correcting For Galaxy Biasmentioning
confidence: 99%
“…where 𝜎 𝑗 is the standard deviation of the redshift distribution. We note that photometric redshift scatter is often approximated as a Gaussian function (Cawthon 2020, LSST Science Collaboration 2009. If 𝑛(𝑧) is a Gaussian (i.e., 𝑛(𝑧)…”
Section: Correcting For Galaxy Biasmentioning
confidence: 99%
“…The noise and systematics of CMB lensing are quite different, so the cross-correlation between the galaxy density, galaxy lensing, and CMB lensing fields, as well as their full joint analysis, make appealing cosmological probes. A joint analysis helps to improve cosmological constraints by breaking degeneracies, for example involving galaxy bias, and by constraining nuisance parameters associated with sources of systematic error in galaxy measurements [16][17][18][19] (e.g. lensing multiplicative bias, photometric redshift errors).…”
mentioning
confidence: 99%
“…Does CMB lensing help constrain the photo-z parameters? CMB lensing has been shown to help with shear calibration [32,59,60], intrinsic alignments [61,62], as well as photo-z errors [33]. We compare the fiducial 3 × 2 LSST analysis with the 6 × 2 analysis of LSST + CMB lensing from a CMB S4-like experiment.…”
Section: Improvements With Cmb Lensingmentioning
confidence: 99%
“…• Inclusion of CMB lensing. We build on [32] and [33] and ask whether CMB lensing helps with calibrating photo-z Gaussian uncertainties and outliers for LSST.…”
Section: Introductionmentioning
confidence: 99%