A Joint Analysis for Cosmology and Photometric Redshift Calculation Using Cross Correlations

Abstract

We present a method of calibrating the properties of photometric redshift bins as part of a larger Markov Chain Monte Carlo (MCMC) analysis for the inference of cosmological parameters. The redshift bins are characterised by their mean and variance, which are varied as free parameters and marginalised over when obtaining the cosmological parameters. We demonstrate that the likelihood function for cross-correlations in an angular power spectrum framework tightly constrains the properties of bins such that they may be well determined, reducing their influence on cosmological parameters and avoiding the bias from poorly estimated redshift distributions. We demonstrate that even with only three photometric and three spectroscopic bins, we can recover accurate estimates of the mean redshift of a bin to within $\Delta \mu \approx 3-4\times 10^{-3}$ and the width of the bin to $\Delta \sigma \approx 1\times 10^{-3}$ for galaxies near $z=1$. This indicates that we may be able to bring down the photometric redshift errors to a level which is in line with the requirements for the next generation of cosmological experiments.

12 Pages, 6 figures

References in corpus (5)

• Calibrating Redshift Distributions Beyond Spectroscopic Limits with Cross-Correlations
• Cosmological baryonic and matter densities from 600,000 SDSS Luminous Red Galaxies with photometric redshifts
• Reconstructing Redshift Distributions with Cross-Correlations: Tests and an Optimized Recipe
• Photometric redshifts: estimating their contamination and distribution using clustering information
• Determining neutrino properties using future galaxy redshift surveys