Cosmological Constraints with Clustering-Based Redshifts

Understand

We demonstrate that observations lacking reliable redshift information, such as photometric and radio continuum surveys, can produce robust measurements of cosmological parameters when empowered by clustering-based redshift estimation.

• This method infers the redshift distribution based on the spatial clustering of sources, using cross-correlation with a reference dataset with known redshifts.
• Applying this method to the existing SDSS photometric galaxies, and projecting to future radio continuum surveys, we show that sources can be efficiently divided into several redshift bins, increasing their ability to constrain cosmological parameters.
• We forecast constraints on the dark-energy equation-of-state and on local non-gaussianity parameters.