Combining spectroscopic and photometric surveys using angular cross-correlations II: Parameter constraints from different physical effects

TL;DR

This paper assesses how combining various physical effects and observables in spectroscopic and photometric galaxy surveys enhances constraints on dark energy and growth parameters, emphasizing the importance of multi-probe analysis.

Contribution

It provides a detailed forecast on the impact of including different physical effects and approximations on parameter constraints, guiding survey optimization.

Findings

Weak lensing increases FoM by 4.8

Redshift Space Distortions increase FoM by 2.1

Baryon Acoustic Oscillations increase FoM by 1.3

Abstract

Future spectroscopic and photometric surveys will measure accurate positions and shapes of an increasing number of galaxies. In the previous paper of this series we studied the effects of Redshift Space Distortions (RSD), baryon acoustic oscillations (BAO) and Weak gravitational Lensing (WL) using angular cross-correlation. Here, we provide a new forecast that explores the contribution of including different observables, physical effects (galaxy bias, WL, RSD, BAO) and approximations (non-linearities, Limber approximation, covariance between probes). The radial information is included by using the cross-correlation of separate narrow redshift bins. For the auto correlation the separation of galaxy pairs is mostly transverse, while the cross-correlations also includes a radial component. We study how this information adds to our figure of merit (FoM), which includes the dark energy equation of state $w(z)$ and the growth history, parameterized by $\gamma$. We show that the Limber approximation and galaxy bias are the most critical ingredients to the modelling of correlations. Adding WL increases our FoM by 4.8, RSD by 2.1 and BAO by 1.3. We also explore how overlapping surveys perform under the different assumption and for different figures of merit. Our qualitative conclusions depend on the survey choices and scales included, but we find some clear tendencies that highlight the importance of combining different probes and can be used to guide and optimise survey strategies.