ISW-LSS cross-correlation in coupled Dark Energy models with massive neutrinos

TL;DR

This paper analyzes the ISW-LSS cross-correlation in coupled Dark Energy models with massive neutrinos, comparing theoretical predictions with observations and exploring future survey capabilities for model discrimination.

Contribution

It provides a comprehensive analysis of the ISW effect in coupled Dark Energy models with neutrinos, including bias rescaling, and assesses future survey prospects for distinguishing models.

Findings

Discrepancies between models and ΛCDM grow with redshift.

Current data cannot distinguish coupled models from ΛCDM.

Upcoming surveys will improve model discrimination through tomographic analysis.

Abstract

We provide an exhaustive analysis of the Integrated Sach-Wolfe effect (ISW) in the context of coupled Dark Energy cosmologies where a component of massive neutrinos is also present. We focus on the effects of both the coupling between Dark Matter and Dark Energy and of the neutrino mass on the cross-correlation between galaxy/quasar distributions and ISW effect. We provide a simple expression to appropriately rescale the galaxy bias when comparing different cosmologies. Theoretical predictions of the cross-correlation function are then compared with observational data. We find that, while it is not possible to distinguish among the models at low redshifts, discrepancies between coupled models and $\Lambda$CDM increase with $z$. In spite of this, current data alone seems not able to distinguish between coupled models and $\Lambda$CDM. However, we show that upcoming galaxy surveys will permit tomographic analysis which allow to better discriminate among the models. We discuss the effects on cross-correlation measurements of ignoring galaxy bias evolution, b(z), and magnification bias correction and provide fitting formulae for b(z) for the cosmologies considered. We compare three different tomographic schemes and investigate how the expected signal to noise ratio, snr, of the ISW-LSS cross-correlation changes when increasing the number of tomographic bins. The dependence of snr on the area of the survey and the survey shot noise is also discussed.