Qualitative probe of interacting dark energy with redshift-space distortions

TL;DR

This study explores how interacting dark energy affects redshift-space distortions and emphasizes the importance of including IDE dynamics in galaxy bias modeling to accurately detect IDE signatures.

Contribution

It introduces a method to incorporate IDE dynamics into galaxy biases and demonstrates their impact on redshift-space distortion measurements.

Findings

Neglecting IDE dynamics can produce artefacts in RSD signals.

Multi-tracer analysis is necessary to reduce cosmic variance effects.

RSDs can constrain IDE models at redshifts up to 1.

Abstract

The imprint of interacting dark energy (IDE) needs to be correctly identified in order to avoid bias in constraints on IDE. This paper investigates the large-scale imprint of IDE in redshift space distortions, using $Euclid$-like photometric prescriptions. A first attempt at incorporating the IDE dynamics in the galaxy (clustering and evolution) biases is made. Without IDE dynamics taken into account in the galaxy biases, as is conventionally done, the results suggest that for a constant dark energy equation of state parameter, an IDE model where the dark energy transfer rate is proportional to the dark energy density exhibits an alternating, positive-negative effect in the redshift space distortions angular power spectrum. However, when the IDE dynamics is incorporated in the galaxy biases, it is found that the apparent positive-negative alternating effect vanishes: implying that neglecting IDE dynamics in the galaxy biases can result in ''artefacts'' that can lead to incorrect identification of the IDE imprint. In general, the results show that multi-tracer analysis will be needed to beat down cosmic variance in order for the redshift space distortions angular power spectrum as a statistic to be a viable diagnostic of IDE. Moreover, it is found that redshift space distortions hold the potential to constrain IDE on large scales, at redshifts $z \,{\leq}\, 1$; with the scenario having IDE dynamics incorporated in the biases showing better potential.