Euclid: Forecast constraints on the cosmic distance duality relation with complementary external probes

TL;DR

This paper assesses Euclid's potential to significantly tighten constraints on deviations from the distance-duality relation, a key test of fundamental cosmological assumptions, using both current data and simulated future observations.

Contribution

It introduces a comprehensive analysis combining current data and simulated Euclid data, employing both parametric and machine learning methods to improve constraints on the DDR.

Findings

Current constraints improved by a factor of 2.5

Euclid can enhance constraints by a factor of 6 with external data

Non-parametric methods see a threefold improvement

Abstract

In metric theories of gravity with photon number conservation, the luminosity and angular diameter distances are related via the Etherington relation, also known as the distance-duality relation (DDR). A violation of this relation would rule out the standard cosmological paradigm and point at the presence of new physics. We quantify the ability of Euclid, in combination with contemporary surveys, to improve the current constraints on deviations from the DDR in the redshift range $0<z<1.6$. We start by an analysis of the latest available data, improving previously reported constraints by a factor of 2.5. We then present a detailed analysis of simulated Euclid and external data products, using both standard parametric methods (relying on phenomenological descriptions of possible DDR violations) and a machine learning reconstruction using Genetic Algorithms. We find that for parametric methods Euclid can (in combination with external probes) improve current constraints by approximately a factor of six, while for non-parametric methods Euclid can improve current constraints by a factor of three. Our results highlight the importance of surveys like Euclid in accurately testing the pillars of the current cosmological paradigm and constraining physics beyond the standard cosmological model.