Strong lensing modeling in galaxy clusters as a promising method to test cosmography I. Parametric dark energy models
Juan Magana, Ana Acebron, Veronica Motta, Tomas Verdugo, Eric Jullo,, Marceau Limousin

TL;DR
This study uses strong lensing data from galaxy clusters to constrain dark energy models, demonstrating the method's potential while highlighting the importance of reducing systematic uncertainties for precise cosmological measurements.
Contribution
The paper introduces a methodology for constraining dark energy models using strong lensing in galaxy clusters, validated with both real and simulated data, and assesses the impact of modeling uncertainties.
Findings
Constraints on $w(z)$ are consistent with other cosmological probes.
Larger positional errors reduce systematic bias in parameter estimation.
Strong lensing in galaxy clusters is a promising tool for cosmography.
Abstract
In this paper we probe five cosmological models for which the dark energy equation of state parameter, , is parameterized as a function of redshift using strong lensing data in the galaxy cluster Abell 1689. We constrain the parameters of the functions by reconstructing the lens model under each one of these cosmologies with strong lensing measurements from two galaxy clusters: Abell 1689 and a mock cluster, Ares, from the Hubble Frontier Fields Comparison Challenge, to validate our methodology. To quantify how the cosmological constraints are biased due to systematic effects in the strong lensing modeling, we carry out three runs considering the following uncertainties for the multiple images positions: 0.25", 0.5", and 1.0". With Ares, we find that larger errors decrease the systematic bias on the estimated cosmological parameters. With real data, our strong-lensing…
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