Testing the Cosmic Distance Duality Relation Using Strong Gravitational Lensing Time Delays and Type Ia Supernovae

TL;DR

This study tests the cosmic distance duality relation by combining strong gravitational lensing time delays and Type Ia supernovae data, finding no significant violations and confirming the relation's robustness.

Contribution

It introduces an ANN-based method to reconstruct supernova distances and tests multiple DDR violation parameterizations with a combined dataset.

Findings

No significant evidence for DDR violations across parameterizations

ANN approach effectively bridges SGL and SNe Ia datasets

Results reinforce the validity of the cosmic distance duality relation

Abstract

We present a comprehensive test of the cosmic distance duality relation (DDR) using a combination of strong gravitational lensing (SGL) time delay measurements and Type Ia supernovae (SNe Ia) data. We investigate three different parameterizations of potential DDR violations. To bridge the gap between SGL and SNe Ia datasets, we implement an artificial neural network (ANN) approach to reconstruct the distance modulus of SNe Ia. Our analysis uniquely considers both scenarios where the absolute magnitude of SNe Ia ($M_B$) is treated as a free parameter and where it is fixed to a Cepheid-calibrated value. Using a sample of six SGL systems and the Pantheon+ SNe Ia dataset, we find no statistically significant evidence for DDR violations across all parameterizations. The consistency of our findings across different parameterizations not only reinforces confidence in the standard DDR but also demonstrates the robustness of our analytical approach.