Revisiting the distance duality relation using a non-parametric regression method
Akshay Rana, Deepak Jain, Shobhit Mahajan, Amitabha Mukherjee

TL;DR
This paper tests the distance duality relation in cosmology using a non-parametric regression method, finding no evidence of deviation from the standard relation up to high redshift, thus supporting current cosmological models.
Contribution
It introduces a model-independent non-parametric approach (LOESS with SIMEX) to test the distance duality relation using diverse observational data.
Findings
No deviation from η=1 within 1σ up to z=2.418
Method effectively reconstructs η(z) without assuming a cosmological model
Consistent with standard cosmological assumptions
Abstract
The interdependence of luminosity distance, and angular diameter distance, given by the distance duality relation (DDR) is very significant in observational cosmology. It is very closely tied with the temperature- redshift relation of Cosmic Microwave Background (CMB) radiation. Any deviation from indicates a possible emergence of new physics. Our aim in this work is to check the consistency of these relations using a non-parametric regression method namely, LOESS with SIMEX. This technique avoids dependency on the cosmological model and works with a minimal set of assumptions. Further, to analyze the efficiency of the methodology, we simulate a dataset of points of data based on a phenomenological model . The error on the simulated data points is obtained by using the temperature of CMB…
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