A Stochastic Approach to Reconstructing the Speed of Light in Cosmology
Cheng-Yu Zhang, Wei Hong, Yu-Chen Wang, Tong-Jie Zhang

TL;DR
This paper employs Gaussian processes to reconstruct the redshift-dependent speed of light using cosmological data, comparing multiple models and constraining their parameters to assess the viability of varying speed of light theories.
Contribution
It introduces a stochastic Gaussian process-based method to reconstruct $c(z)$ from observational data and compares three VSL models, providing new parameter constraints.
Findings
Barrow's VSL model is inconsistent with data.
CPL VSL model fits the data well under certain conditions.
Constant $c$ model also aligns with observations.
Abstract
The Varying Speed of Light (VSL) model describes how the speed of light in a vacuum changes with cosmological redshift. Despite numerous models, there is little observational evidence for this variation. While the speed of light can be accurately measured by physical means, cosmological methods are rarely used. Previous studies quantified the speed of light at specific redshifts using Gaussian processes and reconstructed the redshift-dependent function . It is crucial to quantify the speed of light across varying redshifts. We use the latest data on angular diameter distances and Hubble parameters from baryon acoustic oscillation (BAO) and cosmic chronometer measurements in the redshift interval . The speed of light is determined using Gaussian and deep Gaussian processes to reconstruct , , and . Furthermore,…
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Taxonomy
TopicsCosmology and Gravitation Theories · Relativity and Gravitational Theory
