Testing the speed of light over cosmological distances: the combination of strongly lensed and unlensed supernova Ia
Shuo Cao, Jingzhao Qi, Marek Biesiada, Xiaogang Zheng, Tengpeng Xu,, and Zong-Hong Zhu

TL;DR
This paper proposes a novel method to measure the speed of light over cosmological distances using strongly lensed supernovae Ia, potentially testing variations in fundamental constants with future surveys like LSST.
Contribution
It introduces an original approach combining gravitational lensing and supernova observations to estimate the speed of light at different redshifts, which has not been explored before.
Findings
Predicted constraints on Δc/c at the level of 10^{-3} with LSST data.
Demonstrated the feasibility of using lensed SNe Ia to test for variations in fundamental constants.
Discussed the potential of future surveys to detect hypothetical changes in the speed of light.
Abstract
Probing the speed of light is as an important test of General Relativity but the measurements of using objects in the distant universe have been almost completely unexplored. In this letter, we propose an idea to use the multiple measurements of galactic-scale strong gravitational lensing systems with type Ia supernova acting as background sources to estimate the speed of light. This provides an original method to measure the speed of light using objects located at different redshifts which emitted their light in a distant past. Moreover, we predict that strongly lensed SNe Ia observed by the LSST would produce robust constraints on at the level of . We also discuss whether the future surveys such as LSST may succeed in detecting any hypothetical variation of predicted by theories in which fundamental constants have dynamical nature.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
