Machine learning cosmic backreaction and its effects on observations
Abstract
Symbolic expressions for cosmic backreaction and mean redshift drift in a range of 2-region models in terms of average quantities are presented. The demonstration that these expressions can be obtained constitutes the opening of a new avenue towards understanding the effects of cosmic backreaction in our universe: With a symbolic expression for the redshift drift at hand, the redshift drift can be used to constrain cosmological parameters including the large-scale expansion rate and backreaction. In addition, by introducing symbolic expressions for cosmic backreaction, this quantity can be constrained with observations such as redshift-distance measures.
Cite
@article{arxiv.2305.01224,
title = {Machine learning cosmic backreaction and its effects on observations},
author = {S. M. Koksbang},
journal= {arXiv preprint arXiv:2305.01224},
year = {2023}
}
Comments
6 pages, 3 captioned figures. Accepted for publication in PRL. v2: Updated reference list. No other changes