Neural network reconstruction of cosmology using the Pantheon compilation

Konstantinos F. Dialektopoulos, Purba Mukherjee, Jackson Levi Said, Jurgen Mifsud
5/24/2023
gr-qcastro-ph.COcs.LG

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Abstract

In this work, we reconstruct the Hubble diagram using various data sets, including correlated ones, in Artificial Neural Networks (ANN). Using ReFANN, that was built for data sets with independent uncertainties, we expand it to include non-Guassian data points, as well as data sets with covariance matrices among others. Furthermore, we compare our results with the existing ones derived from Gaussian processes and we also perform null tests in order to test the validity of the concordance model of cosmology.

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Cite this paper

@article{dialektopoulos2023neural,
  title  = {Neural network reconstruction of cosmology using the Pantheon compilation},
  author = {Konstantinos F. Dialektopoulos and Purba Mukherjee and Jackson Levi Said and Jurgen Mifsud},
  year   = {2023},
  eprint = {2305.15499},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2305.15499v2}
}

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