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Title: Neural network reconstruction of cosmology using the Pantheon compilation
Authors: Dialektopoulos, Konstantinos F.
Mukherjee, Purba
Said, Jackson
Mifsud, Jurgen
Keywords: Cosmology -- Research
Neural networks (Computer science)
Statistical astronomy
Issue Date: 2023
Publisher: Springer
Citation: Dialektopoulos, K. F., Mukherjee, P., Said, J. L., & Mifsud, J. (2023). Neural network reconstruction of cosmology using the Pantheon compilation. The European Physical Journal C, 83(10), 956.
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
ISSN: 14346052
Appears in Collections:Scholarly Works - InsSSA

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