arXiv · 2305.15500
Neural network reconstruction of scalar-tensor cosmology
Abstract
Neural networks have shown great promise in providing a data-first approach to exploring new physics. In this work, we use the full implementation of late time cosmological data to reconstruct a number of scalar-tensor cosmological models within the context of neural network systems. In this pipeline, we incorporate covariances in the data in the neural network training algorithm, rather than a likelihood which is the approach taken in Markov chain Monte Carlo analyses. For general subclasses of classic scalar-tensor models, we find stricter bounds on functional models which may help in the understanding of which models are observationally viable.
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Konstantinos F. Dialektopoulos, Purba Mukherjee, Jackson Levi Said, Jurgen Mifsud. 2023-05-24. Neural network reconstruction of scalar-tensor cosmology. https://arxiv.org/abs/2305.15500
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