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Artificial neural network in cosmic landscape. (English) Zbl 1383.85016
Summary: We propose that artificial neural network, the basis of machine learning, is useful to generate the inflationary landscape from a cosmological point of view. Traditional numerical simulations of a global cosmic landscape typically need an exponential complexity when the number of fields is large. However, a basic application of artificial neural network could solve the problem based on the universal approximation theorem of the multilayer perceptron. A toy model in inflation with multiple light fields is investigated numerically as an example of such an application.

85A40 Cosmology
83C45 Quantization of the gravitational field
83F05 Cosmology
62P35 Applications of statistics to physics
83D05 Relativistic gravitational theories other than Einstein’s, including asymmetric field theories
Full Text: DOI
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