https://doi.org/10.1140/epjc/s10052-023-11781-8
Regular Article - Theoretical Physics
Analysis of black hole solutions in parabolic class using neural networks
1
Department of Signal Theory and Communications, Research Group GRAM, University of Alcalá, Alcalá de Henares, Madrid, Spain
2
Department of Mathematics and Statistics, Memorial University of Newfoundland, St John’s, NL, Canada
a ehsan.hatefi@uah.es, ehsanhatefi@gmail.com
Received:
12
March
2023
Accepted:
28
June
2023
Published online:
15
July
2023
In this paper, we introduce a numerical method based on Artificial Neural Networks (ANNs) for the analysis of black hole solutions to the Einstein-axion-dilaton system in a high dimensional parabolic class. Leveraging a profile root-finding technique based on General Relativity we describe an ANN solver to directly tackle the system of ordinary differential equations. Through our extensive numerical analysis, we demonstrate, for the first time, that there is no self-similar critical solution for the parabolic class in the high dimensions of space-time. Specifically, we develop 95% ANN-based confidence intervals for all the solutions in their domains. At the 95% confidence level, our ANN estimators confirm that there is no black hole solution in higher dimensions, hence the gravitational collapse does not occur. Results provide some doubts about the universality of the Choptuik phenomena. Therefore, we conclude that the fastest-growing mode of the perturbations that determine the critical exponent does not exist for the parabolic class in the high dimensions.
© The Author(s) 2023
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