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European Physical Journal C: Particles and Fields
Article . 2023 . Peer-reviewed
License: CC BY
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https://dx.doi.org/10.48550/ar...
Article . 2023
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Analysis of black hole solutions in parabolic class using neural networks

Authors: Hatefi, Ehsan; Hatefi, Armin; López Sastre, Roberto Javier;

Analysis of black hole solutions in parabolic class using neural networks

Abstract

AbstractIn 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.

Country
Spain
Keywords

High Energy Physics - Theory, Telecomunicaciones, FOS: Physical sciences, QC770-798, General Relativity and Quantum Cosmology (gr-qc), Mathematical Physics (math-ph), Computational Physics (physics.comp-ph), Astrophysics, General Relativity and Quantum Cosmology, QB460-466, High Energy Physics - Theory (hep-th), Nuclear and particle physics. Atomic energy. Radioactivity, Physics - Data Analysis, Statistics and Probability, Telecommunication, Physics - Computational Physics, Mathematical Physics, Data Analysis, Statistics and Probability (physics.data-an)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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