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The first AI simulation of a black hole
Published online by Cambridge University Press: 29 March 2021
Abstract
We report the results from our ongoing pilot investigation of the use of deep learning techniques for forecasting the state of turbulent flows onto black holes. Deep neural networks seem to learn well black hole accretion physics and evolve the accretion flow orders of magnitude faster than traditional numerical solvers, while maintaining a reasonable accuracy for a long time.
- Type
- Contributed Papers
- Information
- Proceedings of the International Astronomical Union , Volume 15 , Symposium S359: Galaxy Evolution and Feedback across Different Environments , March 2019 , pp. 329 - 333
- Copyright
- © The Author(s), 2021. Published by Cambridge University Press on behalf of International Astronomical Union
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