Gravitational Duals from Equations of State
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866909753923338240 |
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| author | Bea, Yago Jimenez, Raul Mateos, David Liu, Shuheng Protopapas, Pavlos Tarancón-Álvarez, Pedro Tejerina-Pérez, Pablo |
| author_facet | Bea, Yago Jimenez, Raul Mateos, David Liu, Shuheng Protopapas, Pavlos Tarancón-Álvarez, Pedro Tejerina-Pérez, Pablo |
| contents | Holography relates gravitational theories in five dimensions to four-dimensional quantum field theories in flat space. Under this map, the equation of state of the field theory is encoded in the black hole solutions of the gravitational theory. Solving the five-dimensional Einstein's equations to determine the equation of state is an algorithmic, direct problem. Determining the gravitational theory that gives rise to a prescribed equation of state is a much more challenging, inverse problem. We present a novel approach to solve this problem based on physics-informed neural networks. The resulting algorithm is not only data-driven but also informed by the physics of the Einstein's equations. We successfully apply it to theories with crossovers, first- and second-order phase transitions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2403_14763 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Gravitational Duals from Equations of State Bea, Yago Jimenez, Raul Mateos, David Liu, Shuheng Protopapas, Pavlos Tarancón-Álvarez, Pedro Tejerina-Pérez, Pablo High Energy Physics - Theory Cosmology and Nongalactic Astrophysics Artificial Intelligence Machine Learning General Relativity and Quantum Cosmology Holography relates gravitational theories in five dimensions to four-dimensional quantum field theories in flat space. Under this map, the equation of state of the field theory is encoded in the black hole solutions of the gravitational theory. Solving the five-dimensional Einstein's equations to determine the equation of state is an algorithmic, direct problem. Determining the gravitational theory that gives rise to a prescribed equation of state is a much more challenging, inverse problem. We present a novel approach to solve this problem based on physics-informed neural networks. The resulting algorithm is not only data-driven but also informed by the physics of the Einstein's equations. We successfully apply it to theories with crossovers, first- and second-order phase transitions. |
| title | Gravitational Duals from Equations of State |
| topic | High Energy Physics - Theory Cosmology and Nongalactic Astrophysics Artificial Intelligence Machine Learning General Relativity and Quantum Cosmology |
| url | https://arxiv.org/abs/2403.14763 |