Deep learning bulk spacetime from boundary optical conductivity
Abstract We employ a deep learning method to deduce the bulk spacetime from boundary optical conductivity. We apply the neural ordinary differential equation technique, tailored for continuous functions such as the metric, to the typical class of holographic condensed matter models featuring broken...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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SpringerOpen
2024-03-01
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| Series: | Journal of High Energy Physics |
| Subjects: | |
| Online Access: | https://doi.org/10.1007/JHEP03(2024)141 |
| _version_ | 1797233836866666496 |
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| author | Byoungjoon Ahn Hyun-Sik Jeong Keun-Young Kim Kwan Yun |
| author_facet | Byoungjoon Ahn Hyun-Sik Jeong Keun-Young Kim Kwan Yun |
| author_sort | Byoungjoon Ahn |
| collection | DOAJ |
| description | Abstract We employ a deep learning method to deduce the bulk spacetime from boundary optical conductivity. We apply the neural ordinary differential equation technique, tailored for continuous functions such as the metric, to the typical class of holographic condensed matter models featuring broken translations: linear-axion models. We successfully extract the bulk metric from the boundary holographic optical conductivity. Furthermore, as an example for real material, we use experimental optical conductivity of UPd2Al3, a representative of heavy fermion metals in strongly correlated electron systems, and construct the corresponding bulk metric. To our knowledge, our work is the first illustration of deep learning bulk spacetime from boundary holographic or experimental conductivity data. |
| first_indexed | 2024-04-24T16:22:30Z |
| format | Article |
| id | doaj.art-88e3b0273b1d41649cc629e3659811f2 |
| institution | Directory Open Access Journal |
| issn | 1029-8479 |
| language | English |
| last_indexed | 2024-04-24T16:22:30Z |
| publishDate | 2024-03-01 |
| publisher | SpringerOpen |
| record_format | Article |
| series | Journal of High Energy Physics |
| spelling | doaj.art-88e3b0273b1d41649cc629e3659811f22024-03-31T11:09:00ZengSpringerOpenJournal of High Energy Physics1029-84792024-03-012024313010.1007/JHEP03(2024)141Deep learning bulk spacetime from boundary optical conductivityByoungjoon Ahn0Hyun-Sik Jeong1Keun-Young Kim2Kwan Yun3Department of Physics and Photon Science, Gwangju Institute of Science and TechnologyInstituto de Física Teórica UAM/CSICDepartment of Physics and Photon Science, Gwangju Institute of Science and TechnologyDepartment of Physics and Photon Science, Gwangju Institute of Science and TechnologyAbstract We employ a deep learning method to deduce the bulk spacetime from boundary optical conductivity. We apply the neural ordinary differential equation technique, tailored for continuous functions such as the metric, to the typical class of holographic condensed matter models featuring broken translations: linear-axion models. We successfully extract the bulk metric from the boundary holographic optical conductivity. Furthermore, as an example for real material, we use experimental optical conductivity of UPd2Al3, a representative of heavy fermion metals in strongly correlated electron systems, and construct the corresponding bulk metric. To our knowledge, our work is the first illustration of deep learning bulk spacetime from boundary holographic or experimental conductivity data.https://doi.org/10.1007/JHEP03(2024)141Holography and Condensed Matter Physics (AdS/CMT)Gauge-Gravity Correspondence |
| spellingShingle | Byoungjoon Ahn Hyun-Sik Jeong Keun-Young Kim Kwan Yun Deep learning bulk spacetime from boundary optical conductivity Journal of High Energy Physics Holography and Condensed Matter Physics (AdS/CMT) Gauge-Gravity Correspondence |
| title | Deep learning bulk spacetime from boundary optical conductivity |
| title_full | Deep learning bulk spacetime from boundary optical conductivity |
| title_fullStr | Deep learning bulk spacetime from boundary optical conductivity |
| title_full_unstemmed | Deep learning bulk spacetime from boundary optical conductivity |
| title_short | Deep learning bulk spacetime from boundary optical conductivity |
| title_sort | deep learning bulk spacetime from boundary optical conductivity |
| topic | Holography and Condensed Matter Physics (AdS/CMT) Gauge-Gravity Correspondence |
| url | https://doi.org/10.1007/JHEP03(2024)141 |
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