Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators
Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states wi...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Springer Science and Business Media LLC
2024
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| Online Access: | https://hdl.handle.net/1721.1/155553 |
| _version_ | 1824458221799079936 |
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| author | Lin, Joshua Luo, Di Yao, Xiaojun Shanahan, Phiala E. |
| author2 | Massachusetts Institute of Technology. Center for Theoretical Physics |
| author_facet | Massachusetts Institute of Technology. Center for Theoretical Physics Lin, Joshua Luo, Di Yao, Xiaojun Shanahan, Phiala E. |
| author_sort | Lin, Joshua |
| collection | MIT |
| description | Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed. |
| first_indexed | 2024-09-23T13:26:05Z |
| format | Article |
| id | mit-1721.1/155553 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2025-02-19T04:22:27Z |
| publishDate | 2024 |
| publisher | Springer Science and Business Media LLC |
| record_format | dspace |
| spelling | mit-1721.1/1555532025-01-07T04:39:22Z Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators Lin, Joshua Luo, Di Yao, Xiaojun Shanahan, Phiala E. Massachusetts Institute of Technology. Center for Theoretical Physics Ab-initio simulations of multiple heavy quarks propagating in a Quark-Gluon Plasma are computationally difficult to perform due to the large dimension of the space of density matrices. This work develops machine learning algorithms to overcome this difficulty by approximating exact quantum states with neural network parametrisations, specifically Neural Density Operators. As a proof of principle demonstration in a QCD-like theory, the approach is applied to solve the Lindblad master equation in the 1 + 1d lattice Schwinger Model as an open quantum system. Neural Density Operators enable the study of in-medium dynamics on large lattice volumes, where multiple-string interactions and their effects on string-breaking and recombination phenomena can be studied. Thermal properties of the system at equilibrium can also be probed with these methods by variationally constructing the steady state of the Lindblad master equation. Scaling of this approach with system size is studied, and numerical demonstrations on up to 32 spatial lattice sites and with up to 3 interacting strings are performed. 2024-07-09T20:19:57Z 2024-07-09T20:19:57Z 2024-06-28 2024-07-07T03:10:55Z Article http://purl.org/eprint/type/JournalArticle 1029-8479 https://hdl.handle.net/1721.1/155553 Lin, J., Luo, D., Yao, X. et al. Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators. J. High Energ. Phys. 2024, 211 (2024). PUBLISHER_CC en 10.1007/jhep06(2024)211 Journal of High Energy Physics Creative Commons Attribution https://creativecommons.org/licenses/by/4.0/ The Author(s) application/pdf Springer Science and Business Media LLC Springer Berlin Heidelberg |
| spellingShingle | Lin, Joshua Luo, Di Yao, Xiaojun Shanahan, Phiala E. Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title | Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title_full | Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title_fullStr | Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title_full_unstemmed | Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title_short | Real-time dynamics of the Schwinger model as an open quantum system with Neural Density Operators |
| title_sort | real time dynamics of the schwinger model as an open quantum system with neural density operators |
| url | https://hdl.handle.net/1721.1/155553 |
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