Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning
Abstract Exploring optimized processes of thermodynamics at microscale is vital to exploitation of quantum advantages relevant to microscopic machines and quantum information processing. Here, we experimentally execute a reinforcement learning strategy, using a single trapped 40Ca+ ion, for engineer...
| Main Authors: | , , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2023-10-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-023-01408-5 |
| _version_ | 1827710645906178048 |
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| author | Jiawei Zhang Jiachong Li Qing-Shou Tan Jintao Bu Wenfei Yuan Bin Wang Geyi Ding Wenqiang Ding Liang Chen Leilei Yan Shilei Su Taiping Xiong Fei Zhou Mang Feng |
| author_facet | Jiawei Zhang Jiachong Li Qing-Shou Tan Jintao Bu Wenfei Yuan Bin Wang Geyi Ding Wenqiang Ding Liang Chen Leilei Yan Shilei Su Taiping Xiong Fei Zhou Mang Feng |
| author_sort | Jiawei Zhang |
| collection | DOAJ |
| description | Abstract Exploring optimized processes of thermodynamics at microscale is vital to exploitation of quantum advantages relevant to microscopic machines and quantum information processing. Here, we experimentally execute a reinforcement learning strategy, using a single trapped 40Ca+ ion, for engineering quantum state evolution out of thermal equilibrium. We consider a qubit system coupled to classical and quantum baths, respectively, the former of which is achieved by switching on the spontaneous emission relevant to the qubit and the latter of which is made based on a Jaynes-Cummings model involving the qubit and the vibrational degree of freedom of the ion. Our optimized operations make use of the external control on the qubit, designed by the reinforcement learning approach. In comparison to the conventional situation of free evolution subject to the same Hamiltonian of interest, our experimental implementation presents the evolution of the states with higher fidelity while with less consumption of entropy production and work, highlighting the potential of reinforcement learning in accomplishment of optimized nonequilibrium thermodynamic processes at atomic level. |
| first_indexed | 2024-03-10T17:41:45Z |
| format | Article |
| id | doaj.art-70d188dc6c7b49589a3f2217439e15ba |
| institution | Directory Open Access Journal |
| issn | 2399-3650 |
| language | English |
| last_indexed | 2024-03-10T17:41:45Z |
| publishDate | 2023-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Physics |
| spelling | doaj.art-70d188dc6c7b49589a3f2217439e15ba2023-11-20T09:39:34ZengNature PortfolioCommunications Physics2399-36502023-10-01611810.1038/s42005-023-01408-5Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learningJiawei Zhang0Jiachong Li1Qing-Shou Tan2Jintao Bu3Wenfei Yuan4Bin Wang5Geyi Ding6Wenqiang Ding7Liang Chen8Leilei Yan9Shilei Su10Taiping Xiong11Fei Zhou12Mang Feng13Research Center for Quantum Precision Measurement, Guangzhou Institute of Industry TechnologyResearch Center for Quantum Precision Measurement, Guangzhou Institute of Industry TechnologyKey Laboratory of Hunan Province on Information Photonics and Freespace Optical Communication, College of Physics and Electronics, Hunan Institute of Science and TechnologyState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of SciencesState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of SciencesState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of SciencesState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of SciencesState Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, Wuhan Institute of Physics and Mathematics, Innovation Academy of Precision Measurement Science and Technology, Chinese Academy of SciencesResearch Center for Quantum Precision Measurement, Guangzhou Institute of Industry TechnologySchool of Physics, Zhengzhou UniversitySchool of Physics, Zhengzhou UniversityKey Laboratory of Quantum Information Technology, Guilin University of Electronic TechnologyResearch Center for Quantum Precision Measurement, Guangzhou Institute of Industry TechnologyResearch Center for Quantum Precision Measurement, Guangzhou Institute of Industry TechnologyAbstract Exploring optimized processes of thermodynamics at microscale is vital to exploitation of quantum advantages relevant to microscopic machines and quantum information processing. Here, we experimentally execute a reinforcement learning strategy, using a single trapped 40Ca+ ion, for engineering quantum state evolution out of thermal equilibrium. We consider a qubit system coupled to classical and quantum baths, respectively, the former of which is achieved by switching on the spontaneous emission relevant to the qubit and the latter of which is made based on a Jaynes-Cummings model involving the qubit and the vibrational degree of freedom of the ion. Our optimized operations make use of the external control on the qubit, designed by the reinforcement learning approach. In comparison to the conventional situation of free evolution subject to the same Hamiltonian of interest, our experimental implementation presents the evolution of the states with higher fidelity while with less consumption of entropy production and work, highlighting the potential of reinforcement learning in accomplishment of optimized nonequilibrium thermodynamic processes at atomic level.https://doi.org/10.1038/s42005-023-01408-5 |
| spellingShingle | Jiawei Zhang Jiachong Li Qing-Shou Tan Jintao Bu Wenfei Yuan Bin Wang Geyi Ding Wenqiang Ding Liang Chen Leilei Yan Shilei Su Taiping Xiong Fei Zhou Mang Feng Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning Communications Physics |
| title | Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| title_full | Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| title_fullStr | Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| title_full_unstemmed | Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| title_short | Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| title_sort | single atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning |
| url | https://doi.org/10.1038/s42005-023-01408-5 |
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