Single-atom exploration of optimized nonequilibrium quantum thermodynamics by reinforcement learning

• Published in: Communications physics Vol. 6; no. 1; pp. 286 - 8
• Main Authors: Zhang, Jiawei, Li, Jiachong, Tan, Qing-Shou, Bu, Jintao, Yuan, Wenfei, Wang, Bin, Ding, Geyi, Ding, Wenqiang, Chen, Liang, Yan, Leilei, Su, Shilei, Xiong, Taiping, Zhou, Fei, Feng, Mang
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 07.10.2023; Nature Publishing Group; Nature Portfolio
• Subjects: 639/766/483/481; 639/766/530/951; Accuracy; Algorithms; Calcium isotopes; Consumption; Data processing; Entropy; Evolution; Machine learning; Nonequilibrium thermodynamics; Physics; Physics and Astronomy; Quantum phenomena; Qubits (quantum computing); Spontaneous emission; Thermodynamics

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 40 Ca + ion, for engineering qua...