Zhao Jie, Yu Zhifei, Chen Xin, Wu Yuan, Liang Xinyun, Huang Wenfeng, Zhang Keye, Yuan Chun-Hua, Chen L Q
State Key Laboratory of Precision Spectroscopy, Quantum Institute for Light and Atoms, Department of Physics and Electronic Science, East China Normal University, Shanghai 200062, China.
School of Physics, Hefei University of Technology, Hefei, Anhui 230009, China.
Sci Adv. 2025 May 2;11(18):eadu4888. doi: 10.1126/sciadv.adu4888.
Squeezing states are crucial for advancing quantum metrology beyond the classical limit. Despite this, generating high-performance squeezed light with long-term stability remains a challenge due to system complexity and quantum fragility. We experimentally achieved a record-breaking squeezing level of 4.3 decibels (lossless, 5.9 decibels) using polarization self-rotation (PSR) in atomic vapor, maintaining stability for hours despite environmental disturbances. Overcoming the limitations of the PSR theory model's optimization guidance, which arises from the mutual interference of multiple parameters at this squeezing level, we developed an artificial intelligence (AI) control (AIC) system that harnesses deep learning to discern and manage these complex relationships, thereby enabling self-adapted to external environments. This integrated approach represents a concrete step for the actual application of quantum metrology and information processing, illustrating the synergy between AI and fundamental science in breaking complexity constraints.
压缩态对于推动量子计量学超越经典极限至关重要。尽管如此，由于系统复杂性和量子脆弱性，生成具有长期稳定性的高性能压缩光仍然是一项挑战。我们通过在原子蒸气中使用偏振自旋转（PSR）实验实现了4.3分贝（无损时为5.9分贝）的破纪录压缩水平，尽管存在环境干扰，仍保持了数小时的稳定性。克服了PSR理论模型优化指导的局限性，该局限性源于在此压缩水平下多个参数的相互干扰，我们开发了一种人工智能（AI）控制（AIC）系统，利用深度学习来识别和管理这些复杂关系，从而实现对外部环境的自适应。这种集成方法代表了量子计量学和信息处理实际应用的具体一步，说明了人工智能与基础科学在打破复杂性限制方面的协同作用。
