Ultra-stable and high-performance squeezed vacuum source enabled via artificial intelligence control.

Authors

Jie Zhao, Zhifei Yu, Xin Chen, Yuan Wu, Xinyun Liang, Wenfeng Huang, Keye Zhang, Chun-Hua Yuan, L Q Chen

Published in

Science advances. Volume 11. Issue 18. Pages eadu4888. May 02, 2025. Epub May 02, 2025.

Abstract

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.

PMID:
40315327
Bibliographic data and abstract were imported from PubMed on 03 May 2025.

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