Machine-Learning-Enhanced Quantum Optical Storage in Solids

Autor:	Lei, Yisheng, An, Haechan, Li, Zongfeng, Hosseini, Mahdi
Rok vydání:	2024
Předmět:	Quantum Physics
Druh dokumentu:	Working Paper
Popis:	Quantum memory devices with high storage efficiency and bandwidth are essential elements for future quantum networks. Solid-state quantum memories can provide broadband storage, but they primarily suffer from low storage efficiency. We use passive optimization and machine learning techniques to demonstrate nearly a 6-fold enhancement in quantum memory efficiency. In this regime, we demonstrate coherent and single-photon-level storage with a high signal-to-noise ratio. The optimization technique presented here can be applied to most solid-state quantum memories to significantly improve the storage efficiency without compromising the memory bandwidth. Comment: 5 pages, 3 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.04200 Zobrazit plný text záznamu View this record from Arxiv