1. Optimizing single-photon generation and storage with machine learning
- Author
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Min Xiao, Miao Cai, Keyu Xia (夏可宇), and Yanqing Lu (陆延青)
- Subjects
Physics ,Quantum network ,Photon ,business.industry ,Interface (computing) ,media_common.quotation_subject ,Process (computing) ,Fidelity ,Quantum information processing ,Machine learning ,computer.software_genre ,Quantum system ,Artificial intelligence ,business ,Wave function ,computer ,media_common - Abstract
Single photons are at the heart of quantum information processing. The tasks of generating and storing single photons with arbitrary wave-packet shapes are crucial for building quantum networks, but they remain challenging. Here, we present a general machine learning (ML) algorithm with a self-adaptive process to optimize the control of a cavity-atom system for these tasks. This ML algorithm shows high efficiency and fidelity for both generation and storage of single photons. This ML-enhanced single-photon interface may pave the way for building flexible and reliable quantum networks because this ML algorithm can automatically adjust the quantum system according to single-photon wave functions in an ``intelligent'' way.
- Published
- 2021
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