AI-assisted hyper-dimensional broadband quantum memory with efficiency above 90% in warm atoms
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arXiv
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| Main Authors: | , , , , , , |
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| Format: | Preprint |
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2025
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| _version_ | 1866918133870100480 |
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| author | Wu, Zeliang Guo, Jinxian Yu, Zhifei Huang, Wenfeng Yuan, Chun-Hua Zhang, Weiping Chen, L. Q. |
| author_facet | Wu, Zeliang Guo, Jinxian Yu, Zhifei Huang, Wenfeng Yuan, Chun-Hua Zhang, Weiping Chen, L. Q. |
| contents | High-dimensional broadband quantum memory significantly expands quantum information processing capabilities, but the memory efficiency becomes insufficient when extended to high dimensions. We demonstrate an efficient quantum memory for hyper-dimensional photons encoded with orbital angular momentum (OAM) and spin angular momentum (SAM). OAM information is encoded from -5 to +5, combined with SAM encoding, enabling up to 22 dimensions. To ensure high memory efficiency, an artificial intelligence algorithm, a modified Differential Evolution (DE) algorithm using Chebyshev sampling, is developed to obtain a perfect signal-control waveform matching. Memory efficiency is experimentally achieved at 92% for single-mode Gaussian signal, 91% for information dimension of 6 and 80% for dimensional number to 22. The fidelity is achieved up to 99% for single-mode Gaussian signal, 95.5% for OAM information, 97.4% for SAM information, and 92% for whole hyper-dimensional signal, which is far beyond no-cloning limitation. Our results demonstrate superior performance and potential applications in high-dimensional quantum information processing. This achievement provides a crucial foundation for future quantum communication and quantum computing. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_11098 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | AI-assisted hyper-dimensional broadband quantum memory with efficiency above 90% in warm atoms Wu, Zeliang Guo, Jinxian Yu, Zhifei Huang, Wenfeng Yuan, Chun-Hua Zhang, Weiping Chen, L. Q. Quantum Physics High-dimensional broadband quantum memory significantly expands quantum information processing capabilities, but the memory efficiency becomes insufficient when extended to high dimensions. We demonstrate an efficient quantum memory for hyper-dimensional photons encoded with orbital angular momentum (OAM) and spin angular momentum (SAM). OAM information is encoded from -5 to +5, combined with SAM encoding, enabling up to 22 dimensions. To ensure high memory efficiency, an artificial intelligence algorithm, a modified Differential Evolution (DE) algorithm using Chebyshev sampling, is developed to obtain a perfect signal-control waveform matching. Memory efficiency is experimentally achieved at 92% for single-mode Gaussian signal, 91% for information dimension of 6 and 80% for dimensional number to 22. The fidelity is achieved up to 99% for single-mode Gaussian signal, 95.5% for OAM information, 97.4% for SAM information, and 92% for whole hyper-dimensional signal, which is far beyond no-cloning limitation. Our results demonstrate superior performance and potential applications in high-dimensional quantum information processing. This achievement provides a crucial foundation for future quantum communication and quantum computing. |
| title | AI-assisted hyper-dimensional broadband quantum memory with efficiency above 90% in warm atoms |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2503.11098 |