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Experimental quantum natural gradient optimization in photonics
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DOI：10.1364/OL.494560.png)
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Variational quantum algorithms (VQAs) combining the advantages of parameterized quantum circuits and clas-sical optimizers, promise practical quantum applications in the noisy intermediate-scale quantum era. The perfor-mance of VQAs heavily depends on the optimization method. Compared with gradient-free and ordinary gradient descent methods, the quantum natural gradient (QNG), which mir-rors the geometric structure of the parameter space, can achieve faster convergence and avoid local minima more easily, thereby reducing the cost of circuit executions. We uti-lized a fully programmable photonic chip to experimentally estimate the QNG in photonics for the first time, to the best of our knowledge. We obtained the dissociation curve of the He-H+ cation and achieved chemical accuracy, verifying the outperformance of QNG optimization on a photonic device. Our work opens up a vista of utilizing QNG in photonics to implement practical near-term quantum applications.& COPY; 2023 Optica Publishing Group
Keyword:
EIGENSOLVER
期刊
IF:
3.3
论文数:
4.0W
被引数:
7.6W
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引用论文
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