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arXiv 1909.05074quant-ph
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关于变分量子本征求解器的自然梯度

On the natural gradient for variational quantum eigensolver

Naoki Yamamoto

摘要:

变分量子本征求解器是一种由量子态驱动和经典参数优化相结合的混合算法,用于求解给定哈密顿量的基态。自然梯度法是一种考虑参数空间几何结构的优化方法。最近,Stokes等人发展了将自然梯度用于变分量子本征求解器的一般方法。本文给出了这种优化方法的一些简单的实例,详细地说明了自然梯度优化器是如何利用几何性质来改变和改进普通梯度法的。

英文摘要:

The variational quantum eigensolver is a hybrid algorithm composed of quantum state driving and classical parameter optimization, for finding the ground state of a given Hamiltonian. The natural gradient method is an optimization method taking into account the geometric structure of the parameter space. Very recently, Stokes et al. developed the general method for employing the natural gradient for the variational quantum eigensolver. This paper gives some simple case-studies of this optimization method, to see in detail how the natural gradient optimizer makes use of the geometric property to change and improve the ordinary gradient method.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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