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arXiv 2205.02520quant-ph
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基于高阶Trotter分解的改进量子计算

Improved Quantum Computing with the Higher-order Trotter Decomposition

Xiaodong Yang, Xinfang Nie, Yunlan Ji, Tao Xin, Dawei Lu, Jun Li

摘要:

在设计量子控制时,通常需要用经典计算机模拟受控系统的演化。然而,计算时间演化算子可能是相当消耗资源的,因为总哈密顿量通常难以对角化。在本文中,我们通过用它们的Trotter分解替换时间演化段来缓解这个问题,这将传播子减少到单量子比特操作和固定时间系统演化的组合。由此产生的过程可以提供相当大的速度增益与传播误差的可接受的成本。作为示范,我们应用所提出的策略,以提高效率的梯度上升脉冲工程算法搜索最优控制领域。此外,我们表明,高阶Trotter分解可以提供有效的Ansätze变分量子算法,从而提高性能,解决基态问题。这里提出的策略也适用于许多其他量子优化和模拟任务。

英文摘要:

In designing quantum control, it is generally required to simulate the controlled system evolution with a classical computer. However, computing the time evolution operator can be quite resource-consuming since the total Hamiltonian is often hard to diagonalize. In this paper, we mitigate this issue by substituting the time evolution segments with their Trotter decompositions, which reduces the propagator into a combination of single-qubit operations and fixed-time system evolutions. The resulting procedure can provide substantial speed gain with acceptable costs in the propagator error. As a demonstration, we apply the proposed strategy to improve the efficiency of the gradient ascent pulse engineering algorithm for searching optimal control fields. Furthermore, we show that the higher-order Trotter decompositions can provide efficient Ansätze for the variational quantum algorithm, leading to improved performance in solving the ground-state problem. The strategy presented here is also applicable for many other quantum optimization and simulation tasks.

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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