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arXiv 1910.14596quant-phcs.NAmath.NA
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基于最优多项式的量子本征态滤波及其在求解量子线性系统中的应用

Optimal polynomial based quantum eigenstate filtering with application to solving quantum linear systems

Lin Lin, Yu Tong

摘要:

提出了一种基于量子信号处理(QSP)和极大极小多项式的量子本征态滤波算法。该算法允许我们有效地准备一个给定的哈密顿量的目标本征态,如果我们有机会获得一个初始状态与非平凡的重叠与目标本征态,并有一个合理的下限的谱隙。将该算法应用于量子线性系统问题(QLSP),分别提出了基于量子绝热计算(AQC)和基于量子Zeno效应的两种算法。这两种算法准备的最终解决方案作为一个纯粹的状态,并实现了接近最佳的$\mathcal{\widetilde{O}}(dκ\log(1/ε))$查询复杂度为$d$稀疏矩阵,其中$κ$是条件数,和$ε$是所需的精度。这两种算法都不使用相位估计或幅度放大。

英文摘要:

We present a quantum eigenstate filtering algorithm based on quantum signal processing (QSP) and minimax polynomials. The algorithm allows us to efficiently prepare a target eigenstate of a given Hamiltonian, if we have access to an initial state with non-trivial overlap with the target eigenstate and have a reasonable lower bound for the spectral gap. We apply this algorithm to the quantum linear system problem (QLSP), and present two algorithms based on quantum adiabatic computing (AQC) and quantum Zeno effect respectively. Both algorithms prepare the final solution as a pure state, and achieves the near optimal $\mathcal{\widetilde{O}}(dκ\log(1/ε))$ query complexity for a $d$-sparse matrix, where $κ$ is the condition number, and $ε$ is the desired precision. Neither algorithm uses phase estimation or amplitude amplification.

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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