Quantum algorithm for matrix functions by Cauchy's integral formula

S. Takahira, A. Ohashi, T. Sogabe, T. Usuda
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引用次数: 10

Abstract

For matrix A, vector b and function f, the computation of vector f(A)b arises in many scientific computing applications. We consider the problem of obtaining quantum state |f> corresponding to vector f(A)b. There is a quantum algorithm to compute state |f> using eigenvalue estimation that uses phase estimation and Hamiltonian simulation e^{\im A t}. However, the algorithm based on eigenvalue estimation needs \poly(1/\epsilon) runtime, where \epsilon is the desired accuracy of the output state. Moreover, if matrix A is not Hermitian, \e^{\im A t} is not unitary and we cannot run eigenvalue estimation. In this paper, we propose a quantum algorithm that uses Cauchy's integral formula and the trapezoidal rule as an approach that avoids eigenvalue estimation. We show that the runtime of the algorithm is \poly(\log(1/\epsilon)) and the algorithm outputs state |f> even if A is not Hermitian.
用柯西积分公式求解矩阵函数的量子算法
对于矩阵A、向量b和函数f,在许多科学计算应用中都会出现向量f(A)b的计算。我们考虑了获得与向量f(A)b对应的量子态|f>的问题。有一种量子算法使用相位估计和哈密顿模拟e^ {\im at的特征值估计来计算状态|f>。}然而,基于特征值估计的算法需要\poly (1/ \epsilon)运行时,其中\epsilon是输出状态的期望精度。此外,如果矩阵A不是厄米矩阵,\e ^ {\im A t}不是酉的,我们不能运行特征值估计。本文提出了一种利用柯西积分公式和梯形规则来避免特征值估计的量子算法。我们证明了算法的运行时间为\poly (\log (1/ \epsilon)),即使A不是厄米数,算法也输出状态|f>。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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