线性非单元动力学的量子算法,其对所有参数的依赖性接近最优

Dong An, Andrew M. Childs, Lin Lin
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引用次数: 0

摘要

我们引入了一系列标识,将一般线性非单元演化算子表示为单元演化算子的线性组合,每个算子都求解一个哈密顿模拟问题。这种表述可以指数级地提高最近引入的哈密顿模拟线性组合(LCHS)方法的精度[An, Liu, and Lin, PhysicalReview Letters, 2023]。这种方法首次使量子算法在求解线性微分方程时,既能获得最佳的状态准备成本,又能在所有参数的矩阵查询中获得接近最优的缩放。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantum algorithm for linear non-unitary dynamics with near-optimal dependence on all parameters
We introduce a family of identities that express general linear non-unitary evolution operators as a linear combination of unitary evolution operators, each solving a Hamiltonian simulation problem. This formulation can exponentially enhance the accuracy of the recently introduced linear combination of Hamiltonian simulation (LCHS) method [An, Liu, and Lin, Physical Review Letters, 2023]. For the first time, this approach enables quantum algorithms to solve linear differential equations with both optimal state preparation cost and near-optimal scaling in matrix queries on all parameters.
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