arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2002.12508quant-phcs.NAmath.NA
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近最佳基态制备

Near-optimal ground state preparation

Lin Lin, Yu Tong

摘要:

准备给定哈密顿量的基态并估计其基态能量是重要的但计算困难的任务。然而,如果有一些额外的信息,这些问题可以在量子计算机上有效地解决。我们假设可以有效地制备与基态具有非平凡重叠的初始态,并且基态能量和第一激发能之间的光谱间隙从下面被限制。有了这些假设,我们设计了一个算法,准备的基态时,地面能量的上限是已知的,其运行时间有一个对数依赖于逆误差。当这样的上限未知时,我们提出了一种混合量子经典算法来估计基态能量,其中与[Ge et al. 2019]中提出的当前最先进的算法相比,查询数量对初始状态对所需精度的依赖性呈指数级改善。这两种算法可以结合起来准备一个基态,而不需要知道基态能量的上限。我们还将其应用于非结构化搜索问题和量子近似计数问题,证明了我们的算法达到了复杂度下限。

英文摘要:

Preparing the ground state of a given Hamiltonian and estimating its ground energy are important but computationally hard tasks. However, given some additional information, these problems can be solved efficiently on a quantum computer. We assume that an initial state with non-trivial overlap with the ground state can be efficiently prepared, and the spectral gap between the ground energy and the first excited energy is bounded from below. With these assumptions we design an algorithm that prepares the ground state when an upper bound of the ground energy is known, whose runtime has a logarithmic dependence on the inverse error. When such an upper bound is not known, we propose a hybrid quantum-classical algorithm to estimate the ground energy, where the dependence of the number of queries to the initial state on the desired precision is exponentially improved compared to the current state-of-the-art algorithm proposed in [Ge et al. 2019]. These two algorithms can then be combined to prepare a ground state without knowing an upper bound of the ground energy. We also prove that our algorithms reach the complexity lower bounds by applying it to the unstructured search problem and the quantum approximate counting problem.

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