Even Shorter Quantum Circuit for Phase Estimation on Early Fault-Tolerant Quantum Computers with Applications to Ground-State Energy Estimation

IF 9.3 Q1 PHYSICS, APPLIED PRX quantum : a Physical Review journal Pub Date : 2022-11-22 DOI:10.1103/PRXQuantum.4.020331
Zhiyan Ding, Lin Lin
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引用次数: 22

Abstract

We develop a phase estimation method with a distinct feature: its maximal runtime (which determines the circuit depth) is $\delta/\epsilon$, where $\epsilon$ is the target precision, and the preconstant $\delta$ can be arbitrarily close to $0$ as the initial state approaches the target eigenstate. The total cost of the algorithm satisfies the Heisenberg-limited scaling $\widetilde{\mathcal{O}}(\epsilon^{-1})$. This is different from all previous proposals, where $\delta \gtrsim \pi$ is required even if the initial state is an exact eigenstate. As a result, our algorithm may significantly reduce the circuit depth for performing phase estimation tasks on early fault-tolerant quantum computers. The key technique is a simple subroutine called quantum complex exponential least squares (QCELS). Our algorithm can be readily applied to reduce the circuit depth for estimating the ground-state energy of a quantum Hamiltonian, when the overlap between the initial state and the ground state is large. If this initial overlap is small, we can combine our method with the Fourier filtering method developed in [Lin, Tong, PRX Quantum 3, 010318, 2022], and the resulting algorithm provably reduces the circuit depth in the presence of a large relative overlap compared to $\epsilon$. The relative overlap condition is similar to a spectral gap assumption, but it is aware of the information in the initial state and is therefore applicable to certain Hamiltonians with small spectral gaps. We observe that the circuit depth can be reduced by around two orders of magnitude in numerical experiments under various settings.
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早期容错量子计算机相位估计的更短量子电路及其在基态能量估计中的应用
我们开发了一种具有明显特征的相位估计方法:其最大运行时间(决定电路深度)为$\delta/\epsilon$,其中$\epsilon$是目标精度,并且随着初始状态接近目标特征状态,预常数$\delta$可以任意接近$0$。该算法的总成本满足海森堡有限缩放$\widetilde{\mathcal{O}}(\epsilon^{-1})$。这与之前的所有建议不同,即使初始状态是精确的特征状态,也需要$\delta \gtrsim \pi$。因此,我们的算法可以显著减少在早期容错量子计算机上执行相位估计任务的电路深度。关键技术是一个简单的子程序,称为量子复指数最小二乘(QCELS)。当初始态和基态之间的重叠较大时,我们的算法可以很容易地用于减少估计量子哈密顿函数基态能量的电路深度。如果这个初始重叠很小,我们可以将我们的方法与[Lin, Tong, PRX Quantum 3, 010318, 2022]中开发的傅立叶滤波方法结合起来,与$\epsilon$相比,所得算法可以证明在存在较大相对重叠的情况下减少了电路深度。相对重叠条件类似于谱隙假设,但它知道初始状态的信息,因此适用于谱隙较小的某些哈密顿量。我们观察到,在各种设置下的数值实验中,电路深度可以减小约两个数量级。
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CiteScore
14.60
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