Even shorter quantum circuit for phase estimation on early fault-tolerant quantum computers with applications to ground-state energy estimation

• URL: http://arxiv.org/abs/2211.11973v2
• Date: Sun, 10 Mar 2024 21:53:59 GMT
• Title: Even shorter quantum circuit for phase estimation on early fault-tolerant quantum computers with applications to ground-state energy estimation
• Authors: Zhiyan Ding and Lin Lin
• Abstract summary: We develop a phase estimation method with a distinct feature. The total cost of the algorithm satisfies the Heisenberg-limited scaling $widetildemathcalO(epsilon-1)$. Our algorithm may significantly reduce the circuit depth for performing phase estimation tasks on early fault-tolerant quantum computers.
• Score: 5.746732081406236
• License: http://creativecommons.org/licenses/by/4.0/
• 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 $\widetilde{\mathcal{O}}(\epsilon^{-1})$. 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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