On low-depth algorithms for quantum phase estimation

Hongkang Ni1, Haoya Li2, and Lexing Ying2,1

1Institute for Computational and Mathematical Engineering, Stanford University, Stanford, CA 94305
2Department of Mathematics, Stanford University, Stanford, CA 94305

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Quantum phase estimation is one of the critical building blocks of quantum computing. For early fault-tolerant quantum devices, it is desirable for a quantum phase estimation algorithm to (1) use a minimal number of ancilla qubits, (2) allow for inexact initial states with a significant mismatch, (3) achieve the Heisenberg limit for the total resource used, and (4) have a diminishing prefactor for the maximum circuit length when the overlap between the initial state and the target state approaches one. In this paper, we prove that an existing algorithm from quantum metrology can achieve the first three requirements. As a second contribution, we propose a modified version of the algorithm that also meets the fourth requirement, which makes it particularly attractive for early fault-tolerant quantum devices.

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Cited by

[1] Qiyao Liang, Yiqing Zhou, Archismita Dalal, and Peter Johnson, "Modeling the performance of early fault-tolerant quantum algorithms", Physical Review Research 6 2, 023118 (2024).

[2] Yongdan Yang, Ying Li, Xiaosi Xu, and Xiao Yuan, "Resource-efficient quantum-classical hybrid algorithm for energy gap evaluation", Physical Review A 109 5, 052416 (2024).

[3] Hongkang Ni, Haoya Li, and Lexing Ying, "Quantum Hamiltonian Learning for the Fermi-Hubbard Model", Acta Applicandae Mathematicae 191 1, 2 (2024).

[4] Haoya Li, Hongkang Ni, and Lexing Ying, "Adaptive low-depth quantum algorithms for robust multiple-phase estimation", Physical Review A 108 6, 062408 (2023).

[5] Zhiyan Ding and Lin Lin, "Even Shorter Quantum Circuit for Phase Estimation on Early Fault-Tolerant Quantum Computers with Applications to Ground-State Energy Estimation", PRX Quantum 4 2, 020331 (2023).

[6] Amara Katabarwa, Katerina Gratsea, Athena Caesura, and Peter D. Johnson, "Early Fault-Tolerant Quantum Computing", arXiv:2311.14814, (2023).

[7] Guoming Wang, Daniel Stilck França, Ruizhe Zhang, Shuchen Zhu, and Peter D. Johnson, "Quantum algorithm for ground state energy estimation using circuit depth with exponentially improved dependence on precision", Quantum 7, 1167 (2023).

[8] Haoya Li, Yu Tong, Hongkang Ni, Tuvia Gefen, and Lexing Ying, "Heisenberg-limited Hamiltonian learning for interacting bosons", arXiv:2307.04690, (2023).

[9] Akash Kundu, "Reinforcement learning-assisted quantum architecture search for variational quantum algorithms", arXiv:2402.13754, (2024).

[10] Zhiyan Ding and Lin Lin, "Simultaneous estimation of multiple eigenvalues with short-depth quantum circuit on early fault-tolerant quantum computers", Quantum 7, 1136 (2023).

[11] Arjun Mirani and Patrick Hayden, "Learning interacting fermionic Hamiltonians at the Heisenberg limit", arXiv:2403.00069, (2024).

[12] Changhao Yi, Cunlu Zhou, and Jun Takahashi, "Quantum Phase Estimation by Compressed Sensing", arXiv:2306.07008, (2023).

[13] Jacob S. Nelson and Andrew D. Baczewski, "An assessment of quantum phase estimation protocols for early fault-tolerant quantum computers", arXiv:2403.00077, (2024).

The above citations are from Crossref's cited-by service (last updated successfully 2024-05-25 02:07:46) and SAO/NASA ADS (last updated successfully 2024-05-25 02:07:47). The list may be incomplete as not all publishers provide suitable and complete citation data.