Bounds on a Wavefunction Overlap with Hamiltonian Eigen-states: Performance Guarantees for the Quantum Phase Estimation Algorithm

Estimating the overlap between an approximate wavefunction and a target eigenstate of the system Hamiltonian is essential for the efficiency of quantum phase estimation. In this work, we derive upper and lower bounds on this overlap using expectation values of Hamiltonian powers and bounds on target eigenenergies. The accuracy of these bounds can be systematically improved by computing higher-order Hamiltonian moments and refining eigenenergy estimates. Our method offers a practical approach to assessing initial state quality and can be implemented on both classical and quantum computers.

Publication Details

Journal
ArXiv.org
Published
2025-03-15
Primary Topic
Quantum Computing Algorithms and Architecture
Type
article
Field-Weighted Citation Impact
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article

Bounds on a Wavefunction Overlap with Hamiltonian Eigen-states: Performance Guarantees for the Quantum Phase Estimation Algorithm

ArXiv.org
Quantum Computing Algorithms and Architecture
article

Bounds on a Wavefunction Overlap with Hamiltonian Eigen-states: Performance Guarantees for the Quantum Phase Estimation Algorithm

article en

Abstract

Estimating the overlap between an approximate wavefunction and a target eigenstate of the system Hamiltonian is essential for the efficiency of quantum phase estimation. In this work, we derive upper and lower bounds on this overlap using expectation values of Hamiltonian powers and bounds on target eigenenergies. The accuracy of these bounds can be systematically improved by computing higher-order Hamiltonian moments and refining eigenenergy estimates. Our method offers a practical approach to assessing initial state quality and can be implemented on both classical and quantum computers.

ArXiv.org
Openalex Percentile: Top 73%
Quantum Computing Algorithms and Architecture
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Bounds on a Wavefunction Overlap with Hamiltonian Eigen-states: Performance Guarantees for the Quantum Phase Estimation Algorithm · ArXiv.org (2025) | TGRS Research Map | TGRS