An Improved Implementation Approach for Quantum Phase Estimation on Quantum Computers
Abstract
Quantum phase estimation (QPE) is one of the core algorithms for quantum computing. It has been extensively studied and applied in a variety of quantum applications such as the Shor's factoring algorithm, quantum sampling algorithms and the calculation of the eigenvalues of unitary matrices. The QPE algorithm has been combined with Kitaev's algorithm and the inverse quantum Fourier transform (IQFT) which are utilized as a fundamental component of such quantum algorithms. In this paper, we explore the computational challenges of implementing QPE algorithms on noisy intermediate-scale quantum (NISQ) machines using the IBM Q Experience (e.g., the IBMQX4, 5-qubit quantum computing hardware platform). Our experimental results indicate that the accuracy of finding the phase using these QPE algorithms is severely constrained by the NISQ computer's physical characteristics such as coherence time and error rates. To mitigate these physical limitations, we propose implementing a modified solution by reducing the number of controlled rotation gates and phase shift operations, thereby increasing the accuracy of the finding phase in near-term quantum computers.
Cite
@article{arxiv.1910.11696,
title = {An Improved Implementation Approach for Quantum Phase Estimation on Quantum Computers},
author = {Hamed Mohammadbagherpoor and Young-Hyun Oh and Patrick Dreher and Anand Singh and Xianqing Yu and Andy J. Rindos},
journal= {arXiv preprint arXiv:1910.11696},
year = {2019}
}
Comments
This paper will be published in IEEE International Conference on Rebooting Computing (ICRC 2019). arXiv admin note: substantial text overlap with arXiv:1903.07605