Abstract
Abstract
We propose a realistic hybrid classical-quantum linear solver to solve systems of linear equations of a specific type, and demonstrate its feasibility with Qiskit on IBM Q systems. This algorithm makes use of quantum random walk that runs in $${\bf{O}}$$
O
(N log(N)) time on a quantum circuit made of $${\bf{O}}$$
O
(log(N)) qubits. The input and output are classical data, and so can be easily accessed. It is robust against noise, and ready for implementation in applications such as machine learning.
Funder
Ministry of Science and Technology, Taiwan
Publisher
Springer Science and Business Media LLC
Reference78 articles.
1. Nielsen, M. A. & Chuang, I. L. Quantum Computation and Quantum Information: 10th Anniversary Edition. 10th edn. (Cambridge University Press, New York, NY, USA, 2011).
2. Golub, G. H. & Van Loan, C. F. Matrix Computations (3rd Ed.). (Johns Hopkins University Press, Baltimore, MD, USA, 1996).
3. Saad, Y. Iterative Methods for Sparse Linear Systems. 2nd edn. (Society for Industrial and Applied Mathematics, Philadelphia, PA, USA, 2003).
4. Harrow, A. W., Hassidim, A. & Lloyd, S. Quantum algorithm for linear systems of equations. Phys. Rev. Lett. 103, 150502,
https://doi.org/10.1103/PhysRevLett.103.150502
(2009).
5. Clader, B. D., Jacobs, B. C. & Sprouse, C. R. Preconditioned quantum linear system algorithm. Phys. Rev. Lett. 110, 250504,
https://doi.org/10.1103/PhysRevLett.110.250504
(2013).
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