Estimation of Waveguide Eigenmodes Based on Subspace-Search Variational Quantum Algorithm

The variational quantum eigensolver (VQE), a variational algorithm to approximate the ground state of the given Hamiltonian, is the leading candidate for receiving quantum advantage on noisy intermediate-scale quantum (NISQ) devices. The eigenmode analysis within waveguides, a canonical problem in e...

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Bibliographic Details
Published in:IEEE microwave and wireless technology letters (Print) 2024-10, Vol.34 (10), p.1139-1142
Main Authors: Miao, Zhuo-Wei, Meng, Fanxu
Format: Article
Language:English
Subjects:
Algorithms
Cost analysis
Cost function
Eigenvalue problem
Eigenvalues
Estimation
Finite difference method
Hamiltonian functions
Logic gates
Orthogonality
Quantum circuit
Qubits (quantum computing)
Stationary state
subspace search
Subspaces
Transmission line matrix methods
variational quantum eigensolver (VQE)
waveguide modes
Waveguides
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Summary:The variational quantum eigensolver (VQE), a variational algorithm to approximate the ground state of the given Hamiltonian, is the leading candidate for receiving quantum advantage on noisy intermediate-scale quantum (NISQ) devices. The eigenmode analysis within waveguides, a canonical problem in electromagnetics, can be reformulated as an eigenvalue problem adopting the finite difference method. Therefore, in this work, a subspace-search-based VQE is applied for the computation of the eigenmodes. The proposed algorithm has the promise to show exponential efficiency outperforming over the classical algorithms. Compared with the existing counterparts, our work makes the additional orthogonality constrain unnecessary in the cost function, meantime, avoids the costly inner product evaluation in the cost function, where a few number of ancillary qubits and deeper quantum circuits are indispensable. Comprehensive experimental results show that the proposed framework significantly provides more accurate eigenmode estimation with fewer iterations and shows more favorable resource efficiency.
ISSN:2771-957X
2771-9588
DOI:10.1109/LMWT.2024.3440058