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Constructing an optimal mixer for Quantum Approximate Optimization Algorithm (QAOA) Hamiltonian is crucial for enhancing the performance of QAOA in solving combinatorial optimization problems.
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2022
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X. Liu, R. Shaydulin, and I. Safro, "Quantum approximate optimization algorithm with sparsified phase operator," in 2022 IEEE International Conference on Quantum Computing and Engineering (QCE)
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L. Zhu, H. Lun Tang, F. A. Calderon-Vargas, N. Mayhall, E. Barnes, and S. Economou, "Adaptive quantum approximate optimization algorithm for solving combinatorial problems on a quantum computer," Phys. Rev. Research
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2023
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J. K. Golden, A. Bärtschi, D. O’Malley, and S. Eidenbenz, "Numerical Evidence for Exponential Speed-Up of QAOA over Unstructured Search for Approximate Constrained Optimization," in 2023 IEEE International Conference on Quantum Computing and Engineering (QCE)
2022
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2022
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2022
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2023
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2023
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D. Herman, C. Googin, X. Liu, Y. Sun, A. Galda, I. Safro, M. Pistoia, and Y. Alexeev, "Quantum computing for finance," Nature Reviews Physics
2023
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K. Okada, H. Nishi, T. Kosugi, and Y. Matsushita, "Systematic study on the dependence of the warm-start quantum approximate optimization algorithm on approximate solutions," Scientific Reports
2024
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