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Feedback-based quantum strategies for constrained combinatorial optimization problems
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DOI：10.1016/j.future.2025.107979.png)
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Abstract
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• Feedback-based quantum algorithms are extended to handle invalid configuration constraints. • We introduce a conversion from constrained to unconstrained optimization problems. • As an alternative strategy, Lyapunov-based update laws are proposed for circuit parameters. • Folded spectrum and deflation techniques are used to design the new update laws. • Our approach reduces quantum resources by lowering circuit depth and qubit count.
Keywords:
Variational quantum algorithms
Feedback-based quantum algorithms
Quadratic constrained binary optimization problems
Noisy-intermediate scale quantum algorithms
Folded spectrum method
Hotelling’s deflation method
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