Classical feedback-based optimization matches or exceeds quantum performance in speed and scalability while quantum retains an edge in final solution quality on tested instances.
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HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.
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Feedback-based quantum optimization and its classical counterpart: quantum advantage and the power of classical algorithms
Classical feedback-based optimization matches or exceeds quantum performance in speed and scalability while quantum retains an edge in final solution quality on tested instances.
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Hybrid Real-Imaginary Time Evolution for Low-Depth Hamiltonian Simulation in Quantum Optimization
HAVQDS achieves higher approximation ratios on 6-14 qubit SK instances than adiabatic or CD methods while cutting CNOT counts by 1-2 orders of magnitude.