Hybrid quantum-classical algorithms enhance optimization problems by leveraging quantum computing's ability to explore complex solution spaces efficiently, while utilizing classical computing for tasks that require robust numerical methods. These algorithms, such as the Variational Quantum Eigensolver (VQE) and Quantum Approximate Optimization Algorithm (QAOA), combine quantum circuits with classical optimization to solve problems more effectively than classical methods alone.

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