Hybrid Algorithm

Hybrid quantum-classical algorithms split computation between a quantum processor (QPU) and a classical processor. The QPU prepares and measures quantum states; the classical processor processes the measurement results and updates parameters for the next quantum circuit execution. This design allows running meaningful quantum computations on NISQ hardware, which cannot run arbitrarily deep circuits due to noise. VQE and QAOA are the canonical hybrid algorithms: the QPU evaluates the energy or cost function, and a classical optimizer (COBYLA, gradient descent) updates the circuit parameters. The quantum-classical loop continues until convergence. Hybrid approaches shift some computational burden to classical hardware, making them more noise-tolerant than fully quantum algorithms like QPE. Most useful near-term quantum algorithms follow this hybrid paradigm.