Quantum Circuit Parameters Learning with Gradient Descent Using Backpropagation

Understand

Quantum computing has the potential to outperform classical computers and is expected to play an active role in various fields.

• In quantum machine learning, a quantum computer has been found useful for enhanced feature representation and high dimensional state or function approximation.
• Quantum-Classical hybrid algorithms are proposed in recent years for this purpose under the Noisy-Intermediate Scale Quantum computer (NISQ) environment.
• Under this scheme, the role played by classical computer is the parameter tuning, parameter optimization, and parameter update for the quantum circuit.