Matrix Product State Pre-Training for Quantum Machine Learning

Understand

Hybrid Quantum-Classical algorithms are a promising candidate for developing uses for NISQ devices.

• In particular, Parametrised Quantum Circuits (PQCs) paired with classical optimizers have been used as a basis for quantum chemistry and quantum optimization problems.
• Training PQCs relies on methods to overcome the fact that the gradients of PQCs vanish exponentially in the size of the circuits used.
• Tensor network methods are being increasingly used as a classical machine learning tool, as well as a tool for studying quantum systems.