Predicting With Quantum Circuits

This is the project we presented in IBMQ Hackathon Taiwan. In this event, teams were assigned to a specific topic that dealt with real applications of IMBQ machine, including quantum games, QAOA, Quantum Walks, and even optimization of stock investments. We wanted to impletement VQE in predicting Flock Energies in the first place by following the IBMQ documents. However my team want to add quantum machine learning to our project, we thus tried to combine QNN and VQE. We implemented and evaluated five different hybrid models in predicting MNIST datasets. The final combination QNN and VQE was left to future works.

• Implemented 4qubit‑Ry gate circuits in predicting MNIST dataset with the learning curve converged after ten iterations.

• Analized the potential in predicting molecular ground state energies with Quantum LSTM Meta‑Learner and VQE.