IBM Qiskit2021–2022
Quantum Machine Learning Replication Study
Expressibility of parameterized quantum circuits and QNN classification accuracy via Qiskit
Summary
End-to-end replication of PQC expressibility and QNN classification accuracy studies using Qiskit Machine Learning and PyTorch.
Challenge
Qiskit lacked integrated ML tooling; bridging quantum circuits and classical optimizers required new infrastructure.
Contribution
Built full replication pipeline using Qiskit TorchConnector; reproduced expressibility plots and classification accuracy within 5% error.
Outcome
Demonstrated Qiskit as a viable end-to-end QML platform; contributed to Qiskit community documentation and GitHub.
