MORE

This repo is the code used to produce the results presented in "MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification".

Content

• MORE_clustering.py implements the first step of MORE, which involves translating classical labels into quantum labels. It utilizes the variational quantum clustering algorithm to capture interclass correlations.
• MORE_classification.py implements the second step of MORE, aimed at enhancing model performance. It performs quantum label-based supervised learning to learn data patterns from the training dataset.
• myNeuralNetworkClassifier_1.py and myNeuralNetworkClassifier_2.py are tailored QNN classifiers designed for the respective steps 1 and 2 of MORE.
• myBloch.py implements the customized Bloch sphere visualization.
• baseline_binary.py, baseline_mul_ancilla.py, and baseline_mul_subset.py construct classifiers serving as baseline methods within this study.
• model.py provides the functions of constructing circuits for quantum NN models.
• data_helper.py includes the functions for data processing.
• util.py contains the functions for recording intermediate results.

Contact

If there is any question, please send emails to jwu21@wm.edu.

Citation

If you use this code in your work, please cite our paper.

@article{wu2023more,
  title={MORE: Measurement and Correlation Based Variational Quantum Circuit for Multi-classification},
  author={Wu, Jindi and Hu, Tianjie and Li, Qun},
  journal={arXiv preprint arXiv:2307.11875},
  year={2023}
}