quantum-machine-learning-metallurgy

This code is used in our paper titled "Designing complex concentrated alloys with quantum machine learning and text mining". It consists of tools for (i) data preprocessing, (ii) quantum SVM, and (iii) data postprocessing.

data preprocessing

The data files and Python script can be found in folder data_preprocessing. Simply run

python prepare-test-data-alloy-design.py

This will generate a file named "test-TM-2864.csv" for the training of quantum SVM models.

quantum SVM

The quantum SVM model is trained using both quantum simulator BasicAer and IBM quantum computers. This can be achieved by following the steps in QuantumSVM-HEA.ipynb, or submit it as a remote job with qsvm-HEA.py.

The python script request qiskit, pandas, numpy, etc. Please create a conda enviroment (say quantum) and install these packages before using the script.

Please also install jupyter notebook inside the conda environment if you want to use the interactive .ipynb file. Then activate the environment and start playing.

conda activate quantum
jupyter notebook QuantumSVM-HEA.ipynb

data postprcessing

Please follow the README.md file in the sub-directory simulator_data_process for data post processing.