The package provides an implementation of TTN-VQC to corroborate our theoretical work.
git clone https://github.com/uwjunqi/TTN-VQC.git
cd TTN-VQC
The main dependencies include pytorch, pennylane. To download and install tc:
git clone https://github.com/uwjunqi/Pytorch-Tensor-Train-Network.git
cd Pytorch-Tensor-Train-Network
python setup.py install
reg_add_noise.py: generate noisy image data
reg_ttn_vqc.py: the implementation of TTN-VQC model
reg_pca_vqc.py: the implementation of PCA-VQC model
This package is related to our papers
[1] Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen, Min-Hsiu Hsieh, "Theoretical Error Performance Analysis for Variational Quantum Circuit Based Functional Regression," npj Quantum Information, Nature Publishing Group UK London, Vol. 9, no. 4, 2023
[2] Jun Qi, Chao-Han Huck Yang, Pin-Yu Chen, "QTN-VQC: An End-to-End Learning Framework for Quantum Neural Networks," Physica Scripta, Vol. 99, no. 1, pp. 015111, 2023