An Implementation of Classical-to-Quantum Transfer Learning Algorithm with an Illustration of Quantum Dots
Our codes include the experiments of PCA+VQC, Pre-ResNet18+VQC, and Pre-ResNet50+VQC for charge stability diagrams for Quantum Dots
The main dependencies include pytorch and torchquantum
pip3 install torchquantum
git clone https://gitlab.com/QMAI/mlqe_2023_edx.git
python Pre-ResNet+VQC.py --num_qubits=8 --test_kind='rep' --model_kind='ResNet18'
python Pre-ResNet+VQC.py --num_qubits=8 --test_kind='gen' --model_kind='ResNet18'
python Pre-ResNet+VQC.py --num_qubits=8 --test_kind='rep' --model_kind='ResNet50'
python PCA+VQC.py --num_qubits=8 --test_kind='rep'
python PCA+VQC.py --num_qubits=8 --test_kind='gen'
python PCA+VQC.py --num_qubits=8 --test_kind='gen'
python Pre-ResNet_nn.py --num_qubits=8 --test_kind='rep'
python Pre-ResNet_nn.py --num_qubits=8 --test_kind='gen'