synergy-between-noisy-quantum-computers-and-scalable-classical-deep-learning-for-error-mitigation
Science Score: 26.0%
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- Host: GitHub
- Owner: simonecantori
- Language: Python
- Default Branch: main
- Size: 120 KB
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Created about 2 years ago
· Last pushed almost 2 years ago
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Citation
README.md
Synergy between noisy quantum computers and scalable classical deep learning for quantum error mitigation
This folder contains data from the article referenced above. The data are related to the plots in Fig.7 and Fig.8. It also includes the angles of the quantum circuits and the indices of the physical qubits. They can be used as input features for the neural network.
The loader.py file is used to load these data. The circgen.py file is used to simulate new quantum circuits. The cnn2D.py file includes the two-dimensional convolutional neural network used in this work.
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- Login: simonecantori
- Kind: user
- Repositories: 1
- Profile: https://github.com/simonecantori