A PyTorch-based framework for Quantum Classical Simulation, Quantum Machine Learning, Quantum Neural Networks, Parameterized Quantum Circuits with support for easy deployments on real quantum computers. Researchers on quantum algorithm design, parameterized quantum circuit training, quantum optimal control, quantum machine learning, and quantum neural networks. Dynamic computation graph, automatic gradient computation, fast GPU support, batch model terrorized processing.
Features
- Easy construction and simulation of quantum circuits in PyTorch
- Dynamic computation graph for easy debugging
- Gradient support via autograd
- Batch mode inference and training on CPU/GPU
- Easy deployment on real quantum devices such as IBMQ
- Easy hybrid classical-quantum model construction
Project Samples
License
MIT LicenseFollow TorchQuantum
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