TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch.
- Website: http://tensorly.org/quantum/
- Source-code: https://github.com/tensorly/quantum
- If TensorLy-Quantum is useful in your research, please cite us at: https://arxiv.org/abs/2112.10239
With TensorLy-Quantum, you can easily:
- Create large quantum circuit: Tensor network formalism requires up to exponentially less memory for quantum simulation than traditional vector and matrix approaches.
- Leverage tensor methods: the state vectors are efficiently represented in factorized form as Tensor-Rings (MPS) and the operators as TT-Matrices (MPO)
- Efficient simulation: tensorly-quantum leverages the factorized structure to efficiently perform quantum simulation without ever forming the full, dense operators and state-vectors
- Multi-Basis Encoding: we provide multi-basis encoding out-of-the-box for scalable experimentation
- Solve hard problems: we provide all the tools to solve the MaxCut problem for an unprecendented number of qubits / vertices
pip install tensorly-quantum
git clone https://github.com/tensorly/quantum cd quantum pip install -e .