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Tensor-Based Quantum Machine Learning

Project description

TensorLy-Quantum is a Python library for Tensor-Based Quantum Machine Learning that builds on top of TensorLy and PyTorch.

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

Installing TensorLy-Quantum

Through pip

pip install tensorly-quantum

From source

git clone https://github.com/tensorly/quantum
cd quantum
pip install -e .

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