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.
Website: http://tensorly.org/quantum/
Source-code: https://github.com/tensorly/quantum
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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