TensorQEC

This package utilizes the tensor network to study the properties of quantum error correction(QEC). The main features include

• Incoherent Quantum error correction: In the incoherent quantum error correction scheme, finding the most likely true error from the error syndrome is a standard probabilistic inference problem on boolean variables. This problem is closely connected to tensor networks^[Ferris], which can be solved with existing tools such as TensorInference.jl. Examples are given in the following sections:
  • Inference with Tensor Network
• Coherent quantum error correction: Unlike Clifford gate, non-Clifford gates can not be simulated efficiently in general. By converting the quantum circuit into a tensor network, we can simulate small coherent quantum error correction circuits. Examples are given in the following sections:
  • Coherent Error Simulation
  • Measurement-Free QEC