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[cite], which can be solved with existing tools such as
TensorInference.jl
. Examples are given in the following sections: - 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: