Tensor network based decoders for topological stabilizer codes with diverse qubit error rates

Abstract

To get a reliable and robust computing result for quantum computers, quantum error correction (QEC) is necessary, and various protection codes have been developed. Among them topological stabilizer codes are gaining promise for QEC, because their global properties provided by the topological code structure help protect the logical qubits from noises. While only local measurements are required which makes them possible to be implemented in existing quantum hardware, a decoder needs to be applied to map measurements to error correcting operations. Improving the decoder helps in reducing the logical failure rate of the code. In this master thesis project, a tensor network based decoder which supports decoding certain types of stabilizer codes with diverse qubit error rates is developed, and is used to research the scenarios for stabilizer codes with diverse error rates and the multi-level decoding for concatenated codes such as the XYZ2 code.