TY  - CONF
AU  - Old, Josias
AU  - Rispler, Manuel
TI  - Generalized Belief Propagation Algorithms for Decoding of Surface Codes
M1  - FZJ-2023-05669
PY  - 2023
AB  - Belief propagation (BP) is well-known as a low complexity decoding algorithm with a strong performance for important classes of quantum error correcting codes, e.g. notably for the quantum low-density parity check (LDPC) code class of random expander codes. However, it is also well-known that the performance of BP breaks down when facing topological codes such as the surface code, where naive BP fails entirely to reach a below-threshold regime, i.e. the regime where error correction becomes useful. Previous works have shown, that this can be remedied by resorting to post-processing decoders outside the frame- work of BP. In this work, we present a generalized belief propagation method with an outer re-initialization loop that successfully decodes surface codes, i.e. opposed to naive BP it re- covers the sub-threshold regime known from decoders tailored to the surface code and from statistical-mechanical mappings. We report a threshold of 17% under independent bit-and phase-flip data noise (to be compared to the ideal threshold of 20.6%) and a threshold value of 14% under depolarizing data noise (compared to the ideal threshold of 18.9%), which are on par with thresholds achieved by non- BP post-processing methods.
T2  - Coping with Errors in Scalable Quantum Computing Systems
CY  - 8 Jan 2023 - 11 Jan 2023, Bad Honnef (Germany)
Y2  - 8 Jan 2023 - 11 Jan 2023
M2  - Bad Honnef, Germany
LB  - PUB:(DE-HGF)24
DO  - DOI:10.34734/FZJ-2023-05669
UR  - https://juser.fz-juelich.de/record/1019838
ER  -