Hauptseite > Publikationsdatenbank > Generalized Belief Propagation Algorithms for Decoding of Surface Codes > print

001     1019838
005     20240102203542.0
024 7 _ |a 10.34734/FZJ-2023-05669
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037 _ _ |a FZJ-2023-05669
041 _ _ |a English
100 1 _ |a Old, Josias
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111 2 _ |a Coping with Errors in Scalable Quantum Computing Systems
|c Bad Honnef
|d 2023-01-08 - 2023-01-11
|w Germany
245 _ _ |a Generalized Belief Propagation Algorithms for Decoding of Surface Codes
260 _ _ |c 2023
336 7 _ |a Conference Paper
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520 _ _ |a 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.
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700 1 _ |a Rispler, Manuel
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856 4 _ |y OpenAccess
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