3/21/2023 0 Comments Quantum error correction github![]() ![]() LEMON–an open source C graph template library. Dezső Balázs, Jüttner Alpár, and Kovács Péter.Mathematical Programming Computation 1, 1 ( 2009), 43– 67. Blossom V: A new implementation of a minimum cost perfect matching algorithm. Exponential suppression of bit or phase errors with cyclic error correction. State preservation by repetitive error detection in a superconducting quantum circuit. J., Quintana C., Roushan P., Vainsencher A., Wenner J., Cleland A. Y., Campbell B., Chen Yu, Chen Z., Chiaro B., Dunsworth A., Hoi I.-C., Neill C., O’Malley P. Correcting spanning errors with a fractal code. Parallelized quantum error correction with fracton topological codes. Efficient color code decoders in \( d\ge 2 \) dimensions from toric code decoders. Kubica Aleksander and Delfosse Nicolas.Fault-tolerant error correction with the gauge color code. Brown Benjamin J., Nickerson Naomi H., and Browne Dan E.Single-shot error correction of three-dimensional homological product codes. Quintavalle Armanda O., Vasmer Michael, Roffe Joschka, and Campbell Earl T.Topological and subsystem codes on low-degree graphs with flag qubits. Chamberland Christopher, Zhu Guanyu, Yoder Theodore J., Hertzberg Jared B., and Cross Andrew W. ![]() Li Muyuan, Miller Daniel, Newman Michael, Wu Yukai, and Brown Kenneth R.Pablo Bonilla, Tuckett David K., Bartlett Stephen D., Flammia Steven T., and Brown Benjamin J. Subsystem codes with high thresholds by gauge fixing and reduced qubit overhead. Higgott Oscar and Breuckmann Nikolas P.Constructions and noise threshold of hyperbolic surface codes. Subsystem surface codes with three-qubit check operators. Bravyi Sergey, Duclos-Cianci Guillaume, Poulin David, and Suchara Martin.Dennis Eric, Kitaev Alexei, Landahl Andrew, and Preskill John.Hardness of decoding quantum stabilizer codes. Quantum Information Processing 19, 4 ( 2020), 1– 17. On the hardnesses of several quantum decoding problems. In Proceedings of the 2012 International Symposium on Information Theory and its Applications. On the hardness of decoding quantum stabilizer codes under the depolarizing channel. NP-hardness of decoding quantum error-correction codes. PyMatching supports the use of weighted edges, hook errors, boundaries and measurement errors, enabling fast decoding, and simulation of fault-tolerant quantum computing. PyMatching and its dependencies are open-source, and it can be used to decode any quantum code for which syndrome defects come in pairs using a simple Python interface. We benchmark the performance of PyMatching, showing that local matching is several orders of magnitude faster than implementations of the full MWPM algorithm using NetworkX or Blossom V for problem sizes typically considered in error correction simulations. The decoding performance of local matching is almost identical to that of the standard MWPM decoder in practice, while reducing the computational complexity. PyMatching includes the standard MWPM decoder as well as a variant, which we call local matching, that restricts each syndrome defect to be matched to another defect within a local neighborhood. This article introduces PyMatching, a fast open-source Python package for decoding quantum error-correcting codes with the minimum-weight perfect matching (MWPM) algorithm. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |