Localized statistics decoding for quantum low-density parity-check codes
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| Názov: | Localized statistics decoding for quantum low-density parity-check codes |
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| Autori: | Hillmann, Timo, 1995, Berent, Lucas, Quintavalle, Armanda O., Eisert, Jens, Wille, Robert, Roffe, Joschka |
| Zdroj: | Nature Communications Simulation results for "Localized statistics decoding: A parallel decoding algorithm for quantum low-density parity-check codes". 16(1) |
| Popis: | Quantum low-density parity-check codes are a promising candidate for fault-tolerant quantum computing with considerably reduced overhead compared to the surface code. However, the lack of a practical decoding algorithm remains a barrier to their implementation. In this work, we introduce localized statistics decoding, a reliability-guided inversion decoder that is highly parallelizable and applicable to arbitrary quantum low-density parity-check codes. Our approach employs a parallel matrix factorization strategy, which we call on-the-fly elimination, to identify, validate, and solve local decoding regions on the decoding graph. Through numerical simulations, we show that localized statistics decoding matches the performance of state-of-the-art decoders while reducing the runtime complexity for operation in the sub-threshold regime. Importantly, our decoder is more amenable to implementation on specialized hardware, positioning it as a promising candidate for decoding real-time syndromes from experiments. |
| Popis súboru: | electronic |
| Prístupová URL adresa: | https://research.chalmers.se/publication/548222 https://research.chalmers.se/publication/548222/file/548222_Fulltext.pdf |
| Databáza: | SwePub |
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Nájsť tento článok vo Web of Science | Abstrakt: | Quantum low-density parity-check codes are a promising candidate for fault-tolerant quantum computing with considerably reduced overhead compared to the surface code. However, the lack of a practical decoding algorithm remains a barrier to their implementation. In this work, we introduce localized statistics decoding, a reliability-guided inversion decoder that is highly parallelizable and applicable to arbitrary quantum low-density parity-check codes. Our approach employs a parallel matrix factorization strategy, which we call on-the-fly elimination, to identify, validate, and solve local decoding regions on the decoding graph. Through numerical simulations, we show that localized statistics decoding matches the performance of state-of-the-art decoders while reducing the runtime complexity for operation in the sub-threshold regime. Importantly, our decoder is more amenable to implementation on specialized hardware, positioning it as a promising candidate for decoding real-time syndromes from experiments. |
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| ISSN: | 20411723 20411723 |
| DOI: | 10.1038/s41467-025-63214-7 |