Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding
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arXiv
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| Auteurs principaux: | , , , |
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| Format: | Preprint |
| Publié: |
2026
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| _version_ | 1866908900176953344 |
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| author | Rapp, Lukas Médard, Muriel Tang, Eugene Duffy, Ken R. |
| author_facet | Rapp, Lukas Médard, Muriel Tang, Eugene Duffy, Ken R. |
| contents | We introduce a generalized low-density parity-check decoding framework for quantum Tanner codes utilizing soft-output guessing random additive noise decoding (SOGRAND). By soft-output decoding entire component codes, we mitigate trapping sets and cycles, resulting in improved convergence. SOGRAND, combined with ordered statistic decoding (OSD) post-processing, outperforms the standard belief propagation plus OSD baseline by up to three orders of magnitude in logical error rate, providing a way forward for scalable decoding of the emerging class of Tanner-code-based quantum codes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_18318 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding Rapp, Lukas Médard, Muriel Tang, Eugene Duffy, Ken R. Quantum Physics Information Theory We introduce a generalized low-density parity-check decoding framework for quantum Tanner codes utilizing soft-output guessing random additive noise decoding (SOGRAND). By soft-output decoding entire component codes, we mitigate trapping sets and cycles, resulting in improved convergence. SOGRAND, combined with ordered statistic decoding (OSD) post-processing, outperforms the standard belief propagation plus OSD baseline by up to three orders of magnitude in logical error rate, providing a way forward for scalable decoding of the emerging class of Tanner-code-based quantum codes. |
| title | Efficient Soft-Output Guessing for Enhanced Quantum Tanner Code Decoding |
| topic | Quantum Physics Information Theory |
| url | https://arxiv.org/abs/2603.18318 |