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| Hauptverfasser: | , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| Online-Zugang: | https://arxiv.org/abs/2405.03776 |
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| _version_ | 1866916237680836608 |
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| author | Martínez-García, Fernando Pereira, Francisco Revson F. Parrado-Rodríguez, Pedro |
| author_facet | Martínez-García, Fernando Pereira, Francisco Revson F. Parrado-Rodríguez, Pedro |
| contents | The development and use of large-scale quantum computers relies on integrating quantum error-correcting (QEC) schemes into the quantum computing pipeline. A fundamental part of the QEC protocol is the decoding of the syndrome to identify a recovery operation with a high success rate. In this work, we implement a decoder that finds the recovery operation with the highest success probability by mapping the decoding problem to a spin system and using Population Annealing to estimate the free energy of the different error classes. We study the decoder performance on a 4.8.8 color code lattice under different noise models, including code capacity with bit-flip and depolarizing noise, and phenomenological noise, which considers noisy measurements, with performance reaching near-optimal thresholds. This decoding algorithm can be applied to a wide variety of stabilizer codes, including surface codes and quantum low-density parity-check (qLDPC) codes. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_03776 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Near-optimal decoding algorithm for color codes using Population Annealing Martínez-García, Fernando Pereira, Francisco Revson F. Parrado-Rodríguez, Pedro Quantum Physics The development and use of large-scale quantum computers relies on integrating quantum error-correcting (QEC) schemes into the quantum computing pipeline. A fundamental part of the QEC protocol is the decoding of the syndrome to identify a recovery operation with a high success rate. In this work, we implement a decoder that finds the recovery operation with the highest success probability by mapping the decoding problem to a spin system and using Population Annealing to estimate the free energy of the different error classes. We study the decoder performance on a 4.8.8 color code lattice under different noise models, including code capacity with bit-flip and depolarizing noise, and phenomenological noise, which considers noisy measurements, with performance reaching near-optimal thresholds. This decoding algorithm can be applied to a wide variety of stabilizer codes, including surface codes and quantum low-density parity-check (qLDPC) codes. |
| title | Near-optimal decoding algorithm for color codes using Population Annealing |
| topic | Quantum Physics |
| url | https://arxiv.org/abs/2405.03776 |