Adaptive Window Decoding based on Spatiotemporal Complementary Gap

Abstract

Real-time decoding plays a crucial role in practical fault-tolerant quantum computing. Window decoding, in which the decoding problem is divided into windows, is a promising approach. While reducing the window size is desirable for faster decoding, each window contains a buffer region whose size must typically be at least the code distance to avoid degrading the logical error rate, which limits how much the window can shrink. In this paper, we propose an adaptive decoding scheme in which window decoding is first performed with a small buffer size and a decoding confidence (soft information) is computed; if the confidence is low, the buffer size is enlarged and decoding is redone. This approach reduces the average decoding time, since most shots are decoded with a small buffer. A central challenge in realizing this scheme is that existing forms of soft information are not directly applicable to window decoding, especially with a small buffer. We address this challenge by introducing a new form of soft information, the spatiotemporal complementary gap, specifically designed for this setting. Numerical simulations demonstrate that the proposed scheme reduces the average buffer size by approximately 40% while maintaining the logical error rate. Beyond the reduction of average decoding time, the proposed method is also expected to contribute to reducing the reaction time for non-Clifford operations and relaxing the hardware requirements for real-time decoding.

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BibTeX RIS

BibTeX

@misc{mishima2026adaptive,
  title = {{Adaptive Window Decoding based on Spatiotemporal Complementary Gap}},
  author = {Moeto Mishima and Riki Toshio and Kaito Kishi and Jun Fujisaki and Hirotaka Oshima and Shintaro Sato and Keisuke Fujii},
  howpublished = {arXiv},
  year = {2026},
  month = oct,
  doi = {10.48550/arxiv.2605.14637},
  eprint = {2605.14637},
  archivePrefix = {arXiv},
  url = {https://arxiv.org/abs/2605.14637},
}

RIS

TY  - UNPB
TI  - Adaptive Window Decoding based on Spatiotemporal Complementary Gap
AU  - Moeto Mishima
AU  - Riki Toshio
AU  - Kaito Kishi
AU  - Jun Fujisaki
AU  - Hirotaka Oshima
AU  - Shintaro Sato
AU  - Keisuke Fujii
PY  - 2026
DA  - 2026/10/09
PB  - arXiv
DO  - 10.48550/arxiv.2605.14637
UR  - https://arxiv.org/abs/2605.14637
AB  - Real-time decoding plays a crucial role in practical fault-tolerant quantum computing. Window decoding, in which the decoding problem is divided into windows, is a promising approach. While reducing the window size is desirable for faster decoding, each window contains a buffer region whose size must typically be at least the code distance to avoid degrading the logical error rate, which limits how much the window can shrink. In this paper, we propose an adaptive decoding scheme in which window decoding is first performed with a small buffer size and a decoding confidence (soft information) is computed; if the confidence is low, the buffer size is enlarged and decoding is redone. This approach reduces the average decoding time, since most shots are decoded with a small buffer. A central challenge in realizing this scheme is that existing forms of soft information are not directly applicable to window decoding, especially with a small buffer. We address this challenge by introducing a new form of soft information, the spatiotemporal complementary gap, specifically designed for this setting. Numerical simulations demonstrate that the proposed scheme reduces the average buffer size by approximately 40% while maintaining the logical error rate. Beyond the reduction of average decoding time, the proposed method is also expected to contribute to reducing the reaction time for non-Clifford operations and relaxing the hardware requirements for real-time decoding.
ER  -

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