累计引用
- 近两年引用
- 未提供
- 观测日期
- 2026-07-28
- 推导版本
- qec-impact-v1
Paper · 2024
Bausch et al.
Research record
当前迁移记录只包含书目信息和技术关联,摘要将在获得可靠来源后补充。
Impact snapshots
累计引用
累计引用
Crossref 与 OpenAlex 的口径和更新节奏不同,因此分别披露;这里不计算统一影响力分、热门分或质量分。
Representative roles
Uses correlated matching as a principal experimental baseline for learned surface-code decoding.
Main and supplementary decoder comparisonsUses calibrated experimental measurement information in learned surface-code decoding.
Decoder inputs, calibration and benchmark sectionsDemonstrates a high-accuracy learned decoder on experimental surface-code data.
Main text and Figs. 1–4; learned decoder, training inputs and experimental resultsConnected entities
学习 syndrome history、软读出和设备图到逻辑纠错的映射,重点考察泛化、漂移和实时部署。
原始来源在上述位置定义、构造、实现或实证讨论了“机器学习 Decoder”,用于支撑该技术实体与论文的显式连接。
在 matching 图的构造、重加权或流水线修正中显式利用相关故障机制,使解码不再假设所有 detector 边彼此独立。
Uses correlated matching as an experimental baseline for AlphaQubit.
保留读出幅度、置信度或似然,而非过早压缩为硬比特,并把校准后的软信息传给 decoder。
Supplies a modern independent use of calibrated measurement information.