Evolutionary Discovery of Bivariate Bicycle Codes with LLM-Guided Search
Juan Cruz-Benito et al. · 2026 · arXiv.org
| 编号 QE144 | 主题 qLDPC 码 | 链接 arXiv:2606.02418 |
摘要
摘要保留原文（英文）
摘要取自 arXiv / 出版方元数据，未作翻译，以保证与原文一致。
Quantum LDPC code discovery requires searching large algebraic design spaces while reliably certifying the parameters and equivalence classes of any candidates found. We introduce an LLM-guided evolutionary workflow in which language models mutate Python programs that generate bivariate-bicycle and perturbed bivariate-bicycle code ans”atze. Across five campaigns, the system performed approximately 1{,}650 evolutionary iterations, screened about candidate codes, and required hours of computation and US$400 in LLM inference cost. Candidate codes are evaluated through a staged validation pipeline combining rank computation, distance estimation and certification, mixed-integer linear programming, BLISS Tanner-graph deduplication, decomposability analysis, and local-Clifford equivalence checks. At block length , the workflow identifies 465 distinct candidate codes: 97 CSS bivariate-bicycle codes and 368 non-CSS perturbed variants. The CSS search recovers known high-performing codes and finds new finite-length representatives, including an indecomposable [[288,16,12]] code and higher-weight codes with up to at di
本站词条在引用该文献时，会以 wikilink（sources/QE144）链接到本页；右侧「反向链接」面板自动列出所有引用它的词条。