用量子处理器解析文艺复兴文本,构建可运行的文学-硬件基准测试集。
QOuLiPo: What a quantum computer sees when it reads a book

- 将文本转为图结构,用原子量子处理器编码其拓扑骨架。
- 29篇人工设计文本实现高精度结构复现,自然文本则揭示作品独特性差异。
- 为未来中性原子量子机提供可扩展的数字人文测试基准,适合跨学科研究者。
本文将八部文艺复兴及古典传承时期经典文本(从奥古斯丁到伽利略)输入中性原子量子处理器,通过图结构转换:每个文本单元作为原子,边表示物理阻塞约束或语义关联。提出刚性度量ρ,区分《七日谈》(刚性,12个核心章节)与波爱修斯著作(全可替换)。反向设计:选取硬件原生支持的目标图,生成29篇符合拓扑约束的文本,统称QOuLiPo,扩展了奥利波传统。在Pasqal FRESNEL处理器上,最大达100原子规模,人工文本实现高近似率,最优案例完全复现骨架。单人可通过云平台端到端完成该流程。报告的是应用层成果,非加速;这些人类主义文本已可直接部署于正在扩展的量子硬件,补充传统文本分析。数字人文界应提前熟悉此硬件:当前工程设计将决定未来硬件评估标准。
原文摘要 · Abstract (English)
What does a book look like to a quantum computer? This paper takes eight classical works of the Renaissance and its late-antique inheritance -- from Augustine to Galileo -- and runs each through a neutral-atom quantum processor. The bridge is graphs: each textual unit becomes an atom, and graph edges are physical blockade constraints for engineered exact unit-disk designs, or a 2D approximation to the semantic graph for natural texts. Three contributions follow. First, we introduce rigidity rho, a metric for how unique a book's structural backbone is -- distinguishing Marguerite de Navarre's Heptameron (rigid, twelve-nouvelle hard core) from Boethius (fully fungible, every chapter substitutable). Second, we invert the pipeline: rather than extracting a graph from existing prose, we pick a target graph the hardware encodes natively, and write a book whose structure matches it. The twenty-nine texts written this way, collected under the name QOuLiPo, extend the OuLiPo tradition to graph-topological constraints and, together with the eight natural texts, form a benchmark distribution against which neutral-atom hardware can be tracked as it scales. Third, we run both natural and engineered texts on Pasqal's FRESNEL processor up to one hundred atoms; engineered texts reach high approximation ratios, the cleanest instances returning the exact backbone. A cloud-accessible quantum machine plus an agentic coding environment now lets a single investigator run this pipeline end-to-end. What is reported is an application layer, not a speedup -- humanistic instances ready to load onto neutral-atom processors as they scale, already complementing classical text analysis. The Digital Humanities community has a stake in building familiarity with this hardware now: the engineered-corpus design choices made today fix the benchmark distribution future hardware will be measured against.
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