发表机构
Algocyte; Oxford Immune Algorithmics; Oxford University Innovation; London Institute for Healthcare Engineering（Algocyte; 牛津免疫算法公司; 牛津大学创新公司; 伦敦医疗工程研究所）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究用信息论方法重建未破译历史文本的几何结构，验证斐斯托斯圆盘等语料的结构可恢复性，并区分组织重建与语义破译。
AI 中文摘要
在先前的工作中，我们建立了从非随机信息中恢复几何与拓扑的充分条件，并通过阿雷西博信息展示了重建过程。未破译的历史记录提出了一个相关问题：单向通信，无法获知制作者的意图或编码惯例。在此，我们将这一框架扩展到斐斯托斯圆盘、安第斯奇普、朗格朗格、印度河铭文和伏尼契手稿，并使用埃及布局和阿雷西博作为对照。算法信息动力学（AID）指导结构扰动，结合经典信息度量、预测编码、压缩和基于算法概率的估计。斐斯托斯圆盘在位置控制后保留了0.714比特的过量相邻符号互信息；其真实分割位于一个广阔的信息盆地内，跨面边界预测的AUC达到0.76和0.86。重复性解释了其主要递归，而测试的螺旋嵌入未提供额外交叉缠绕结构的证据。在多个语料库中，比较性迁移在精确共享局部对之外持续存在。奇普绳结形式在控制度、深度、纤维和捻度后区分真实附件（调整后p=0.009）；受约束分配恢复了8.75%的隐藏父节点，而随机期望为7.87%。行对齐测试在校正后未提供可比证据。校准的BDM恢复了阿雷西博的23列宽度（搜索校正p=0.005），而可执行对照检测到空间依赖性并通过干预生成器消除之。这些发现将基于信息的结构重建与干预推理联系起来，区分可恢复的组织与语义破译。
英文摘要
In previous work, we established sufficient conditions for recovering geometry and topology from non-random information, demonstrating reconstruction with the Arecibo message. Undeciphered historical records present a related problem: one-way communication without access to their makers' intentions or encoding conventions. Here we extend this framework to the Phaistos Disc, Andean khipu, Rongorongo, Indus inscriptions and the Voynich manuscript, using Egyptian layouts and Arecibo as controls. Algorithmic information dynamics (AID) guides structural perturbations, combining classical information measures, predictive coding, compression and algorithmic-probability-based estimates. Phaistos retains 0.714 bits of excess adjacent-sign mutual information after positional controls; its authentic segmentation lies within a broad information basin, and cross-face boundary prediction achieves AUCs of 0.76 and 0.86. Repetition explains its principal recurrence, while the tested spiral embeddings provide no evidence of additional cross-winding structure. Across several corpora, comparative transfer persists beyond exact shared local pairs. Khipu knot forms distinguish authentic attachments after controlling for degree, depth, fibre and twist (adjusted $p=0.009$); constrained assignment recovers 8.75\% of concealed parents against 7.87\% expected by chance. Row-alignment tests yield no comparable evidence after correction. Calibrated BDM recovers Arecibo's 23-column width (search-corrected $p=0.005$), while executable controls detect spatial dependence and eliminate it through interventions on the generator. These findings connect information-based structural reconstruction with interventional reasoning, distinguishing recoverable organisation from semantic decipherment.
Comments56 pages
