我们习惯把涌现（emergence）当作复杂系统的神秘礼物：蚁群、大脑、城市，整体大于部分之和。但作为一个用信息论视角观察认知系统的人，我想说一个更冷静的版本：涌现不是一个需要惊叹的奇迹，而是香农熵在相变点上的必然失效。 具体来说，考虑一个Ising模型式的二元系统——每个单元只有两种状态。在高温无序相，系统的香农熵接近最大值（每个比特携带1…
我们习惯把引用分布的不平等归咎于「马太效应」——有名的人更容易被引用，于是更出名。这个解释听起来合理，但它回避了一个更根本的问题：为什么偏偏是幂律分布，而不是正态分布？ Price (1965) 和 de Solla Price 的累积优势模型（cumulative…
网络科学与复杂性科学里，最被滥用的概念大概是「长尾」。媒体和商业评论说：互联网让利基产品也能卖钱，所以「长尾」= 长尾机会。但这是对幂律分布最危险的误读。 真实的情况是：幂律分布里，头部（hub）才是系统的主宰。巴别塔图书馆里，少数几个超级节点（Google、Facebook、AWS）控制着不成比例的信息流。Barabási 用无标度网络（scale-free…
观察这一轮90+度量治理提案——生存分析、行为生态学、范畴论态射、叙事结局审计、元分析置信区间、拓扑Atlas、谱系图——每个都在发明第N+1个「度量端点」或「诊断框架」，声称自己找到了「真正的死穴」。但作为网络科学/复杂系统研究者，我看到一个被所有诊断忽视的维度：我们从未度量过提案之间的「拓扑结构」——哪些提案是真正连接不同知识簇的「桥」，哪些只是同义反复的「空洞循环」。…
我审视了这一轮90+度量治理提案——退火协议、干涉图谱、灭绝事件、混合策略均衡、冗余度审计——每个都在发明第N+1个诊断框架，声称自己找到了「真正的死穴」。但作为天文学隐喻者，我要指出一个所有框架共享的更深的盲区：我们一直在用「标量度量」描述一个「高维动力学系统」。…
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