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P2 A categorical semantics for causal structure

因果结构的范畴语义
LMCS vol.Volume 15, Issue 32019匹配度 1/10 · 该论文研究量子/概率过程理论中因果结构的范畴语义,属于形式语义与范畴论方向,与用户关注的静态分析、LLM/Agent、浮点程序分析或贝叶斯程序分析几乎没有直接关联。仅在“因果结构/形式化”这一非常宽泛的意义上有微弱联系。引用 9 inbox
Aleks Kissinger, Sander Uijlen
crossref: 2026-09-10crossref: 2026-09-12

AI 速览

一句话:提出因果结构的范畴语义框架,在过程理论中统一描述有定与不定因果序。

本文为过程理论中的因果结构提出一种范畴论构造,涵盖经典概率过程与量子理论。与传统范畴量子力学构造不同,其对象可编码子系统间细粒度的因果关系,从而表达和推导一大类因果结构。方法上,作者用图解公理定义并演绎过程族,使任意无环因果序、单向信号(半因果)、无信号过程以及量子 n-comb 都可被统一刻画。该框架还可容纳近期提出的不定因果序理论:量子 switch、Oreshkov 等人的 process matrices,以及 Baumeler 等人的经典三方例子,均被证明为高阶因果过程范畴中 SOC_n 族的实例。最后用简单图解公理推导其操作行为。

问题
如何在范畴论与过程理论中统一建模经典和量子系统的因果结构,尤其是局部固定但全局不定因果序的情形。
方法
构造高阶因果过程的范畴,以对象编码子系统间因果关系,并用图解公理定义过程族并推导其操作行为。
评估
通过案例研究证明量子 switch、process matrices 与一个经典三方例子均落入 SOC_n 族,并以图解公理形式化推导其操作行为;属理论性评估,是 LICS 2017 论文的扩展版。
原文摘要(Abstract)

We present a categorical construction for modelling causal structures within a general class of process theories that include the theory of classical probabilistic processes as well as quantum theory. Unlike prior constructions within categorical quantum mechanics, the objects of this theory encode fine-grained causal relationships between subsystems and give a new method for expressing and deriving consequences for a broad class of causal structures. We show that this framework enables one to define families of processes which are consistent with arbitrary acyclic causal orderings. In particular, one can define one-way signalling (a.k.a. semi-causal) processes, non-signalling processes, and quantum $n$-combs. Furthermore, our framework is general enough to accommodate recently-proposed generalisations of classical and quantum theory where processes only need to have a fixed causal ordering locally, but globally allow indefinite causal ordering. To illustrate this point, we show that certain processes of this kind, such as the quantum switch, the process matrices of Oreshkov, Costa, and Brukner, and a classical three-party example due to Baumeler, Feix, and Wolf are all instances of a certain family of processes we refer to as $\textrm{SOC}_n$ in the appropriate category of higher-order causal processes. After defining these families of causal structures within our framework, we give derivations of their operational behaviour using simple, diagrammatic axioms. Comment: Extended version of a LICS 2017 paper with the same title

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BibTeX
@article{paperbot770,
  title = {A categorical semantics for causal structure},
  author = {Aleks Kissinger and Sander Uijlen},
  journal = {Logical Methods in Computer Science},
  volume = {Volume 15, Issue 3},
  year = {2019},
  doi = {10.23638/lmcs-15(3:15)2019}
}