English

The resource theory of causal influence and knowledge of causal influence

Statistics Theory 2026-01-13 v2 Quantum Physics Statistics Theory

Abstract

Understanding and quantifying causal relationships between variables is essential for reasoning about the physical world. In this work, we develop a resource-theoretic framework to do so. Here, we focus on the simplest nontrivial setting -- two variables that are causally ordered, meaning that the first has the potential to influence the second, without hidden confounding. First, we introduce the resource theory that directly quantifies causal influence of a functional dependence in this setting and show that the problem of deciding convertibility of resources and identifying a complete set of monotones has a relatively straightforward solution. Following this, we introduce the resource theory that arises naturally when one has uncertainty about the functional dependence. We describe a linear program for deciding the question of whether one resource (i.e., state of knowledge about the functional dependence) can be converted to another. Then, we focus on the case where the variables are binary. In this case, we identify a triple of monotones that are complete in the sense that they capture the partial order over the set of all resources, and we provide an interpretation of each.

Keywords

Cite

@article{arxiv.2512.11209,
  title  = {The resource theory of causal influence and knowledge of causal influence},
  author = {Marina Maciel Ansanelli and Beata Zjawin and David Schmid and Yìlè Yīng and John H. Selby and Ciarán M. Gilligan-Lee and Ana Belén Sainz and Robert W. Spekkens},
  journal= {arXiv preprint arXiv:2512.11209},
  year   = {2026}
}

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37 pages