Analysing causal structures with entropy

TL;DR

This paper reviews entropy-based methods for causal inference, comparing classical, quantum, and post-quantum cases, and discusses their applications, limitations, and open problems.

Contribution

It unifies and clarifies entropic techniques for causal structure analysis, establishing new connections and highlighting their applications in quantum cryptography.

Findings

Entropic methods can distinguish classical from quantum causes.

Unified terminology improves understanding of entropic causal analysis.

Limitations of entropic approaches are identified and discussed.

Abstract

A central question for causal inference is to decide whether a set of correlations fit a given causal structure. In general, this decision problem is computationally infeasible and hence several approaches have emerged that look for certificates of compatibility. Here we review several such approaches based on entropy. We bring together the key aspects of these entropic techniques with unified terminology, filling several gaps and establishing new connections regarding their relation, all illustrated with examples. We consider cases where unobserved causes are classical, quantum and post-quantum and discuss what entropic analyses tell us about the difference. This has applications to quantum cryptography, where it can be crucial to eliminate the possibility of classical causes. We discuss the achievements and limitations of the entropic approach in comparison to other techniques and point out the main open problems.