Quantum causal modelling

TL;DR

This paper introduces a novel quantum causal modelling framework that extends classical causal inference tools to quantum systems, incorporating indefinite causal order and addressing limitations of classical methods.

Contribution

It develops quantum analogues of core causal modelling concepts, enabling the discovery of causal structure in quantum systems using the process matrix formalism.

Findings

Defines quantum Causal Markov Condition and Faithfulness.

Extends to structures with indefinite causal order.

Provides a foundation for quantum causal discovery.

Abstract

Causal modelling provides a powerful set of tools for identifying causal structure from observed correlations. It is well known that such techniques fail for quantum systems, unless one introduces `spooky' hidden mechanisms. Whether one can produce a genuinely quantum framework in order to discover causal structure remains an open question. Here we introduce a new framework for quantum causal modelling that allows for the discovery of causal structure. We define quantum analogues for many of the core features of classical causal modelling techniques, including the Causal Markov Condition and Faithfulness. Based on the process matrix formalism, this framework naturally extends to generalised structures with indefinite causal order.