Quantum causal models via QBism

TL;DR

This paper develops a quantum causal modeling framework rooted in QBism, emphasizing the role of the observer's probability assignments and introducing a layered, reversible causal structure that distinguishes measurements from interventions.

Contribution

It introduces a novel quantum causal model based on QBism, incorporating a special rule for un-measurements and a layered, reversible causal structure.

Findings

Quantum measurements have a unique status separate from interventions.

A special rule for un-measurements aligns with QBist interpretations.

Quantum causal structures are inherently layered and can be symmetric under causal reversal.

Abstract

This paper presents a framework for Quantum causal modeling based on the interpretation of causality as a relation between an observer's probability assignments to hypothetical or counterfactual experiments. The framework is based on the principle of `causal sufficiency': that it should be possible to make inferences about interventions using only the probabilities from a single `reference experiment' plus causal structure in the form of a DAG. This leads to several interesting results: we find that quantum measurements deserve a special status distinct from interventions, and that a special rule is needed for making inferences about what would happen if they are not performed (`un-measurements'). One natural candidate for this rule is found to be an equation of importance to the QBist interpretation of quantum mechanics. We find that the causal structure of quantum systems must have a `layered' structure, and that the model can naturally be made symmetric under reversal of the causal arrows.