Quantum mechanics has achieved unparalleled success as an operational theory,
describing a wide range of experiments to remarkable accuracy. However, the physical …

Figure 1: In statistics, causal models can be used to extract cause-effect relationships from
empirical data on a complex system. Existing models, however, do not apply if at least one …

In this article we set out to understand the significance of the process matrix formalism and
the quantum causal modelling programme for ongoing disputes about the role of causation …

Causal influences are at the core of any empirical science, the reason why its quantification
is of paramount relevance for the mathematical theory of causality and applications …

In classical physics, the Kolmogorov extension theorem lays the foundation for the theory of
stochastic processes. It has been known for a long time that, in its original form, this theorem …

Through the introduction of his 'common cause principle'[The Direction of Time, 1956], Hans
Reichenbach was the first to formulate a precise link relating causal claims to statements of …

It is known that the classical framework of causal models is not general enough to allow for
causal reasoning about quantum systems. While the framework has been generalized in a …

Reichenbach's principle asserts that if two observed variables are found to be correlated,
then there should be a causal explanation of these correlations. Furthermore, if the …

Though the topic of causal inference is typically considered in the context of classical
statistical models, recent years have seen great interest in extending causal inference …

We introduce a formalism for the evaluation of counterfactual queries in the framework of
quantum causal models, by generalising the three-step procedure of abduction, action, and …