A convergent inflation hierarchy for quantum causal structures

Understand

A causal structure is a description of the functional dependencies between random variables.

• A distribution is compatible with a given causal structure if it can be realized by a process respecting these dependencies.
• Deciding whether a distribution is compatible with a structure is a practically and fundamentally relevant, yet very difficult problem.
• Only recently has a general class of algorithms been proposed: These so-called inflation techniques associate to any causal structure a hierarchy of increasingly strict compatibility tests, where each test can be formulated as a computationally efficient convex optimization problem.