Quantum Inflation: A General Approach to Quantum Causal Compatibility
This work addresses a foundational gap in quantum causality, with potential applications in quantum networks, thermodynamics, and biology.
The authors tackled the problem of characterizing quantum causal models by introducing quantum inflation, a systematic technique to falsify compatibility with observed correlations, and demonstrated its power by reproducing known results and solving open problems in paradigmatic examples.
Causality is a seminal concept in science: Any research discipline, from sociology and medicine to physics and chemistry, aims at understanding the causes that could explain the correlations observed among some measured variables. While several methods exist to characterize classical causal models, no general construction is known for the quantum case. In this work, we present quantum inflation, a systematic technique to falsify if a given quantum causal model is compatible with some observed correlations. We demonstrate the power of the technique by reproducing known results and solving open problems for some paradigmatic examples of causal networks. Our results may find applications in many fields: from the characterization of correlations in quantum networks to the study of quantum effects in thermodynamic and biological processes.