Inflation: a Python library for classical and quantum causal compatibility

Abstract

We introduce Inflation, a Python library for assessing whether an observed probability distribution is compatible with a causal explanation. This is a central problem in both theoretical and applied sciences, which has recently witnessed significant advances from the area of quantum nonlocality, namely, in the development of inflation techniques. Inflation is an extensible toolkit that is capable of solving pure causal compatibility problems and optimization over (relaxations of) sets of compatible correlations in both the classical and quantum paradigms. The library is designed to be modular and with the ability of being ready-to-use, while keeping an easy access to low-level objects for custom modifications.

19 pages, 2 figures. The Inflation GitHub repository is in https://www.github.com/ecboghiu/inflation and the Inflation documentation is in https://ecboghiu.github.io/inflation V2: Accepted version

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Cited by in corpus (8)

• Semidefinite programming relaxations for quantum correlations
• Hierarchical certification of nonclassical network correlations
• Post-quantum nonlocality in the minimal triangle scenario
• Local models and Bell inequalities for the minimal triangle network
• Distinguishing quantum causal scenarios with indistinguishable classical analogs: The significance of intermediate latents
• Experimental genuine quantum nonlocality in the triangle network
• Guarantees on the structure of experimental quantum networks
• Symmetric observations without symmetric causal explanations