English

Outer approximations of classical multi-network correlations

Quantum Physics 2022-02-10 v1 Statistics Theory Methodology Statistics Theory

Abstract

We propose a framework, named the postselected inflation framework, to obtain converging outer approximations of the sets of probability distributions that are compatible with classical multi-network scenarios. Here, a network is a bilayer directed acyclic graph with a layer of sources of classical randomness, a layer of agents, and edges specifying the connectivity between the agents and the sources. A multi-network scenario is a list of such networks, together with a specification of subsets of agents using the same strategy. An outer approximation of the set of multi-network correlations provides means to certify the infeasibility of a list of agent outcome distributions. We furthermore show that the postselected inflation framework is mathematically equivalent to the standard inflation framework: in that respect, our results allow to gain further insights into the convergence proof of the inflation hierarchy of Navascu\`es and Wolfe [arXiv:1707.06476], and extend it to the case of multi-network scenarios.

Keywords

Cite

@article{arxiv.2202.04103,
  title  = {Outer approximations of classical multi-network correlations},
  author = {Victor Gitton},
  journal= {arXiv preprint arXiv:2202.04103},
  year   = {2022}
}

Comments

41 + 27 pages, 11 figures, lots of tensor networks

R2 v1 2026-06-24T09:27:06.542Z