PIRSA:26020052 Scientific Series Quantum Foundations

DOI10.48660/26020052

Series: Quantum Foundations

(2026). Nonlocal correlation in open and closed network scenarios and its application to the communication games. (VIRTUAL). Perimeter Institute. https://pirsa.org/26020052

Nonlocal correlation in open and closed network scenarios and its application to the communication games. (VIRTUAL). Perimeter Institute, Feb. 19, 2026, https://pirsa.org/26020052 

@misc{ pirsa_PIRSA:26020052,
  doi = {10.48660/26020052},
  url = {https://pirsa.org/26020052},
  author = {},
  keywords = {Quantum Foundations},
  language = {en},
  title = {Nonlocal correlation in open and closed network scenarios and its application to the  communication games. (VIRTUAL)},
  publisher = {Perimeter Institute},
  year = {2026},
  month = {feb},
  note = {PIRSA:26020052 see, \url{https://pirsa.org}}
}

Abstract

The study of quantum correlations in multipartite network scenarios represents a significant extension of nonlocality research beyond the standard Bell–CHSH framework. Quantum networks comprise multiple parties interconnected by several independent quantum sources that
distribute quantum states among them. A fundamental question in this context is whether the resulting input–output correlations generated by such networks admit a local classical explanation or not. Unlike standard Bell scenarios, the set of locally reproducible correlations in quantum
networks is generally non-convex. As a consequence, characterising nonlocality becomes highly nontrivial, and only limited classes of nonlinear inequalities are known, primarily for certain open network configurations where some parties have measurement inputs while others do not. For
many important scenarios—such as closed-loop networks and higher-dimensional open networks—no complete set of inequalities is known, making the identification of nonlocal correlations particularly challenging.
In this talk, I will briefly review selected open network scenarios and the corresponding nonlocality inequalities, as well as closed-loop network scenarios where inequality-based methods are unavailable. I will discuss alternative approaches used to determine the nature of correlations in
both cases. Finally, I will present some of our recent results along with an overview of current developments in the field.

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