Possibilistic approach to network nonlocality

TL;DR

This paper introduces a possibilistic framework for analyzing network nonlocality, providing algorithms and inequalities to identify nonlocal patterns in quantum networks with binary outcomes.

Contribution

It develops a possibilistic approach to network nonlocality, including algorithms and Bell-type inequalities, extending analysis to partially correlated sources.

Findings

Identified nonlocal outcome patterns in triangle and square networks.

Constructed nonlinear Bell-type inequalities for nonlocality detection.

Demonstrated quantum nonlocality in the square network with binary outcomes.

Abstract

The investigation of Bell nonlocality traditionally relies on joint probabilities of observing certain measurement outcomes. In this work we explore a possibilistic approach, where only patterns of possible outcomes matter, and apply it to Bell nonlocality in networks with independent sources. We present various algorithms for determining whether a given outcome pattern can be achieved via classical resources or via non-signaling resources. Next we illustrate these methods considering the triangle and square networks (with binary outputs and no inputs), identifying patterns that are incompatible with the network structure, as well as patterns that imply nonlocality. In particular, we obtain an example of quantum nonlocality in the square network with binary outcomes. Moreover, we show how to construct certificates for detecting the nonlocality of a certain pattern, in the form of nonlinear Bell-type inequalities involving joint probabilities. Finally, we show that these inequalities remain valid in the case where the sources in the network become partially correlated.