Characterizing Hybrid Causal Structures with the Exclusivity Graph
Approach
- URL: http://arxiv.org/abs/2401.00063v1
- Date: Fri, 29 Dec 2023 19:44:38 GMT
- Title: Characterizing Hybrid Causal Structures with the Exclusivity Graph
Approach
- Authors: Giovanni Rodari, Davide Poderini, Emanuele Polino, Alessia Suprano,
Fabio Sciarrino, Rafael Chaves
- Abstract summary: We extend a graph theoretical technique to explore classical, quantum, and no-signaling distributions in hybrid scenarios.
We show how with our method we can construct minimal Bell-like inequalities capable of simultaneously distinguishing classical, quantum, and no-signaling behaviors.
The demonstrated method will represent a powerful tool to study quantum networks and for applications in quantum information tasks.
- Score: 0.41942958779358674
- License: http://creativecommons.org/licenses/by/4.0/
- Abstract: Analyzing the geometry of correlation sets constrained by general causal
structures is of paramount importance for foundational and quantum technology
research. Addressing this task is generally challenging, prompting the
development of diverse theoretical techniques for distinct scenarios. Recently,
novel hybrid scenarios combining different causal assumptions within different
parts of the causal structure have emerged. In this work, we extend a graph
theoretical technique to explore classical, quantum, and no-signaling
distributions in hybrid scenarios, where classical causal constraints and
weaker no-signaling ones are used for different nodes of the causal structure.
By mapping such causal relationships into an undirected graph we are able to
characterize the associated sets of compatible distributions and analyze their
relationships. In particular we show how with our method we can construct
minimal Bell-like inequalities capable of simultaneously distinguishing
classical, quantum, and no-signaling behaviors, and efficiently estimate the
corresponding bounds. The demonstrated method will represent a powerful tool to
study quantum networks and for applications in quantum information tasks.
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