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Pré-Publication, Document De Travail Année : 2023

Semidefinite programming relaxations for quantum correlations

Résumé

Semidefinite programs are convex optimisation problems involving a linear objective function and a domain of positive semidefinite matrices. Over the last two decades, they have become an indispensable tool in quantum information science. Many otherwise intractable fundamental and applied problems can be successfully approached by means of relaxation to a semidefinite program. Here, we review such methodology in the context of quantum correlations. We discuss how the core idea of semidefinite relaxations can be adapted for a variety of research topics in quantum correlations, including nonlocality, quantum communication, quantum networks, entanglement, and quantum cryptography.

Dates et versions

hal-04267171 , version 1 (01-11-2023)

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Armin Tavakoli, Alejandro Pozas-Kerstjens, Peter Brown, Mateus Araújo. Semidefinite programming relaxations for quantum correlations. 2023. ⟨hal-04267171⟩
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