PIRSA:23020049

Video URL

https://pirsa.org/23020049

Infinite Dimensional Optimisation Problems in Quantum Information — An operator algebra approach to the NPA Hierarchy

Zeiss, J. (2023). Infinite Dimensional Optimisation Problems in Quantum Information — An operator algebra approach to the NPA Hierarchy. Perimeter Institute for Theoretical Physics. https://pirsa.org/23020049

Zeiss, Julius. Infinite Dimensional Optimisation Problems in Quantum Information — An operator algebra approach to the NPA Hierarchy. Perimeter Institute for Theoretical Physics, Feb. 14, 2023, https://pirsa.org/23020049 

          @misc{ scivideos_PIRSA:23020049,
            doi = {10.48660/23020049},
            url = {https://pirsa.org/23020049},
            author = {Zeiss, Julius},
            keywords = {Quantum Foundations},
            language = {en},
            title = {Infinite Dimensional Optimisation Problems in Quantum Information {\textemdash} An operator algebra approach to the NPA Hierarchy},
            publisher = {Perimeter Institute for Theoretical Physics},
            year = {2023},
            month = {feb},
            note = {PIRSA:23020049 see, \url{https://scivideos.org/pirsa/23020049}}
          }

Julius Zeiss Universität zu Köln

Talk numberPIRSA:23020049
DOI10.48660/23020049
Source RepositoryPIRSA
Collection
Talk Type Scientific Series
Subject

Abstract

The theory of polynomial optimisation considers a polynomial objective function subject to countable many polynomial constraints. In a seminal contribution Navascués, Pironio and Acín (NPA) generalised a previous result from Lassere, allowing for its application in quantum information theory by considering its non-commutative variant. Non-commutative variables are represented as bounded operators on potentially infinite dimensional Hilbert spaces. These infinite-dimensional non-commutative polynomials optimisation (NPO) problems are recast as a complete hierarchy of semidefinite programming (SDP) relaxations by a suitable partitioning of the underlying spaces.

The reformulation into convex optimisation problems allows for numerical analysis. We focus on an operator theoretical approach to the NPA hierarchy and show its equiv-
alence to the original NPA hierarchy. To do so, we introduce the necessary mathematical preliminaries from operator algebra theory and semidefinite programming. We conclude by showing how certain relations on operators translate to SDP relaxations yielding drastically reduced problem sizes.

Zoom Link: https://pitp.zoom.us/j/98583295694?pwd=SlcvNG90RzFrODBKSHNaUi84bG9DZz09