A unified approach to quantum de Finetti theorems and SoS rounding via geometric quantization
Sujit Rao

TL;DR
This paper establishes a unified framework connecting quantum de Finetti theorems and SoS hierarchy rounding through geometric quantization, leading to new proofs, applications, and bounds in quantum information and optimization.
Contribution
It introduces a novel approach linking quantum de Finetti theorems with sum-of-squares rounding via geometric quantization, providing new proofs and applications.
Findings
Recasting HSoS algorithms as quantization and eigenvector extraction.
Recovering quantum de Finetti theorems through Husimi distribution and quantization.
New proofs of de Finetti theorems and applications to quantum Max-$d$-Cut.
Abstract
The sum-of-squares hierarchy of semidefinite programs has become a common tool for algorithm design in theoretical computer science, including problems in quantum information. In this work we study a connection between a Hermitian version of the SoS hierarchy, related to the quantum de Finetti theorem, and geometric quantization of compact K\"ahler manifolds (such as complex projective space , the set of all pure states in a -dimensional Hilbert space). We show that previously known HSoS rounding algorithms can be recast as quantizing an objective function to obtain a finite-dimensional matrix, finding its top eigenvector, and then (possibly nonconstructively) rounding it by using a version of the Husimi quasiprobability distribution. Dually, we recover most known quantum de Finetti theorems by doing the same steps in the reverse order: a quantum state is first…
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Taxonomy
TopicsQuantum Mechanics and Applications · Advanced Topics in Algebra · Quantum Information and Cryptography
