Quantum· 2026Q1
Certified bounds on optimization problems in quantum theory
- 0citations
- Q1SCImago
- 2026year
Short summary
A new framework extracts rigorous certified bounds from inexact numerical data for non-commutative optimization problems, crucial for quantum information theory.
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Key points
- Introduces a framework for extracting rigorous certified bounds from inexact numerical data for non-commutative optimization problems.
- Addresses the issue of semidefinite solver bounds exceeding global optima in quantum information theory.
- Applies the framework to paradigmatic problems in quantum information theory.
- Provides an extension for sparsity and symmetry-adapted semidefinite relaxations.
AI-generated from the title and abstract; the full text is not read.
Abstract
Semidefinite relaxations of polynomial optimization have become a central tool for addressing the non-convex optimization problems over non-commutative operators that are ubiquitous in quantum information theory and, more in general, quantum physics. Yet, as these global relaxation methods are solved numerically, the bounds issued by the semidefinite solver can – and often do – exceed the global optimum, undermining their certifiability. To counter this issue, we introduce a framework for extracting rigorous certified bounds on non-commutative optimization problems from inexact numerical data, and apply it to several paradigmatic problems in quantum information theory. An extension to sparsity and symmetry-adapted semidefinite relaxations is also provided and compared to the general dense scheme. Our results establish rational post-processing as a practical route to reliable certification, pushing semidefinite optimization toward a certifiable standard for quantum information science.
The authors' abstract, as published at the source. Quantum, 2026 · DOI ↗
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Field: Numerical Analysis
Numerical AnalysisMathematics