ProvideQ: A Quantum Optimization Toolbox
Domenik Eichhorn, Nick Poser, Maximilian Schweikart, Ina Schaefer

TL;DR
ProvideQ is a software toolbox that facilitates the integration of quantum and classical optimization techniques through Meta-Solver strategies, enabling practical hybrid solvers for real-world problems.
Contribution
It introduces the ProvideQ toolbox, a novel software platform that simplifies the development and configuration of hybrid quantum-classical solvers using decomposition techniques.
Findings
Meta-Solver strategies enable current quantum subroutines to be applied practically.
The toolbox supports multiple quantum backends for seamless execution.
More advanced hardware is needed for quantum solutions to outperform classical methods.
Abstract
Hybrid solvers for combinatorial optimization problems combine the advantages of classical and quantum computing to overcome difficult computational challenges. Although their theoretical performance seems promising, their practical applicability is challenging due to the lack of a technological stack that can seamlessly integrate quantum solutions with existing classical optimization frameworks. We tackle this challenge by introducing the ProvideQ toolbox, a software tool that enables users to easily adapt and configure hybrid solvers via Meta-Solver strategies. A Meta-Solver strategy implements decomposition techniques, which splits problems into classical and quantum subroutines. The ProvideQ toolbox enables the interactive creation of such decompositions via a Meta-Solver configuration tool. It combines well-established classical optimization techniques with quantum circuits that…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Code & Models
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsQuantum Computing Algorithms and Architecture · Complexity and Algorithms in Graphs · Constraint Satisfaction and Optimization
