Domenik Eichhorn, Nick Poser, Maximilian Schweikart, Ina Schaefer.
In our third ProvideQ paper, we put focus on the technical
realisation of the toolbox.
This paper was presented at IEEE’s QSW 2025 conference.
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 are seamlessly executable on multiple backends.
This paper introduces the technical details of the ProvideQ toolbox, explains
its architecture, and demonstrates possible applications for several
real-world use cases.
Our proof of concept shows that Meta-Solver strategies already enable the
application of quantum subroutines today, however, more sophisticated hardware
is required to make their performance competitive.
Read’n’cite
We have uploaded a recent preprint to the
arXiv and you can get the official
publication from
the publisher’s page.
Cite
@INPROCEEDINGS{11134346, author={Eichhorn, Domenik and Poser, Nick and Schweikart, Maximilian and Schaefer, Ina}, booktitle={2025 IEEE International Conference on Quantum Software (QSW)}, title={ProvideQ: A Quantum Optimization Toolbox}, year={2025}, volume={}, number={}, pages={206-214}, keywords={Quantum algorithm;Algorithms;Quantum mechanics;Computer architecture;Hardware;Software tools;Quantum circuit;Optimization;quantum computing;quantum software;quantum algorithm;hybrid optimization}, doi={10.1109/QSW67625.2025.00032}}