QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers

Fuente: arXiv
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Main Authors: Meli, Natacha Kuete, Golyanik, Vladislav, Benkner, Marcel Seelbach, Moeller, Michael
Format: Preprint
Published: 2025
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author Meli, Natacha Kuete
Golyanik, Vladislav
Benkner, Marcel Seelbach
Moeller, Michael
author_facet Meli, Natacha Kuete
Golyanik, Vladislav
Benkner, Marcel Seelbach
Moeller, Michael
contents There is growing interest in solving computer vision problems such as mesh or point set alignment using Adiabatic Quantum Computing (AQC). Unfortunately, modern experimental AQC devices such as D-Wave only support Quadratic Unconstrained Binary Optimisation (QUBO) problems, which severely limits their applicability. This paper proposes a new way to overcome this limitation and introduces QuCOOP, an optimisation framework extending the scope of AQC to composite and binary-parametrised, possibly non-quadratic problems. The key idea of QuCOOP~is to iteratively approximate the original objective function by a sequel of local (intermediate) QUBO forms, whose binary parameters can be sampled on AQC devices. We experiment with quadratic assignment problems, shape matching and point set registration without knowing the correspondences in advance. Our approach achieves state-of-the-art results across multiple instances of tested problems.
format Preprint
id arxiv_https___arxiv_org_abs_2503_19718
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers
Meli, Natacha Kuete
Golyanik, Vladislav
Benkner, Marcel Seelbach
Moeller, Michael
Quantum Physics
There is growing interest in solving computer vision problems such as mesh or point set alignment using Adiabatic Quantum Computing (AQC). Unfortunately, modern experimental AQC devices such as D-Wave only support Quadratic Unconstrained Binary Optimisation (QUBO) problems, which severely limits their applicability. This paper proposes a new way to overcome this limitation and introduces QuCOOP, an optimisation framework extending the scope of AQC to composite and binary-parametrised, possibly non-quadratic problems. The key idea of QuCOOP~is to iteratively approximate the original objective function by a sequel of local (intermediate) QUBO forms, whose binary parameters can be sampled on AQC devices. We experiment with quadratic assignment problems, shape matching and point set registration without knowing the correspondences in advance. Our approach achieves state-of-the-art results across multiple instances of tested problems.
title QuCOOP: A Versatile Framework for Solving Composite and Binary-Parametrised Problems on Quantum Annealers
topic Quantum Physics
url https://arxiv.org/abs/2503.19718