QC-Adviser: Quantum Hardware Recommendations for Solving Industrial Optimization Problems

Djamel Laps-Bouraba; Markus Zajac; Uta Störl

doi:10.18420/inf2025_156

QC-Adviser: Quantum Hardware Recommendations for Solving Industrial Optimization Problems

Quantum Physics 2025-09-17 v2 Human-Computer Interaction

Authors: Djamel Laps-Bouraba , Markus Zajac , Uta Störl

View on arXiv ↗ PDF ↗ DOI ↗

Abstract

The availability of quantum hardware via the cloud offers opportunities for new approaches to computing optimization problems in an industrial environment. However, selecting the right quantum hardware is difficult for non-experts due to its technical characteristics. In this paper, we present the QC-Adviser prototype, which supports users in selecting suitable quantum annealer hardware without requiring quantum computing knowledge.

Keywords

quantum annealing quantum computing

Cite

@article{arxiv.2505.07625,
  title  = {QC-Adviser: Quantum Hardware Recommendations for Solving Industrial Optimization Problems},
  author = {Djamel Laps-Bouraba and Markus Zajac and Uta Störl},
  journal= {arXiv preprint arXiv:2505.07625},
  year   = {2025}
}

Comments

GI Quantum Computing Workshop 2025

Related papers

View all related →

Information Retrieval · Computer Science

Feature Selection for Recommender Systems with Quantum Computing

Riccardo Nembrini, Maurizio Ferrari Dacrema, Paolo Cremonesi

2021-10-12

Optimization and Control · Mathematics

On the Emerging Potential of Quantum Annealing Hardware for Combinatorial Optimization

Byron Tasseff, Tameem Albash, Zachary Morrell, Marc Vuffray +3