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Hauptverfasser: Remme, Lian, Weinert, Alexander, Waschk, Andre
Format: Preprint
Veröffentlicht: 2025
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Online-Zugang:https://arxiv.org/abs/2505.12853
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author Remme, Lian
Weinert, Alexander
Waschk, Andre
author_facet Remme, Lian
Weinert, Alexander
Waschk, Andre
contents Quantum computers do not run in isolation; rather, they are embedded in quantum-classical hybrid architectures. In these setups, a quantum processing unit communicates with a classical device in near-real time. To enable efficient hybrid computations, it is mandatory to optimize quantum-classical hybrid code. To the best of our knowledge, no previous work on the optimization of hybrid code nor on metrics for which to optimize such code exists. In this work, we take a step towards optimization of hybrid programs by introducing seven optimization routines and three metrics to evaluate the effectiveness of the optimization. We implement these routines for the hybrid quantum language Quil and show that our optimizations improve programs according to our metrics. This lays the foundation for new kinds of hybrid optimizers that enable real-time collaboration between quantum and classical devices.
format Preprint
id arxiv_https___arxiv_org_abs_2505_12853
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Optimization of Hybrid Quantum-Classical Algorithms
Remme, Lian
Weinert, Alexander
Waschk, Andre
Distributed, Parallel, and Cluster Computing
Quantum computers do not run in isolation; rather, they are embedded in quantum-classical hybrid architectures. In these setups, a quantum processing unit communicates with a classical device in near-real time. To enable efficient hybrid computations, it is mandatory to optimize quantum-classical hybrid code. To the best of our knowledge, no previous work on the optimization of hybrid code nor on metrics for which to optimize such code exists. In this work, we take a step towards optimization of hybrid programs by introducing seven optimization routines and three metrics to evaluate the effectiveness of the optimization. We implement these routines for the hybrid quantum language Quil and show that our optimizations improve programs according to our metrics. This lays the foundation for new kinds of hybrid optimizers that enable real-time collaboration between quantum and classical devices.
title Optimization of Hybrid Quantum-Classical Algorithms
topic Distributed, Parallel, and Cluster Computing
url https://arxiv.org/abs/2505.12853