Adaptive Quantum Algorithm Parallel Expansion Strategy

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces an adaptive quantum algorithm parallel expansion strategy designed to optimize computational performance in quantum computing environments. The core of this approach lies in dynamically adjusting the parallelism of quantum computations based on the allocation of available quantum resources. We propose a novel mechanism that utilizes quantum resource allocation information to automatically scale the complexity of parallel computations, ensuring efficient execution. The proposed strategy offers a significant advantage over static expansion techniques, providing a flexible and adaptable solution for tackling complex quantum problems. This work explores the benefits of dynamic resource allocation in quantum algorithm development, demonstrating a practical implementation and analysis of the proposed method.

DOI: 10.5281/zenodo.22268431

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