Based Quantum Decoherence Distributed Computation (DBCQ)

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper proposes a novel approach to distributed computing leveraging the unique properties of quantum decoherence. The core idea centers around decomposing complex computational tasks into smaller, manageable sub-tasks that can be concurrently executed on a network of quantum nodes. By exploiting the inherent sensitivity of quantum systems to environmental interactions – specifically decoherence – we aim to achieve significant improvements in computational efficiency and enhanced security compared to classical distributed computing paradigms. The framework presented here offers a fundamentally different perspective, shifting from traditional error correction strategies to actively harnessing the effects of decoherence to guide the computation. The design incorporates specific algorithms tailored to maximize the benefits of decoherence, focusing on probabilistic outcomes and iteratively refining results. This approach introduces a degree of inherent randomness within the computation, which, when carefully managed, can be utilized to obfuscate intermediate results and improve security. The theoretical analysis details the key mathematical models and formulas underpinning the DBCQ framework, including decoherence rates, qubit fidelity, and the probabilistic convergence of solutions. This work provides a foundational understanding of this emerging field, laying the groundwork for future research and development in quantum-enhanced distributed computing.

DOI: 10.5281/zenodo.22336114

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