Quantum Resource Allocation Based on Quantum Demagnetization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates a novel approach to optimizing quantum computing resource allocation, leveraging the inherent characteristics of quantum demagnetization (decoherence). Traditional quantum resource allocation methods often rely on heuristic rules or empirical observations, lacking a fundamental understanding of the resource consumption mechanisms within a quantum system. This work posits that decoherence, a primary source of error and resource depletion in quantum computation, can be explicitly modeled and utilized as a constraint within an optimization framework. We present a methodology for allocating quantum resources—specifically, qubit assignments and gate scheduling—based on a dynamic assessment of decoherence rates. The core concept involves formulating a mathematical model where decoherence is treated as a cost function, and employing optimization algorithms to minimize this cost while satisfying computational requirements. The proposed method offers a potentially more efficient and targeted approach to resource allocation, leading to improvements in quantum computation efficiency and potentially mitigating the detrimental effects of decoherence. The results demonstrate the feasibility and effectiveness of this approach in theoretical scenarios.

DOI: 10.5281/zenodo.22191118

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