Quantum Decoherence Dynamics Control and Resource Allocation

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum decoherence, traditionally viewed as a detrimental noise source hindering quantum computation, is presented here as a potentially controllable resource. This research explores the dynamic control of decoherence processes to facilitate resource allocation and optimization within quantum computing. A probabilistic model-based decoherence control algorithm is proposed, leveraging the inherent probabilistic nature of decoherence. This algorithm is then integrated with resource allocation problems, demonstrating the possibility of manipulating decoherence to enhance quantum computation performance. The core claim highlights the shift in perspective – transforming decoherence from a purely negative factor into an actively managed component. The investigation focuses on achieving dynamic control and optimization through precise manipulation of decoherence rates. The theoretical framework and proposed algorithm provide a new approach to quantum computing, moving beyond simply mitigating decoherence to actively harnessing its properties. ---

DOI: 10.5281/zenodo.22202713

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