Quantum Entanglement Adaptive Model (QCAM)

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum entanglement, a bizarre phenomenon where two or more particles become inextricably linked, holds immense promise for revolutionizing quantum computing and quantum communication. This research introduces the Quantum Entanglement Adaptive Model (QCAM), a novel approach to quantum system optimization that leverages the dynamic nature of entangled states. Traditional quantum algorithms often rely on pre-defined parameters, limiting their adaptability. QCAM dynamically adjusts quantum system parameters based on the evolution of entangled states, enabling a more intelligent and efficient approach to quantum computation and communication. This work presents a framework for designing a quantum system capable of optimizing its behavior through the subtle yet profound effects of entangled states. The core claim is that QCAM will provide a significant advancement over existing quantum algorithms, particularly in scenarios involving complex and evolving entangled states.

DOI: 10.5281/zenodo.22275049

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