Quantum Adaptive Geometry Model

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum Adaptive Geometry Model explores the potential of utilizing quantum entanglement and self-adaptive mechanisms to revolutionize computational efficiency and precision. This research focuses on designing a quantum-based geometry model capable of automated geometric transformation optimization. The core claim posits that this model, through the combined effects of quantum entanglement and self-adaptation, will significantly enhance computational capabilities. This paper details the theoretical framework, proposed algorithm, and initial experimental results demonstrating the model's capability to adjust geometric transformations with minimal computational overhead. We will discuss the underlying mathematical principles and potential applications of this approach, emphasizing the benefits of quantum mechanics for geometric optimization.

DOI: 10.5281/zenodo.22205597

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