Based Quantum Entanglement of Self-Adaptive Geometric Modeling

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel geometric modeling approach based on quantum entanglement, designed to simulate complex geometric structures with high precision and efficiency. The core of the system leverages the unique properties of entangled quantum states to dynamically adjust geometric parameters, allowing for automated optimization of the resulting geometry. The paper details the fundamental principles of this method, emphasizing the role of entanglement in achieving precise geometric representation and optimized parameter adjustment. We present a theoretical framework and initial experimental validation demonstrating the potential of this approach to address challenges in geometric modeling, particularly those involving intricate, dynamically evolving structures. The research explores the implications of entanglement in enhancing geometric fidelity and provides a foundation for future advancements in quantum-enhanced geometry.

DOI: 10.5281/zenodo.22197166

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