Nonlinear Quantum Adaptive Geometry Modeling

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

This paper introduces a novel approach to geometry modeling utilizing nonlinear quantum adaptive geometry transformations. We propose a method that transforms complex geometric models into adaptable geometric models, enabling self-adaptive deformation within the model. The core mechanism involves a quantum process that dynamically adjusts geometric parameters based on a feedback loop, resulting in a highly flexible and responsive model. This approach offers significant advantages over traditional methods, particularly in handling intricate geometries and complex deformations. This research addresses the limitations of existing techniques by introducing a fundamentally new method that leverages quantum mechanics to achieve a level of adaptability not previously attainable. This work demonstrates the feasibility and potential of this approach through mathematical analysis and illustrative examples.

DOI: 10.5281/zenodo.22266693

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