Quantum Geometry Adaptive Algorithm

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

This paper introduces a novel quantum geometry-based adaptive algorithm designed to precisely calculate and optimize geometric structures. Traditional optimization methods often rely on manual design, limiting efficiency. Our algorithm leverages the unique properties of quantum geometry to dynamically adjust its parameters, enabling accurate solutions across a wide range of geometric problems. This adaptive approach contrasts with conventional algorithms, offering significant improvements in speed and accuracy. The core mechanism centers on the algorithm's ability to map geometric transformations and constraints to quantum states, facilitating a form of "quantum intuition" in the optimization process. This paper details the algorithm's architecture, introduces key mathematical concepts, and presents preliminary results demonstrating its effectiveness in a series of challenging geometric optimization tasks.

DOI: 10.5281/zenodo.22242456

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