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Quantum Geometry: Adaptive Topology Algorithm

Jincheng Zhang

Published Sep 6, 2026• 0 citations
Publisher

Abstract

Quantum Geometry explores the intersection of quantum mechanics and geometry, investigating the interplay between quantum states and topological properties. This paper introduces an adaptive topology algorithm designed to address the limitations of traditional topological data analysis, leveraging quantum entanglement to dynamically construct and manipulate topological structures. We propose a novel method that utilizes quantum entanglement to simulate self-learning and evolution within a quantum framework, ultimately enabling efficient and flexible processing of topological information crucial for quantum computation. The core mechanism centers around the application of entangled qubits to iteratively refine and expand topological landscapes, achieving a level of precision and adaptability unattainable with conventional methods. The paper demonstrates the efficacy of this approach through a series of simulations illustrating the algorithm's ability to generate complex topological patterns. We highlight the potential impact of this algorithm on the development of robust quantum algorithms and the exploration of novel topological phenomena.

DOI
10.5281/zenodo.22476631

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