Quantum Topology: Adaptive Geometry Regularization

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum topology, a burgeoning field of physics, presents a unique challenge to traditional computational methods. The inherent fragility of quantum states necessitates careful consideration of their manipulation and preservation. This paper explores the application of adaptive geometry regularization to quantum systems, aiming to enhance their stability and computational efficiency. We propose a novel framework that leverages the self-organizing properties of quantum topology, specifically through a process of dynamic optimization. This optimization is driven by the inherent structure of the quantum system, resulting in a system that exhibits enhanced resilience to perturbations. The core mechanism centers on utilizing the self-similarity inherent in quantum topological configurations to guide the optimization process. This approach promises to overcome limitations in current quantum algorithms and potentially unlock new computational pathways.

DOI: 10.5281/zenodo.22220329

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