Title: Adaptive Topology for Optimization – Quantum-Enhanced Topology Adjustment

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the application of adaptive topology for optimization, utilizing quantum entanglement to accelerate the convergence of optimization algorithms. Traditional optimization methods often struggle with complex, high-dimensional spaces, necessitating computationally intensive search procedures. We introduce a novel technique that dynamically adjusts the topology of the problem space during optimization, leveraging quantum entanglement to create correlations between variables and enhance the evaluation of potential solutions. This approach aims to overcome the limitations of conventional methods by enabling a more holistic and flexible assessment of the search space. The core mechanism involves creating entangled pairs of variables, allowing for a more efficient exploration of the solution space. We demonstrate the effectiveness of this method through a series of simulations, showcasing significant improvements in convergence speed and solution quality compared to existing techniques. The potential implications of this research extend beyond optimization, potentially offering new insights into quantum information processing and computational geometry.

DOI: 10.5281/zenodo.22302383

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