Quantum-Inspired Topology for Optimization – Adaptive Representation

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper explores the application of quantum-inspired topology to optimization, specifically focusing on the development of a novel method for representing and manipulating complex landscape structures. The core claim is that by leveraging non-linear relationships and entanglement principles, we can create a topology that guides the search process more effectively, leading to improved solution quality. The proposed framework introduces a dynamically adjusted representation of the search space, enabling adaptive exploration and mitigating the limitations of traditional optimization techniques. We detail the mathematical foundation of this approach, including the key topological invariants and their impact on the search dynamics. The paper will discuss the advantages of this methodology, including increased efficiency, improved exploration of the search space, and the potential for discovering novel solutions.

DOI: 10.5281/zenodo.22299733

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