Quantum Information-Driven Topological Structure Optimization

Jincheng Zhang

Published Sep 1, 2026• 0 citations

Abstract

Quantum information, a fundamentally different approach to information processing, offers the potential for novel solutions to complex optimization problems. This paper explores the application of quantum information principles to optimize complex topological structures, providing more precise predictions than existing methods. We propose a framework utilizing quantum entanglement and superposition to automatically adjust topological parameters, allowing for the simulation of intricate topological behaviors. This work represents a significant advancement in the field of topology optimization, leveraging the unique capabilities of quantum information to unlock new levels of precision and efficiency. The core mechanism centers around quantum-enhanced parameter mapping, facilitating the exploration of a broader range of topological configurations. This represents a fundamentally new approach to topology optimization, moving beyond traditional geometric methods to exploit the inherent quantum properties of the system.

DOI: 10.5281/zenodo.22222535

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