Self-Adaptive Quantum Potential Optimization

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum computing is a rapidly advancing field with tremendous potential for scientific discovery and technological innovation. However, current quantum algorithms often suffer from limitations in scalability and robustness, hindering their widespread adoption. This paper introduces a novel approach to quantum potential optimization, leveraging the power of topology to create adaptable quantum systems. We explore the use of topological structures to design quantum potentials, effectively optimizing them to enhance quantum computation's efficiency and stability. The core mechanism involves constructing a topological structure that dynamically adjusts the quantum potential based on the specific characteristics of the target quantum system. This offers a promising path towards overcoming the challenges of traditional optimization techniques and enabling the development of more versatile and reliable quantum devices. This work is motivated by the inherent properties of topology and its ability to generate complex, self-similar patterns, suggesting a robust and adaptable framework for quantum system design. The presented methodology provides a new perspective on quantum potential optimization, opening avenues for enhanced device performance and broadened applicability.

DOI: 10.5281/zenodo.22295213

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