Self-Adaptive Topological Transformations for Quantum Computing

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper investigates the potential of self-adaptive topological transformations for enhancing the efficiency and stability of quantum computation. Traditional quantum algorithms often suffer from limitations in robustness and scalability, prompting the exploration of novel approaches. We propose a new method leveraging the unique properties of topological quantum states to dynamically adjust the geometry of the qubit system, mitigating errors and enhancing computational capabilities. This research focuses on the design of a self-adaptive transformation process that adapts to the specific noise characteristics of the quantum hardware, thereby improving overall performance. The core claim centers on the utilization of self-adaptive topological transformations to overcome inherent challenges in quantum computation. This work presents a novel framework demonstrating improved fidelity and extended coherence times in quantum simulations and computations. We aim to provide a foundation for future advancements in quantum information processing.

DOI: 10.5281/zenodo.22322076

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