Core Claim: Design a self-adaptive topological quantum computing framework for predicting quantum system evolution, and provide more effective quantum algorithm design.

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing offers the potential for exponentially faster computations compared to classical computers, but the design and optimization of quantum algorithms remain a significant challenge. This research explores a novel approach to quantum system evolution prediction using a self-adaptive topological framework. We propose a dynamic modeling strategy that leverages topology to represent the evolution of quantum states, allowing for the prediction of complex quantum behavior. The framework incorporates a continuous, self-consistent evolution process, enabling the identification of key transition points and the generation of more effective quantum algorithms. This work represents a significant advancement in quantum system dynamics prediction, offering a robust and adaptable methodology for exploring and designing new quantum algorithms. The core of our approach lies in the creation of a self-adaptive topology that evolves alongside the quantum system, providing a dynamic and predictive tool. This dynamic evolution, coupled with our modeling approach, promises to significantly enhance the efficiency and versatility of quantum computation. Specifically, we demonstrate the framework's ability to accurately predict the behavior of various quantum systems, including those exhibiting complex entanglement dynamics, opening doors to the development of novel quantum algorithms.

DOI: 10.5281/zenodo.22186224

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