Title: Adaptive Quantum Computation Algorithm for Topological Optimization

Jincheng Zhang

Published Sep 2, 2026• 0 citations

Abstract

Quantum computation is rapidly advancing, demanding sophisticated algorithms for simulation and optimization. Traditional methods often rely on manual parameter tuning, limiting scalability and efficiency. This paper introduces an adaptive quantum computation algorithm based on topological optimization, leveraging the non-local properties of quantum entanglement to dynamically model quantum states and enhance the accuracy of physical simulations and numerical calculations. We propose a novel framework that automatically adjusts quantum parameters to optimize performance. This approach offers a significant advancement over existing techniques, providing a robust and automated solution for complex quantum computations. The core mechanism centers around exploiting the inherent dynamics of quantum systems through topological structures, enabling adaptive optimization of quantum states. The algorithm's design directly addresses the limitations of traditional quantum computing by automating the optimization process. This work aims to provide a foundation for developing more efficient and scalable quantum algorithms.

DOI: 10.5281/zenodo.22251330

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