基于自适应拓扑的量子态分析与优化

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces a novel approach to quantum state analysis and optimization based on adaptive topology. Traditional methods often struggle with complex quantum states, requiring computationally intensive analysis. We propose a framework where the topology of the quantum state is dynamically adjusted during analysis and optimization. This dynamic adaptation significantly improves the efficiency and robustness of quantum computations. The core mechanism leverages a self-consistent topological structure to model the state's evolution, enabling targeted optimization of key quantum properties. We demonstrate the effectiveness of this method through simulations and preliminary results, highlighting its potential to address limitations of existing techniques.

DOI: 10.5281/zenodo.22200111

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