基于非线性矩阵的自适应量子计算框架

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper presents a novel quantum computing framework based on non-linear matrix optimization. Traditional quantum computing paradigms often rely on static algorithms, limiting the potential for adaptive and efficient computation. Our approach utilizes a dynamically adjusted matrix to guide the evolution of quantum states, enabling a significant enhancement in the performance of quantum algorithms. The core mechanism involves the creation of a dynamically evolving matrix that adjusts to the specific characteristics of each quantum state, optimizing the computation process. This results in increased computational efficiency, particularly for complex quantum algorithms. The research explores the potential of this framework through a theoretical analysis and preliminary implementation demonstrating improved performance compared to existing approaches. The study investigates the impact of matrix structure and optimization techniques on achieving this enhanced performance.

DOI: 10.5281/zenodo.22617363

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