基于量子纠缠的非线性矩阵的自适应计算

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

This paper introduces a novel approach to matrix computation utilizing the unique properties of quantum entanglement. Traditional matrix operations are fundamentally limited by classical computational constraints. We propose a method that leverages entanglement to enable a fundamentally more efficient and stable computation compared to conventional algorithms. The core of this work lies in the design of a quantum-enhanced matrix transformation process, driven by entangled qubits. This approach offers the potential for exponential speedups in certain matrix-based computations, particularly those involving complex eigenvalue problems. The paper details the mathematical framework underpinning this quantum computation, including the representation of entangled states, the quantum transformation steps, and the resulting computational efficiency. We demonstrate the effectiveness of this method through theoretical analysis and preliminary numerical simulations, showcasing its potential for revolutionizing matrix operations.

DOI: 10.5281/zenodo.22291028

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