Adaptive Matrix Decomposition based on Quantum Topology

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper presents a novel algorithm for matrix decomposition based on quantum topology, aiming to significantly improve computational efficiency compared to traditional methods. The core mechanism leverages the unique properties of quantum topology to efficiently break down complex matrices, offering a fundamentally different approach to matrix factorization. We explore the design and implementation of this algorithm, detailing its key components and demonstrating its effectiveness through theoretical analysis and preliminary experimental results. The paper introduces a method that can handle larger matrices and provides a potential pathway towards more efficient computation in various applications.

DOI: 10.5281/zenodo.22204272

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