Dynamic Quantum Matrix Self-Organization

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper investigates the dynamic computation of self-organized quantum matrices, aiming to develop a novel matrix multiplication framework based on quantum computation. The core focus is on achieving rapid computation through the inherent properties of self-organized quantum structures. We explore a method predicated on leveraging the dynamics of these matrices to drastically reduce computational complexities. The research presents a new approach to matrix operations that leverages quantum algorithms for enhanced performance and efficiency. The paper outlines the key concepts and proposes a preliminary implementation of the framework, demonstrating the potential of self-organized quantum matrices for dynamic matrix computation. This work represents a significant step towards more efficient matrix operations, particularly when dealing with complex or large matrices. The investigation delves into the potential of self-organization as a building block for improved computational capabilities.

DOI: 10.5281/zenodo.22191729

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