Quantum Matrix Solving Algorithm: An Adaptive Approach

Jincheng Zhang

Published Sep 4, 2026• 0 citations

Abstract

Quantum matrix solving is a challenging problem in cryptography and optimization, particularly when dealing with complex geometries and nonlinear errors. Traditional methods often require precise parameter adjustments, which can be computationally expensive and susceptible to errors. This paper proposes an adaptive quantum matrix solving algorithm that leverages quantum entanglement and superposition to dynamically adjust parameters during the solving process, offering improved efficiency and robustness. We present a novel mechanism utilizing these quantum phenomena to overcome limitations of existing techniques. This algorithm demonstrates potential for enhanced performance in scenarios demanding high accuracy and resilience against noise.

DOI: 10.5281/zenodo.22291717

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