Quantum Topological Optimization of Hidden Matrices

Jincheng Zhang

Published Sep 3, 2026• 0 citations

Abstract

Quantum topological optimization is a rapidly growing field with the potential to revolutionize quantum computing. This paper investigates a novel approach to optimizing hidden matrix properties using a dynamically adjusted topology. We introduce a quantum topological deformation mechanism that allows the algorithm to automatically tailor the structure of hidden matrices based on the specific characteristics of the target task. This optimization aims to enhance quantum computation efficiency. The core mechanism involves leveraging the inherent topological properties of quantum states to dynamically adjust the matrix's structure. The algorithm demonstrates a significant improvement in the performance of quantum computations compared to traditional approaches. This work presents a new framework for optimizing quantum matrix properties, offering a pathway towards more efficient and robust quantum algorithms.

DOI: 10.5281/zenodo.22265715

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