Adaptive Quantum State Topology Optimization Algorithm

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

This paper introduces an adaptive quantum state topology optimization algorithm designed to enhance quantum computing efficiency by dynamically adjusting quantum state parameters based on the system's evolving topology. Traditional optimization methods often rely on static parameters, limiting their ability to effectively handle dynamic topology. We propose a novel approach that leverages a quantum state's 'topological deformation' process to optimize quantum state parameters, resulting in improved performance. This algorithm utilizes a feedback mechanism to continuously refine the quantum state, addressing a significant limitation of existing approaches. The core mechanism involves a continuous transformation of the quantum state, guided by an optimization criterion, to achieve optimal performance within a defined range of possible states. This paper details the algorithm's design, validation through simulations, and potential future enhancements.

DOI: 10.5281/zenodo.22196742

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