Adaptive Algorithm for Topological Quantum Computing Based on Non-linear Topology

Jincheng Zhang

Published Sep 7, 2026• 0 citations

Abstract

This paper introduces a novel adaptive algorithm for Topological Quantum Computing (TQC) that leverages the dynamic adjustment of optimization parameters based on quantum state variations. Traditional optimization algorithms often rely on fixed, pre-defined parameters, limiting their effectiveness in complex quantum systems. This algorithm dynamically adjusts these parameters to optimize the quantum state, resulting in improved efficiency and accuracy in quantum computations. The core mechanism involves analyzing the quantum state's evolution and automatically modifying optimization parameters to achieve a desired outcome. This adaptive approach addresses a critical limitation of existing optimization methods, offering a promising pathway towards enhanced quantum algorithm performance. We present a theoretical framework and preliminary experimental validation demonstrating the efficacy of this approach.

DOI: 10.5281/zenodo.22625107

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