Self-Adaptive Spin Quantum Computing Algorithm

Jincheng Zhang

Published Sep 5, 2026• 0 citations

Abstract

This paper introduces a novel self-adaptive spin quantum computing algorithm designed to enhance computational precision and efficiency. Traditional spin adjustment mechanisms often rely on fixed parameter settings, limiting the algorithm's capabilities. We propose a dynamic adjustment strategy that adapts the spin parameters during the computation process. This adaptive approach allows for finer control of the spin state, leading to improved performance in complex calculations. The core mechanism involves a feedback loop that continuously monitors and adjusts the spin parameters based on the current state of the computation, thereby optimizing the outcome. We present a detailed analysis of the algorithm's performance and discuss its potential applications in various quantum computing tasks.

DOI: 10.5281/zenodo.22325722

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