基于自适应的量子态预测算法

Jincheng Zhang

Published Aug 31, 2026• 0 citations

Abstract

Quantum computing holds immense potential for revolutionizing various fields, and the accurate prediction of quantum states is crucial for realizing this potential. Traditional approaches often rely on computationally intensive models that struggle to adapt to the complex dynamics of quantum systems. This paper introduces a novel self-adaptive quantum state prediction algorithm designed to address this challenge. The algorithm learns from the instantaneous evolution of quantum states, dynamically adjusting its prediction models to achieve improved accuracy and efficiency. We present a comprehensive analysis of the algorithm's performance, demonstrating its effectiveness in predicting quantum state transitions, and exploring its potential for enhancing quantum computation.

DOI: 10.5281/zenodo.22190072

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