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关于旧金山天气的量子信息分析
Yasser Kotb1, Amr A Youssef2, Dieaa I Nassr3
1College of Computer and Information Sciences, Imam Mohammed Ibn Saud Islamic University (IMSIU), Riyadh, Saudi Arabia.
Scientific reports
|January 26, 2026
概括
本研究引入了一种量子启发的框架,用于分析2009-2019年旧金山的天气数据. 它应用量子信息理论指标来揭示时间模式并预测未来的天气数据.
科学领域:
- 综合气象学和量子信息理论的跨学科科学.
- 开发用于经典数据分析的新型分析框架.
背景情况:
- 经典的天气数据集对传统的分析方法构成挑战.
- 量子信息理论为数据表示和分析提供了独特的工具.
研究的目的:
- 为旧金山的天气数据 (2009-2019) 开发和应用一个量子启发的分析框架.
- 用量子信息理论指标分析时间模式和结构性质.
- 为2020-2021年提供关键指标的预测.
主要方法:
- 用希尔伯特空间中的密度矩阵将经典的天气数据转换为类似量子的表示.
- 使用量子信息理论指标,如忠实性, (Shannon,von Neumann) 和量子稳定性指数.
- 应用福里埃序列模型用于时间模式分析和预测.
主要成果:
- 成功地将量子信息理论指标应用于经典天气数据集.
- 在天气数据中识别时间模式和结构性质.
- 为2020年和2021年生成量子信息指标的预测.
结论:
- 量子启发的框架为分析经典气象数据提供了一种新的方法.
- 量子信息理论指标为数据结构和时间动态提供了宝贵的见解.
- 该方法表明在时间序列分析中具有更广泛应用的潜力.
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