复杂系统的动态理论,具有双向微观-宏观因果关系
John Harte1,2,3, Micah Brush4, Kaito Umemura5
1The Energy and Resources Group, University of California, Berkeley, CA 94720.
概括
本研究介绍了一种动态理论,它结合了自上而下的推断和自下而上的机制,以建模复杂的,规模交织的系统. 该理论预测了系统对干扰的反应,并解释了诸如hysteresis之类的现象.
科学领域:
- 对复杂系统的多学科方法.
- 理论物理学和应用科学 理论物理学和应用科学
背景情况:
- 复杂的系统表现出微观动态,依赖于宏观变量.
- 规模交织系统需要综合建模方法,因为自上而下或自下而上的方法是不够的.
研究的目的:
- 开发和探索一个集成自上而下的信息理论推理与自下而上的机制的动态理论.
- 为了预测受到扰乱的规模交织系统的行为.
主要方法:
- 开发了一个动态理论,结合了信息理论推理和状态变量依赖机制.
- 使用了来自Maxent解决方案的拉格朗日乘数的分析表达式,以实现高效的计算.
- 将理论应用于各种系统,包括化学热力学,流行病学,经济学和生态学.
主要成果:
- 该理论预测了非静止的概率分布,并将宏观变量轨迹与这些分布联系起来.
- 经过证明的尺度交织导致缓慢恢复,变红的光谱和低维示例中的歇斯底里.
- 能够快速计算高维系统中的状态变量轨迹.
结论:
- 综合理论为理解和预测规模交织的复杂系统的行为提供了一个强大的框架.
- 突出了在自然科学和社会科学中广泛适用的潜力.
- 提供了诸如歇斯底里斯和由于尺度交织而改变的系统动态等现象的见解.
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