没有平衡的统计力学由Doob h转换和变量自回归网络揭示
Yixin Zhao1,2,3, Ying Tang4,5, Pan Zhang1,2
1School of Fundamental Physics and Mathematical Sciences, Hangzhou Institute for Advanced Study, UCAS, Hangzhou 310024, China.
本研究引入了一种使用变量自回归网络 (VAN) 来分析随机系统中罕见事件的新方法. 它可以采样概率分布,并计算复杂动态的大偏差统计.
科学领域:
- 非平衡的统计力学.
- 计算物理学的计算物理.
- 随机过程是指随机的过程.
背景情况:
- 描述非平衡动态通常涉及概率分布和轨迹合集.
- 罕见的时空过程至关重要,但对研究具有挑战性.
- 杜布动态有效地样本罕见的轨迹,但与概率分布的演变扎.
研究的目的:
- 开发一种方法来采样罕见轨迹的概率分布的时间演变.
- 为了实现对罕见事件的大偏差统计的计算.
- 扩大Doob动态在分析复杂的随机系统中的应用.
主要方法:
- 通过近似倾斜发电机的领先固态来构建Doob动态.
- 使用变量自回归网络 (VAN) 作为一个关键的替代品.
- 将该方法应用于东方和弗雷德里克森-安德森格子模型.
主要成果:
- 成功采样了罕见轨迹的概率分布的时间演变.
- 对一维和二维格子模型进行计算的大偏差统计.
- 证明了基于VAN的Doob动态方法的有效性.
结论:
- 拟议的基于VAN的Doob动态方法有效地捕捉了罕见的轨迹动态和概率分布.
- 这种方法推进了对非平衡系统和大偏差理论的研究.
- 需要进一步的研究来解决当前方法的局限性.
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