在异构的扩散系统中,非马科夫式的路径实现一致性
1Bhabha Atomic Research Centre, University of Bayreuth, Experimental Physics I, Universitätsstr. 30, 95447 Bayreuth, Germany and Radiation & Photochemistry Division, Mumbai 400085, India.
Physical review. E
|December 23, 2025
概括
我们引入了一种新的代理协调模型,即合记忆图过程 (CMGP),即使具有不同的代理动态,也可以实现持续的对齐. 这种"幽灵连贯性"来自于出现的相关性,而不是直接的重叠.
科学领域:
- 统计物理 统计物理
- 复杂的系统复杂的系统.
- 活动物质 活动物质
背景情况:
- 时间连贯性 (持续对齐) 可以在具有不同的动态的代理之间出现.
- 经典的扩散模型在代理动态中与强烈的异质性和不对称性作斗争.
- 现有的模型往往需要互惠或共同的噪声进行同步.
研究的目的:
- 引入一种新型模型,即合记忆图过程 (CMGP),以实现时间连贯性.
- 为了证明CMGP能够在没有互惠或共同噪音的情况下产生同步行为.
- 探索"幽灵连贯性"的现象 - - 在异质系统中没有轨迹融合的连贯性.
主要方法:
- 结合记忆图过程 (CMGP) 模型的开发.
- 分析由定向,距离合产生的新出现的远距离相关性.
- 使用贝叶斯优化来识别支持幽灵连贯性的参数区域.
主要成果:
- CMGP 实现了超过固有的内存时间的长时间连贯性,即使与扩展指数不匹配.
- 连贯性的持久性来自于合场内出现的相关性,而不是直接的内核重叠.
- 确定了广泛的参数区域,支持"幽灵连贯性",同时保持独特的代理动态.
结论:
- 在异质活性系统和粘弹性环境中,CMGP提供了一个最小的协调机制.
- 这个机制捕获了同步现象,这些现象在不对称的标准随机模型下无法解释.
- 突出了在复杂系统中实现协调行为时出现的相关性的重要性.
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