在可扩展的随机网络中统一非马科夫动力学和代理异质性
Aurélien Pélissier1,2,3, Miroslav Phan1,2, Didier Le Bail4
1IBM Research Europe, Rüschlikon, Switzerland.
Nature communications
|March 2, 2026
概括
我们开发了MOSAIC,这是一个新的计算框架,用于模拟具有个体代理差异的复杂系统. 这种方法准确地模拟了随机过程中的异质性和记忆,克服了古典方法的局限性.
科学领域:
- 计算生物学 计算生物学
- 复杂系统模拟复杂系统的模拟.
- 随机模型建模 随机模型建模
背景情况:
- 随机过程是许多科学领域的基础.
- 像吉尔斯皮算法这样的经典模拟方法受到同质性和马科维动力学假设的限制.
- 现实世界的系统经常表现出代理异质性和记忆效应,这些效应并未被现有模型所捕获.
研究的目的:
- 引入MOSAIC (具有个体复杂性的随机代理模型),一个新的计算框架.
- 为了能够准确的模拟随机系统与异质的代理和内存.
- 为现有方法提供可扩展和计算效率高的替代方案.
主要方法:
- 莫赛克将特定的特征直接嵌入到模拟动态中.
- 它将异质速率,动态交互偏好和非马科夫等待时间分布统一起来.
- 该框架保持了与吉尔斯皮式算法相比较的计算效率.
主要成果:
- 摩赛克成功地重现了传统方法遗漏的经验特征.
- 延迟生化反应,免疫细胞动态和社交网络的模拟证明了它的能力.
- 该框架捕捉了从代理异质性和记忆中产生的复杂行为.
结论:
- MOSAIC为模拟异质随机系统提供了一个通用和可扩展的解决方案.
- 它克服了经典方法的局限性,通过结合单个代理复杂性.
- 这使MOSAIC成为推进各种科学领域研究的实用工具.
相关概念视频
Entropy Change in Reversible Processes
In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
State Space Representation
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