Physics of complex systems: emergent properties, criticality and dynamical networks

复杂系统物理学：涌现属性、临界性和动态网络

• 批准号: RGPIN-2020-05221
• 负责人: Davidsen, Joern
• 金额: $ 3.64万
• 依托单位: University of Calgary
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2021
• 资助国家: 加拿大
• 起止时间: 2021-01-01 至 2022-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=740462
• 关键词: Physics; complex; systems; emergent; properties

Physical, geophysical, chemical, living and man-made systems often show behaviors that cannot be understood by studying their building blocks or constituents to ever finer detail but that are emergent. The concept of emergence can be summarized by the statement that there exists an entity (e.g. an organism) which is more than the sum of its parts. This is often used as the defining property of a complex system. Many of these complex systems can be represented as a collection of dynamical units coupled via complex architectures. Complex network theory offers a unified description of these complex systems and has been invaluable in discovering unifying characteristics and principles despite the intrinsic differences between systems. Understanding these emergent characteristics and principles, their stability and the self-organization processes leading to them is one of the central quests of modern physics. Prominent examples include seismicity and neural signaling or biological signaling processes in general, with immense importance for society. A detailed understanding of seismicity is required to ensure successful seismic hazard assessment and to explore the possibility of successful earthquake prediction. A detailed understanding of the brain is essential to tackle brain related diseases such as Alzheimer's and epilepsy. The research program "Physics of complex systems: Emergent properties, criticality and dynamical networks" will establish new general concepts and data analysis tools to characterize and understand complex systems, will identify generic and universal properties by analyzing model systems and large scale data sets, and will collaborate with leading experimental groups to develop accurate theories for specific classes of systems. The phenomena under consideration include earthquake triggering in lab, natural and human-made settings as well as neuronal dynamics. We expect that our research will close a critical knowledge gap in our understanding of material failure, which is essential for progress in predicting the failure point. The proposed research will also allow us to develop probabilistic forecasting schemes suitable for seismicity induced by fluid injections. In addition, we anticipate that our unique study of the emergent properties in neuronal systems will enable us to make significant contributions to drug development related to neuronal diseases. This highlights the conceptual importance and far-reaching applications of this research program, promoting interdisciplinary approaches in general and the application of modern tools of statistical physics, nonlinear dynamics and complex network theory to fields outside the classical realm of physics in particular. At the same time, the research program will train highly qualified personnel and provide them with a unique, modern and interdisciplinary skill set benefiting the Canadian industry and Canada as a whole.

物理、地球物理、化学、生物和人造系统经常表现出一些行为，这些行为无法通过更详细地研究它们的组成部分或成分来理解，但这些行为是新兴的。涌现的概念可以用这样一句话来概括：存在一个实体(例如一个有机体)，它大于其各部分的总和。这通常被用作复杂系统的定义属性。这些复杂系统中的许多可以表示为通过复杂体系结构耦合的动态单元的集合。复杂网络理论提供了对这些复杂系统的统一描述，尽管系统之间存在内在差异，但它在发现统一的特征和原理方面具有无可估量的价值。理解这些涌现的特征和原理、它们的稳定性以及导致它们的自组织过程是现代物理学的中心任务之一。突出的例子包括地震活动和神经信号或生物信号过程，对社会具有巨大的重要性。需要对地震活动有详细的了解，以确保成功的地震危险性评估，并探索成功预测地震的可能性。对大脑的详细了解对于解决阿尔茨海默氏症和癫痫等与大脑相关的疾病至关重要。“复杂系统物理学：紧急性质、临界性和动态网络”的研究计划将建立新的一般概念和数据分析工具来表征和理解复杂系统，将通过分析模型系统和大规模数据集来确定通用和普遍性质，并将与领先的实验小组合作，为特定类别的系统开发准确的理论。正在考虑的现象包括实验室中的地震触发、自然和人为环境以及神经元动力学。我们预计，我们的研究将填补我们在理解材料失效方面的一个关键知识鸿沟，这对于预测故障点的进展至关重要。拟议的研究还将使我们能够开发适合于流体注入引起的地震活动的概率预测方案。此外，我们预计，我们对神经系统紧急特性的独特研究将使我们能够为与神经疾病相关的药物开发做出重大贡献。这突出了这一研究计划在概念上的重要性和深远的应用，促进了总体上的跨学科方法，特别是将统计物理、非线性动力学和复杂网络理论的现代工具应用于经典物理领域以外的领域。与此同时，该研究计划将培养高素质的人才，并为他们提供独特的、现代的和跨学科的技能，使加拿大工业和整个加拿大受益。