Machine-Aided General Framework for Fluctuating Dynamic Density Functional Theory (MAGFFDDFT)

波动动态密度泛函理论的机器辅助通用框架 (MAGFFDDFT)

• 批准号: EP/X038645/1
• 负责人: Serafim Kalliadasis
• 金额: $ 195.56万
• 依托单位: Imperial College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2023
• 资助国家: 英国
• 起止时间: 2023 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FX038645%2F1
• 关键词: Machine; Aided; General; Framework; Fluctuating

Many-body systems are ubiquitous in nature, ranging from stellar clusters to soft matter and down to the quantum scale of electrons. Classical fluids are many-body systems at sufficiently high temperatures that quantum effects can be neglected, and which can be easily deformed or structurally altered by external forces and thermal fluctuations. Hence, classical fluids encompass a wide spectrum of simple and complex systems often inherently multiscale. As a result, fluids often exhibit complex behaviour characterised by phase transitions, critical phenomena and emergent properties. Apart from the purely theoretical interest, fluids are central in a wide spectrum of natural phenomena and applications. Not surprisingly, they have been an active topic of both fundamental and applied research for several decades. Major advances, often from statistical mechanics, include the development of coarse-grained models for the evolution of observables by averaging out the microscopic properties and retaining the main effects at the macroscale. However, despite the considerable attention a large number of problems remain unresolved. In particular, existing models suffer from serious limitations including unknown functions-parameters and assumptions-simplifications, e.g. close-to-equilibrium conditions, which often restrict their applicability to largely idealised systems. The aim of the proposed research is to develop a machine-aided generic theoretical-numerical framework that would overcome existing limitations and shortcomings and would allow us to obtain rationally and systematically optimal low-dimensional general laws governing the dynamics of observables, which in turn can be used for the accurate, efficient and systematic analysis of classical fluids and complex multiscale systems in general. This in turn would allow us to advance our understanding of observable dynamics in a wide spectrum of areas, from engineering and physics which so far lack a formal unified framework.

多体系统本质上是普遍存在的，从恒星簇到软物质，再到电子的量子标度。经典的流体是在足够高的温度下可以忽略量子效应的多体系统，并且可以很容易地通过外力和热波动对其进行变形或结构改变。因此，经典的流体涵盖了广泛的简单和复杂的系统通常是固有的多尺度。结果，流体通常表现出复杂的行为，其特征是相变，关键现象和新兴特性。除了纯粹的理论兴趣外，流体在各种自然现象和应用中都是中心的。毫不奇怪，几十年来，它们一直是基本和应用研究的积极主题。通常来自统计力学的主要进步包括开发通过平均显微镜特性并保留在宏观上的主要效应来开发可观察到的粗粒模型。然而，尽管有很大的关注，许多问题仍未解决。特别是，现有模型受到严重局限性，包括未知的功能参数和假设简化，例如接近平衡的条件通常会限制其在很大程度上是理想化系统的适用性。拟议研究的目的是开发一个机器辅助的通用理论数字框架，该框架将克服现有的局限性和缺点，并使我们能够以理性和系统地最佳的最佳低维度一般规律获得，依次是可观察到的动态，这反过来又可以通常，用于对经典流体和复杂多尺度系统进行准确，高效和系统的分析。反过来，这将使我们能够从迄今为止缺乏正式的统一框架的工程和物理学来提高对广泛领域的可观察动态的理解。