Collaborative Research: NSCI: SI2-SSE: Time Stepping and Exchange-Correlation Modules for Massively Parallel Real-Time Time-Dependent DFT

高性能(HPC)计算的最新进展可以模拟复杂材料中电子的量子动力学，这种模拟对于推进各种医疗和半导体技术至关重要，从质子束癌症治疗到制造速度更快、更小的电子产品。与此同时，现代高性能计算机日益增长的规模和复杂性暴露了开发科学软件的需求，这种软件是为拥有大量处理器的计算机量身定做的，以便模拟可以有效地利用日益增长的计算能力。这个项目为拥有数万和数十万处理器的高性能计算机开发了用于模拟电子量子动力学的科学软件，这些计算机正在变得越来越普遍。这项工作围绕拟议的软件建立了HPC学术研究社区，通过扩展现有的可用于量子动力学模拟的软件，使其具有更好的用户友好特性和分析技术。在这个过程中，这个项目邀请研究生和职业生涯早期的研究人员使用并进一步开发一般高性能计算机的科学软件。此外，还将举办暑期实习班，进行动手培训。开源软件将在Github(公共存储库)上向社区提供。含时密度泛函理论中的实时传播理论(RT-TDDFT)无论是在线性区域还是在线性响应之外的非平衡电子动力学研究中都变得越来越流行。RT-TDDFT可以结合在Ehrenfest动力学中研究量子力学电子与经典离子运动的耦合动力学。尽管RT-TDDFT有着巨大的前景，但它在计算上要求非常高，特别是对于研究大型凝聚态系统。巨大的成本来自电子动力学数值积分的小时间步长，使得精确的(混合)交换关联(XC)泛函不可行，尽管它们有明显的好处。此外，虽然现代高性能计算(HPC)有助于解决重大科学问题，但大规模并行、混合范例架构提出了新的挑战。为了充分利用现代大规模并行高性能计算的优势，需要发展理论和算法方法。这项工作为QB@ll程序的RT-TDDFT软件组件建立了新的模块，使大量研究人员能够使用大规模并行HPC对复杂凝聚相系统中的非平衡电子动力学进行高级第一性原理模拟。这是通过开发(1)高效率和高精度地实时传播基本非线性偏微分方程组的新的数值积分模块和(2)使用现代亚广义梯度XC泛函改进基本电子结构的近似的新模块来实现的。此外，这项工作通过(1)开发界面友好的功能，将QB@ll与其他代码和分析技术连接起来，以及(2)通过在TDDFT暑期学校使用QB@ll代码纳入关于RT-TDDFT的实践培训，建立了围绕QB@ll代码的RT-TDDFT的HPC学术研究社区。该项目得到了计算机和信息科学与工程局的高级数字基础设施办公室、数学和物理科学局的材料研究司和化学司的支持。

Recent advances in high-performance (HPC) computing allow simulations of quantum dynamics of electrons in complex materials, and such simulations are central to advancing various medical and semiconductor technologies, ranging from proton beam cancer therapy to fabricating faster and smaller electronics. At the same time, the increasing scale and complexity of modern high-performance computers exposed a need for development of scientific software that is tailored for computers with large numbers of processors so that simulations can efficiently take advantage of increasing computing power. This project advances scientific software for simulating quantum dynamics of electrons for high-performance computers with tens and hundreds of thousands of processors that are becoming widely available. This work builds the HPC academic research community around the proposed software by extending the existing software available for quantum dynamics simulation with better user-friendly features and analysis techniques. In the process, this project engages graduate students and early-career researchers to use and further develop scientific software for high-performance computers in general. Additionally, a summer school for hands-on training will be conducted. The open source software will be made available to the community on Github (public repository). Real-time propagation in time-dependent density functional theory (RT-TDDFT) is becoming increasingly popular for studying non-equilibrium electronic dynamics both in the linear regime and beyond linear response. RT-TDDFT can be combined to study coupled dynamics of quantum-mechanical electrons with the movement of classical ions within Ehrenfest dynamics. In spite of its great promise, RT-TDDFT is computationally very demanding, especially for studying large condensed-matter systems. The large cost arises from small time steps of numerical integration of the electron dynamics, rendering accurate (hybrid) exchange-correlation (XC) functionals unfeasible, despite their clear benefits. In addition, while modern high-performance computing (HPC) helps tackling great scientific questions, massively parallel, hybrid-paradigm architectures present new challenges. Theoretical and algorithmic methods need to be developed in order to take full advantage of modern massively parallel HPC. This work builds new modules for the RT-TDDFT software component of the Qb@ll code, that enables a large community of researchers to perform advanced first-principles simulations of non-equilibrium electron dynamics in complex condensed-phase systems, using massively parallel HPC. This is done through developing (1) new modules for numerical integration that propagate the underlying non-linear partial differential equations in real time with high efficiency and accuracy, and (2) new modules for improved approximations of the underlying electronic structure, using a modern meta-generalized-gradient XC functional. Furthermore, the work builds the HPC academic research community around RT-TDDFT within the Qb@ll code through (1) development of user-friendly features that interface Qb@ll with other code and analysis techniques and (2) engagement of early-career scientists by incorporating hands-on training on RT-TDDFT using the Qb@ll code in TDDFT summer school.This project is supported by the Office of Advanced Cyberinfrastructure in the Directorate for Computer and Information Science and Engineering, the Materials Research Division and Chemistry Division in the Directorate of Mathematical and Physical Sciences.