CAREER: Turbo-Charging Hybrid Functional Electronic Structure Calculations via Adaptive Compression Methods

职业：通过自适应压缩方法进行涡轮增压混合功能电子结构计算

• 批准号: 1652330
• 负责人: Lin Lin
• 金额: $ 40万
• 依托单位: University of California-Berkeley
• 依托单位国家: 美国
• 项目类别: Continuing Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-05-01 至 2023-04-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1652330&HistoricalAwards=false
• 关键词: CAREER; Turbo; Charging; Hybrid; Functional

This project aims to improve numerical methods for the simulation of electronic structure in atoms and molecules. Electronic structure theories, particularly represented by Kohn-Sham density functional theory (KS-DFT), have been developed into workhorse tools with a wide range of applications in physics, chemistry, materials science, and biology. High fidelity electronic structure simulation requires the solution of increasingly larger and more complex problems. Efficient, accurate, and scalable numerical methods can transform the range of applicability of electronic structure theories and enable scientific applications that are beyond reach today. The education component of this project focuses on introducing electronic structure theories to graduate students, early career researchers, and advanced undergraduate students with mathematical backgrounds. Efficient techniques developed in the applied mathematics community, after adapted to specific computational problems, can be valuable tools to reduce the cost of electronic structure calculations. Electronic structure theories can also offer new ideas and application areas for the development of general mathematical and numerical techniques. Currently there is a high language barrier between the applied mathematics community and the electronic structure community. This project will develop new education activities, such as new topic courses and summer school activities, with the goal of reducing the language barrier and bridging the gap between the two communities. The research component of this project aims at significantly reducing the computational cost for KS-DFT calculations with high fidelity hybrid exchange-correlation functionals. Mathematically, hybrid functionals involve the Fock exchange operator, which is generally nonlocal and full-rank, and its treatment is computationally very challenging. This project will develop an adaptive compression strategy for treating the Fock exchange operator, and accelerate two important types of calculations with hybrid functionals: ab initio molecular dynamics, and real-time time dependent density functional theory. The new methods will be transferred to community electronic structure software packages used by chemists and materials scientists, and be validated by simulation with real materials. The goal is to transform how hybrid functional electronic structure calculations are performed for large, complex systems.

该项目旨在改进模拟原子和分子电子结构的数值方法。电子结构理论，特别是以Kohn-Sham密度泛函理论（KS-DFT）为代表，已经发展成为在物理，化学，材料科学和生物学中具有广泛应用的主力工具。 高保真电子结构模拟要求解决越来越大和越来越复杂的问题。 高效、准确和可扩展的数值方法可以改变电子结构理论的适用范围，并实现当今无法实现的科学应用。 该项目的教育部分侧重于向研究生，早期职业研究人员和具有数学背景的高年级本科生介绍电子结构理论。在应用数学界开发的有效技术，在适应特定的计算问题后，可以成为降低电子结构计算成本的有价值的工具。电子结构理论还可以为一般数学和数值技术的发展提供新的思路和应用领域。目前，应用数学界和电子结构界之间存在着很高的语言障碍。该项目将开发新的教育活动，如新的专题课程和暑期学校活动，目的是减少语言障碍，弥合两个社区之间的差距。 该项目的研究部分旨在显着降低KS-DFT计算的计算成本与高保真混合交换相关泛函。在数学上，混合泛函涉及Fock交换算子，它通常是非局部和满秩的，并且它的处理在计算上非常具有挑战性。 该项目将开发一种自适应压缩策略来处理Fock交换算子，并加速两种重要的混合泛函计算：从头算分子动力学和实时时间依赖密度泛函理论。 新方法将被转移到化学家和材料科学家使用的社区电子结构软件包中，并通过真实的材料模拟进行验证。目标是改变大型复杂系统的混合功能电子结构计算方式。

项目成果

Fast Real-Time Time-Dependent Density Functional Theory Calculations with the Parallel Transport Gauge

使用并行传输规进行快速实时瞬态密度泛函理论计算

• DOI: 10.1021/acs.jctc.8b00580
• 发表时间: 2018
• 期刊: Journal of Chemical Theory and Computation
• 影响因子: 5.5
• 作者: Jia, Weile;An, Dong;Wang, Lin-Wang;Lin, Lin
• 通讯作者: Lin, Lin

Globally Constructed Adaptive Local Basis Set for Spectral Projectors of Second Order Differential Operators

• DOI: 10.1137/17m1140236
• 发表时间: 2017-07
• 期刊: Multiscale Model. Simul.
• 作者: Yingzhou Li;Lin Lin-Lin

Numerical methods for Kohn–Sham density functional theory

• DOI: 10.1017/s0962492919000047
• 发表时间: 2019-05
• 期刊: Acta Numerica
• 影响因子: 14.2
• 作者: Lin Lin-Lin;Jianfeng Lu;Lexing Ying

Explicitly antisymmetrized neural network layers for variational Monte Carlo simulation

• DOI: 10.1016/j.jcp.2022.111765
• 发表时间: 2021-12
• 期刊: J. Comput. Phys.
• 作者: Jeffmin Lin;Gil Goldshlager;Lin Lin-Lin

Staggered mesh method for correlation energy calculations of solids: Random phase approximation in direct ring coupled cluster doubles and adiabatic connection formalisms

• DOI: 10.1021/acs.jctc.1c00985
• 发表时间: 2021-09
• 期刊: Journal of chemical theory and computation
• 影响因子: 5.5
• 作者: Xin Xing;Lin Lin-Lin