Collaborative Research: Frameworks: Scalable Modular Software and Methods for High-Accuracy Materials and Condensed Phase Chemistry Simulation
Collaborative Research: Frameworks: Scalable Modular Software and Methods for High-Accuracy Materials and Condensed Phase Chemistry Simulation
批准号:
1931321
负责人:
Timothy Berkelbach
金额:
$45.0万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-10-01 至 2022-09-30
中文摘要
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英文摘要
How electrons are arranged in materials gives rise to a large variety of different behaviors. We can observe these behaviors and use them in various technologies. However, the prediction of these behaviors is a serious challenge. This makes the successful design of new materials harder. The goal of the Materials Genome Initiative is to use computer simulations to model electrons according to the laws of quantum physics. This will allow researchers to design new materials with desired properties. This project aims to build fast and accurate computer programs which simulate those new materials. These programs combine advances in computer science, quantum chemistry, and condensed-matter physics. They will be implemented in an open-source Python-based community code. This distribution model allows other researchers to use this code and to contribute new features.This research addresses gaps in existing software cyberinfrastructure in quantum materials simulation, by developing novel parallel implementations of low-scaling, high-accuracy methods. In particular, new techniques for mean-field calculations will be developed, which will act as groundwork for periodic coupled-cluster and quantum Monte Carlo methods. State-of-the-art techniques in sparsity and tensor decomposition will be employed to achieve good system-size scaling while retaining accuracy within each of these numerical schemes. Critically, the methods will be developed using efficient high-level software abstractions, implemented as Python-level modules within PySCF that leverage the Cyclops library for massively-parallel execution. The library software infrastructure will also be extended to maximize productivity via source-to-source automatic differentiation, as well as to enable execution of sparse kernels on emerging GPU-based supercomputing architectures. This award is jointly supported by the NSF Office of Advanced Cyberinfrastructure, and the Division of Materials Research and the Division of Chemistry within the NSF Directorate of Mathematical and Physical Sciences.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
Absorption Spectra of Solids from Periodic Equation-of-Motion Coupled-Cluster Theory
周期运动方程耦合团簇理论的固体吸收光谱
DOI:
10.1021/acs.jctc.1c00692
发表时间:
2021
期刊:
Journal of Chemical Theory and Computation
影响因子:
5.5
作者:
[Wang, Xiao, Berkelbach, Timothy C.]
通讯作者:
Berkelbach, Timothy C.
DOI:
10.1021/acs.jpclett.0c03274
发表时间:
2021-01-21
期刊:
JOURNAL OF PHYSICAL CHEMISTRY LETTERS
影响因子:
5.7
作者:
[Lau, Bryan T. G., Knizia, Gerald, Berkelbach, Timothy C.]
通讯作者:
Berkelbach, Timothy C.
Fast periodic Gaussian density fitting by range separation
通过范围分离进行快速周期性高斯密度拟合
DOI:
10.1063/5.0046617
发表时间:
2021
期刊:
The Journal of Chemical Physics
影响因子:
--
作者:
[Ye, Hong-Zhou, Berkelbach, Timothy C.]
通讯作者:
Berkelbach, Timothy C.
CAREER: Spectroscopy of Metals from Ab Initio Quantum Chemistry
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批准号:1848369
-
项目类别:Standard Grant
-
资助金额:$50.61万
-
财政年份:2019
-
负责人:Timothy Berkelbach
-
依托单位:
国内基金
海外基金
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