课题基金 / 基金详情

CAREER: Research and training in advanced computational methods for quantum and statistical mechanics

CAREER: Research and training in advanced computational methods for quantum and statistical mechanics
职业:量子和统计力学高级计算方法的研究和培训
批准号:
1454939
负责人:
Jianfeng Lu
金额:
$42.0万
依托单位:
依托单位国家:
美国
项目类别:
Continuing Grant
财政年份:
2015
资助国家:
美国
项目状态:
已结题
起止时间:
2015-09-01 至 2020-08-31

项目摘要

项目成果

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中文摘要
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英文摘要
Ab initio simulations have become widely used scientific workhorses with applications in physics, chemistry, materials science, and many related fields, but the reach of simulations is limited by computational complexity. To go beyond current capabilities in realistic and predictive ab initio simulations, it is necessary to address the current bottlenecks. This project aims to greatly enlarge the scope of ab initio simulations and open up major new areas for electronic-structure-theory-based predictive methodologies that are not possible today. This research lies at the intersection of multiple disciplines. The project connects advanced state-of-the-art techniques in computational mathematics to challenging problems arising from chemistry and materials science. The integrated research program will bring together ideas and techniques, which will not only help advance the application areas, but also has the potential to open up new research areas in mathematics.The research goal of this project is to innovate and analyze efficient algorithms based on advanced computational mathematics for electronic structure theory and computational statistical mechanics, which will greatly advance the scope of ab initio simulations with applications in chemistry, materials science, and many related fields. More specifically, topics considered include: (1) reduced scaling methods for electronic structure theory, which will extend the system size of the simulation; (2) efficient sampling algorithms for metastable systems, which will bridge the temporal scales; and (3) algorithms that go beyond Born-Oppenheimer approximation, which will give a more accurate account of quantum effects in classical dynamics. The educational objectives of this proposal are to prepare and train students for interdisciplinary research and to disseminate knowledge from graduate and undergraduate students to high school students and the general public in the U.S. and abroad.
期刊论文(1)
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会议论文
DOI: 10.22331/q-2019-10-28-199
发表时间: 2019
期刊: Quantum
影响因子: 6.4
作者: [Cao, Yu, Lu, Jianfeng]
通讯作者: Lu, Jianfeng
Innovation of Numerical Methods for High-Dimensional Partial Differential Equations
  • 批准号:
    2309378
  • 项目类别:
    Standard Grant
  • 资助金额:
    $40.0万
  • 财政年份:
    2023
  • 负责人:
    Jianfeng Lu
  • 依托单位:
EAGER: QAC-QSA: Resource Reduction in Quantum Computational Chemistry Mapping by Optimizing Orbital Basis Sets
  • 批准号:
    2037263
  • 项目类别:
    Standard Grant
  • 资助金额:
    $30.0万
  • 财政年份:
    2020
  • 负责人:
    Jianfeng Lu
  • 依托单位:
Innovative Numerical Methods for High-Dimensional Applications
  • 批准号:
    2012286
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $29.31万
  • 财政年份:
    2020
  • 负责人:
    Jianfeng Lu
  • 依托单位:
Mathematical Problems for Electronic Structure Models
  • 批准号:
    1312659
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $16.8万
  • 财政年份:
    2013
  • 负责人:
    Jianfeng Lu
  • 依托单位:
国内基金
海外基金
Research on Quantum Field Theory without a Lagrangian Description
  • 批准号:
    24ZR1403900
  • 项目类别:
    省市级项目
  • 资助金额:
    --
  • 批准年份:
    2024
  • 负责人:
    SATOSHI NAWATA
  • 依托单位:
Cell Research
Cell Research
Cell Research (细胞研究)