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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
合作研究:框架:用于高精度材料和凝聚相化学模拟的可扩展模块化软件和方法
批准号:
1931328
负责人:
Garnet Chan
金额:
$45.0万
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

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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(2)
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科研奖励(0)
会议论文
Using Hyperoptimized Tensor Networks and First-Principles Electronic Structure to Simulate the Experimental Properties of the Giant {Mn 84 } Torus
使用超优化张量网络和第一原理电子结构模拟巨型{Mn 84 }环面的实验特性
DOI: 10.1021/acs.jpclett.2c00354
发表时间: 2022
期刊: The Journal of Physical Chemistry Letters
影响因子: --
作者: [Chen, Dian-Teng, Helms, Phillip, Hale, Ashlyn R., Lee, Minseong, Li, Chenghan, Gray, Johnnie, Christou, George, Zapf, Vivien S., Chan, Garnet Kin-Lic, Cheng, Hai-Ping]
通讯作者: Cheng, Hai-Ping
Quantum Chemistry via General Tensor Networks
  • 批准号:
    2102505
  • 项目类别:
    Standard Grant
  • 资助金额:
    $46.5万
  • 财政年份:
    2021
  • 负责人:
    Garnet Chan
  • 依托单位:
Enabling Quantum Leap: Quantum algorithms for quantum chemistry and materials
  • 批准号:
    1909531
  • 项目类别:
    Standard Grant
  • 资助金额:
    $8.84万
  • 财政年份:
    2019
  • 负责人:
    Garnet Chan
  • 依托单位:
To the limits of the density matrix renormalization group in quantum chemistry, and beyond
  • 批准号:
    1665333
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $45.0万
  • 财政年份:
    2017
  • 负责人:
    Garnet Chan
  • 依托单位:
Collaborative Research: SI2-SSI: Software Framework for Electronic Structure of Molecules and Solids
  • 批准号:
    1657286
  • 项目类别:
    Standard Grant
  • 资助金额:
    $60.0万
  • 财政年份:
    2016
  • 负责人:
    Garnet Chan
  • 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)