课题基金 / 基金详情

Computational methods in atomic collision theory

Computational methods in atomic collision theory
原子碰撞理论的计算方法
批准号:
LP0560904
负责人:
Prof Igor Bray
金额:
$8.33万
依托单位:
依托单位国家:
澳大利亚
项目类别:
Linkage Projects
财政年份:
2005
资助国家:
澳大利亚
项目状态:
已结题
起止时间:
2005-09-22 至 2008-12-31

项目摘要

项目成果

Prof Igor Bray的其他基金

相似基金

相关文献

中文摘要
翻译
点击翻译按钮获取中文摘要
英文摘要
We will develop computational methods for solving interactions between particles on the atomic scale. Computational problems, of particular interest to the industry partner, are the treatment of large-scale ill-conditioned linear systems, and the extension of the Gaussian molecular structure package to collision physics. We have been world-leaders in the field of atomic collision theory for almost a decade, and now, utilising the latest software and hardware, will have the capacity to extend the numerical techniques to a vast range of collision systems of interest to science and industry, where visualisation and sheer computer power will play a major role in both code development and production runs.
期刊论文(0)
专著(0)
科研奖励(0)
会议论文
Electron-molecule collisions in fusion and astrophysical plasmas
  • 批准号:
    DP240101184
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $29.09万
  • 财政年份:
    2024
  • 负责人:
    Prof Igor Bray
  • 依托单位:
Antihydrogen formation
  • 批准号:
    DP190101195
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $29.48万
  • 财政年份:
    2019
  • 负责人:
    Prof Igor Bray
  • 依托单位:
Electron, positron, and heavy-particle collisions with molecules
  • 批准号:
    DP180100433
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $30.21万
  • 财政年份:
    2018
  • 负责人:
    Prof Igor Bray
  • 依托单位:
Quantum collision theory for astrophysics, fusion energy and hadron therapy
  • 批准号:
    DP160102106
  • 项目类别:
    Discovery Projects
  • 资助金额:
    $29.11万
  • 财政年份:
    2016
  • 负责人:
    Prof Igor Bray
  • 依托单位:
国内基金
海外基金
复杂图像处理中的自由非连续问题及其水平集方法研究
  • 批准号:
    60872130
  • 项目类别:
    面上项目
  • 资助金额:
    28.0万元
  • 批准年份:
    2008
  • 负责人:
    刘国才
  • 依托单位:
Computational Methods for Analyzing Toponome Data