Techniques for evolving Einstein's equations

爱因斯坦方程的演化技术

基本信息

  • 批准号:
    0505761
  • 负责人:
  • 金额:
    $ 12万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2005
  • 资助国家:
    美国
  • 起止时间:
    2005-07-01 至 2008-06-30
  • 项目状态:
    已结题

项目摘要

This award supports a research program to use analytical and numerical techniques in the study of sources of gravitational waves with emphasis on binary black hole collisions. Gravitational wave detectors such as LIGO urgently need the gravitational waveforms that would be obtained from the successful numerical simulation of these systems. These simulations are of a complexity such that special advances in techniques and infrastructure for the numerical solution of Einstein's equations are needed. The project includes further development and application to binary black hole simulations of state-of-the-art techniques from computational physics and applied mathematics. The numerical solution of Einstein's equations has historically posed unique, problems associated with features inherent to Einstein's theory, such as gauge conditions and constraint violations. As part of this project novel techniques whose goal is to deal with these unique problems will be developed or extended and applied to binary black hole collisions. At the analytical level the project includes development and application of techniques to deal with constraint instabilities, boundary conditions for Einstein's equations, and coordinate conditions. At the discrete level it includes development and application techniques for multi-patch simulations, high order methods, methods for matching Einstein's equations to perturbative and other modules, constraint projection and variational integrators. The development of the necessary computational infrastructure to apply these techniques will be done in close collaboration with the Cactus development group at LSU. LSU provides an unique assembly of experts in numerical relativity and scientific computing whose expertise can be leveraged by this project.
该奖项支持一项研究计划,利用分析和数值技术来研究引力波源,重点是双黑洞碰撞。 LIGO 等引力波探测器迫切需要从这些系统的成功数值模拟中获得引力波形。这些模拟非常复杂,因此需要在技术和基础设施方面取得特殊进步才能对爱因斯坦方程进行数值求解。该项目包括对计算物理和应用数学最先进技术的二元黑洞模拟的进一步开发和应用。爱因斯坦方程的数值解在历史上提出了与爱因斯坦理论固有特征相关的独特问题,例如规范条件和约束违反。作为该项目的一部分,旨在解决这些独特问题的新技术将被开发或扩展并应用于双黑洞碰撞。在分析层面,该项目包括处理约束不稳定性、爱因斯坦方程边界条件和坐标条件的技术的开发和应用。在离散层面,它包括多面片模拟的开发和应用技术、高阶方法、将爱因斯坦方程与微扰和其他模块相匹配的方法、约束投影和变分积分器。应用这些技术所需的计算基础设施的开发将与路易斯安那州立大学的仙人掌开发小组密切合作。路易斯安那州立大学在数值相对论和科学计算方面拥有独特的专家组合,该项目可以利用他们的专业知识。

项目成果

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Manuel Tiglio其他文献

Hyperparameter Optimization of an hp-Greedy Reduced Basis for Gravitational Wave Surrogates
引力波替代物的 hp 贪婪约简基的超参数优化
  • DOI:
    10.3390/universe10010006
  • 发表时间:
    2023-12-23
  • 期刊:
  • 影响因子:
    2.9
  • 作者:
    F. Cerino;J. A. Diaz;Emmanuel A. Tassone;Manuel Tiglio;Atuel Villegas
  • 通讯作者:
    Atuel Villegas

Manuel Tiglio的其他文献

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{{ truncateString('Manuel Tiglio', 18)}}的其他基金

Reduced Basis, Symbolic Regression, and Closed Form Expressions for Gravitational Waves
引力波的约化基、符号回归和闭合形式表达式
  • 批准号:
    1607646
  • 财政年份:
    2016
  • 资助金额:
    $ 12万
  • 项目类别:
    Standard Grant
Reduced Order Modeling for Gravitational Waves
引力波的降阶建模
  • 批准号:
    1500818
  • 财政年份:
    2014
  • 资助金额:
    $ 12万
  • 项目类别:
    Continuing Grant
Reduced Order Modeling for Gravitational Waves
引力波的降阶建模
  • 批准号:
    1316424
  • 财政年份:
    2013
  • 资助金额:
    $ 12万
  • 项目类别:
    Continuing Grant
Reduced Basis for Gravitational Waves: Select, Solve, Represent, Predict
引力波的简化基础:选择、求解、表示、预测
  • 批准号:
    1208861
  • 财政年份:
    2012
  • 资助金额:
    $ 12万
  • 项目类别:
    Continuing Grant
Algorithms and Scientific Computing for Gravitational Waves Source Modeling
引力波源建模的算法和科学计算
  • 批准号:
    1005632
  • 财政年份:
    2010
  • 资助金额:
    $ 12万
  • 项目类别:
    Continuing Grant
Algorithms, Scientific Computing, and Numerical Studies in Classical and Quantum General Relativity
经典和量子广义相对论中的算法、科学计算和数值研究
  • 批准号:
    0908457
  • 财政年份:
    2009
  • 资助金额:
    $ 12万
  • 项目类别:
    Standard Grant
Numerical simulations of Einstein's equations
爱因斯坦方程的数值模拟
  • 批准号:
    0801213
  • 财政年份:
    2008
  • 资助金额:
    $ 12万
  • 项目类别:
    Continuing Grant

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