Collaborative Research: Accelerating the Pace of Discovery in Numerical Relativity by Improving Computational Efficiency and Scalability

协作研究:通过提高计算效率和可扩展性来加快数值相对论的发现步伐

基本信息

  • 批准号:
    2207615
  • 负责人:
  • 金额:
    $ 36万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2022
  • 资助国家:
    美国
  • 起止时间:
    2022-09-01 至 2025-08-31
  • 项目状态:
    未结题

项目摘要

The dawn of gravitational wave astronomy is just beginning, and the LIGO and Virgo gravitational wave detectors have already made some stunning discoveries. Future upgrades to these detectors, as well as the advent of new detectors, such as Kagra, will significantly expand the range of gravitational wave science. As the sensitivity of gravitational wave detectors improves over the next decade, the accuracy of numerical solutions of these events must correspondingly increase by at least an order of magnitude in the same time frame. This is a significant computational challenge that must be met to enable the full scientific potential of the new detectors. This project will study mergers of binary neutron stars and black holes using computer simulations created by Dendro-GR, a new computer code that runs very efficiently on the largest supercomputers. Tests of general relativity will also be performed by examining alternative models of gravity. New algorithms for solving differential equations will be explored to improve the efficiency of long simulations of binary mergers. Work done for this project will promote the progress of science and contribute to undergraduate and graduate training in multiple STEM fields including computer science, mathematics, and physics. Finally, Dendro-GR is an open source project.This project will study the dynamics of merging binary compact objects at the frontier of current computational capabilities. The ability to model a wide variety of possible mergers will correspondingly increase the ability of gravitational wave scientists to find and understand these high-energy events, and to search for possible new physics that lies beyond our current gravitational models. This project will be directed at the following goals: (1) The Dendro-GR computational framework will be expanded to calculate gravitational waveforms for binary neutron star inspirals of sufficient accuracy to be used in waveform catalogs. (2) Binary black hole inspirals with large mass ratios will be studied to expand the range of current waveform catalogs. (3) Gravitational waveforms for merging black hole binaries will be calculated within alternative gravitational theories to probe possible deviations from the predictions of general relativity and to search for new physics beyond our current model for gravity. (4) The computational challenge of improving accuracy in numerical relativity will be studied by focusing on reducing the time-to-solution. This complicated problem requires a broad approach that uses GPUs, innovative finite differencing, improved spatial discretizations, and exposing the temporal discretization to more parallelism.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.
引力波天文学的曙光才刚刚开始,LIGO和Virgo引力波探测器已经取得了一些惊人的发现。未来对这些探测器的升级,以及新探测器的出现,如Kagra,将显着扩大引力波科学的范围。随着引力波探测器的灵敏度在未来十年内的提高,这些事件的数值解的精度必须在同一时间范围内相应地提高至少一个数量级。这是一个重大的计算挑战,必须满足,使新探测器的全部科学潜力。该项目将使用Dendro-GR创建的计算机模拟来研究双中子星和黑洞的合并,Dendro-GR是一种新的计算机代码,可以在最大的超级计算机上非常有效地运行。广义相对论的检验也将通过检验引力的替代模型来进行。将探索求解微分方程的新算法,以提高二元合并长时间模拟的效率。为这个项目所做的工作将促进科学的进步,并有助于多个STEM领域的本科生和研究生培训,包括计算机科学,数学和物理学。最后,Dendro-GR是一个开源项目。该项目将研究在当前计算能力的前沿合并二进制紧凑对象的动力学。对各种可能的合并进行建模的能力将相应地提高引力波科学家发现和理解这些高能事件的能力,并寻找超越我们当前引力模型的可能的新物理。该项目将针对以下目标:(1)Dendro-GR计算框架将扩展到计算足够精度的双中子星星吸入的重力波形,以用于波形目录。(2)我们将研究具有大质量比的双黑洞吸气,以扩大当前波形目录的范围。(3)合并黑洞双星的引力波形将在其他引力理论中计算,以探测与广义相对论预测的可能偏差,并寻找超越我们目前引力模型的新物理。(4)提高数值相对论精度的计算挑战将通过集中减少求解时间来研究。这个复杂的问题需要一个广泛的方法,使用GPU,创新的有限差分,改进的空间离散化,并暴露时间离散化更多的并行性。这个奖项反映了NSF的法定使命,并已被认为是值得通过评估使用基金会的智力价值和更广泛的影响审查标准的支持。

项目成果

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David Neilsen其他文献

David Neilsen的其他文献

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{{ truncateString('David Neilsen', 18)}}的其他基金

Collaborative Research: Massively Parallel Simulations of Compact Objects
协作研究:紧凑物体的大规模并行模拟
  • 批准号:
    1912883
  • 财政年份:
    2019
  • 资助金额:
    $ 36万
  • 项目类别:
    Standard Grant
Collaborative Research: Compact Binary Mergers in the Advanced LIGO Era
合作研究:先进 LIGO 时代的紧凑型二元合并
  • 批准号:
    1607356
  • 财政年份:
    2016
  • 资助金额:
    $ 36万
  • 项目类别:
    Continuing Grant
Collaborative Research: Loud, Bright, and Hot Binary Mergers
合作研究:响亮、明亮、热门的二元合并
  • 批准号:
    1308727
  • 财政年份:
    2013
  • 资助金额:
    $ 36万
  • 项目类别:
    Continuing Grant
Collaborative Research: A Study and implementation of Semantic Constructs for Highly Scalable Leading-edge Scientific Computing
协作研究:高度可扩展的前沿科学计算的语义结构的研究和实现
  • 批准号:
    0832966
  • 财政年份:
    2008
  • 资助金额:
    $ 36万
  • 项目类别:
    Standard Grant
Black Holes: Excision and Matter Interactions
黑洞:切除和物质相互作用
  • 批准号:
    0502218
  • 财政年份:
    2005
  • 资助金额:
    $ 36万
  • 项目类别:
    Standard Grant

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  • 批准号:
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  • 批准号:
    10774081
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  • 项目类别:
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协作研究:SaTC:核心:中:加速保护隐私的机器学习即服务:从算法到硬件
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