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ACQUISITION OF A VERSATILE HIGH PERFORMANCE COMPUTING FACILITY FOR GRAVITATIONAL WAVE SOURCE

ACQUISITION OF A VERSATILE HIGH PERFORMANCE COMPUTING FACILITY FOR GRAVITATIONAL WAVE SOURCE
购买用于引力波源的多功能高性能计算设备
批准号:
0619274
负责人:
Vassiliki Kalogera
金额:
$41.62万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2006
资助国家:
美国
项目状态:
已结题
起止时间:
2006-10-01 至 2008-09-30

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中文摘要
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英文摘要
This award supports the acquisition of high-performance computing equipment that will enable research on the theory of gravitational-wave (GW) sources. The work will involve both research and technology training of undergraduate and graduate students. The equipment consists of a large computer cluster (56 nodes, each with two dual-core CPUs) with gigabit networking, designed for high computational efficiency-to-cost ratio for GW source simulations. In addition, 16 of the nodes will be equipped with specialized hardware (GRAPE boards) for direct N-body simulations in stellar dynamics. A major storage component is also part of the proposed system. Visualizations from the simulation results will be developed for use in both research analysis and training as well as for public outreach presentations at the nearby Adler Planetarium. For this development effort will be enabled by the acquisition of a Tiled Wall Display (almost 25 million pixels) operated by a small cluster of 7 nodes with high-level graphics capabilities. All the acquired instrumentation will be used in a wide range of computational astrophysics projects on binary star evolution and compact object formation, stellar dynamics, and hydrodynamics. The results will greatly improve the understanding of the most important GW sources for current laser interferometer detectors, and they will also allow for better physical interpretation of future GW observations. Examples of specific projects include: (i) modeling populations of binary compact objects driven to inspiral by GW emission; the primary goal is the application of empirical constraints to theoretical models and the derivation of reliable predictions for binary inspiral detection rates and for measurements of source properties. (ii) dynamical simulations of black holes in dense star clusters; frequent dynamical interactions in these systems can lead to the formation of large numbers of merging black hole binaries and may be the dominant source of detectable black hole mergers for ground-based interferometers such as LIGO. (iii) hydrodynamic calculations of the final mergers of compact binaries containing a black hole and a neutron star; these will be performed using a sophisticated 3-D relativistic hydrodynamics code and will represent a significant improvement over previous, more approximate treatments based on Newtonian gravity. The study of GW sources is also important in many other areas of astrophysics. For example, coalescing compact binaries may also be sources of gamma-ray bursts, and they may play a key role for the production of many heavy elements in galaxies. The research activities enabled by this instrumentation will involve the training of several undergraduate and graduate students, including students from under-represented minorities. A graduate student studying high performance computing and a team of up to about ten undergraduates will also be trained in all phases of the instrument acquisition, set-up, and commissioning.
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Gravitational-Wave Data Analysis and Population Inference
  • 批准号:
    2207945
  • 项目类别:
    Standard Grant
  • 资助金额:
    $62.87万
  • 财政年份:
    2022
  • 负责人:
    Vassiliki Kalogera
  • 依托单位:
Gravitational-Wave Inference from Binary Compact Objects
  • 批准号:
    1912648
  • 项目类别:
    Standard Grant
  • 资助金额:
    $55.92万
  • 财政年份:
    2019
  • 负责人:
    Vassiliki Kalogera
  • 依托单位:
MRI: Acquisition of a High-Performance Computing Cluster to Unveil the Sources of Gravitational Waves
  • 批准号:
    1726951
  • 项目类别:
    Standard Grant
  • 资助金额:
    $34.99万
  • 财政年份:
    2017
  • 负责人:
    Vassiliki Kalogera
  • 依托单位:
Gravitational-Wave Inference from Binary Compact Objects
  • 批准号:
    1607709
  • 项目类别:
    Continuing Grant
  • 资助金额:
    $48.0万
  • 财政年份:
    2016
  • 负责人:
    Vassiliki Kalogera
  • 依托单位:
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