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AccelNet-Implementation: HSF-India - Research Software Networks in Physics

AccelNet-Implementation: HSF-India - Research Software Networks in Physics
AccelNet-实施:HSF-印度 - 物理学研究软件网络
批准号:
2201990
负责人:
David Lange
金额:
$200.0万
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
项目状态:
未结题
起止时间:
2022-10-01 至 2027-09-30

项目摘要

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中文摘要
翻译
HSF-India将把印度的网络加入美国和欧洲的网络,建立国际研究软件合作,以实现实验粒子、核物理和天体粒子物理实验的科学目标。科学家触手可及的悬而未决的问题包括暗物质的起源、希格斯玻色子的性质、物质的结构组成以及解释中微子质量的机制。这些都是下一代实验设施要解决的一些最优先的科学驱动因素,包括欧洲核子研究中心的高光度大型强子对撞机、费米实验室的深层地下中微子实验和布鲁克海文国家实验室的电子离子对撞机。为了充分实现它们的发现潜力,需要新一代软件算法和方法。软件是这项研究的智力产品,而不仅仅是一个关键工具。它已经成为设计和最大限度地发挥大型数据密集型科学项目的物理发现潜力的关键因素。建立这些研究软件合作是具有挑战性的,而且本质上是国际化的,与实验项目本身的国际性相匹配。HSF-印度将通过参与一个多元化的研究社区,为美国学生、博士后和早期职业人员提供重要的国际团队科学经验。HSF-印度将建立国际合作结构,以实现粒子、核物理和天体粒子物理发现的关键软件领域的创新,并为整个科学领域的类似国际合作奠定基础。它将通过利用国际培训网络、奖学金和专注于软件的研究人员交流,在其在美国、欧洲和印度的网络中为特定项目的研究软件合作提供种子。HSF-印度将在这些种子的基础上迭代地建立广泛和可持续的国际研究软件合作,包括三个关键研究主题:关于下一代分析方法的工具和技术、新颖的模拟技术和开放科学工具。它将专注于早期职业研究人员的机会,并与整个网络中更资深的研究人员建立指导和共同指导关系。通过与数据科学、人工智能和更广泛的计算机科学界接触,该项目将促进围绕研究软件的自下而上的联盟,包括物理学和其他领域。HSF-India旨在建立一个环境,让具有不同背景、技能和兴趣的研究人员能够聚集在一起,建立创新的合作,支持新的工具和技术,同时弥合研究差距,使未来的科学设施成为可能。通过国际网络到网络合作加速研究(AccelNet)计划旨在加快科学发现的进程,并为多团队国际合作准备下一代美国研究人员。AccelNet计划支持美国研究网络和海外互补网络之间的战略联系,这些网络将利用研究和教育资源来应对需要大量国际协调努力的重大科学挑战。该奖项反映了NSF的法定使命,并通过使用基金会的智力优势和更广泛的影响审查标准进行评估,被认为值得支持。
英文摘要
HSF-India will join networks in India to networks in the U.S. and Europe to build the international research software collaborations required to reach the science goals of experimental particle, nuclear and astroparticle physics experiments. Unanswered questions within reach of scientists include the origin of dark matter, properties of the Higgs Boson, the structural makeup of matter, and the mechanism to explain neutrino mass. These are some of the highest priority science drivers to be addressed by next-generation experimental facilities including the high-luminosity Large Hadron Collider at CERN, the Deep Underground Neutrino Experiment at Fermilab and the Electron Ion Collider at Brookhaven National Laboratory. To fully realize their discovery potential a new generation of software algorithms and approaches is required. Software is an intellectual product of this research, not just a critical tool. It has become a critical element to design and maximize the physics discovery potential of large data intensive science projects. Building these research software collaborations is challenging and inherently international matching the international nature of the experimental undertakings themselves. HSF-India will provide U.S. students, postdocs and early career personnel significant experience in international team science through engagement in a diverse research community.HSF-India will build international collaborative structures to enable innovation in critical software areas for discovery in particle, nuclear and astroparticle physics and lay the foundations for similar international collaborations across the scientific spectrum. It will seed research software collaborations on specific projects across its networks in the U.S., Europe, and India by leveraging an international training network, fellowships, and software-focused researcher exchanges. HSF-India will iteratively build on these seeds towards a broad and sustainable international research software collaboration with three key research themes: tools and techniques on next-generation analysis approaches, novel simulation techniques, and tools for Open Science. It will focus on opportunities for early-career researchers and establish mentoring and co-mentoring relationships with more senior researchers across the networks. By engaging with the data-science, artificial intelligence, and broader computer science communities the project will foster bottom-up alliances around research software, for physics and beyond. HSF-India aims to establish an environment where researchers with diverse backgrounds, skill sets and interests can come together and build innovative collaborations that sustain novel tools and techniques while bridging research gaps to enable future scientific facilities.The Accelerating Research through International Network-to-Network Collaborations (AccelNet) program is designed to accelerate the process of scientific discovery and prepare the next generation of U.S. researchers for multiteam international collaborations. The AccelNet program supports strategic linkages among U.S. research networks and complementary networks abroad that will leverage research and educational resources to tackle grand scientific challenges that require significant coordinated international efforts.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.
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ELEMENTS: CLAD ENABLING DIFFERENTIABLE PROGRAMMING IN SCIENCE
  • 批准号:
    2311471
  • 项目类别:
    Standard Grant
  • 资助金额:
    $60.0万
  • 财政年份:
    2023
  • 负责人:
    David Lange
  • 依托单位:
Elements: C++ as a service - rapid software development and dynamic interoperability with Python and beyond
  • 批准号:
    1931408
  • 项目类别:
    Standard Grant
  • 资助金额:
    $59.96万
  • 财政年份:
    2019
  • 负责人:
    David Lange
  • 依托单位:
EAGER: Computed Tomography of Early Age Structure of Hydrated Portland Cement
CAREER: Career Development Research Plan Toward Microstructural Engineering of Concrete
海外基金