Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP)

探索了解宇宙中物质的基本组成部分及其相互作用是人类最古老、最雄心勃勃的科学努力之一。在基本粒子物理学中，迄今为止最成功的理论被称为粒子物理的“标准模型”。欧洲核子研究中心的大型强子对撞机(LHC)等实验设备代表着这一探索向前迈出的一大步，希格斯玻色子的发现就是明证。这一全球科学计划的下一阶段将是高光度大型强子对撞机(HL-LHC)，它将从2029年开始收集数据，一直持续到2030年的S。HL-LHC的主要科学目标是探索超越标准模型的物理。尽管标准模型到目前为止已经成功地解释了实验证据，但科学家们知道它并不完整，因为它没有考虑暗物质或中微子的质量。在HL-LHC时代，ATLAS和CMS实验将记录的碰撞数据是发现希格斯玻色子的100倍的10倍。因此，必须在获取、管理、处理和分析HL-LHC数据的软件方面取得重大研发进展，以实现升级的加速器和探测器以及计划中的大型强子对撞机科学计划的科学潜力。在此背景下，高能物理软件研究与创新研究所(IRIS-HEP)将发挥主导作用，提供所需的软件和计算系统，以应对高光度时代大型强子对撞机带来的挑战。该项目解决了国际上“2020年代HEP软件和计算研发路线图”的关键要素，并实施了2022年12月发布的更新的“IRIS-HEP下一阶段HL-LHC物理软件升级战略计划”。IRIS-HEP将推动三个高影响力领域的研发：(1)开发用于数据重建和触发的创新算法；(2)开发高性能分析系统，以减少“洞察时间”并最大限度地发挥HL-LHC的科学潜力；以及(3)为社区即将到来的艾字节时代开发数据组织、管理和访问(DOMA)系统。IRIS-HEP将继续对今天的分布式高吞吐量计算(DHTC)进行投资，并建立一条集成路径，将其设施研发活动交付到分布式生产基础设施中。作为一个知识中心，IRIS-HEP将领导以下工作：(1)在HEP与网络基础设施、数据科学和计算机科学界之间建立融合研究，以寻找新的方法来解决HL-LHC时代HEP实验中引人注目的软件和计算挑战，(2)与强调专业发展和培训的美国大学和实验室的研究人员和学生广泛接触，以及(3)在所需的二十年内维持HEP软件和与算法及其实施相关的基础知识。除了实现最好的HL-LHC科学之外，IRIS-HEP还将把更大的网络基础设施和HEP社区聚集在一起，以解决亿级高通量计算和艾字节规模数据集交汇处的复杂问题，其方式与许多具有新的数据密集型需求的研究领域广泛相关。该研究所以暑期学校和研究员计划的形式提供的教育和培训将有助于培养一支高素质的STEM工作队伍。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。

The quest to understand the fundamental building blocks of matter in the Universe and their interactions is one of the oldest and most ambitious of human scientific endeavors. In Elementary Particles Physics, the most successful theory to date is known as the "Standard Model" of particle physics. Experimental facilities such as CERN's Large Hadron Collider (LHC) represent a huge step forward in this quest as evidenced by the discovery of the Higgs boson. The next phase of this global scientific project will be the High-Luminosity LHC (HL-LHC), which will collect data starting circa 2029 and continue into the 2030's. The primary science goal at the HL-LHC is to search for physics beyond the Standard Model. While the Standard Model has been successful in explaining experimental evidence to date, scientists know that it is not be complete, because it does not account for Dark Matter or neutrino masses, for example. In the HL-LHC era, the ATLAS and CMS experiments will record 10 times as much data from 100 times as many collisions as were used to discover the Higgs boson. As such, significant R&D advances must be achieved in the software for acquiring, managing, processing and analyzing HL-LHC data to realize the scientific potential of the upgraded accelerator and detectors and the planned LHC science program. In this context, the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) will play a leading role to deliver the software and computing systems required to meet the challenges posed by the LHC in the High Luminosity era.This project addresses key elements of the international "Roadmap for HEP Software and Computing R&D for the 2020s" and implements the updated "IRIS-HEP Strategic Plan for the Next Phase of Software Upgrades for HL-LHC Physics" published in December 2022. IRIS-HEP will advance R&D in three high-impact areas: (1) development of innovative algorithms for data reconstruction and triggering; (2) development of highly performant analysis systems that reduce `time-to-insight' and maximize the HL-LHC scientific potential; and (3) development of data organization, management and access (DOMA) systems for the community's upcoming Exabyte era. IRIS-HEP will sustain investments in today's distributed high-throughput computing (DHTC) and build an integration path to deliver its Facilities R&D activities into the distributed production infrastructure. As an intellectual hub, IRIS-HEP will lead efforts to (1) build convergence research between HEP and the Cyberinfrastructure, Data Science and Computer Science communities for novel approaches to address the compelling software and computing challenges of HL-LHC era HEP experiments, (2) engage broadly with researchers and students from U.S. Universities and labs emphasizing professional development and training, and (3) sustain HEP software and underlying knowledge related to the algorithms and their implementations over the two decades required. In addition to enabling the best possible HL-LHC science, IRIS-HEP will bring together the larger Cyberinfrastructure and HEP communities to address the complex issues at the intersection of Exascale high-throughput computing and Exabyte-scale datasets in ways broadly relevant to many research domains with emerging data-intensive needs. The education and training provided by the Institute in the form of summer schools and a fellows program will contribute to a highly qualified STEM workforce.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.