The quest to understand the fundamental building blocks of nature 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. 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 2026 and continue into the 2030's. The primary science goal at the HL-LHC is to search for physics beyond the Standard Model. 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 physics program. In this context, the Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) will play a leading role to meet the software and computing challenges of the HL-LHC.

The Institute for Research and Innovation in Software for High Energy Physics (IRIS-HEP) addresses key elements of the international "Roadmap for HEP Software and Computing R&D for the 2020s" and implements the "Strategic Plan for a Scientific Software Innovation Institute (S2I2) for High Energy Physics" submitted to the NSF in December 2017. 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 physics 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 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 as most students and even most post-docs move into the private sector taking their skills with them.

This project advances the objectives of the National Strategic Computing Initiative (NSCI) and the objectives of "Harnessing the Data Revolution", one of the 10 Big Ideas for Future NSF Investments.

This project is supported by the Office of Advanced Infrastructure in the Directorate for Computer and Information Science and Engineering and the Division of Physics in the Directorate for Mathematical and Physical Sciences.

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.

National Science Foundation (NSF)
Division of Advanced CyberInfrastructure (ACI)
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Bogdan Mihaila
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Princeton University
United States
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