Strategic Plan for a Scientific Software Innovation Institute (S2I2) for High Energy Physics

Abstract

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. Facilities such as CERN's Large Hadron Collider (LHC) represent a huge step forward in this quest. The discovery of the Higgs boson, the observation of exceedingly rare decays of B mesons, and stringent constraints on many viable theories of physics beyond the Standard Model (SM) demonstrate the great scientific value of the LHC physics program. 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 is to search for physics beyond the SM and, should it be discovered, to study its details and implications. During the HL-LHC era, the ATLAS and CMS experiments will record circa 10 times as much data from 100 times as many collisions as in LHC Run 1. The NSF and the DOE are planning large investments in detector upgrades so the HL-LHC can operate in this high-rate environment. A commensurate investment in R&D for the software for acquiring, managing, processing and analyzing HL-LHC data will be critical to maximize the return-on-investment in the upgraded accelerator and detectors. The strategic plan presented in this report is the result of a conceptualization process carried out to explore how a potential Scientific Software Innovation Institute (S2I2) for High Energy Physics (HEP) can play a key role in meeting HL-LHC challenges.

References in corpus (11)

• Observation of a new particle in the search for the Standard Model Higgs boson with the ATLAS detector at the LHC
• Event generation with SHERPA 1.1
• CaloGAN: Simulating 3D High Energy Particle Showers in Multi-Layer Electromagnetic Calorimeters with Generative Adversarial Networks
• A Roadmap for HEP Software and Computing R&D for the 2020s
• Edward: A library for probabilistic modeling, inference, and criticism
• Better Higgs-CP Tests Through Information Geometry
• The Matrix Element Method and its Application to Measurements of the Top Quark Mass
• HEPCloud, a New Paradigm for HEP Facilities: CMS Amazon Web Services Investigation
• Matrix Element Method in HEP: Transfer Functions, Efficiencies, and Likelihood Normalization
• b tagging in ATLAS and CMS
• Accessing Masses Beyond Collider Reach - in EFT

Cited by in corpus (4)

• Deep Learning and its Application to LHC Physics
• Enabling real-time multi-messenger astrophysics discoveries with deep learning
• Interactive Tools for Reproducible Science -- Understanding, Supporting, and Motivating Reproducible Science Practices
• Learning from the Pandemic: the Future of Meetings in HEP and Beyond