The Large Hadron Collider (LHC) is the largest international scientific project partially supported by the United States. The goal of scientists at the LHC is to understand how matter behaves under the extreme conditions thought to have existed in the very early universe. This understanding informs the current scientific understanding of the evolution of the universe from the distant past to the present day. The behavior of matter under such conditions is investigated by analyzing the data from billions of high-energy particle collisions and comparing the results of these analyses to predictions made by theoretical physicists. LHC data are analyzed using many different software systems, called analysis frameworks, written by different research groups from around the world. While these frameworks are individually powerful tools, it is difficult for a scientist to form a global understanding of all the data from the LHC. This project will create a unifying software system, based upon a new programming language that allows scientists to describe their analysis ideas in a natural way. The system will advance science by making it considerably easier to run multiple analyses of data in an organized fashion, thereby yielding results that are impossible to obtain otherwise. The new language, called Analysis Description Language (ADL), reflects the way scientists at the LHC think about the analysis of data. Crucially, ADL does so in a way that is independent of the analysis frameworks in which the analyses are ultimately run. ADL also serves as a reliable intermediary between high energy physics analyses and natural language interfaces through Large Language Models and artificial intelligence-based assistants. For this reason, the proposed software system opens the way for students and science teachers to participate in the exciting research at the LHC by lowering the barrier to exploring the scientific principles and reasoning that underpin the research without requiring training in complex analyses frameworks.
Many data analyses at the Large Hadron Collider (LHC) at the European Organization for Nuclear Research (CERN) have yielded small deviations from the predictions of the Standard Model, the best current theory of particle physics. To further investigate these deviations, a potential discovery at the LHC requires global assessments of the results of multiple analyses. To date, no cyberinfrastructure exists to make such a task routine. The project addresses this need through cyberinfrastructure called the Analysis Collaborative Ecosystem for High-Energy Physics (ACEHEP). This cyberinfrastructure builds on the Analysis Description Language (ADL), a declarative, domain-specific language that expresses the physics algorithms of analyses in a transparent, structured way, decoupled from the analysis (software) frameworks in which analyses are executed. The cyberinfrastructure will enable the meta-analysis of large collections of LHC analyses, enable analysis queries, and facilitate the coordinated execution of multiple analyses. The latter is possible because the analysis descriptions are executable. This project will complete interfaces between ADL and three modern high-energy physics (HEP) analysis frameworks (TIMBER, RDataFrame, and Coffea); complete an interpreter for the language; build tools to query databases of analyses written in ADL; and build a fine-tuned large-language model that can translate between ADL and English, assisting in analysis queries. A key component of this project is to bring to production level the compiler infrastructure required to build these interfaces and the interpreter.
This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Physics at the Information Frontier Program in the Physics Section of 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.