AI-Ready Control System for the Fermilab Accelerator Complex
Tia Miceli, Erik Gottschalk, Donovan Tooke, Evan Milton, Robert Santucci, Hayden Hoschouer, Michael Balcewicz, Jennifer Case, Abhishek Deshpande, Kit Fieldhouse, Sudeshna Ganguly, Beau Harrison, Aisha Ibrahim, Thomas Kobilarcik, Michael Olander, Abhishek Pathak, Jason St. John

TL;DR
This paper discusses the development of an AI-ready control system for Fermilab's accelerator complex, focusing on infrastructure, data quality, and workflow integration to enable reliable AI/ML applications in accelerator operations.
Contribution
It introduces a comprehensive framework combining MLOps, data quality standards, and LLM integration to facilitate AI/ML deployment in accelerator control systems.
Findings
Established a MLOps framework for accelerator AI/ML lifecycle
Defined data quality standards for trustworthy AI applications
Demonstrated AI/ML use cases in beam diagnostics and control
Abstract
Reliable, high-intensity operation of the Fermilab Accelerator Complex is critical to the success of the Long-Baseline Neutrino Facility and Deep Underground Neutrino Experiment. We describe the requirements and infrastructure necessary to support routine use of artificial intelligence and machine learning (AI/ML) in the accelerator control system. Three capabilities are identified: a machine learning operations (MLOps) framework standardizing the lifecycle of AI/ML automation from data management through deployment and monitoring; a data quality framework defining and enforcing standards required to build trustworthy AI/ML applications; and workflow integration with large language models to assist physicists, engineers, and operators with information retrieval, code development, and routine analysis. Use cases spanning beam diagnostics, beam control, and support system automation…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsComputational Physics and Python Applications · International Science and Diplomacy · Neutrino Physics Research
