Erik Gottschalk | Searcharxiv

arXiv2026

AI-Ready Control System for the Fermilab Accelerator Complex

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 illustrate the technical requirements across the complex.

physics.acc-ph↗

arXiv1999

Triggering BTeV

BTeV is a collider experiment at Fermilab designed for precision studies of CP violation and mixing. Unlike most collider experiments, the BTeV detector has a forward geometry that is optimized for the measurement of B and charm decays in a high-rate environment. While the rate of B production gives BTeV an advantage of almost four orders of magnitude over e+e- B factories, the BTeV Level 1 trigger must be able to accept data at a rate of 100 Gigabytes per second, reconstruct tracks and vertices, trigger on B events with high efficiency, and reject minimum bias events by a factor of 100:1. An overview of the Level 1 trigger will be presented.

hep-ex↗