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Tia Miceli

Publications and source records attributed to Tia Miceli.

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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

Twinac: A Universal Framework for Virtual Accelerator Controls

We propose a universal framework for a system of virtual accelerator controls (Twinac), a standard toolkit for research institutions to design, maintain, and use a real-time, end-to-end "digital twin" of their particle accelerator facility. This virtual counterpart will mirror any physical accelerator to provide (1) predictive maintenance; (2) surveillance of hidden environmental factors, such as seasonal temperature variations, which could impact performance of power supplies, magnets, and other instruments; and (3) a capability to model novel ways to operate the accelerator without risking equipment damage. Twinac is envisioned as accelerator facility agnostic, allowing institutions to share and reuse myriad simulation approaches (analytics-based, A.I.-driven, or combinations of the like) across facilities. The Twinac system lays the groundwork for a collaborative network of institutions to maintain and update this shared virtual accelerator technology.

physics.acc-ph

Exploring Neutrino Interactions with MicroBooNE

Recently, MiniBooNE observed an electromagnetic excess at low energy. What is the nature of this excess? What about the nature of the low-energy excess at LSND 20 years ago? The MicroBooNE detector will see neutrinos from the same Booster beam at Fermilab as used by MiniBooNE. MicroBooNE's design will enable us to discriminate photons from electrons elucidating the MiniBooNE and LSND low-energy electromagnetic excesses. MicroBooNE is a 170 ton liquid argon time projection chamber (LArTPC) capable of imaging neutrino interactions with the detail of a bubble chamber, but with electronic data acquisition and processing. In addition to shining light on the low-energy excesses and measuring low-energy neutrino cross sections, MicroBooNE is leading the way for a more extensive short-baseline neutrino physics program at Fermilab and it also serves as a R&D project towards a long-baseline multi-kiloton scale LArTPC detector.

physics.ins-det

Improving Dark Matter Searches by Measuring the Nucleon Axial Form Factor: Perspectives from MicroBooNE

The MicroBooNE neutrino experiment at Fermilab is constructing a liquid-argon time-projection chamber for the Booster Neutrino Beam to study neutrino oscillations and interactions with nucleons and nuclei, starting in 2014. We describe the experiment and focus on its unique abilities to measure cross sections at low values of $Q^2$. In particular, the neutral-current elastic scattering cross section is especially interesting, as it is sensitive to the contribution of the strange sea quark spin to the angular-momentum of the nucleon, $Δs$. Implications for dark-matter searches are discussed.

hep-ex