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arXiv · 2511.19141

Automated RF Phase Adjustment for Beam Stabilization in the Fermilab Linac

R. R. Chichili·J. A. Sulskis·R. Sharankova·B. Vamanan·S. Ravi
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Abstract

The Fermilab Linac experiences longitudinal beam phase drift, leading to increased particle loss, conventionally corrected through labor-intensive manual RF adjustments. This project explores machine learning-based automation for drift correction, employing a prototype-based classification approach. Our model utilizes a 34-dimensional feature set (RF settings and BPM readings) and leverages a 7x27 response matrix for system modeling. To overcome limited real-world data, we generate synthetic data, enhancing model training and generalizability. Custom loss functions, including a surrogate energy-consistent loss and a temporal smoothness constraint, ensure physically plausible drift predictions. The goal is a robust system for autonomous phase adjustments, ensuring stable beam acceleration and reduced manual intervention.

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R. R. Chichili, J. A. Sulskis, R. Sharankova, B. Vamanan, S. Ravi. 2025-11-24. Automated RF Phase Adjustment for Beam Stabilization in the Fermilab Linac. https://doi.org/10.18429/jacow-napac2025-mop011

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