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Sharankova, R. (ORCID:000000027014593X)

Publications and source records attributed to Sharankova, R. (ORCID:000000027014593X).

Diagnostics for Linac Optimization With Machine Learning

The Fermilab Linac delivers 400 MeV H- beam to the rest of the accelerator chain. Providing stable intensity, energy, and emittance is key since it directly affects downstream machines. To counter fluctuations of Linac output due to various effects to be described below we are working on implementing dynamic longitudinal parameter optimization based on Machine Learning (ML). As inputs for the ML model, signals from beam diagnostics have to be well understood and reliable. In this paper we discuss the status and plans for ML-based optimization as well as preliminary results of diagnostics studies.

43 PARTICLE ACCELERATORS↗

Operation of the H- Linac at FNAL

The Fermi National Accelerator Laboratory (FNAL) Linac has been in operation for 52 years. In approximately four years, it will be replaced by a new 800 MeV superconducting machine, the PIP-II SRF Linac. In the current configuration, the Linac delivers H- ions at 400 MeV and injects protons by charge exchange into the Booster synchrotron. Despite its age, the Linac is the most stable accelerator in the FNAL complex, reliably sending 22 mA in daily operations. We will discuss the status of the operation, beam studies, and plans.

43 PARTICLE ACCELERATORS↗