19–24 May 2024
Music City Center
US/Central timezone

Machine learning for orbit steering in synchrotrons

TUCN2
21 May 2024, 15:20
20m
Room 104 (Music City Center)

Room 104

Music City Center

201 Rep. John Lewis Way S, Nashville, TN 37203, USA
Contributed Oral Presentation MC2.A04 Circular Accelerators TUCN: Photon Sources and Electron Accelerators (Contributed)

Speaker

Simona Bettoni (Paul Scherrer Institut)

Description

In the latest years Machine Learning (ML) has seen an unprecedented diffusion in the most different fields in simulations and real life as well. Probably two of the first and most used ML applications in accelerators are the optimization of the final performance of the machines, and the so called virtual diagnostics. In the latest years ML was successfully applied to improve the machine safety performing fault detection or to prevent interlocks. In this work we explored the possibility to use a ML approach to efficiently steer the beam in case the lattice contains high order magnets (sextupolar order and higher). We applied this scheme to SLS 2.0, the synchrotron upgrading at the Paul Scherrer Institut.

Region represented Europe
Paper preparation format LaTeX

Primary author

Simona Bettoni (Paul Scherrer Institut)

Co-authors

Jonas Kallestrup (Paul Scherrer Institut) Michael Böge (Paul Scherrer Institut) Romana Boiger (Paul Scherrer Institut)

Presentation materials

There are no materials yet.