7–12 May 2023
Venice, Italy
Europe/Zurich timezone

A machine learning approach to shaping magnetic fringe fields for beam dynamics control

WEPA107
10 May 2023, 16:30
2h
Salone Adriatico

Salone Adriatico

Poster Presentation MC5.D13: Machine Learning Wednesday Poster Session

Speaker

Thomas Gallagher (The University of Liverpool)

Description

Fringe fields at the entrance and exit of multipole magnets can adversely affect the dynamics of particles in the beam, but there is also the possibility that fringe fields of the right form could be used to enhance the accelerator performance. Accelerator design work could benefit from efficient and realistic models of multipole fringe fields at an early stage in the design process. We explore novel techniques based upon analytical solutions of multipole fringe fields to produce magnets that satisfy specific requirements for the beam dynamics. Machine learning techniques are used in the design process currently being developed, to link properties of the beam dynamics to the magnet geometry in an efficient way.

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Primary author

Thomas Gallagher (The University of Liverpool)

Co-authors

Andrzej Wolski (The University of Liverpool) Bruno Muratori (Science and Technology Facilities Council)

Presentation materials

There are no materials yet.