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The Bayesian Optimization for Ion Steering (BOIS) method automates beam steering at TRIUMF ISAC. This new technique achieves results comparable to human operators, ensuring reliable experimental beam delivery.

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Area of Science:

  • Particle accelerator physics
  • Computational physics

Background:

  • The TRIUMF ISAC facility requires precise control of ion beams for experiments.
  • Manual beam steering is operator-dependent and can be time-consuming.

Purpose of the Study:

  • To develop and implement an automated beam steering method for the TRIUMF ISAC facility.
  • To reduce reliance on human operators and improve the efficiency of beam delivery.

Main Methods:

  • The Bayesian Optimization for Ion Steering (BOIS) method was developed as part of the TRIUMF automatic beam tuning program.
  • BOIS controls steerers for corrective centroid steering after theoretical transverse optics are established.
  • Proof-of-concept solutions, scaleBOIS and boundBOIS, were explored for path selection with minimal steering.

Main Results:

  • BOIS was successfully tested on low energy and post-accelerated beams at the ISAC facility.
  • The automated method achieved steering results comparable to those of experienced human operators.
  • The system demonstrated robustness and repeatability in beam steering operations.

Conclusions:

  • Automated steering using BOIS reduces operational overhead and reliance on specialized expertise.
  • The method ensures reliable beam delivery, directly supporting TRIUMF's scientific mission.
  • BOIS offers a scalable and deployable solution for particle accelerator beam tuning.