Bayesian optimization algorithms for accelerator physics
Ryan Roussel,
Auralee L. Edelen,
Tobias Boltz
et al.
Abstract:Accelerator physics relies on numerical algorithms to solve optimization problems in online accelerator control and tasks such as experimental design and model calibration in simulations. The effectiveness of optimization algorithms in discovering ideal solutions for complex challenges with limited resources often determines the problem complexity these methods can address. The accelerator physics community has recognized the advantages of Bayesian optimization algorithms, which leverage statistical surrogate … Show more
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