Preliminary Application of Bayesian Inference in Accelerator Commissioning

Yue Hao, Department of Physics and Astronomy, NSCL/FRIB Michigan State University USA

In this talk we will report the preliminary application of the Bayesian Inference of the unknown parameters of accelerator model using the Facility for Rare Isotope Beams (FRIB) commissioning data. The inference result not only indicates the value of the unknown parameter, but also the confidence of adopting the value. The Bayesian approach provides an alternative method to understand the difference between the accelerator model and the hardware and may help achieving ultimate beam parameters of FRIB.

Please direct all questions to the following contacts - Your question will be routed to get you an answer as quickly as possible.

• MSUStatSymposium2018@stt.msu.edu
• Michigan State University
  Department of Statistics and Probability
  Room C413 Wells Hall
  619 Red Cedar Road
  East Lansing, MI 48824