Uncertainty aware machine-learning-based surrogate models for particle accelerators: Study at the Fermilab Booster Accelerator Complex

Malachi Schram, Kishansingh Rajput, Karthik Somayaji NS, Peng Li, Jason St. John, Himanshu Sharma

Open source

DOI: 10.1103/physrevaccelbeams.26.044602
Published: 4
Container: Physical Review Accelerators and Beams
Publisher: Not recorded
Open access: yes

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Cite this work

BibTeX

@article{allodium:10.1103/physrevaccelbeams.26.044602,
  title = {Uncertainty aware machine-learning-based surrogate models for particle accelerators: Study at the Fermilab Booster Accelerator Complex},
  author = {Malachi Schram and Kishansingh Rajput and Karthik Somayaji NS and Peng Li and Jason St. John and Himanshu Sharma},
  year = {2023},
  journal = {Physical Review Accelerators and Beams},
  doi = {10.1103/physrevaccelbeams.26.044602},
  url = {https://doi.org/10.1103/physrevaccelbeams.26.044602}
}

RIS

TY  - JOUR
TI  - Uncertainty aware machine-learning-based surrogate models for particle accelerators: Study at the Fermilab Booster Accelerator Complex
AU  - Malachi Schram
AU  - Kishansingh Rajput
AU  - Karthik Somayaji NS
AU  - Peng Li
AU  - Jason St. John
AU  - Himanshu Sharma
PY  - 2023
JO  - Physical Review Accelerators and Beams
DO  - 10.1103/physrevaccelbeams.26.044602
UR  - https://doi.org/10.1103/physrevaccelbeams.26.044602
ER  -

APA

Schram, M., Rajput, K., NS, K. S., Li, P., John, J. S., & Sharma, H. (2023). Uncertainty aware machine-learning-based surrogate models for particle accelerators: Study at the Fermilab Booster Accelerator Complex. Physical Review Accelerators and Beams. https://doi.org/10.1103/physrevaccelbeams.26.044602

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doaj · retrieved 2026-09-25T02:50:01.671Z