24 citations · 27 across the 2 of their papers we have counts for
4 papers
Strategies in Education, Outreach, and Inclusion to Enhance the US Workforce in Accelerator Science and Engineering
M. Bai, W. A. Barletta, D. L. Bruhwiler +17
We summarize the community-based consensus for improvements concerning education, public outreach, and inclusion in Accelerator Science and Engineering that will enhance the workfo…
Improving Surrogate Model Accuracy for the LCLS-II Injector Frontend Using Convolutional Neural Networks and Transfer Learning
Lipi Gupta, Auralee Edelen, Nicole Neveu +3
Machine learning models of accelerator systems (`surrogate models') are able to provide fast, accurate predictions of accelerator physics phenomena. However, approaches to date typ…
OPAL a Versatile Tool for Charged Particle Accelerator Simulations
Andreas Adelmann, Pedro Calvo, Matthias Frey +9
Many sophisticated computer models have been developed to understand the behaviour of particle accelerators. Even these complex models often do not describe the measured data. Inte…
Machine Learning for Orders of Magnitude Speedup in Multi-Objective Optimization of Particle Accelerator Systems
Auralee Edelen, Nicole Neveu, Yannick Huber +3
High-fidelity physics simulations are powerful tools in the design and optimization of charged particle accelerators. However, the computational burden of these simulations often l…