Speaker
Description
In this groundbreaking study, an advanced particle-in-cell (PIC) simulation code,QuickPIC, is used to explore beam physics within Plasma Wakefield Accelerators (PWFA). The primary aim is to comprehensively analyze beam distributions, particularly those exhibiting perturbations with significant instabilities. To connect simulated beam distributions to physical observables, the study uses cutting-edge neural networks. This research underscores the transformative potential of machine learning (ML) in unraveling PWFA complexities and enhancing our capabilities in the development of advanced accelerators.
Funding Agency
This work was performed with the support of the US DOE, Division of HEP, under Contract No. DE-SC0009914, NSF PHY-1549132 CBB, DARPA under Contract N.HR001120C007.
Region represented | North America |
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Paper preparation format | LaTeX |