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20162022
most citedSimulations of Future Particle Accelerators: Issues and Mitigations

7 citations · 16 across the 8 of their papers we have counts for

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8 papers · 1 filter

physics.acc-ph20222 cited

Feedback and control systems for future linear colliders: White Paper for Snowmass 2021 Topical Group AF07-RF

Daniele Filippetto, Carlos Serrano, Qiang Du +9

Particle accelerators for high energy physics will generate TeV-scale particle beams in large, multi-Km size machines colliding high brightness beams at the interaction point [1-4]…

physics.acc-ph20221 cited

Adaptive Machine Learning for Time-Varying Systems: Towards 6D Phase Space Diagnostics of Short Intense Charged Particle Beams

Alexander Scheinker, Spencer Gessner

As charged particle bunches become shorter and more intense, the effects of nonlinear intra-bunch collective interactions such as space charge forces and bunch-to-bunch influences…

physics.acc-ph20217 cited

Simulations of Future Particle Accelerators: Issues and Mitigations

D. Sagan, M. Berz, N. M. Cook +15

The ever increasing demands placed upon machine performance have resulted in the need for more comprehensive particle accelerator modeling. Computer simulations are key to the succ…

physics.acc-ph20211 cited

Adaptive deep learning for time-varying systems with hidden parameters: Predicting changing input beam distributions of compact particle accelerators

Alexander Scheinker, Frederick Cropp, Sergio Paiagua +1

Machine learning (ML) tools such as encoder-decoder deep convolutional neural networks (CNN) are able to extract relationships between inputs and outputs of large complex systems d…

physics.acc-ph2020

Online Multi-Objective Particle Accelerator Optimization of the AWAKE Electron Beam Line for Simultaneous Emittance and Orbit Control

Alexander Scheinker, Simon Hirlaende, Francesco Maria Velotti +4

Multi-objective optimization is important for particle accelerators where various competing objectives must be satisfied routinely such as, for example, transverse emittance vs bun…

physics.acc-ph20205 cited

Advanced Control Methods for Particle Accelerators (ACM4PA) 2019 Workshop Report

Alexander Scheinker, Claudio Emma, Auralee L. Edelen +1

Los Alamos is currently developing novel particle accelerator controls and diagnostics algorithms to enable higher quality beams with lower beam losses than is currently possible.…