activity
20182024
most citedMachine Learning for Orders of Magnitude Speedup in Multi-Objective Optimization of Particle Accelerator Systems

101 citations · 152 across the 9 of their papers we have counts for

collaborators

9 papers

physics.comp-ph2024

A Massively Parallel Performance Portable Free-space Spectral Poisson Solver

Sonali Mayani, Veronica Montanaro, Antoine Cerfon +3

Vico et al. (2016) suggest a fast algorithm for computing volume potentials, beneficial to fields with problems requiring the solution of the free-space Poisson's equation, such as…

physics.comp-ph2022★ 2 cited

Scaling and performance portability of the particle-in-cell scheme for plasma physics applications through mini-apps targeting exascale architectures

Sriramkrishnan Muralikrishnan, Matthias Frey, Alessandro Vinciguerra +5

We perform a scaling and performance portability study of the particle-in-cell scheme for plasma physics applications through a set of mini-apps we name "Alpine", which can make us…

physics.acc-ph2021★ 4 cited

Input Beam Matching and Beam Dynamics Design Optimization of the IsoDAR RFQ using Statistical and Machine Learning Techniques

Daniel Koser, Loyd Waites, Daniel Winklehner +3

We present a novel machine learning-based approach to generate fast-executing virtual radiofrequency quadrupole (RFQ) particle accelerators using surrogate modelling. These could p…

physics.comp-ph2020★ 1 cited

Sparse Grids based Adaptive Noise Reduction strategy for Particle-In-Cell schemes

Sriramkrishnan Muralikrishnan, Antoine J. Cerfon, Matthias Frey +2

We propose a sparse grids based adaptive noise reduction strategy for electrostatic particle-in-cell (PIC) simulations. Our approach is based on the key idea of relying on sparse g…

physics.comp-ph2020★ 6 cited

Global Sensitivity Analysis on Numerical Solver Parameters of Particle-In-Cell Models in Particle Accelerator Systems

Matthias Frey, Andreas Adelmann

Every computer model depends on numerical input parameters that are chosen according to mostly conservative but rigorous numerical or empirical estimates. These parameters could fo…

physics.acc-ph2019★ 24 cited

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…