Author: Frey, M.
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Computer Architecture Independent Adaptive Geometric Multigrid Solver for AMR-PIC  
  • M. Frey, A. Adelmann
    PSI, Villigen PSI, Switzerland
  Funding: SNSF project 200021159936
The accurate and efficient simulation of neighboring bunch effects in high intensity cyclotrons requires to solve large-scale N-body problems of O(109…10zEhNZeHn) particles coupled with Maxwell’s equations. In order to capture the effects of halo creation and evolution of such simulations with standard particle-in-cell models an extremely fine mesh with O(108…109) grid points is necessary to meet the condition of high resolution. This requirement represents a waste of memory in regions of void, therefore, the usage of block-structured adaptive mesh refinement algorithms is more suitable. The N-body problem is then solved on a hierarchy of levels and grids using geometric multigrid algorithms. We show benchmarks of a new implementation of an adaptive geometric multigrid algorithm using 2nd generation Trilinos packages that ran on Piz Daint with O(104…105) cores.
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Surrogate Models for Beam Dynamics in Charged Particle Accelerators  
  • A.L. Edelen
    SLAC, Menlo Park, California, USA
  • D. Acharya, A. Adelmann, M. Frey
    PSI, Villigen PSI, Switzerland
  • N.R. Neveu
    ANL, Argonne, Illinois, USA
  High-fidelity, PIC-based beam dynamics simulations are time and resource intensive. Consider a high dimensional search space, that is far too large to probe with such a high resolution simulation model. We demonstrate that a coarse sampling of the search space can produce surrogate models, which are accurate and fast to evaluate. In constructing the surrogate models, we use artificial neural networks [1] and multivariate polynomial chaos expansion [2]. The performance of both methods are demonstrated in a comparison with high-fidelity simulations, using OPAL, of the Argonne Wakefield Accelerator [3]. We claim that such surrogate models are good candidates for accurate on-line modeling of large, complex accelerator systems. We also address how to estimate the accuracy of the surrogate model and how to refine the surrogate model under changing machine conditions. [1] A. L. Edelen et al., arXiv:1610.06151[physics.acc- ph] [2] A. Adelmann, arXiv:1509.08130v6[physics.acc- ph] [3] N. Neveu et al., 2017 J. Phys.: Conf. Ser. 874 012062  
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Trimcoil Optimisation Using Multi-Objective Optimisation Techniques and HPC  
  • M. Frey, A. Adelmann, J. Snuverink
    PSI, Villigen PSI, Switzerland
  Funding: SNSF project 200021159936
Uncertainties in the bunch injection (i.e. energy, radius, radial momentum and angle) as well as magnet inaccuracies harm the isochronicity of the PSI 590 MeV Ring Cyclotron. An additional magnetic field provided by trim coils is an effective solution to restore this condition. Therefore, an accurate description of trim coils is essential to match the turn pattern of the machine in simulations. However, due to the high-dimensional search space consisting of 21 design variables and more than 180 objectives the turns cannot be matched in a straightforward manner and without sufficient HPC resources. In this talk we present a realistic trim coil model for the PSI 590 MeV Ring Cyclotron implemented in OPAL that was used together with its built-in multi-objective optimisation algorithm to find the 4 injection parameters and the magnetic field strengths of 17 trim coils. The optimisations were performed on Piz Daint (currently 3rd fastest supercomputer world-wide) with more than 1000 cores per job.
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