Accelerator Modelling and Advanced Simulations Group

Accelerator Modelling and Advanced Simulations (AMAS)

Particle accelerators have helped to enable some of the most remarkable discoveries of the 20th century and are one of the bases of PSI. Accelerator-based systems have now been proposed to address problems of great importance to our society, which are basically related to energy, biology and the environment. Given the importance of particle accelerators, it is imperative that the most advanced numerical methods and high-performance computing tools be brought to bear on their design, optimization, and operation of such machines.

Computational accelerator physics which qualifies to perform system simulations or start-to-end simulations, is very demanding in terms of: interdisciplinary teamwork (physics, numerical mathematics and computational science) and computational resources. The AMAS group is part of the LSM, the Laboratory for Scientific Computing and Modeling situated in the NES division.

Mission

Bridging the gap between qualitative and quantitative modelling by combining and extending the latest developments in:

  • Accelerator-Physics
  • Numerical-Modelling and
  • High-Performance Computer Science

AMAS performs research in the area of accelerator system simulation, participates in educational efforts, maintains/establishes national and international collaboration. AMAS applies the developed methods to PSI's existing and future machines which in turn provide benchmarks for our methods.

AMAS

AMAS designs and adapts simulation tools for the needs of PSI with respect to realistic accelerator system simulation. Research in the area of methods and algorithms in a general beam dynamic context to fulfil the special modelling needs of current and future PSI accelerator projects. Actively use the simulation tools in order to calibrate the used model, and better understand the existing PSI machines. Participate in new projects at PSI and in the community.

Educational effort in hosting summer students and providing masters and PhD. thesis primary at the EPFL and ETHZ, in computational accelerator physics including aspects of high-performance computing, within the thematic framework of multi-scale modelling.

OPAL

IPPL

Latest Documents

ETH

  • Sadr M, Hadjiconstantinou NG, Gorji MH
    Wasserstein-penalized entropy closure: a use case for stochastic particle methods
    Journal of Computational Physics. 2024; 511: 113066 (27 pp.). https://doi.org/10.1016/j.jcp.2024.113066
    DORA PSI
  • Albà A, Adelmann A, Münster L, Rochman D, Boiger R
    Fast uncertainty quantification of spent nuclear fuel with neural networks
    Annals of Nuclear Energy. 2024; 196: 110204 (8 pp.). https://doi.org/10.1016/j.anucene.2023.110204
    DORA PSI
  • Gassner M, Barranco Garcia J, Tanadini-Lang S, Bertoldo F, Fröhlich F, Guckenberger M, et al.
    Saliency-enhanced content-based image retrieval for diagnosis support in dermatology consultation: reader study
    JMIR Dermatology. 2023; 6(1): e42129 (10 pp.). https://doi.org/10.2196/42129
    DORA PSI
  • Winklehner D, Adelmann A, Alonso JR, Calabretta L, Okuno H, Planche T, et al.
    High-power fixed-field accelerators
    Journal of Instrumentation. 2023; 18(5): T05008 (59 pp.). https://doi.org/10.1088/1748-0221/18/05/T05008
    DORA PSI
  • Li S, Adelmann A
    Time series forecasting methods and their applications to particle accelerators
    Physical Review Accelerators and Beams. 2023; 26(2): 024801 (16 pp.). https://doi.org/10.1103/PhysRevAccelBeams.26.024801
    DORA PSI
  • Albà A, Seok J, Adelmann A, Doran S, Ha G, Lee S, et al.
    Benchmarking collective effects of electron interactions in a wiggler with OPAL-FEL
    Computer Physics Communications. 2022; 280: 108475 (9 pp.). https://doi.org/10.1016/j.cpc.2022.108475
    DORA PSI
  • Koser D, Waites L, Winklehner D, Frey M, Adelmann A, Conrad J
    Input beam matching and beam dynamics design optimizations of the IsoDAR RFQ using statistical and machine learning techniques
    Frontiers in Physics. 2022; 10: 875889 (10 pp.). https://doi.org/10.3389/fphy.2022.875889
    DORA PSI
  • Winklehner D, Conrad JM, Schoen D, Yampolskaya M, Adelmann A, Mayani S, et al.
    Order-of-magnitude beam current improvement in compact cyclotrons
    New Journal of Physics. 2022; 24(2): 023038 (22 pp.). https://doi.org/10.1088/1367-2630/ac5001
    DORA PSI
  • Boiger R, Modini RL, Moallemi A, Degen D, Adelmann A, Gysel-Beer M
    Retrieval of aerosol properties from in situ, multi-angle light scattering measurements using invertible neural networks
    Journal of Aerosol Science. 2022; 163: 105977 (20 pp.). https://doi.org/10.1016/j.jaerosci.2022.105977
    DORA PSI
  • Bellotti R, Boiger R, Adelmann A
    Fast, efficient and flexible particle accelerator optimisation using densely connected and invertible neural networks
    Information. 2021; 12(9): 351 (21 pp.). https://doi.org/10.3390/INFO12090351
    DORA PSI
  • Muralikrishnan S, Cerfon AJ, Frey M, Ricketson LF, Adelmann A
    Sparse grid-based adaptive noise reduction strategy for particle-in-cell schemes
    Journal of Computational Physics: X. 2021; 11: 100094 (31 pp.). https://doi.org/10.1016/j.jcpx.2021.100094
    DORA PSI
  • Kranjčević M, Riemann B, Adelmann A, Streun A
    Multiobjective optimization of the dynamic aperture using surrogate models based on artificial neural networks
    Physical Review Accelerators and Beams. 2021; 24(1): 014601 (15 pp.). https://doi.org/10.1103/PhysRevAccelBeams.24.014601
    DORA PSI
  • Li S, Zacharias M, Snuverink J, Coello de Portugal J, Perez-Cruz F, Reggiani D, et al.
    A novel approach for classification and forecasting of time series in particle accelerators
    Information. 2021; 12(3): 121 (21 pp.). https://doi.org/10.3390/info12030121
    DORA PSI
  • Frey M, Adelmann A
    Global sensitivity analysis on numerical solver parameters of particle-in-cell models in particle accelerator systems
    Computer Physics Communications. 2020; 258: 107577 (17 pp.). https://doi.org/10.1016/j.cpc.2020.107577
    DORA PSI
  • Edelen A, Neveu N, Frey M, Huber Y, Mayes C, Adelmann A
    Machine learning for orders of magnitude speedup in multiobjective optimization of particle accelerator systems
    Physical Review Accelerators and Beams. 2020; 23(4): 044601 (23 pp.). https://doi.org/10.1103/PhysRevAccelBeams.23.044601
    DORA PSI
  • Rizzoglio V, Adelmann A, Gerbershagen A, Meer D, Nesteruk KP, Schippers JM
    Uncertainty quantification analysis and optimization for proton therapy beam lines
    Physica Medica. 2020; 75: 11-18. https://doi.org/10.1016/j.ejmp.2020.05.013
    DORA PSI
  • Kranjčević M, Adelmann A, Arbenz P, Citterio A, Stingelin L
    Multi-objective shape optimization of radio frequency cavities using an evolutionary algorithm
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2019; 920: 106-114. https://doi.org/10.1016/j.nima.2018.12.066
    DORA PSI
  • Xu H, Locans U, Adelmann A, Stingelin L
    Calculation of longitudinal collective instabilities with mbtrack-cuda
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2019; 922: 345-351. https://doi.org/10.1016/j.nima.2019.01.041
    DORA PSI
  • Neveu N, Spentzouris L, Adelmann A, Ineichen Y, Kolano A, Metzger-Kraus C, et al.
    Parallel general purpose multiobjective optimization framework with application to electron beam dynamics
    Physical Review Accelerators and Beams. 2019; 22(5): 054602 (11 pp.). https://doi.org/10.1103/PhysRevAccelBeams.22.054602
    DORA PSI
  • Nesteruk KP, Calzolaio C, Meer D, Rizzoglio V, Seidel M, Schippers JM
    Large energy acceptance gantry for proton therapy utilizing superconducting technology
    Physics in Medicine and Biology. 2019; 64(17): 175007 (13 pp.). https://doi.org/10.1088/1361-6560/ab2f5f
    DORA PSI
  • Adelmann A
    On nonintrusive uncertainty quantification and surrogate model construction in particle accelerator modeling
    SIAM-ASA Journal on Uncertainty Quantification. 2019; 7(2): 383-416. https://doi.org/10.1137/16M1061928
    DORA PSI
  • Kranjčević M, Gorgi Zadeh S, Adelmann A, Arbenz P, van Rienen U
    Constrained multiobjective shape optimization of superconducting rf cavities considering robustness against geometric perturbations
    Physical Review Accelerators and Beams. 2019; 22(12): 122001 (14 pp.). https://doi.org/10.1103/PhysRevAccelBeams.22.122001
    DORA PSI
  • Niedermayer U, Adelmann A, Bettoni S, Calvi M, Dehler M, Ferrari E, et al.
    Challenges in simulating beam dynamics of dielectric laser acceleration
    International Journal of Modern Physics A. 2019; 34(36): 1942031 (15 pp.). https://doi.org/10.1142/S0217751X19420314
    DORA PSI
  • Frey M, Adelmann A, Locans U
    On architecture and performance of adaptive mesh refinement in an electrostatics Particle-In-Cell code
    Computer Physics Communications. 2020; 247: 106912 (18 pp.). https://doi.org/10.1016/j.cpc.2019.106912
    DORA PSI
  • Frey M, Snuverink J, Baumgarten C, Adelmann A
    Matching of turn pattern measurements for cyclotrons using multiobjective optimization
    Physical Review Accelerators and Beams. 2019; 22(6): 064602 (13 pp.). https://doi.org/10.1103/PhysRevAccelBeams.22.064602
    DORA PSI
  • Kolano A, Adelmann A, Barlow R, Baumgarten C
    Intensity limits of the PSI Injector II cyclotron
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2018; 885: 54-59. https://doi.org/10.1016/j.nima.2017.12.045
    DORA PSI
  • Rizzoglio V, Adelmann A, Baumgarten C, Meer D, Snuverink J, Talanov V
    On the accuracy of Monte Carlo based beam dynamics models for the degrader in proton therapy facilities
    Nuclear Instruments and Methods in Physics Research, Section A: Accelerators, Spectrometers, Detectors and Associated Equipment. 2018; 898: 1-10. https://doi.org/10.1016/j.nima.2018.04.057
    DORA PSI
  • Adelmann A, Hermann B, Ischebeck R, Kaluza MC, Locans U, Sauerwein N, et al.
    Real-time tomography of gas-jets with a Wollaston Interferometer
    Applied Sciences. 2018; 8(3): 443 (21 pp.). https://doi.org/10.3390/app8030443
    DORA PSI

2017

  • Evolution of a beam dynamics model for the transport line in a proton therapy facility Rizzoglio V, Adelmann A, Baumgarten C, Frey M, Gerbershagen A, Meer D, Schippers J M
    Physical Review Accelerators and Beams 20, 124702 (2017).
    DOI: 10.1103/PhysRevAccelBeams.20.124702
  • Real-time computation of parameter fitting and image reconstruction using graphical processing units Locans Uldis, Adelmann Andreas, Suter Andreas, Fischer Jannis, Lustermann Werner, Dissertori Gunther, Wang Qiulin
    COMPUTER PHYSICS COMMUNICATIONS 215, 71-80 (2017).
    DOI: 10.1016/j.cpc.2017.02.007
  • Realistic simulations of a cyclotron spiral inflector within a particle-in-cell framework Winklehner Daniel, Adelmann Andreas, Gsell Achim, Kaman Tulin, Campo Daniela
    Physical Review Accelerators and Beams 20, 124201 (2017).
    DOI: 10.1103/PhysRevAccelBeams.20.124201
  • Simulations and measurements of proton beam energy spectrum after energy degradation Gerbershagen A, Adelmann A, Dolling R, Meer D, Rizzoglio V, Schippers J M
    8TH INTERNATIONAL PARTICLE ACCELERATOR CONFERENCE (IPAC 2017) 874, UNSP 012108 (2017).
    DOI: 10.1088/1742-6596/874/1/012108

2016

  • Analysis and suppression of RF radiation from the PSI 590 MeV cyclotron Flat Top Cavity Pogue N J, Stingelin L, Adelmann A
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 828, 156-162 (2016).
    DOI: 10.1016/j.nima.2016.05.026
  • Examination of the plasma located in PSI Ring Cyclotron Pogue N J, Adelmann A, Schneider M, Stingelin L
    NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION A-ACCELERATORS SPECTROMETERS DETECTORS AND ASSOCIATED EQUIPMENT 821, 87-92 (2016).
    DOI: 10.1016/j.nima.2016.03.013
  • The Dynamic Kernel Scheduler-Part 1 Adelmann Andreas, Locans Uldis, Suter Andreas
    COMPUTER PHYSICS COMMUNICATIONS 207, 83-90 (2016).
    DOI: 10.1016/j.cpc.2016.05.013

2015

  • Multilevel Monte Carlo for the Feynman-Kac formula for the Laplace equation Pauli Stefan, Gantner Robert Nicholas, Arbenz Peter, Adelmann Andreas
    BIT Numerical Mathematics 55, 1125-1143 (2015).
    DOI: 10.1007/s10543-014-0543-8

2014

  • A novel adaptive time stepping variant of the Boris-Buneman integrator for the simulation of particle accelerators with space charge Toggweiler Matthias, Adelmann Andreas, Arbenz Peter, Yang Jianjun
    JOURNAL OF COMPUTATIONAL PHYSICS 273, 255-267 (2014).
    DOI: 10.1016/j.jcp.2014.05.008
  • Cyclotrons as Drivers for Precision Neutrino Measurements Adelmann A, Alonso J, Barletta W A, Conrad J M, Shaevitz M H, Spitz J, Toups M, Winslow M A
    Advances in High Energy Physics , 347097 (2014).
    DOI: 10.1155/2014/347097