Author: De Maria, R.
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TUPMW015 Symplectic Tracking of Multi-Isotopic Heavy-Ion Beams in SixTrack 1450
  • P.D. Hermes, R. Bruce, R. De Maria
    CERN, Geneva, Switzerland
  Funding: Work suppported by the Wolfgang Gentner Programme of the German BMBF
The software SixTrack provides symplectic proton tracking over a large number of turns. The code is used for the tracking of beam halo particles and the simulation of their interaction with the collimators to study the efficiency of the LHC collimation system. Tracking simulations for heavy-ion beams require taking into account the mass to charge ratio of each particle because heavy ions can be subject to fragmentation at their passage through the collimators. In this paper we present the derivation of a Hamiltonian for multi-isotopic heavy-ion beams and symplectic tracking maps derived from it. The resulting tracking maps were implemented in the tracking software SixTrack. With this modification, SixTrack can be used to natively track heavy-ion beams of multiple isotopes through a magnetic accelerator lattice.
DOI • reference for this paper ※ DOI:10.18429/JACoW-IPAC2016-TUPMW015  
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WEPOY044 Review of CPU and GPU Faddeeva Implementations 3090
  • A. Oeftiger, R. De Maria, L. Deniau, K.S.B. Li, E. McIntosh, L. Moneta
    CERN, Geneva, Switzerland
  • A. Aviral
    BITS Pilani, Pilani, India
  • S. Hegglin
    ETH, Zurich, Switzerland
  • A. Oeftiger
    EPFL, Lausanne, Switzerland
  Funding: CERN, Doctoral Studentship EPFL, Doctorate
The Faddeeva error function is frequently used when computing electric fields generated by two-dimensional Gaussian charge distributions. Numeric evaluation of the Faddeeva function is particularly challenging since there is no single expansion that converges rapidly over the whole complex domain. Various algorithms exist, even in the recent literature there have been new proposals. The many different implementations in computer codes offer different trade-offs between speed and accuracy. We present an extensive benchmark of selected algorithms and implementations for accuracy, speed and memory footprint, both for CPU and GPU architectures.
DOI • reference for this paper ※ DOI:10.18429/JACoW-IPAC2016-WEPOY044  
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