• Medientyp: E-Artikel
  • Titel: Parameter Tuning for the NFFT Based Fast Ewald Summation
  • Beteiligte: Nestler, Franziska [VerfasserIn]
  • Erschienen: Chemnitz : Frontiers Research Foundation, [2016]
  • Sprache: Englisch
  • DOI: 10.3389/fphy.2016.00028
  • ISSN: 2296-424X
  • Schlagwörter: P2NFFT ; Fourier-Transformation ; Physik ; NFFT ; particle methods ; ScaFaCoS ; science-physics ; Publikationsfonds ; Ewald summation ; Finite-Punktmengen-Methode ; P3M ; Ewald-Summation ; nichtäquidistante schnelle Fourier-Transformation ; Technische Universität Chemnitz ; nonequispaced fast Fourier transform ; science-mathematics ; Mathematik ; Partikelmethoden ; Publication fund
  • Entstehung:
  • Anmerkungen: Hinweis: Link zur Originalpublikation in der Zeitschrift "Frontiers in Physics" URL: http://dx.doi.org/10.3389/fphy.2016.00028 DOI: 10.3389/fphy.2016.00028
    Quelle: Front. Phys. 4:28. doi: 10.3389/fphy.2016.00028

  • Beschreibung: The computation of the Coulomb potentials and forces in charged particle systems under 3d-periodic boundary conditions is possible in an efficient way by utilizing the Ewald summation formulas and applying the fast Fourier transform (FFT). In this paper we consider the particle-particle NFFT (P2NFFT) approach, which is based on the fast Fourier transform for nonequispaced data (NFFT) and compare the error behaviors regarding different window functions, which are used in order to approximate the given continuous charge distribution by a mesh based charge density. Typically B-splines are applied in the scope of particle mesh methods, as for instance within the well-known particle-particle particle-mesh (P3M) algorithm. The publicly available P2NFFT algorithm allows the application of an oversampled FFT as well as the usage of different window functions. We consider for the first time also an approximation by Bessel functions and show how the resulting root mean square errors in the forces can be predicted precisely and efficiently. The results show that, if the parameters are tuned appropriately, the Bessel window function is in many cases even the better choice in terms of computational costs. Moreover, the results indicate that it is often advantageous in terms of efficiency to spend some oversampling within the NFFT while using a window function with a smaller support.
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