Accelerated Cartesian expansion (ACE) based framework for the rapid evaluation of diffusion, lossy wave, and Klein-Gordon potentials

  • Authors:

  • M. Vikram;A. Baczewski;B. Shanker;L. Kempel

  • Affiliations:

  • Michigan State University, Department of Electrical and Computer Engineering, East Lansing, MI, USA;Michigan State University, Department of Electrical and Computer Engineering, East Lansing, MI, USA and Michigan State University, Department of Physics and Astronomy, East Lansing, MI, USA;Michigan State University, Department of Electrical and Computer Engineering, East Lansing, MI, USA and Michigan State University, Department of Physics and Astronomy, East Lansing, MI, USA;Michigan State University, Department of Electrical and Computer Engineering, East Lansing, MI, USA

  • Venue:
  • Journal of Computational Physics
  • Year:
  • 2010

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Abstract

Diffusion, lossy wave, and Klein-Gordon equations find numerous applications in practical problems across a range of diverse disciplines. The temporal dependence of all three Green's functions are characterized by an infinite tail. This implies that the cost complexity of the spatio-temporal convolutions, associated with evaluating the potentials, scales as ON"s^2N"t^2, where N"s and N"t are the number of spatial and temporal degrees of freedom, respectively. In this paper, we discuss two new methods to rapidly evaluate these spatio-temporal convolutions by exploiting their block-Toeplitz nature within the framework of accelerated Cartesian expansions (ACE). The first scheme identifies a convolution relation in time amongst ACE harmonics and the fast Fourier transform (FFT) is used for efficient evaluation of these convolutions. The second method exploits the rank deficiency of the ACE translation operators with respect to time and develops a recursive numerical compression scheme for the efficient representation and evaluation of temporal convolutions. It is shown that the cost of both methods scales as O(N"sN"tlog^2N"t). Several numerical results are presented for the diffusion equation to validate the accuracy and efficacy of the fast algorithms developed here.