584 research outputs found
A SVD accelerated kernel-independent fast multipole method and its application to BEM
The kernel-independent fast multipole method (KIFMM) proposed in [1] is of
almost linear complexity. In the original KIFMM the time-consuming M2L
translations are accelerated by FFT. However, when more equivalent points are
used to achieve higher accuracy, the efficiency of the FFT approach tends to be
lower because more auxiliary volume grid points have to be added. In this
paper, all the translations of the KIFMM are accelerated by using the singular
value decomposition (SVD) based on the low-rank property of the translating
matrices. The acceleration of M2L is realized by first transforming the
associated translating matrices into more compact form, and then using low-rank
approximations. By using the transform matrices for M2L, the orders of the
translating matrices in upward and downward passes are also reduced. The
improved KIFMM is then applied to accelerate BEM. The performance of the
proposed algorithms are demonstrated by three examples. Numerical results show
that, compared with the original KIFMM, the present method can reduce about 40%
of the iterating time and 25% of the memory requirement.Comment: 19 pages, 4 figure
Adaptive quadrature by expansion for layer potential evaluation in two dimensions
When solving partial differential equations using boundary integral equation
methods, accurate evaluation of singular and nearly singular integrals in layer
potentials is crucial. A recent scheme for this is quadrature by expansion
(QBX), which solves the problem by locally approximating the potential using a
local expansion centered at some distance from the source boundary. In this
paper we introduce an extension of the QBX scheme in 2D denoted AQBX - adaptive
quadrature by expansion - which combines QBX with an algorithm for automated
selection of parameters, based on a target error tolerance. A key component in
this algorithm is the ability to accurately estimate the numerical errors in
the coefficients of the expansion. Combining previous results for flat panels
with a procedure for taking the panel shape into account, we derive such error
estimates for arbitrarily shaped boundaries in 2D that are discretized using
panel-based Gauss-Legendre quadrature. Applying our scheme to numerical
solutions of Dirichlet problems for the Laplace and Helmholtz equations, and
also for solving these equations, we find that the scheme is able to satisfy a
given target tolerance to within an order of magnitude, making it useful for
practical applications. This represents a significant simplification over the
original QBX algorithm, in which choosing a good set of parameters can be hard
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