137 research outputs found
Efficient sum-of-exponentials approximations for the heat kernel and their applications
In this paper, we show that efficient separated sum-of-exponentials
approximations can be constructed for the heat kernel in any dimension. In one
space dimension, the heat kernel admits an approximation involving a number of
terms that is of the order for any x\in\bbR and
, where is the desired precision. In all
higher dimensions, the corresponding heat kernel admits an approximation
involving only terms for fixed accuracy
. These approximations can be used to accelerate integral
equation-based methods for boundary value problems governed by the heat
equation in complex geometry. The resulting algorithms are nearly optimal. For
points in the spatial discretization and time steps, the cost is
in terms of both memory and CPU time for
fixed accuracy . The algorithms can be parallelized in a
straightforward manner. Several numerical examples are presented to illustrate
the accuracy and stability of these approximations.Comment: 23 pages, 5 figures, 3 table
Solving Fredholm second-kind integral equations with singular right-hand sides on non-smooth boundaries
A numerical scheme is presented for the solution of Fredholm second-kind
boundary integral equations with right-hand sides that are singular at a finite
set of boundary points. The boundaries themselves may be non-smooth. The
scheme, which builds on recursively compressed inverse preconditioning (RCIP),
is universal as it is independent of the nature of the singularities. Strong
right-hand-side singularities, such as with close to
, can be treated in full machine precision. Adaptive refinement is used only
in the recursive construction of the preconditioner, leading to an optimal
number of discretization points and superior stability in the solve phase. The
performance of the scheme is illustrated via several numerical examples,
including an application to an integral equation derived from the linearized
BGKW kinetic equation for the steady Couette flow.Comment: 29 pages, 19 figure
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