7,173 research outputs found
The exponentially convergent trapezoidal rule
It is well known that the trapezoidal rule converges geometrically when applied to analytic functions on periodic intervals or the real line. The mathematics and history of this phenomenon are reviewed and it is shown that far from being a curiosity, it is linked with computational methods all across scientific computing, including algorithms related to inverse Laplace transforms, special functions, complex analysis, rational approximation, integral equations, and the computation of functions and eigenvalues of matrices and operators
On the numerical stability of Fourier extensions
An effective means to approximate an analytic, nonperiodic function on a
bounded interval is by using a Fourier series on a larger domain. When
constructed appropriately, this so-called Fourier extension is known to
converge geometrically fast in the truncation parameter. Unfortunately,
computing a Fourier extension requires solving an ill-conditioned linear
system, and hence one might expect such rapid convergence to be destroyed when
carrying out computations in finite precision. The purpose of this paper is to
show that this is not the case. Specifically, we show that Fourier extensions
are actually numerically stable when implemented in finite arithmetic, and
achieve a convergence rate that is at least superalgebraic. Thus, in this
instance, ill-conditioning of the linear system does not prohibit a good
approximation.
In the second part of this paper we consider the issue of computing Fourier
extensions from equispaced data. A result of Platte, Trefethen & Kuijlaars
states that no method for this problem can be both numerically stable and
exponentially convergent. We explain how Fourier extensions relate to this
theoretical barrier, and demonstrate that they are particularly well suited for
this problem: namely, they obtain at least superalgebraic convergence in a
numerically stable manner
Discontinuous collocation methods and gravitational self-force applications
Numerical simulations of extereme mass ratio inspirals, the mostimportant
sources for the LISA detector, face several computational challenges. We
present a new approach to evolving partial differential equations occurring in
black hole perturbation theory and calculations of the self-force acting on
point particles orbiting supermassive black holes. Such equations are
distributionally sourced, and standard numerical methods, such as
finite-difference or spectral methods, face difficulties associated with
approximating discontinuous functions. However, in the self-force problem we
typically have access to full a-priori information about the local structure of
the discontinuity at the particle. Using this information, we show that
high-order accuracy can be recovered by adding to the Lagrange interpolation
formula a linear combination of certain jump amplitudes. We construct
discontinuous spatial and temporal discretizations by operating on the
corrected Lagrange formula. In a method-of-lines framework, this provides a
simple and efficient method of solving time-dependent partial differential
equations, without loss of accuracy near moving singularities or
discontinuities. This method is well-suited for the problem of time-domain
reconstruction of the metric perturbation via the Teukolsky or
Regge-Wheeler-Zerilli formalisms. Parallel implementations on modern CPU and
GPU architectures are discussed.Comment: 29 pages, 5 figure
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