276 research outputs found
On the resolution power of Fourier extensions for oscillatory functions
Functions that are smooth but non-periodic on a certain interval possess
Fourier series that lack uniform convergence and suffer from the Gibbs
phenomenon. However, they can be represented accurately by a Fourier series
that is periodic on a larger interval. This is commonly called a Fourier
extension. When constructed in a particular manner, Fourier extensions share
many of the same features of a standard Fourier series. In particular, one can
compute Fourier extensions which converge spectrally fast whenever the function
is smooth, and exponentially fast if the function is analytic, much the same as
the Fourier series of a smooth/analytic and periodic function.
With this in mind, the purpose of this paper is to describe, analyze and
explain the observation that Fourier extensions, much like classical Fourier
series, also have excellent resolution properties for representing oscillatory
functions. The resolution power, or required number of degrees of freedom per
wavelength, depends on a user-controlled parameter and, as we show, it varies
between 2 and \pi. The former value is optimal and is achieved by classical
Fourier series for periodic functions, for example. The latter value is the
resolution power of algebraic polynomial approximations. Thus, Fourier
extensions with an appropriate choice of parameter are eminently suitable for
problems with moderate to high degrees of oscillation.Comment: Revised versio
Detection of Edges in Spectral Data II. Nonlinear Enhancement
We discuss a general framework for recovering edges in piecewise smooth
functions with finitely many jump discontinuities, where . Our approach is based on two main aspects--localization using
appropriate concentration kernels and separation of scales by nonlinear
enhancement.
To detect such edges, one employs concentration kernels, ,
depending on the small scale . It is shown that odd kernels, properly
scaled, and admissible (in the sense of having small -moments of
order ) satisfy , thus recovering both the location and amplitudes of all edges.As
an example we consider general concentration kernels of the form
to detect edges from the first
spectral modes of piecewise smooth f's. Here we improve in
generality and simplicity over our previous study in [A. Gelb and E. Tadmor,
Appl. Comput. Harmon. Anal., 7 (1999), pp. 101-135]. Both periodic and
nonperiodic spectral projections are considered. We identify, in particular, a
new family of exponential factors, , with superior
localization properties.
The other aspect of our edge detection involves a nonlinear enhancement
procedure which is based on separation of scales between the edges, where
, and the smooth regions where . Numerical examples demonstrate that by coupling
concentration kernels with nonlinear enhancement one arrives at effective edge
detectors
An adaptive pseudospectral method for discontinuous problems
The accuracy of adaptively chosen, mapped polynomial approximations is studied for functions with steep gradients or discontinuities. It is shown that, for steep gradient functions, one can obtain spectral accuracy in the original coordinate system by using polynomial approximations in a transformed coordinate system with substantially fewer collocation points than are necessary using polynomial expansion directly in the original, physical, coordinate system. It is also shown that one can avoid the usual Gibbs oscillation associated with steep gradient solutions of hyperbolic pde's by approximation in suitably chosen coordinate systems. Continuous, high gradient solutions are computed with spectral accuracy (as measured in the physical coordinate system). Discontinuous solutions associated with nonlinear hyperbolic equations can be accurately computed by using an artificial viscosity chosen to smooth out the solution in the mapped, computational domain. Thus, shocks can be effectively resolved on a scale that is subgrid to the resolution available with collocation only in the physical domain. Examples with Fourier and Chebyshev collocation are given
Extension of Chebfun to Periodic Functions
Algorithms and underlying mathematics are presented for numerical computation with periodic functions via approximations to machine precision by trigonometric polynomials, including the solution of linear and nonlinear periodic ordinary differential equations. Differences from the nonperiodic Chebyshev case are highlighted
A rational spectral collocation method with adaptively transformed Chebyshev grid points
A spectral collocation method based on rational interpolants and adaptive grid points is presented. The rational interpolants approximate analytic functions with exponential accuracy by using prescribed barycentric weights and transformed Chebyshev points. The locations of the grid points are adapted to singularities of the underlying solution, and the locations of these singularities are approximated by the locations of poles of Chebyshev-Padé approximants. Numerical experiments on two time-dependent problems, one with finite time blow-up and one with a moving front, indicate that the method far outperforms the standard Chebyshev spectral collocation method for problems whose solutions have singularities in the complex plan close to [-1,1]
Spectral method for matching exterior and interior elliptic problems
A spectral method is described for solving coupled elliptic problems on an
interior and an exterior domain. The method is formulated and tested on the
two-dimensional interior Poisson and exterior Laplace problems, whose solutions
and their normal derivatives are required to be continuous across the
interface. A complete basis of homogeneous solutions for the interior and
exterior regions, corresponding to all possible Dirichlet boundary values at
the interface, are calculated in a preprocessing step. This basis is used to
construct the influence matrix which serves to transform the coupled boundary
conditions into conditions on the interior problem. Chebyshev approximations
are used to represent both the interior solutions and the boundary values. A
standard Chebyshev spectral method is used to calculate the interior solutions.
The exterior harmonic solutions are calculated as the convolution of the
free-space Green's function with a surface density; this surface density is
itself the solution to an integral equation which has an analytic solution when
the boundary values are given as a Chebyshev expansion. Properties of Chebyshev
approximations insure that the basis of exterior harmonic functions represents
the external near-boundary solutions uniformly. The method is tested by
calculating the electrostatic potential resulting from charge distributions in
a rectangle. The resulting influence matrix is well-conditioned and solutions
converge exponentially as the resolution is increased. The generalization of
this approach to three-dimensional problems is discussed, in particular the
magnetohydrodynamic equations in a finite cylindrical domain surrounded by a
vacuum
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
- …