108 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
On the computation of Gaussian quadrature rules for Chebyshev sets of linearly independent functions
We consider the computation of quadrature rules that are exact for a
Chebyshev set of linearly independent functions on an interval . A
general theory of Chebyshev sets guarantees the existence of rules with a
Gaussian property, in the sense that basis functions can be integrated
exactly with just points and weights. Moreover, all weights are positive
and the points lie inside the interval . However, the points are not the
roots of an orthogonal polynomial or any other known special function as in the
case of regular Gaussian quadrature. The rules are characterized by a nonlinear
system of equations, and earlier numerical methods have mostly focused on
finding suitable starting values for a Newton iteration to solve this system.
In this paper we describe an alternative scheme that is robust and generally
applicable for so-called complete Chebyshev sets. These are ordered Chebyshev
sets where the first elements also form a Chebyshev set for each . The
points of the quadrature rule are computed one by one, increasing exactness of
the rule in each step. Each step reduces to finding the unique root of a
univariate and monotonic function. As such, the scheme of this paper is
guaranteed to succeed. The quadrature rules are of interest for integrals with
non-smooth integrands that are not well approximated by polynomials
Fast Algorithms for the computation of Fourier Extensions of arbitrary length
Fourier series of smooth, non-periodic functions on are known to
exhibit the Gibbs phenomenon, and exhibit overall slow convergence. One way of
overcoming these problems is by using a Fourier series on a larger domain, say
with , a technique called Fourier extension or Fourier
continuation. When constructed as the discrete least squares minimizer in
equidistant points, the Fourier extension has been shown shown to converge
geometrically in the truncation parameter . A fast algorithm has been described to compute Fourier extensions for the case
where , compared to for solving the dense discrete
least squares problem. We present two algorithms for
the computation of these approximations for the case of general , made
possible by exploiting the connection between Fourier extensions and Prolate
Spheroidal Wave theory. The first algorithm is based on the explicit
computation of so-called periodic discrete prolate spheroidal sequences, while
the second algorithm is purely algebraic and only implicitly based on the
theory
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
On the eigenmodes of periodic orbits for multiple scattering problems in 2D
Wave propagation and acoustic scattering problems require vast computational
resources to be solved accurately at high frequencies. Asymptotic methods can
make this cost potentially frequency independent by explicitly extracting the
oscillatory properties of the solution. However, the high-frequency wave
pattern becomes very complicated in the presence of multiple scattering
obstacles. We consider a boundary integral equation formulation of the
Helmholtz equation in two dimensions involving several obstacles, for which ray
tracing schemes have been previously proposed. The existing analysis of ray
tracing schemes focuses on periodic orbits between a subset of the obstacles.
One observes that the densities on each of the obstacles converge to an
equilibrium after a few iterations. In this paper we present an asymptotic
approximation of the phases of those densities in equilibrium, in the form of a
Taylor series. The densities represent a full cycle of reflections in a
periodic orbit. We initially exploit symmetry in the case of two circular
scatterers, but also provide an explicit algorithm for an arbitrary number of
general 2D obstacles. The coefficients, as well as the time to compute them,
are independent of the wavenumber and of the incident wave. The results may be
used to accelerate ray tracing schemes after a small number of initial
iterations.Comment: 24 pages, 9 figures and the implementation is available on
https://github.com/popsomer/asyBEM/release
High-frequency asymptotic compression of dense BEM matrices for general geometries without ray tracing
Wave propagation and scattering problems in acoustics are often solved with
boundary element methods. They lead to a discretization matrix that is
typically dense and large: its size and condition number grow with increasing
frequency. Yet, high frequency scattering problems are intrinsically local in
nature, which is well represented by highly localized rays bouncing around.
Asymptotic methods can be used to reduce the size of the linear system, even
making it frequency independent, by explicitly extracting the oscillatory
properties from the solution using ray tracing or analogous techniques.
However, ray tracing becomes expensive or even intractable in the presence of
(multiple) scattering obstacles with complicated geometries. In this paper, we
start from the same discretization that constructs the fully resolved large and
dense matrix, and achieve asymptotic compression by explicitly localizing the
Green's function instead. This results in a large but sparse matrix, with a
faster associated matrix-vector product and, as numerical experiments indicate,
a much improved condition number. Though an appropriate localisation of the
Green's function also depends on asymptotic information unavailable for general
geometries, we can construct it adaptively in a frequency sweep from small to
large frequencies in a way which automatically takes into account a general
incident wave. We show that the approach is robust with respect to non-convex,
multiple and even near-trapping domains, though the compression rate is clearly
lower in the latter case. Furthermore, in spite of its asymptotic nature, the
method is robust with respect to low-order discretizations such as piecewise
constants, linears or cubics, commonly used in applications. On the other hand,
we do not decrease the total number of degrees of freedom compared to a
conventional classical discretization. The combination of the ...Comment: 24 pages, 13 figure
- …