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We are concerned here with fullydiscrete spectral/pseudospectral approximations to initialboundary value problems associated with hyperbolic equations. In this context, the spectral (and respectively, the pseudospectral) approximations consist of truncation (and, respectively, collocation) of Nterm spatial expansions, which are expressed in terms of general Jacobi polynomials; Chebyshev and Legendre expansions are the ones most frequently found in practice. We will show that such Nterm approximations are stable, provided their time step, , fulfills the CFLlike condition, .
To clarify the origin of such a CFLlike condition in our case, we recall that the Jacobi polynomials are in fact the eigenfunctions of secondorder singular SturmLiouville problems. Our arguments show that the main reason for the above CFL limitation is the growth of the Nth eigenvalue associated with these SturmLiouville problems.
We start with the scalar constantcoefficient hyperbolic equation,
which is augmented with homogeneous conditions at the inflow boundary,
To approximate (meth_cheb.1), we use forward Euler timedifferencing on the left,
and either spectral or dospectral differencing on the right. Thus, we
seek a temporal sequence of spatial polynomials, , such that
Here, is a polynomial which characterizes the specific
(pseudo)spectral method we employ, v' denotes spatial differentiation,
and is a free scalar
multiplier to be determined by the boundary constraint
We shall study the so called spectral tau method associated with
general Jacobi polynomials ,
. The generality of our spectral formulation includes
as a special
case, the dospectral Jacobi methods which are collocated
at the interior
extrema of , i.e.,
Indeed, the spectral and dospectral
Jacobi methods are closely related since is a
scalar multiple of .
For example, and
correspond to Chebyshev spectral and psidospectral methods, respectively.
Let be the N distinct zeros
of the forcing polynomial .
For Jacobi type methods,
(meth_cheb.4) and (meth_cheb.5), the
nodes are the zeros of Jacobi polynomials associated
with the Gauss and GaussLobatto quadrature rules, with minimal gridsize
of order
The spectral approximation
(meth_cheb.3a)
restricted to these points reads
and is augmented with the homogeneous boundary conditions
Equations (meth_cheb.7a), (meth_cheb.7b) furnish a complete equivalent formulation of the
spectral approximation (meth_cheb.3a), (meth_cheb.3b).
An essential ingredient in a stability
theory of such approximations lies in the choice of appropriate
weighted norms
We now make the definition of
. We say the approximation (meth_cheb.7a),
(meth_cheb.7b) is stable
if there exist discrete weights,
, and a constant independent of N, such that
and it is strongly stable
if (meth_cheb.9) holds
with Const = 1 and ,
With this in mind we turn to our main stability result stating
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.
1. .
Theorem 4.1 deals with the
stability of both the spectral tau methods
associated with , and the closely related dospectral methods
associated with .
In each case, there are (at least two) different weighted stability results,
based on
different choices of discrete weighted norms; these discrete weights
are given by
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2. . The CFL condition (meth_cheb.12)
places an
stability restriction on the time step . Indeed, this
stability restriction involves two factors :
the eigenvalues associated with Jacobi equation (2.4.9),
and the collocated Gauss nodes,
which accumulate within neighborhoods near the boundaries,
Thus,
the CFL condition (meth_cheb.12) boils down to
(For the practical range of parameters, , we have
).
3. . The stability statement
asserted in theorem (4.1) is formulated
in terms of discrete
seminorms, , which are weighted by either
(meth_cheb.14a) or (meth_cheb.14b).
We note that are in fact
welldefined norms on the space of polynomials satisfying the
vanishing boundary condition (meth_cheb.7b), i.e.,
corresponding to (meth_cheb.14a) or (meth_cheb.14b)
we have
and in view of (2.5.16),
Moreover, in view of (meth_cheb.15b), one may convert the
stability statement (meth_cheb.13)
into the usual type stability estimate at the expense of possible
algebraic growth which reads
4. . Let us integrate by parts the
differential equation (meth_cheb.1) against (1 + x)u.
Thanks to the homogeneous
boundary condition (meth_cheb.2) we find
and therefore,
This estimate corresponds to the special case of the stability statement
(meth_cheb.13)
for the spectral Legendre tau method () weighted by
(meth_cheb.14b). The exponential time decay indicated in
(meth_cheb.20), and more generally in
(meth_cheb.13), is due to the special choice of weighted
stability norms. The
weights in (meth_cheb.14a),
(meth_cheb.14b) involve the essential
factors or which amplify the
inflow boundary values in comparison to the outflow ones. Since in the
current homogeneous case, vanishing inflow data is propagating into the
domain, this results in the exponential time decay indicated in
(meth_cheb.20) and
likewise in the stability statement (meth_cheb.13).
5. . A stability statement similar to theorem 4.1 is valid in the inflow case where a < 0. Assume that the CFL condition (meth_cheb.12) holds with , then (meth_cheb.13) follows with discrete weights or .
As we noted before, there are several variants of theorem 4.1; we quote below two of these variants.
6. .
The spectral Jacobi method (meth_cheb.4) satisfies the
stability estimate (meth_cheb.13) with
we proceed as follows. Squaring of (meth_cheb.7a) yields
and we turn to estimate the two expressions, I and II,
on the right of (meth_cheb.22).
First let us note that since the polynomial
vanishes at the inflow boundary, (meth_cheb.3b), we have
Also, a straightforward computation shows that
where is given in (meth_cheb.21b).
Now, since , the Gauss quadrature rule (Gauss.rule) implies
We integrate by parts the righthand side of I, substitute
from (meth_cheb.23), and in view of (meth_cheb.24) we obtain
Next, let us consider the second expression,
II, on the right of (meth_cheb.22).
As before, we substitute
from (meth_cheb.23) and obtain
To proceed we invoke the following
In fact, one more application of Gauss quadrature yields
The inequalities (meth_cheb.29), (meth_cheb.28)
together with (meth_cheb.27) imply
and the result (meth_cheb.13) follows.
Since is proportional to , we conclude the stability of the dospectral method (meth_cheb.5), with and .
As mentioned before, alternative variants of theorem 4.1 are possible. For example, one may employ a stable norm weighted by (instead of the weights used before. This yields the

The spectral Jacobi tau method (meth_cheb.4).
satisfies the stability estimate (meth_cheb.13) with
and
we omit the detailed derivation ( which as before, hinges on the exactness of Gauss quadrature rule for 2Npolynomials), consult (2.5.4). If we replace the Gauss quadrature rule by the GaussLobatto one, we are led to stability of the dospectral method (meth_cheb.5) with and with the same given in (meth_cheb.32b).