Bramble–Hilbert lemma

In mathematics, particularly numerical analysis, the Bramble–Hilbert lemma, named after James H. Bramble and Stephen Hilbert, bounds the error of an approximation of a function by a polynomial of order at most in terms of derivatives of of order . Both the error of the approximation and the derivatives of are measured by norms on a bounded domain in . This is similar to classical numerical analysis, where, for example, the error of linear interpolation can be bounded using the second derivative of . However, the Bramble–Hilbert lemma applies in any number of dimensions, not just one dimension, and the approximation error and the derivatives of are measured by more general norms involving averages, not just the maximum norm.

Additional assumptions on the domain are needed for the Bramble–Hilbert lemma to hold. Essentially, the boundary of the domain must be "reasonable". For example, domains that have a spike or a slit with zero angle at the tip are excluded. Lipschitz domains are reasonable enough, which includes convex domains and domains with continuously differentiable boundary.

The main use of the Bramble–Hilbert lemma is to prove bounds on the error of interpolation of function by an operator that preserves polynomials of order up to , in terms of the derivatives of of order . This is an essential step in error estimates for the finite element method. The Bramble–Hilbert lemma is applied there on the domain consisting of one element (or, in some superconvergence results, a small number of elements).

The one-dimensional case edit

Before stating the lemma in full generality, it is useful to look at some simple special cases. In one dimension and for a function   that has   derivatives on interval  , the lemma reduces to

 

where   is the space of all polynomials of degree at most   and   indicates the  th derivative of a function  .

In the case when  ,  ,  , and   is twice differentiable, this means that there exists a polynomial   of degree one such that for all  ,

 

This inequality also follows from the well-known error estimate for linear interpolation by choosing   as the linear interpolant of  .

Statement of the lemma edit

[dubious ]

Suppose   is a bounded domain in  ,  , with boundary   and diameter  .   is the Sobolev space of all function   on   with weak derivatives   of order   up to   in  . Here,   is a multiindex,     and   denotes the derivative   times with respect to  ,   times with respect to  , and so on. The Sobolev seminorm on   consists of the   norms of the highest order derivatives,

 

and

 

  is the space of all polynomials of order up to   on  . Note that   for all   and  , so   has the same value for any  .

Lemma (Bramble and Hilbert) Under additional assumptions on the domain  , specified below, there exists a constant   independent of   and   such that for any   there exists a polynomial   such that for all  

 

The original result edit

The lemma was proved by Bramble and Hilbert [1] under the assumption that   satisfies the strong cone property; that is, there exists a finite open covering   of   and corresponding cones   with vertices at the origin such that   is contained in   for any    .

The statement of the lemma here is a simple rewriting of the right-hand inequality stated in Theorem 1 in.[1] The actual statement in [1] is that the norm of the factorspace   is equivalent to the   seminorm. The   norm is not the usual one but the terms are scaled with   so that the right-hand inequality in the equivalence of the seminorms comes out exactly as in the statement here.

In the original result, the choice of the polynomial is not specified, and the value of constant and its dependence on the domain   cannot be determined from the proof.

A constructive form edit

An alternative result was given by Dupont and Scott [2] under the assumption that the domain   is star-shaped; that is, there exists a ball   such that for any  , the closed convex hull of   is a subset of  . Suppose that   is the supremum of the diameters of such balls. The ratio   is called the chunkiness of  .

Then the lemma holds with the constant  , that is, the constant depends on the domain   only through its chunkiness   and the dimension of the space  . In addition,   can be chosen as  , where   is the averaged Taylor polynomial, defined as

 

where

 

is the Taylor polynomial of degree at most   of   centered at   evaluated at  , and   is a function that has derivatives of all orders, equals to zero outside of  , and such that

 

Such function   always exists.

For more details and a tutorial treatment, see the monograph by Brenner and Scott.[3] The result can be extended to the case when the domain   is the union of a finite number of star-shaped domains, which is slightly more general than the strong cone property, and other polynomial spaces than the space of all polynomials up to a given degree.[2]

Bound on linear functionals edit

This result follows immediately from the above lemma, and it is also called sometimes the Bramble–Hilbert lemma, for example by Ciarlet.[4] It is essentially Theorem 2 from.[1]

Lemma Suppose that   is a continuous linear functional on   and   its dual norm. Suppose that   for all  . Then there exists a constant   such that

 

References edit

  1. ^ a b c d J. H. Bramble and S. R. Hilbert. Estimation of linear functionals on Sobolev spaces with application to Fourier transforms and spline interpolation. SIAM J. Numer. Anal., 7:112–124, 1970.
  2. ^ a b Todd Dupont and Ridgway Scott. Polynomial approximation of functions in Sobolev spaces. Math. Comp., 34(150):441–463, 1980.
  3. ^ Susanne C. Brenner and L. Ridgway Scott. The mathematical theory of finite element methods, volume 15 of Texts in Applied Mathematics. Springer-Verlag, New York, second edition, 2002. ISBN 0-387-95451-1
  4. ^ Philippe G. Ciarlet. The finite element method for elliptic problems, volume 40 of Classics in Applied Mathematics. Society for Industrial and Applied Mathematics (SIAM), Philadelphia, PA, 2002. Reprint of the 1978 original [North-Holland, Amsterdam]. ISBN 0-89871-514-8

External links edit