Bramble–Hilbert lemma

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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 u by a polynomial of order at most m1 in terms of derivatives of u of order m. Both the error of the approximation and the derivatives of u are measured by Lp norms on a bounded domain in n. This is similar to classical numerical analysis, where, for example, the error of linear interpolation u can be bounded using the second derivative of u. However, the Bramble–Hilbert lemma applies in any number of dimensions, not just one dimension, and the approximation error and the derivatives of u 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 u by an operator that preserves polynomials of order up to m1, in terms of the derivatives of u of order m. 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

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

infvPm1u(k)v(k)Lp(a,b)C(m,k)(ba)mku(m)Lp(a,b) for each integer km and extended real p1,

where Pm1 is the space of all polynomials of degree at most m1 and f(k) indicates the kth derivative of a function f.

In the case when p=, m=2, k=0, and u is twice differentiable, this means that there exists a polynomial v of degree one such that for all x(a,b),

|u(x)v(x)|C(ba)2sup(a,b)|u|.

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

Statement of the lemma

Template:Dubious Suppose Ω is a bounded domain in n, n1, with boundary Ω and diameter d. Wpk(Ω) is the Sobolev space of all function u on Ω with weak derivatives Dαu of order |α| up to k in Lp(Ω). Here, α=(α1,α2,,αn) is a multiindex, |α|= α1+α2++αn and Dα denotes the derivative α1 times with respect to x1, α2 times with respect to x2, and so on. The Sobolev seminorm on Wpm(Ω) consists of the Lp norms of the highest order derivatives,

|u|Wpm(Ω)=(|α|=mDαuLp(Ω)p)1/p if 1p<

and

|u|Wm(Ω)=max|α|=mDαuL(Ω)

Pk is the space of all polynomials of order up to k on n. Note that Dαv=0 for all vPm1 and |α|=m, so |u+v|Wpm(Ω) has the same value for any vPm1.

Lemma (Bramble and Hilbert) Under additional assumptions on the domain Ω, specified below, there exists a constant C=C(m,Ω) independent of p and u such that for any uWpm(Ω) there exists a polynomial vPm1 such that for all k=0,,m,

|uv|Wpk(Ω)Cdmk|u|Wpm(Ω).

The original result

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

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 Wpm(Ω)/Pm1 is equivalent to the Wpm(Ω) seminorm. The Wpm(Ω) norm is not the usual one but the terms are scaled with d 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 Ω cannot be determined from the proof.

A constructive form

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

Then the lemma holds with the constant C=C(m,n,γ), that is, the constant depends on the domain Ω only through its chunkiness γ and the dimension of the space n. In addition, v can be chosen as v=Qmu, where Qmu is the averaged Taylor polynomial, defined as

Qmu=BTymu(x)ψ(y)dx,

where

Tymu(x)=k=0m1|α|=k1α!Dαu(y)(xy)α

is the Taylor polynomial of degree at most m1 of u centered at y evaluated at x, and ψ0 is a function that has derivatives of all orders, equals to zero outside of B, and such that

Bψdx=1.

Such function ψ 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 Ω 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

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 Wpm(Ω) and Wpm(Ω) its dual norm. Suppose that (v)=0 for all vPm1. Then there exists a constant C=C(Ω) such that

|(u)|CWpm(Ω)|u|Wpm(Ω).

References

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