Sobolev Spaces

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For any integer n ≥ 0, the Sobolev space Hn(R) is defined to be the set of functions f which are square-integrable together with all their derivatives of order up to n:

f ∈ Hn(R) ⇐⇒ ∫-∞ [f2 + ∑k=1n (dkf/dxk)2 dx ≤ ∞

This is a linear space, and in fact a Hilbert space with norm given by:

∥f∥Hn = ∫-∞ [f2 + ∑k=1n (dkf/dxk)2) dx]1/2

It is a standard fact that this norm of f can be expressed in terms of the Fourier transform fˆ (appropriately normalized) of f by:

∥f∥2Hn = ∫-∞ [(1 + y2)n |fˆ(y)|2 dy

The advantage of that new definition is that it can be extended to non-integral and non-positive values. For any real number s, not necessarily an integer nor positive, we define the Sobolev space Hs(R) to be the Hilbert space of functions associated with the following norm:

∥f∥2Hs = ∫-∞ [(1 + y2)s |fˆ(y)|2 dy —– (1)

Clearly, H0(R) = L2(R) and Hs(R) ⊂ Hs′(R) for s ≥ s′ and in particular Hs(R) ⊂ L2(R) ⊂ H−s(R), for s ≥ 0. Hs(R) is, for general s ∈ R, a space of (tempered) distributions. For example δ(k), the k-th derivative of a delta Dirac distribution, is in H−k−1/2</sup−ε(R) for ε > 0.

In the case when s > 1/2, there are two classical results.

Continuity of Multiplicity:

If s > 1/2, if f and g belong to Hs(R), then fg belongs to Hs(R), and the map (f,g) → fg from Hs × Hs to Hs is continuous.

Denote by Cbn(R) the space of n times continuously differentiable real-valued functions which are bounded together with all their n first derivatives. Let Cnb0(R) be the closed subspace of Cbn(R) of functions which converges to 0 at ±∞ together with all their n first derivatives. These are Banach spaces for the norm:

∥f∥Cbn = max0≤k≤n supx |f(k)(x)| = max0≤k≤n ∥f(k)∥ C0b

Sobolev embedding:

If s > n + 1/2 and if f ∈ Hs(R), then there is a function g in Cnb0(R) which is equal to f almost everywhere. In addition, there is a constant cs, depending only on s, such that:

∥g∥Cbn ≤ c∥f∥Hs

From now on we shall always take the continuous representative of any function in Hs(R). As a consequence of the Sobolev embedding theorem, if s > 1/2, then any function f in Hs(R) is continuous and bounded on the real line and converges to zero at ±∞, so that its value is defined everywhere.

We define, for s ∈ R, a continuous bilinear form on H−s(R) × Hs(R) by:

〈f, g〉= ∫-∞ (fˆ(y))’ gˆ(y)dy —– (2)

where z’ is the complex conjugate of z. Schwarz inequality and (1) give that

|< f , g >| ≤ ∥f∥H−s∥g∥Hs —– (3)

which indeed shows that the bilinear form in (2) is continuous. We note that formally the bilinear form (2) can be written as

〈f, g〉= ∫-∞ f(x) g(x) dx

where, if s ≥ 0, f is in a space of distributions H−s(R) and g is in a space of “test functions” Hs(R).

Any continuous linear form g → u(g) on Hs(R) is, due to (1), of the form u(g) = 〈f, g〉 for some f ∈ H−s(R), with ∥f∥H−s = ∥u∥(Hs)′, so that henceforth we can identify the dual (Hs(R))′ of Hs(R) with H−s(R). In particular, if s > 1/2 then Hs(R) ⊂ C0b0 (R), so H−s(R) contains all bounded Radon measures.

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