TheoremBase

Rademacher's Theorem in Rn\mathbb{R}^n

A Lipschitz function on Euclidean space is differentiable outside a Borel null set, with derivative the vector of its partial derivatives and with gradient bounded by the Lipschitz constant; the same holds for locally Lipschitz maps into Rm\mathbb{R}^m on an open set.

Statement

We work in the setting of Product Measures and Lebesgue Measure on ℝⁿ: Standing Notation and Background, whose notation is fixed for every dimension and is used here with natural numbers n,mn,m satisfying 1≤n1\le n and 1≤m1\le m: the Euclidean norm ∥ ⋅ ∥\lVert\,\cdot\,\rVert, dot product, distance dEd_{E}, notion of openness and closed balls, the Borel σ\sigma-algebra B(Rn)\mathcal{B}(\mathbb{R}^{n}), Lebesgue measure λn\lambda_{n}, the notion of a null subset, and the convention that Lipschitz maps between subsets of Euclidean spaces are understood for the restricted Euclidean distances, are as fixed there.

Let L∈RL\in\mathbb{R} with 0≤L0\le L and let f:Rn→Rf:\mathbb{R}^{n}\to\mathbb{R} be Lipschitz with constant LL, that is ∣f(y)−f(z)∣≤L∥y−z∥|f(y)-f(z)|\le L\lVert y-z\rVert for all y,z∈Rny,z\in\mathbb{R}^{n}. Where all nn partial derivatives of ff exist at a point xx, we write Df(x)=(∂1f(x),…,∂nf(x))∈RnDf(x)=(\partial_{1}f(x),\dots,\partial_{n}f(x))\in\mathbb{R}^{n} for the gradient of ff at xx. Then the following hold.

1. (Differentiability almost everywhere) There is a set N∈B(Rn)N\in\mathcal{B}(\mathbb{R}^{n}) with λn(N)=0\lambda_{n}(N)=0 such that for every x∈Rn∖Nx\in\mathbb{R}^{n}\setminus N all nn partial derivatives of ff exist at xx and, for every ε∈R\varepsilon\in\mathbb{R} with 0<ε0<\varepsilon, there is δ∈R\delta\in\mathbb{R} with 0<δ0<\delta such that

∣f(x+h)−f(x)−Df(x)⋅h∣≤ε ∥h∥for every h∈Rn with ∥h∥<δ.\bigl|f(x+h)-f(x)-Df(x)\cdot h\bigr|\le\varepsilon\,\lVert h\rVert\qquad\text{for every }h\in\mathbb{R}^{n}\text{ with }\lVert h\rVert<\delta .

2. (Identification of the derivative) At every point xx as in claim 1, the function ff is differentiable with derivative matrix the real matrix AA with one row and nn columns whose entries are A1i=∂if(x)A_{1i}=\partial_{i}f(x) for 1≤i≤n1\le i\le n; by claim 2 of The Derivative Is the Jacobian Matrix, and Is Unique this matrix is the Jacobian matrix of ff at xx.

3. (Bound on the gradient) At every point xx as in claim 1 one has ∥Df(x)∥≤L\lVert Df(x)\rVert\le L.

4. (Locally Lipschitz maps into Rm\mathbb{R}^{m}) Let U⊆RnU\subseteq\mathbb{R}^{n} be open and let T:U→RmT:U\to\mathbb{R}^{m} be locally Lipschitz on UU. Then the set of those x∈Ux\in U at which TT is not differentiable is null. At every x∈Ux\in U at which TT is differentiable, the derivative matrix of TT at xx is the real matrix with mm rows and nn columns whose entry in row kk and column ii is the partial derivative ∂iTk(x)\partial_{i}T_{k}(x) of the kkth coordinate function of TT.

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