TheoremBase

Quadratic Test Functions, Limits, Translation and Locality for Approximability by Test Data

Approximability by test data can always be realised with quadratic test functions; it follows at a point of twice differentiability, is stable under limits of the approximating data, transforms predictably under translation and affine perturbation, and depends only on the values of the function near the point.

Statement

In the setting of Second-Order Equations on Euclidean Open Sets we use the real numbers and absolute value ∣⋅∣|\cdot|, the Euclidean norm ∥ ⋅ ∥\lVert\,\cdot\,\rVert, dot product, sum and difference of points, Euclidean distance dEd_{E} and notion of openness, the set S(q)\mathcal{S}(q) of symmetric real matrices, the identity matrix IqI_{q}, the matrix-vector product, the norm ∥ ⋅ ∥\lVert\,\cdot\,\rVert and the distance dS(q)d_{\mathcal{S}(q)}, the notion of a function of class C2C^{2} together with its gradient DφD\varphi and Hessian D2φD^{2}\varphi, and the notions of local maximum and local minimum relative to a subset, all with a natural number nn satisfying 1≤n1\le n. We abbreviate ∥z∥2=∥z∥⋅∥z∥\lVert z\rVert^{2}=\lVert z\rVert\cdot\lVert z\rVert, and s2\tfrac{s}{2} denotes the product of s∈Rs\in\mathbb{R} with the multiplicative inverse of 2=1+12=1+1, which exists by claim 8 of Elementary Order Arithmetic in an Ordered Field.

Convergence of a sequence in a metric space is as defined there; convergence in Rn\mathbb{R}^{n} refers to dEd_{E}, convergence in S(n)\mathcal{S}(n) to dS(n)d_{\mathcal{S}(n)}, and convergence in R\mathbb{R} to the metric of The Absolute Value Metric on the Real Numbers. Twice differentiability at a point with a given first-order coefficient and Hessian is as defined there. That a quadruple is approximable by test data from above or from below for a function is as defined there.

Let U⊆RnU\subseteq\mathbb{R}^{n} be open, let u:U→Ru:U\to\mathbb{R}, let x0∈Ux_{0}\in U, let p∈Rnp\in\mathbb{R}^{n} and let X∈S(n)X\in\mathcal{S}(n). Then the following hold.

1. (Quadratic test functions suffice) The quadruple (x0,u(x0),p,X)\bigl(x_{0},u(x_{0}),p,X\bigr) is approximable by test data from above for uu if and only if for every positive ε∈R\varepsilon\in\mathbb{R} there exist y∈Uy\in U, r∈Rnr\in\mathbb{R}^{n}, Y∈S(n)Y\in\mathcal{S}(n) and a positive δ∈R\delta\in\mathbb{R} such that

dE(y,x0)<ε,∣u(y)−u(x0)∣<ε,∥r−p∥<ε,dS(n)(Y,X)<ε,d_{E}(y,x_{0})<\varepsilon,\qquad |u(y)-u(x_{0})|<\varepsilon,\qquad \lVert r-p\rVert<\varepsilon,\qquad d_{\mathcal{S}(n)}(Y,X)<\varepsilon,

and

u(z)  ≤  u(y)+r⋅(z−y)+12 (z−y)⋅(Y(z−y))for every z∈U with dE(z,y)<δ.u(z)\;\le\;u(y)+r\cdot(z-y)+\tfrac{1}{2}\,(z-y)\cdot\bigl(Y(z-y)\bigr)\qquad\text{for every }z\in U\text{ with }d_{E}(z,y)<\delta .

The corresponding statement holds for approximability from below, with the last displayed inequality replaced by

u(z)  ≥  u(y)+r⋅(z−y)+12 (z−y)⋅(Y(z−y)).u(z)\;\ge\;u(y)+r\cdot(z-y)+\tfrac{1}{2}\,(z-y)\cdot\bigl(Y(z-y)\bigr).

2. (Points of twice differentiability) If uu is twice differentiable at x0x_{0} with first-order coefficient pp and Hessian XX, then (x0,u(x0),p,X)\bigl(x_{0},u(x_{0}),p,X\bigr) is approximable by test data both from above and from below for uu.

3. (Limits of test data) Let (yk)k∈N(y_{k})_{k\in\mathbb{N}} be a sequence in UU, let (pk)k∈N(p_{k})_{k\in\mathbb{N}} be a sequence in Rn\mathbb{R}^{n} and let (Xk)k∈N(X_{k})_{k\in\mathbb{N}} be a sequence in S(n)\mathcal{S}(n) such that for every k∈Nk\in\mathbb{N} the quadruple (yk,u(yk),pk,Xk)\bigl(y_{k},u(y_{k}),p_{k},X_{k}\bigr) is approximable by test data from above for uu. Suppose (yk)(y_{k}) converges to x0x_{0} in Rn\mathbb{R}^{n}, (u(yk))\bigl(u(y_{k})\bigr) converges to u(x0)u(x_{0}) in R\mathbb{R}, (pk)(p_{k}) converges to pp in Rn\mathbb{R}^{n} and (Xk)(X_{k}) converges to XX in S(n)\mathcal{S}(n). Then (x0,u(x0),p,X)\bigl(x_{0},u(x_{0}),p,X\bigr) is approximable by test data from above for uu. The corresponding statement holds for approximability from below.

4. (Translation and affine perturbation) Let b,q∈Rnb,q\in\mathbb{R}^{n} and c∈Rc\in\mathbb{R}, put U−b={z∈Rn:z+b∈U}U-b=\{z\in\mathbb{R}^{n}:z+b\in U\}, which is open by Quadratic and Affine Functions of Class C2C^2, Translation, and Quadratic Perturbation of Semiconvexity (ii), and let u~:U−b→R\tilde{u}:U-b\to\mathbb{R} be given by u~(z)=u(z+b)+q⋅z+c\tilde{u}(z)=u(z+b)+q\cdot z+c. Then (x0,u(x0),p,X)\bigl(x_{0},u(x_{0}),p,X\bigr) is approximable by test data from above for uu if and only if (x0−b,u~(x0−b),p+q,X)\bigl(x_{0}-b,\tilde{u}(x_{0}-b),p+q,X\bigr) is approximable by test data from above for u~\tilde{u}. The corresponding statement holds for approximability from below.

5. (Locality) Let U′⊆RnU'\subseteq\mathbb{R}^{n} be open, let u′:U′→Ru':U'\to\mathbb{R}, and let W⊆RnW\subseteq\mathbb{R}^{n} be open with x0∈Wx_{0}\in W, W⊆UW\subseteq U, W⊆U′W\subseteq U' and u(z)=u′(z)u(z)=u'(z) for every z∈Wz\in W. If (x0,u(x0),p,X)\bigl(x_{0},u(x_{0}),p,X\bigr) is approximable by test data from above for uu, then (x0,u′(x0),p,X)\bigl(x_{0},u'(x_{0}),p,X\bigr) is approximable by test data from above for u′u'. The corresponding statement holds for approximability from below.

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