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Uniform quadratic-form bounds for positive definite symmetric matrices and smoothness of the inverse

Statement

Let m≥1 and let B∈Sym⁡m(R) be positive definite, that is BT=B and zTBz>0 for every nonzero z∈Rm with the standard coordinate inner product.

(a) There are real numbers 0<a≤b with a ∣z∣2≤zTBz≤b ∣z∣2 for every z∈Rm; equivalently aI≤B≤bI in the Loewner order. They can be taken to be the least and largest eigenvalues of B.

(b) B is invertible and 1bI≤B−1≤1aI, so in particular ∥B−1z∥≤a−1∥z∥.

(c) Let Λ be a compact topological space and let B:Λ→Sym⁡m(R) be continuous with B(λ) positive definite for every λ∈Λ. Then there are constants 0<a≤b with aI≤B(λ)≤bI for every λ∈Λ.

(d) Let D⊆Rp be open and let B:D→Sym⁡m(R) be smooth with B(x)≥aI for a constant a>0 and all x∈D. Then x↦B(x)−1 is smooth on D and B(x)−1≤a−1I there.

Facts & Assumptions

Given: m≥1, a symmetric positive definite B, and in (c), (d) the stated parameter families.

[L1]

Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal basis of eigenvectors, and all its eigenvalues are real (Real spectral theorem: a self-adjoint endomorphism of a finite-dimensional real inner product space has an orthonormal eigenbasis).

[L4]

Polynomial and rational functions with nonvanishing denominator are smooth, and smoothness is preserved by composition (Cr and smooth maps between smooth manifolds, Ck Euclidean maps and diffeomorphisms).

Proof

technique · direct
1.1L1algebra

(Spectral representation and the bounds (a).) By [L1] choose an orthonormal basis e1,…,em of Rm with Bei=λiei and real λi. Writing z=∑iziei gives zTBz=∑iλizi2 and ∣z∣2=∑izi2. If some λi≤0, then eiTBei=λi≤0 with ei≠0, contradicting positive definiteness; so all λi>0. Put a:=min⁡iλi and b:=max⁡iλi; both are positive and a∣z∣2≤zTBz≤b∣z∣2 follows from the representation. This is (a).

2.1step 1.1L1givenalgebra

(Uniform bounds for an arbitrary compact topological parameter space (c).) If Λ=∅, take a=b=1 and the conclusion is vacuous. For each λ∈Λ, let aλ>0 and bλ be the uniquely determined smallest and largest eigenvalues of B(λ) from step 1.1. Continuity of the finitely many matrix entries gives an open neighborhood Vλ on which every entry of B(μ)−B(λ) has absolute value less than aλ/(2m). For μ∈Vλ, ∣zT(B(μ)−B(λ))z∣≤aλ2m(∑i∣zi∣)2≤aλ2∣z∣2, where the last inequality follows by summing 2∣zizj∣≤zi2+zj2 over the finite pairs. Hence (aλ/2)∣z∣2≤zTB(μ)z≤(bλ+aλ/2)∣z∣2. The neighborhoods Vλ cover Λ; compactness, in its open-cover definition, gives finitely many Vλ1,…,Vλq covering it, with q≥1 in the nonempty case. Set a=min⁡jaλj/2>0 and b=max⁡j(bλj+aλj/2). The preceding inequalities give the uniform bounds at every parameter. This uses no metric on Λ and selects only a finite subcover; the eigenvalue constants are canonical, so no arbitrary-index choice of bases is needed.

2.2step 1.1L1algebra

(Inverse bounds (b).) In the same eigenbasis, B−1ei=λi−1ei and λi−1∈[b−1,a−1], so b−1∣z∣2≤zTB−1z≤a−1∣z∣2; in particular B−1 exists.

3.1step 2.2step 2.1L2L4algebra∎

(Smoothness of the inverse (d).) On D, x↦det⁡B(x)≥am>0: the determinant is the product of the eigenvalues, each at least a by (a) applied at x, or equivalently det⁡ is continuous and positive. The adjugate entries are polynomial in the entries of B, hence smooth in x, and dividing by the smooth nonzero function det⁡B is smooth by [L4]; so B(x)−1 is smooth and satisfies the bound by (b).

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