TheoremBase

Expanding the quadratic form on a sum recovers the bilinear form from the quadratic one, so equal quadratic forms give equal entries; the coefficients of a second-order expansion are then separated by testing along a ray and letting the parameter tend to zero.

Proof

We use the notation of the statement. Algebraic manipulations of dot products use The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite, and ∥v∥2=v⋅v\lVert v\rVert^{2}=v\cdot v is claim 1 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square. We write e1,…,ene_{1},\dots,e_{n} for the standard basis vectors of Rn\mathbb{R}^{n}, so that the iith coordinate of v∈Rnv\in\mathbb{R}^{n} equals v⋅eiv\cdot e_{i}.

Claim 1. Let D∈S(n)D\in\mathcal{S}(n) and let u,v∈Rnu,v\in\mathbb{R}^{n}. By The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite and claim 1 of Linearity, Compatibility with the Matrix Product, and a Norm Bound for the Matrix-Vector Product,

(u+v)⋅(D(u+v))=u⋅(Du)+u⋅(Dv)+v⋅(Du)+v⋅(Dv).(u+v)\cdot\bigl(D(u+v)\bigr)=u\cdot(Du)+u\cdot(Dv)+v\cdot(Du)+v\cdot(Dv).

Since DD is symmetric, D⊤=DD^{\top}=D, so claim 5 of Elementary Properties of the Transpose of a Real Matrix gives v⋅(Du)=(D⊤v)⋅u=(Dv)⋅u=u⋅(Dv)v\cdot(Du)=(D^{\top}v)\cdot u=(Dv)\cdot u=u\cdot(Dv), the last step by claim 1 of The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite. Hence

u⋅(Dv)=12[(u+v)⋅(D(u+v))−u⋅(Du)−v⋅(Dv)].(P)u\cdot(Dv)=\tfrac{1}{2}\Bigl[(u+v)\cdot\bigl(D(u+v)\bigr)-u\cdot(Du)-v\cdot(Dv)\Bigr]. \tag{P}

Now let B,C∈S(n)B,C\in\mathcal{S}(n) have the same quadratic form. Applying (P) to BB and to CC, and noting that the right-hand side of (P) involves only the quadratic form, we get u⋅(Bv)=u⋅(Cv)u\cdot(Bv)=u\cdot(Cv) for all u,v∈Rnu,v\in\mathbb{R}^{n}. Take u=eiu=e_{i} and v=ejv=e_{j}. By Matrix-Vector Product the iith coordinate of BejBe_{j} is ∑k=1nBik(ej)k=Bij\sum_{k=1}^{n}B_{ik}(e_{j})_{k}=B_{ij}, and that coordinate equals ei⋅(Bej)e_{i}\cdot(Be_{j}) by Orthonormal Families, Standard Basis Vectors, and Plane Rotations of Euclidean Space; likewise for CC. Hence Bij=CijB_{ij}=C_{ij} for all i,j∈{1,…,n}i,j\in\{1,\dots,n\}, that is B=CB=C.

Claim 2. Let ε∈R\varepsilon\in\mathbb{R} with 0<ε0<\varepsilon and let δ>0\delta>0 be as in the hypothesis for this ε\varepsilon. Subtracting the two estimates and using claim 5 of Properties of the Absolute Value in an Ordered Field, every hh with ∥h∥<δ\lVert h\rVert<\delta satisfies

∣(p′−p)⋅h+12 h⋅(B′h)−12 h⋅(Bh)∣≤2ε∥h∥2.(D)\Bigl|(p'-p)\cdot h+\tfrac{1}{2}\,h\cdot(B'h)-\tfrac{1}{2}\,h\cdot(Bh)\Bigr|\le2\varepsilon\lVert h\rVert^{2}. \tag{D}

We first show p=p′p=p'. Suppose p≠p′p\neq p' and put u=(p′−p)/∥p′−p∥u=(p'-p)/\lVert p'-p\rVert, so ∥u∥=1\lVert u\rVert=1 by claim 5 of Properties of the Euclidean Norm on Rn\mathbb{R}^n: Square, Distance, Vanishing, Coordinate Bounds, Homogeneity, Triangle Inequalities and Expansion of a Square and (p′−p)⋅u=∥p′−p∥(p'-p)\cdot u=\lVert p'-p\rVert. Let t∈Rt\in\mathbb{R} with 0<t<δ0<t<\delta and put h=tuh=tu, so ∥h∥=t<δ\lVert h\rVert=t<\delta. By The Dot Product on Rn\mathbb{R}^n Is Symmetric, Bilinear and Positive Definite and claim 1 of Linearity, Compatibility with the Matrix Product, and a Norm Bound for the Matrix-Vector Product the expression inside the absolute value in (D) equals t ∥p′−p∥+12t2(u⋅(B′u)−u⋅(Bu))t\,\lVert p'-p\rVert+\tfrac{1}{2}t^{2}\bigl(u\cdot(B'u)-u\cdot(Bu)\bigr), so by claim 6 of Properties of the Absolute Value in an Ordered Field and claim 3 of that lemma,

t ∥p′−p∥≤2εt2+12t2∣u⋅(B′u)−u⋅(Bu)∣,t\,\lVert p'-p\rVert\le2\varepsilon t^{2}+\tfrac{1}{2}t^{2}\bigl|u\cdot(B'u)-u\cdot(Bu)\bigr| ,

and dividing by the positive number tt,

∥p′−p∥≤t(2ε+12∣u⋅(B′u)−u⋅(Bu)∣).\lVert p'-p\rVert\le t\Bigl(2\varepsilon+\tfrac{1}{2}\bigl|u\cdot(B'u)-u\cdot(Bu)\bigr|\Bigr).

The bracket does not depend on tt, so by The Archimedean Property of the Real Numbers the right-hand side is smaller than ∥p′−p∥\lVert p'-p\rVert for tt small enough, a contradiction. Hence p=p′p=p'.

With p=p′p=p', (D) becomes ∣12h⋅(B′h)−12h⋅(Bh)∣≤2ε∥h∥2\bigl|\tfrac{1}{2}h\cdot(B'h)-\tfrac{1}{2}h\cdot(Bh)\bigr|\le2\varepsilon\lVert h\rVert^{2} for ∥h∥<δ\lVert h\rVert<\delta. Let u∈Rnu\in\mathbb{R}^{n} with ∥u∥=1\lVert u\rVert=1 and let tt with 0<t<δ0<t<\delta; taking h=tuh=tu and using bilinearity as above gives 12t2∣u⋅(B′u)−u⋅(Bu)∣≤2εt2\tfrac{1}{2}t^{2}\bigl|u\cdot(B'u)-u\cdot(Bu)\bigr|\le2\varepsilon t^{2}, so

∣u⋅(B′u)−u⋅(Bu)∣≤4ε.\bigl|u\cdot(B'u)-u\cdot(Bu)\bigr|\le4\varepsilon .

This holds for every ε>0\varepsilon>0, so u⋅(B′u)=u⋅(Bu)u\cdot(B'u)=u\cdot(Bu) for every unit vector uu. For general h≠0h\neq0, writing h=∥h∥ uh=\lVert h\rVert\,u with u=h/∥h∥u=h/\lVert h\rVert of norm 11 and using bilinearity gives h⋅(B′h)=∥h∥2 u⋅(B′u)=∥h∥2 u⋅(Bu)=h⋅(Bh)h\cdot(B'h)=\lVert h\rVert^{2}\,u\cdot(B'u)=\lVert h\rVert^{2}\,u\cdot(Bu)=h\cdot(Bh), and for h=0h=0 both sides vanish. By claim 1, B=B′B=B'.

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