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Proof of The Trace as a Sum of Quadratic Forms, its Monotonicity and a Norm Bound

lemmalem:trace-quadratic-forms-2026a
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· 4,429 chars · 15 deps · depth 17 Reason: First publication. Proof of the trace identities: the entry identity (AX)_{kj}=(Xa_k)_j for symmetric X, combined with the entrywise-sum form of the trace, followed by specialisation to the identity matrix and termwise comparison of the sums.

The key step identifies the (k,j)(k,j) entry of AXAX with the jjth coordinate of XakXa_k, using the symmetry of XX; the entrywise-sum form of the trace then turns tr(AAX)\operatorname{tr}(A^{\top}AX) into the sum of the quadratic forms of XX at the rows of AA. The remaining claims specialise AA to the identity matrix or compare the sums termwise.

Proof

Conventions. The notation is that of the statement; sums over an index range are the finite sums of R\mathbb{R}, and \le is the order of the ordered field of real numbers.

Claim 1. Fix XS(p)X\in\mathcal{S}(p).

Step 1. For every k[m]k\in[m] and every j[p]j\in[p],

(AX)kj=(Xak)j.(AX)_{kj}=(Xa_{k})_{j}.

Indeed, the definition of the product of real matrices gives (AX)kj=l=1pAklXlj(AX)_{kj}=\sum_{l=1}^{p}A_{kl}X_{lj}, while the definition of the matrix-vector product gives (Xak)j=l=1pXjl(ak)l(Xa_{k})_{j}=\sum_{l=1}^{p}X_{jl}(a_{k})_{l}, and (ak)l=Akl(a_{k})_{l}=A_{kl} by the definition of the row aka_{k}. Since XX is symmetric, Xjl=XljX_{jl}=X_{lj} by Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §symmetric, and multiplication in R\mathbb{R} is commutative, so the two families of summands agree term by term and the two sums are equal.

Step 2. Both AA and AXAX lie in Mm×p(R)\mathcal{M}_{m\times p}(\mathbb{R}), so claim 4 of Basic Properties of the Trace, applied with AA in the role of UU and AXAX in the role of VV, gives

tr(A(AX))=k=1m j=1pAkj(AX)kj.\operatorname{tr}\bigl(A^{\top}(AX)\bigr)=\sum_{k=1}^{m}\ \sum_{j=1}^{p}A_{kj}(AX)_{kj}.

By Associativity of the Matrix Product the left-hand side is tr(AAX)\operatorname{tr}(A^{\top}AX). By Step 1 and the identity (ak)j=Akj(a_{k})_{j}=A_{kj}, the inner sum equals j=1p(ak)j(Xak)j\sum_{j=1}^{p}(a_{k})_{j}(Xa_{k})_{j}, which is ak(Xak)a_{k}\cdot(Xa_{k}) by the coordinate formula for the dot product. This proves claim 1.

Claim 2. The identity matrix IpI_{p} lies in S(p)\mathcal{S}(p) by Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §symmetric, so claim 1 applies with X=IpX=I_{p}. On the left, AAIp=AAA^{\top}AI_{p}=A^{\top}A by The Identity Matrix is a Two-Sided Multiplicative Identity. On the right, Ipak=akI_{p}a_{k}=a_{k} by claim 2 of Linearity of the Matrix-Vector Product and the Quadratic Form as a Double Sum, and akak=ak2a_{k}\cdot a_{k}=\lVert a_{k}\rVert^{2} by claim 1 of Elementary Properties of the Euclidean Norm on Rn\mathbb{R}^n. Claim 2 follows.

Claim 3. Let XS(p)X\in\mathcal{S}(p). The statement holds for every choice of the two dimensions and of the matrix, so we may apply claim 1 with pp in the role of mm and with IpI_{p} in the role of AA. By the definition of the identity matrix the entry (Ip)kj(I_{p})_{kj} equals 11 if k=jk=j and 00 otherwise, which is precisely the jjth coordinate of eke_{k} by Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §basis; hence the kkth row of IpI_{p} is eke_{k}. Moreover IpI_{p} is symmetric by Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §symmetric, so Ip=IpI_{p}^{\top}=I_{p}, and IpIpX=IpX=XI_{p}I_{p}X=I_{p}X=X by The Identity Matrix is a Two-Sided Multiplicative Identity. Claim 1 therefore reads tr(X)=k=1pek(Xek)\operatorname{tr}(X)=\sum_{k=1}^{p}e_{k}\cdot(Xe_{k}).

Claim 4. Let X,YS(p)X,Y\in\mathcal{S}(p) satisfy XYX\preceq Y. By Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §ordering we have z(Xz)z(Yz)z\cdot(Xz)\le z\cdot(Yz) for every zRpz\in\mathbb{R}^{p}, and in particular ak(Xak)ak(Yak)a_{k}\cdot(Xa_{k})\le a_{k}\cdot(Ya_{k}) for every k[m]k\in[m]. Claim 1 of Comparison and Absolute Value Bounds for Finite Sums of Real Numbers gives

k=1mak(Xak)k=1mak(Yak),\sum_{k=1}^{m}a_{k}\cdot(Xa_{k})\le\sum_{k=1}^{m}a_{k}\cdot(Ya_{k}),

and claim 1 above identifies the two sides with tr(AAX)\operatorname{tr}(A^{\top}AX) and tr(AAY)\operatorname{tr}(A^{\top}AY). Running the same argument with eke_{k} in place of aka_{k} and invoking claim 3 in place of claim 1 gives tr(X)tr(Y)\operatorname{tr}(X)\le\operatorname{tr}(Y).

Claim 5. Let XS(p)X\in\mathcal{S}(p). By claim 3 above and by claim 2 of Comparison and Absolute Value Bounds for Finite Sums of Real Numbers,

tr(X)k=1pek(Xek).\bigl|\operatorname{tr}(X)\bigr|\le\sum_{k=1}^{p}\bigl|e_{k}\cdot(Xe_{k})\bigr| .

For each k[p]k\in[p], claim 2 of Properties of the Norm of a Symmetric Real Matrix gives ek(Xek)Xek2|e_{k}\cdot(Xe_{k})|\le\lVert X\rVert\lVert e_{k}\rVert^{2}, and ek=1\lVert e_{k}\rVert=1 by Real Matrices, Symmetric Matrices and the Semidefinite Ordering: Standing Notation §basis, so ek2=1\lVert e_{k}\rVert^{2}=1 and hence ek(Xek)X|e_{k}\cdot(Xe_{k})|\le\lVert X\rVert. Therefore, by claim 1 of Comparison and Absolute Value Bounds for Finite Sums of Real Numbers and claim 3 of Properties of Finite Sums,

k=1pek(Xek)k=1pX=Xk=1p1=βpX,\sum_{k=1}^{p}\bigl|e_{k}\cdot(Xe_{k})\bigr|\le\sum_{k=1}^{p}\lVert X\rVert=\lVert X\rVert\sum_{k=1}^{p}1=\beta_{p}\lVert X\rVert ,

the last two equalities using X1=X\lVert X\rVert\cdot1=\lVert X\rVert and the commutativity of multiplication. Transitivity of \le now gives claim 5.

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