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Mathematics · Ch 1 — Applications of Matrices and Determinants

Adjoint of a Square Matrix

1.2.1

Adjoint of a Square Matrix

Let A=[aij]A=[a_{ij}] be a square matrix of order nn, with determinant ∣A∣|A| (also written det⁡(A)\det(A)). Deleting row ii and column jj of AA leaves a sub-matrix of order (n−1)(n-1); its determinant is the minor MijM_{ij} of the entry aija_{ij}. The cofactor of aija_{ij} is the signed minor

Aij=(−1)i+jMij.A_{ij}=(-1)^{i+j}M_{ij}.

Key row/column fact. The sum of the products of a row's entries with their own cofactors reproduces the determinant: ai1Ai1+ai2Ai2+⋯+ainAin=∣A∣a_{i1}A_{i1}+a_{i2}A_{i2}+\cdots+a_{in}A_{in}=|A| (Laplace expansion along row ii). But the sum of a row's entries against a different row's cofactors is always 00: ai1Ak1+ai2Ak2+⋯+ainAkn=0a_{i1}A_{k1}+a_{i2}A_{k2}+\cdots+a_{in}A_{kn}=0 for i≠ki\ne k (this determinant would have two identical rows, hence vanish).

Definition (adjoint). Replace every entry aija_{ij} of AA by its cofactor AijA_{ij} to get the matrix of cofactors; the adjoint of AA, written adj⁡A\operatorname{adj}A, is the transpose of the matrix of cofactors:

adj⁡A=[Aij]T.\operatorname{adj}A=[A_{ij}]^T.

So the (i,j)(i,j) entry of adj⁡A\operatorname{adj}A is the cofactor AjiA_{ji} of the transposed position.

Theorem 1.1 (the central identity). For every square matrix AA of order nn,

A(adj⁡A)=(adj⁡A)A=∣A∣ In.A(\operatorname{adj}A)=(\operatorname{adj}A)A=|A|\,I_n.

Proof idea. The (i,i)(i,i) entry of the product A(adj⁡A)A(\operatorname{adj}A) is ∑kaikAik=∣A∣\sum_k a_{ik}A_{ik}=|A| (own-row-cofactor sum), while every off-diagonal (i,k)(i,k) entry, i≠ki\ne k, is ∑jaijAkj=0\sum_j a_{ij}A_{kj}=0 (mismatched-row-cofactor sum) -- so the product is exactly ∣A∣|A| down the diagonal and 00 elsewhere, i.e. ∣A∣In|A|I_n. The same argument applied column-wise gives (adj⁡A)A=∣A∣In(\operatorname{adj}A)A=|A|I_n too. …