Matrix Product with Adjugate Matrix
Theorem
Let $R$ be a commutative ring with unity.
Let $\mathbf A \in R^{n \times n}$ be a square matrix of order $n$.
Let $\adj {\mathbf A}$ be its adjugate matrix.
Then:
\(\ds \mathbf A \cdot \adj {\mathbf A}\) | \(=\) | \(\ds \map \det {\mathbf A} \cdot \mathbf I_n\) | ||||||||||||
\(\ds \adj {\mathbf A} \cdot \mathbf A\) | \(=\) | \(\ds \map \det {\mathbf A} \cdot \mathbf I_n\) |
where $\map \det {\mathbf A}$ is the determinant of $\mathbf A$, and $\mathbf I_n$ denotes the unit matrix of order $n$.
Proof
Let $\mathbf A = \paren {a_{i j} }$.
Let $A_{i j}$ denote the cofactor of $a_{i j} \in \mathbf A$.
Right Multiplication
We show that $\mathbf A \cdot \adj {\mathbf A} = \map \det {\mathbf A} \cdot \mathbf I_n$.
Let $i, j \in \set {1, \ldots, n}$.
If $i = j$, expanding $\map \det {\mathbf A}$ along row $i$ shows that:
- $\ds \map \det {\mathbf A} = \sum_{k \mathop = 1}^n a_{i k} A_{i k}$
If $i \ne j$, define $\mathbf A'$ as the matrix obtained by replacing row $j$ of $\mathbf A$ with row $i$ of $\mathbf A$.
Then $\mathbf A' = \begin {bmatrix} a' \end {bmatrix}_n$ has two identical rows, so:
\(\ds 0_R\) | \(=\) | \(\ds \map \det {\mathbf A'}\) | Square Matrix with Duplicate Rows has Zero Determinant | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{k \mathop = 1}^n a'_{j k} A'_{j k}\) | expanding $\map \det {\mathbf A'}$ along row $j$ | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{k \mathop = 1}^n a_{i k} A_{j k}\) |
By definition of matrix product, element $\tuple {i, j}$ of $\mathbf A \cdot \adj {\mathbf A}$ is:
- $\ds \sum_{k \mathop = 1}^n a_{i k} A_{j k} = \begin {cases} 0_R & \text {for} & i \ne j \\ \map \det {\mathbf A} & \text {for} & i = j \end {cases}$
Hence:
- $\mathbf A \cdot \adj {\mathbf A} = \map \det {\mathbf A} \cdot \mathbf I_n$
$\Box$
Left Multiplication
We show that $\adj {\mathbf A} \cdot \mathbf A = \map \det {\mathbf A} \cdot \mathbf I_n$.
Let $i, j \in \set {1, \ldots, n}$.
If $i = j$, expanding $\map \det {\mathbf A}$ along column $j$ shows that:
- $\ds \map \det {\mathbf A} = \sum_{k \mathop = 1}^n a_{k j} A_{k j}$
If $i \ne j$, define $\mathbf A'$ as the matrix obtained by replacing column $i$ of $\mathbf A$ with column $j$ of $\mathbf A$.
Then $\mathbf A' = \begin{bmatrix} a' \end{bmatrix}_n$ has two identical columns, so:
\(\ds 0_R\) | \(=\) | \(\ds \map \det {\mathbf A'}\) | Square Matrix with Duplicate Columns has Zero Determinant | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{k \mathop = 1}^n a'_{k i} A'_{k i}\) | expanding $\map \det {\mathbf A'}$ along column $i$ | |||||||||||
\(\ds \) | \(=\) | \(\ds \sum_{k \mathop = 1}^n a_{k j} A_{k i}\) |
By definition of matrix product, element $\tuple {i, j}$ of $\adj {\mathbf A} \cdot \mathbf A$ is:
- $\ds \sum_{k \mathop = 1}^n A_{k i} a_{k j} = \begin {cases} 0_R & \text {for} & i \ne j \\ \map \det {\mathbf A} & \text {for} & i = j \end {cases}$
Hence:
- $\adj {\mathbf A} \cdot \mathbf A = \map \det {\mathbf A} \cdot \mathbf I_n$
$\blacksquare$
Also see
Sources
- 1994: Robert Messer: Linear Algebra: Gateway to Mathematics: $\S 7.4$
- 1997: Donald E. Knuth: The Art of Computer Programming: Volume 1: Fundamental Algorithms (3rd ed.) ... (previous) ... (next): $\S 1.2.3$: Sums and Products: Exercises -- Second Set
- 1998: Richard Kaye and Robert Wilson: Linear Algebra ... (previous) ... (next): Part $\text I$: Matrices and vector spaces: $1$ Matrices: $1.7$ Minors and cofactors: $(2)$
- 2014: Christopher Clapham and James Nicholson: The Concise Oxford Dictionary of Mathematics (5th ed.) ... (previous) ... (next): adjoint
- 2021: Richard Earl and James Nicholson: The Concise Oxford Dictionary of Mathematics (6th ed.) ... (previous) ... (next): adjoint (adjugate) (of a matrix)