For a square matrix A of order m, another square matrix B of the same order is called the inverse of A if AB=BA=I, the identity matrix of order m; B is written A−1, and by the same relation A is equally the inverse of B, so A=B−1. A matrix is called invertible exactly when such a B exists, which happens if and only ifA is non-singular, ∣A∣=0. The inverse, when it exists, is always unique: if B and C were both inverses of A, then B=BI=B(AC)=(BA)C=IC=C, so B=C. Two standard routes compute A−1 — the elementary-transformation method and the adjoint-formula method — and both must agree, since the inverse is unique. Beyond direct computation, the defining relation AA−1=A−1A=I is itself a powerful algebraic tool: a matrix equation such as AX=B (with A square and non-singular) is solved by pre-multiplying both sides by A−1, giving X=A−1B; an equation XA=B is instead solved by post-multiplying by A−1, giving X=BA−1 — the side on which A−1 is applied must match the side on which A originally …
The adjoint method uses A−1=∣A∣1adj(A), valid because ∣A∣=10=0, so the matrix is non-singular and invertible. Computing all cofactors and transposing gives the inverse below. …