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TheoremProved

Invertibility criterion via the determinant

Statement

A square matrix AA is invertible if and only if det⁡(A)≠0\det(A)\neq 0; when it is invertible, A−1=1det⁡(A)adj⁡(A)A^{-1}=\dfrac{1}{\det(A)}\operatorname{adj}(A), where adj⁡(A)\operatorname{adj}(A) is the adjugate (transpose of the cofactor matrix).

Why is it true?

A linear map can be undone exactly when it does not collapse space to a lower dimension — since the determinant already measures exactly this "does it collapse volume to zero" question, invertibility and det⁡≠0\det\neq 0 are really the same statement seen from two angles: one algebraic (does an inverse matrix exist), one geometric (is the volume-scaling factor nonzero).

Proof sketch

(⇒\Rightarrow) Suppose AA is invertible, so there is a matrix A−1A^{-1} with AA−1=IAA^{-1}=I. Applying the multiplicativity theorem proved above, det⁡(A)det⁡(A−1)=det⁡(AA−1)=det⁡(I)=1\det(A)\det(A^{-1})=\det(AA^{-1})=\det(I)=1. Since the product of the two numbers det⁡(A)\det(A) and det⁡(A−1)\det(A^{-1}) equals 11, neither of them can be 00 — so det⁡(A)≠0\det(A)\neq 0.

(⇐\Leftarrow), worked concretely for 2×22\times 2: suppose A=(abcd)A=\begin{pmatrix}a&b\\ c&d\end{pmatrix} has det⁡(A)=ad−bc≠0\det(A)=ad-bc\neq 0. Define adj⁡(A)=(d−b−ca)\operatorname{adj}(A)=\begin{pmatrix}d&-b\\ -c&a\end{pmatrix}. Multiplying directly, A⋅adj⁡(A)=(abcd)(d−b−ca)=(ad−bc−ab+abcd−cd−cb+ad)=(ad−bc00ad−bc)=det⁡(A) IA\cdot\operatorname{adj}(A)=\begin{pmatrix}a&b\\ c&d\end{pmatrix}\begin{pmatrix}d&-b\\ -c&a\end{pmatrix}=\begin{pmatrix}ad-bc&-ab+ab\\ cd-cd&-cb+ad\end{pmatrix}=\begin{pmatrix}ad-bc&0\\ 0&ad-bc\end{pmatrix}=\det(A)\,I, exactly the identity A⋅adj⁡(A)=det⁡(A) IA\cdot\operatorname{adj}(A)=\det(A)\,I. The same computation in the other order gives adj⁡(A)⋅A=det⁡(A) I\operatorname{adj}(A)\cdot A=\det(A)\,I as well.

Since det⁡(A)≠0\det(A)\neq 0, divide both sides of A⋅adj⁡(A)=det⁡(A)IA\cdot\operatorname{adj}(A)=\det(A)I by the scalar det⁡(A)\det(A) to get A⋅adj⁡(A)det⁡(A)=IA\cdot\dfrac{\operatorname{adj}(A)}{\det(A)}=I, and likewise from the other order adj⁡(A)det⁡(A)⋅A=I\dfrac{\operatorname{adj}(A)}{\det(A)}\cdot A=I. This exhibits an explicit two-sided inverse A−1=1det⁡(A)adj⁡(A)A^{-1}=\dfrac{1}{\det(A)}\operatorname{adj}(A), so AA is invertible.

For general nn (illustrated at n=3n=3), the same argument works because the Laplace cofactor expansion gives ∑jaijCij=det⁡(A)\sum_j a_{ij}C_{ij}=\det(A) (expanding along row ii) while ∑jaijCkj=0\sum_j a_{ij}C_{kj}=0 for i≠ki\neq k (this sum is the cofactor expansion of a matrix with row ii copied into row kk, which has two equal rows and hence determinant 00 by the table above). Assembling these row-by-row identities into matrix form gives exactly A⋅adj⁡(A)=det⁡(A)IA\cdot\operatorname{adj}(A)=\det(A)I for every size nn, so whenever det⁡(A)≠0\det(A)\neq 0 the same division argument as in the 2×22\times 2 case produces A−1=adj⁡(A)/det⁡(A)A^{-1}=\operatorname{adj}(A)/\det(A); conversely, if det⁡(A)=0\det(A)=0, the first paragraph's contrapositive rules out invertibility entirely, since det⁡(A)det⁡(A−1)=1\det(A)\det(A^{-1})=1 would force det⁡(A)≠0\det(A)\neq 0. This proves the criterion in both directions.

Topics that use this theorem

Step-by-step proofs

No step-by-step proof yet for this theorem.

References

  1. Eric W. Weisstein (MathWorld) (2024). Determinant
  2. Gilbert Strang (2016). Introduction to Linear Algebra