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Question 110 of 118

Q.If A=[235−2]A=\begin{bmatrix}2 & 3\\5 & -2\end{bmatrix} be such that λA−1=A\lambda A^{-1}=A, then λ\lambda is :

(a) 1919
(b) 1717
(c) 2121
(d) 1414
Tamil Nadu DgeTamil Nadu HSC (DGE) Board 2025MCQ· 1mImportance★★★★★
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Concept understanding — Adjoint and Inverse of a Matrix

For a square matrix A=[aij]A=[a_{ij}] of order nn, the cofactor of aija_{ij} is the signed minor Aij=(−1)i+jMijA_{ij}=(-1)^{i+j}M_{ij} (the minor MijM_{ij} is the determinant left after deleting row ii and column jj). Replace every entry of AA by its cofactor to get the cofactor matrix; its transpose is the adjoint, adj⁡A\operatorname{adj}A.

Theorem (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.

This follows from Laplace expansion: a row's entries dotted with their own cofactors reproduce ∣A∣|A|, while a row's entries dotted with a different row's cofactors always give 00 -- so the product matrix is ∣A∣|A| on the diagonal and 00 off it.

Definition of the inverse. A square matrix BB with AB=BA=InAB=BA=I_n is called the inverse of AA, written A−1A^{-1}. The inverse, when it exists, is unique. A−1A^{-1} exists if and only if AA is non-singular (∣A∣≠0|A|\ne0): dividing the central identity by ∣A∣|A| (possible exactly when ∣A∣≠0|A|\ne0) gives the working formula

A−1=1∣A∣adj⁡A.A^{-1}=\dfrac{1}{|A|}\operatorname{adj}A.

A singular matrix (∣A∣=0|A|=0) has no inverse.

Worked illustration (order 2). For A=(abcd)A=\begin{pmatrix}a & b\\ c & d\end{pmatrix}, the cofactors are A11=d, A12=−c, A21=−b, A22=aA_{11}=d,\ A_{12}=-c,\ A_{21}=-b,\ A_{22}=a, so adj⁡A=(d−b−ca)\operatorname{adj}A=\begin{pmatrix}d & -b\\ -c & a\end{pmatrix} (swap the diagonal entries, negate the off-diagonal ones) and A−1=1ad−bc(d−b−ca)A^{-1}=\dfrac{1}{ad-bc}\begin{pmatrix}d & -b\\ -c & a\end{pmatrix} whenever ad−bc≠0ad-bc\ne0.

Standing laws of inverses (for non-singular A,BA,B of the same order, λ≠0\lambda\ne0 a scalar):

  1. ∣A−1∣=1∣A∣|A^{-1}|=\dfrac{1}{|A|}.
  2. (AT)−1=(A−1)T(A^T)^{-1}=(A^{-1})^T.
  3. (λA)−1=1λA−1(\lambda A)^{-1}=\dfrac1\lambda A^{-1}.
  4. Left/right cancellation: AB=AC⇒B=CAB=AC\Rightarrow B=C; BA=CA⇒B=CBA=CA\Rightarrow B=C (pre/post-multiply by A−1A^{-1}) -- this fails when AA is singular.
  5. Reversal law: (AB)−1=B−1A−1(AB)^{-1}=B^{-1}A^{-1} (note the order flips, exactly as for transposes).
  6. Double inverse: (A−1)−1=A(A^{-1})^{-1}=A.

Six adjoint identities (non-singular AA, order nn): (i) adj⁡(A−1)=(adj⁡A)−1=A∣A∣\operatorname{adj}(A^{-1})=(\operatorname{adj}A)^{-1}=\dfrac{A}{|A|}; (ii) ∣adj⁡A∣=∣A∣n−1|\operatorname{adj}A|=|A|^{n-1}; (iii) adj⁡(adj⁡A)=∣A∣n−2A\operatorname{adj}(\operatorname{adj}A)=|A|^{n-2}A; (iv) adj⁡(λA)=λn−1adj⁡A\operatorname{adj}(\lambda A)=\lambda^{n-1}\operatorname{adj}A; (v) ∣adj⁡(adj⁡A)∣=∣A∣(n−1)2|\operatorname{adj}(\operatorname{adj}A)|=|A|^{(n-1)^2}; (vi) (adj⁡A)T=adj⁡(AT)(\operatorname{adj}A)^T=\operatorname{adj}(A^T); and for two non-singular matrices of the same order, adj⁡(AB)=(adj⁡B)(adj⁡A)\operatorname{adj}(AB)=(\operatorname{adj}B)(\operatorname{adj}A) (order reverses, exactly like the inverse and the transpose). …

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