Question:

Inverse of a diagonal matrix (if it exists) is a

Updated On: Jul 6, 2022
  • skew symmetric matrix
  • non-invertible matrix
  • diagonal matrix
  • none of these
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The Correct Option is C

Solution and Explanation

Let A= diag (d1,d2,d3,...,dn)(d_1, d_2, d_3, ... , d_n). As A is invertible, therefore, det A0A \neq 0 d1d2d3...dn0\Rightarrow \, d_1 \, d_2 \, d_3 ... d_n \neq 0 di0\Rightarrow \, d_i \neq 0 for i=1,2,3,...,n,i = 1, 2, 3, ... , n, Here, cofactor of each non-diagonal entry is 0 and coafctor of aija_{ij} =(1)i+i = (-1)^{i + i} det (diag d1,d2,......,di1,di+1,....,dn){d_1, d_2 ,......, d_{i-1} , d_{i +1}, ...., d_n)} =d1d2......di1di+1....dn = d_1 d_2 ...... d_{i-1} d_{i+1} .... d_n =1di(d1d2...di1didi+1....dn)=Adi = \frac{1}{d_i} (d_1 d_2 ... d_{i-1} d_i d_{i+1} .... d_n) = \frac{|A|}{d_i} A1=1A(adjA)=diag(1d1,1d2,....,1dn)\therefore \, A^{-1} = \frac{1}{|A|} \left(\text{adj} A\right) = \text{diag} \left(\frac{1}{d_{1} }, \frac{1}{d_{2} },...., \frac{1}{d_{n}}\right) which is a diagonal matrix.
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Concepts Used:

Matrices

Matrix:

A matrix is a rectangular array of numbers, variables, symbols, or expressions that are defined for the operations like subtraction, addition, and multiplications. The size of a matrix is determined by the number of rows and columns in the matrix.

The basic operations that can be performed on matrices are:

  1. Addition of Matrices - The addition of matrices addition can only be possible if the number of rows and columns of both the matrices are the same.
  2. Subtraction of Matrices - Matrices subtraction is also possible only if the number of rows and columns of both the matrices are the same.
  3. Scalar Multiplication - The product of a matrix A with any number 'c' is obtained by multiplying every entry of the matrix A by c, is called scalar multiplication. 
  4. Multiplication of Matrices - Matrices multiplication is defined only if the number of columns in the first matrix and rows in the second matrix are equal. 
  5. Transpose of Matrices - Interchanging of rows and columns is known as the transpose of matrices.