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If A = \(\left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & −\cos \theta\end{array}\right)\) , then which of the following are correct?

1. A + adj A is a null matrix

2. A −1  + adj A is a null matrix

3. A − A −1  is a null matrix

Select the correct answer using the code given below :

This question was previously asked in
NDA I 2022 GAT Previous Year Paper (10-Apr-2022)
The correct answer is

1, 2 and 3

Analyzing Matrix Properties and Statements

We are given a matrix \( A = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \) and asked to check the correctness of three statements involving matrix A, its inverse (A-1), and its adjugate (adj A).

Calculating Determinant of Matrix A

First, let's find the determinant of matrix A. The determinant of a 3x3 matrix \(\left(\begin{array}{ccc}a & b & c \\ d & e & f \\ g & h & i\end{array}\right)\) is given by \( a(ei-fh) - b(di-fg) + c(dh-eg) \).

For matrix A:

\( \det(A) = 1 \times ((\cos \theta)(-\cos \theta) - (\sin \theta)(\sin \theta)) - 0 \times (...) + 0 \times (...) \)

\( \det(A) = 1 \times (-\cos^2 \theta - \sin^2 \theta) \)

\( \det(A) = -(\cos^2 \theta + \sin^2 \theta) \)

Using the trigonometric identity \( \cos^2 \theta + \sin^2 \theta = 1 \):

\( \det(A) = -1 \)

Since the determinant is non-zero, the inverse A-1 exists.

Calculating Adjugate of Matrix A

The adjugate of a matrix is the transpose of its cofactor matrix. The cofactor \( C_{ij} \) is calculated as \( (-1)^{i+j} M_{ij} \), where \( M_{ij} \) is the minor determinant.

Let's find the cofactor matrix C:

  • \( C_{11} = (-1)^{1+1} \det \left(\begin{array}{cc} \cos \theta & \sin \theta \\ \sin \theta & -\cos \theta \end{array}\right) = 1 \times (-\cos^2 \theta - \sin^2 \theta) = -1 \)
  • \( C_{12} = (-1)^{1+2} \det \left(\begin{array}{cc} 0 & \sin \theta \\ 0 & -\cos \theta \end{array}\right) = -1 \times (0 - 0) = 0 \)
  • \( C_{13} = (-1)^{1+3} \det \left(\begin{array}{cc} 0 & \cos \theta \\ 0 & \sin \theta \end{array}\right) = 1 \times (0 - 0) = 0 \)
  • \( C_{21} = (-1)^{2+1} \det \left(\begin{array}{cc} 0 & 0 \\ \sin \theta & -\cos \theta \end{array}\right) = -1 \times (0 - 0) = 0 \)
  • \( C_{22} = (-1)^{2+2} \det \left(\begin{array}{cc} 1 & 0 \\ 0 & -\cos \theta \end{array}\right) = 1 \times (-\cos \theta - 0) = -\cos \theta \)
  • \( C_{23} = (-1)^{2+3} \det \left(\begin{array}{cc} 1 & 0 \\ 0 & \sin \theta \end{array}\right) = -1 \times (\sin \theta - 0) = -\sin \theta \)
  • \( C_{31} = (-1)^{3+1} \det \left(\begin{array}{cc} 0 & 0 \\ \cos \theta & \sin \theta \end{array}\right) = 1 \times (0 - 0) = 0 \)
  • \( C_{32} = (-1)^{3+2} \det \left(\begin{array}{cc} 1 & 0 \\ 0 & \sin \theta \end{array}\right) = -1 \times (\sin \theta - 0) = -\sin \theta \)
  • \( C_{33} = (-1)^{3+3} \det \left(\begin{array}{cc} 1 & 0 \\ 0 & \cos \theta \end{array}\right) = 1 \times (\cos \theta - 0) = \cos \theta \)

The cofactor matrix C is:

\( C = \left(\begin{array}{ccc}-1 & 0 & 0 \\ 0 & -\cos \theta & -\sin \theta \\ 0 & -\sin \theta & \cos \theta\end{array}\right) \)

The adjugate matrix adj(A) is the transpose of C:

\( \text{adj}(A) = C^T = \left(\begin{array}{ccc}-1 & 0 & 0 \\ 0 & -\cos \theta & -\sin \theta \\ 0 & -\sin \theta & \cos \theta\end{array}\right) \)

Calculating Inverse of Matrix A

The inverse of matrix A is given by the formula \( A^{-1} = \frac{1}{\det(A)} \text{adj}(A) \).

\( A^{-1} = \frac{1}{-1} \left(\begin{array}{ccc}-1 & 0 & 0 \\ 0 & -\cos \theta & -\sin \theta \\ 0 & -\sin \theta & \cos \theta\end{array}\right) \)

\( A^{-1} = -1 \times \left(\begin{array}{ccc}-1 & 0 & 0 \\ 0 & -\cos \theta & -\sin \theta \\ 0 & -\sin \theta & \cos \theta\end{array}\right) \)

\( A^{-1} = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \)

Notice that \( A^{-1} = A \).

Also, from the formula \( A^{-1} = \frac{1}{\det(A)} \text{adj}(A) \), we have \( \text{adj}(A) = \det(A) \times A^{-1} = -1 \times A^{-1} = -A^{-1} \).

Checking the Statements

Let's verify each given statement using the calculated values of A, A-1, and adj A.

Statement 1: A + adj A is a null matrix

A + adj A \( = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) + \left(\begin{array}{ccc}-1 & 0 & 0 \\ 0 & -\cos \theta & -\sin \theta \\ 0 & -\sin \theta & \cos \theta\end{array}\right) \)

\( = \left(\begin{array}{ccc}1 + (-1) & 0 + 0 & 0 + 0 \\ 0 + 0 & \cos \theta + (-\cos \theta) & \sin \theta + (-\sin \theta) \\ 0 + 0 & \sin \theta + (-\sin \theta) & -\cos \theta + \cos \theta\end{array}\right) \)

\( = \left(\begin{array}{ccc}0 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0\end{array}\right) \)

The result is the null matrix. So, Statement 1 is correct.

Statement 2: A-1 + adj A is a null matrix

We know that adj(A) = -A-1.

A-1 + adj A \( = A^{-1} + (-A^{-1}) \)

\( = A^{-1} - A^{-1} \)

\( = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) - \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \)

\( = \left(\begin{array}{ccc}1 - 1 & 0 - 0 & 0 - 0 \\ 0 - 0 & \cos \theta - \cos \theta & \sin \theta - \sin \theta \\ 0 - 0 & \sin \theta - \sin \theta & -\cos \theta - (-\cos \theta)\end{array}\right) \)

\( = \left(\begin{array}{ccc}0 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0\end{array}\right) \)

The result is the null matrix. So, Statement 2 is correct.

Statement 3: A - A-1 is a null matrix

We found that A-1 = A.

A - A-1 \( = A - A \)

\( = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) - \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \)

\( = \left(\begin{array}{ccc}1 - 1 & 0 - 0 & 0 - 0 \\ 0 - 0 & \cos \theta - \cos \theta & \sin \theta - \sin \theta \\ 0 - 0 & \sin \theta - \sin \theta & -\cos \theta - (-\cos \theta)\end{array}\right) \)

\( = \left(\begin{array}{ccc}0 & 0 & 0 \\ 0 & 0 & 0 \\ 0 & 0 & 0\end{array}\right) \)

The result is the null matrix. So, Statement 3 is correct.

All three statements are correct.

Conclusion

Based on our calculations, all three statements are correct:

  1. A + adj A is a null matrix
  2. A-1 + adj A is a null matrix
  3. A - A-1 is a null matrix

Revision Table: Key Matrix Concepts

Concept Definition/Formula Notes
Determinant (\(\det(A)\)) A scalar value computed from the elements of a square matrix. A matrix is invertible if and only if its determinant is non-zero.
Minor (\(M_{ij}\)) The determinant of the submatrix obtained by deleting row i and column j. Used in calculating cofactors.
Cofactor (\(C_{ij}\)) \(C_{ij} = (-1)^{i+j} M_{ij}\) Signed minor. Used to find the adjugate and inverse.
Adjugate (\(\text{adj}(A)\)) The transpose of the cofactor matrix. Related to the inverse by \(\text{adj}(A) = \det(A) \times A^{-1}\).
Inverse (\(A^{-1}\)) A matrix such that \(A A^{-1} = A^{-1} A = I\) (Identity matrix). Exists only for non-singular (invertible) matrices. \( A^{-1} = \frac{1}{\det(A)} \text{adj}(A) \).
Null Matrix A matrix where all elements are zero. Represented by O. A + (-A) = O.

Additional Information: Special Types of Matrices

The given matrix A has some interesting properties. Let's explore some related matrix types:

  • Orthogonal Matrix: A square matrix Q is orthogonal if \( Q^T Q = Q Q^T = I \). This implies \( Q^{-1} = Q^T \). The determinant of an orthogonal matrix is either 1 or -1.
  • Involutory Matrix: A square matrix A is involutory if \( A^2 = I \). This implies \( A^{-1} = A \). Our matrix A satisfies \( A^2 = I \) because \( A^{-1} = A \). Let's verify this: \( A^2 = A \times A = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & \cos \theta & \sin \theta \\ 0 & \sin \theta & -\cos \theta\end{array}\right) \) \( = \left(\begin{array}{ccc}1 \times 1 + 0 + 0 & 0 + 0 + 0 & 0 + 0 + 0 \\ 0 + \cos^2 \theta + \sin^2 \theta & 0 + \cos \theta \sin \theta - \sin \theta \cos \theta & 0 + \cos \theta \sin \theta - \sin \theta (-\cos \theta) \\ 0 + \sin \theta \cos \theta - \cos \theta \sin \theta & 0 + \sin^2 \theta + (-\cos \theta)(-\cos \theta) & 0 + \sin \theta \sin \theta + (-\cos \theta)(-\cos \theta)\end{array}\right) \) \( = \left(\begin{array}{ccc}1 & 0 & 0 \\ 1 & 0 & 2 \sin \theta \cos \theta \\ 0 & \sin^2 \theta + \cos^2 \theta & \sin^2 \theta + \cos^2 \theta\end{array}\right) \) - Correction in multiplication: \( (A^2)_{22} = 0 \times 0 + \cos\theta \times \cos\theta + \sin\theta \times \sin\theta = \cos^2\theta + \sin^2\theta = 1 \) \( (A^2)_{23} = 0 \times 0 + \cos\theta \times \sin\theta + \sin\theta \times (-\cos\theta) = \cos\theta \sin\theta - \sin\theta \cos\theta = 0 \) \( (A^2)_{32} = 0 \times 0 + \sin\theta \times \cos\theta + (-\cos\theta) \times \sin\theta = \sin\theta \cos\theta - \cos\theta \sin\theta = 0 \) \( (A^2)_{33} = 0 \times 0 + \sin\theta \times \sin\theta + (-\cos\theta) \times (-\cos\theta) = \sin^2\theta + \cos^2\theta = 1 \)

    \( A^2 = \left(\begin{array}{ccc}1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1\end{array}\right) \)

    So, \( A^2 = I \), which confirms A is an involutory matrix, hence \( A^{-1} = A \).

  • Relationship between Adjugate and Inverse: The property \( \text{adj}(A) = \det(A) \times A^{-1} \) is a fundamental relationship. In our case, \( \det(A) = -1 \), so \( \text{adj}(A) = -A^{-1} \). This relationship simplifies verifying statement 2 once statement 1 or the property \( A^{-1} = A \) is established.

Understanding these matrix properties helps in quickly verifying the given statements.

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