We compute \( M \) as \( M = A^\dagger B A \). The adjoint (conjugate transpose) of \( A \), \( A^\dagger \), and the product \( A^\dagger B A \) lead to a specific form of \( M \):
\[ M = \begin{pmatrix} 1 & i \\ 0 & 1 \end{pmatrix}. \]
To find \( M^{2023} \), we observe the pattern of powers of \( M \):
\[ M^2 = \begin{pmatrix} 1 & 2i \\ 0 & 1 \end{pmatrix}, \quad M^3 = \begin{pmatrix} 1 & 3i \\ 0 & 1 \end{pmatrix}, \quad M^n = \begin{pmatrix} 1 & ni \\ 0 & 1 \end{pmatrix}. \]
Thus:
\[ M^{2023} = \begin{pmatrix} 1 & 2023i \\ 0 & 1 \end{pmatrix}. \]
The inverse of \( AM^{2023}A^\dagger \) can be found using the forms of \( A \), \( M^{2023} \), and \( A^\dagger \). The computation shows that:
\[ AM^{2023}A^\dagger = \begin{pmatrix} 1 & 2023i \\ 0 & 1 \end{pmatrix}. \]
Therefore, its inverse is:
\[ \text{Inverse} = \begin{pmatrix} 1 & -2023i \\ 0 & 1 \end{pmatrix}. \]
Thus, the correct answer is Option (3).
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.
There are many types of matrices and are further categorized on the basis of the value of their elements, their order, number of rows and columns, etc.
Read More: Matrices