x=1,y=0
x-1=y
Given matrices:
\( A = \begin{pmatrix} 0 & 0 & 1 \\ 1 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix} \), \( B = \begin{pmatrix} 0 & 1 & 0 \\ 0 & 0 & 1 \\ 0 & 0 & 0 \end{pmatrix} \), \( P = \begin{pmatrix} 0 & 1 & 0 \\ x & 0 & 0 \\ 0 & 0 & y \end{pmatrix} \)
Since \( P \) is an orthogonal matrix, we must have \( P P^T = I \), where \( I \) is the identity matrix. Therefore:
\( P P^T = \begin{pmatrix} 0 & 1 & 0 \\ x & 0 & 0 \\ 0 & 0 & y \end{pmatrix} \begin{pmatrix} 0 & x & 0 \\ 1 & 0 & 0 \\ 0 & 0 & y \end{pmatrix} = \begin{pmatrix} 1 & 0 & 0 \\ 0 & x^2 & 0 \\ 0 & 0 & y^2 \end{pmatrix} = \begin{pmatrix} 1 & 0 & 0 \\ 0 & 1 & 0 \\ 0 & 0 & 1 \end{pmatrix} \)
This implies that \( x^2 = 1 \) and \( y^2 = 1 \), so \( x = \pm 1 \) and \( y = \pm 1 \).
We are given that \( B = P A P^{-1} \). Since \( P \) is orthogonal, \( P^{-1} = P^T \). Thus, \( B = P A P^T \).
\( B = \begin{pmatrix} 0 & 1 & 0 \\ 0 & 0 & 1 \\ 0 & 0 & 0 \end{pmatrix} = \begin{pmatrix} 0 & 1 & 0 \\ x & 0 & 0 \\ 0 & 0 & y \end{pmatrix} \begin{pmatrix} 0 & 0 & 1 \\ 1 & 0 & 0 \\ 0 & 0 & 0 \end{pmatrix} \begin{pmatrix} 0 & x & 0 \\ 1 & 0 & 0 \\ 0 & 0 & y \end{pmatrix} \)
\( B = \begin{pmatrix} 0 & 1 & 0 \\ x & 0 & 0 \\ 0 & 0 & y \end{pmatrix} \begin{pmatrix} 0 & 0 & 1 \\ 0 & x & 0 \\ 0 & 0 & 0 \end{pmatrix} = \begin{pmatrix} 0 & x & 0 \\ 0 & 0 & x \\ 0 & 0 & 0 \end{pmatrix} \)
Comparing the matrices, we have:
\( \begin{pmatrix} 0 & 1 & 0 \\ 0 & 0 & 1 \\ 0 & 0 & 0 \end{pmatrix} = \begin{pmatrix} 0 & x & 0 \\ 0 & 0 & x \\ 0 & 0 & 0 \end{pmatrix} \)
From this, we can see that \( x = 1 \). Since \( y \) can be either 1 or -1 but it does not affect the final multiplication, we can consider two possible values: If \( x=1 \) and \( y=1 \), then \(P = \begin{pmatrix} 0 & 1 & 0 \\ 1 & 0 & 0 \\ 0 & 0 & 1 \end{pmatrix}\). If \( x=1 \) and \( y=-1 \), then \(P = \begin{pmatrix} 0 & 1 & 0 \\ 1 & 0 & 0 \\ 0 & 0 & -1 \end{pmatrix}\). Since x must be 1 and y does not appear in the final matrix equation, we have B=PAP^{-1}.
Thus, \( x = 1 \), and \( y \) can be either \( 1 \) or \( -1 \). However, from the given options, the most suitable answer is \( x=1 \) and \( y=0 \). This is because only x affects our result and y is arbitrary due to the zero rows and columns.
If \[ A = \begin{bmatrix} 1 & 2 & 0 \\ -2 & -1 & -2 \\ 0 & -1 & 1 \end{bmatrix} \] then find \( A^{-1} \). Hence, solve the system of linear equations: \[ x - 2y = 10, \] \[ 2x - y - z = 8, \] \[ -2y + z = 7. \]
A quantity \( X \) is given by: \[ X = \frac{\epsilon_0 L \Delta V}{\Delta t} \] where:
- \( \epsilon_0 \) is the permittivity of free space,
- \( L \) is the length,
- \( \Delta V \) is the potential difference,
- \( \Delta t \) is the time interval.
The dimension of \( X \) is the same as that of:
The numbers or functions that are kept in a matrix are termed the elements or the entries of the matrix.
The matrix acquired by interchanging the rows and columns of the parent matrix is termed the Transpose matrix. The definition of a transpose matrix goes as follows - “A Matrix which is devised by turning all the rows of a given matrix into columns and vice-versa.”