Matrix Transposition

Transposition of a Matrix #

The transpose of a matrix is obtained by swapping rows and columns.

If

\[ A = [a_{ij}] \]

then the transpose of ( A ), denoted ( A^T ), is:

\[ A^T = [a_{ji}] \]

Rules of Matrix Transposition #

1. Transpose of a Transpose #

\[ (A^T)^T = A \]

Intuition
Swapping rows and columns twice returns the original matrix.


2. Transpose of a Sum #

\[ (A + B)^T = A^T + B^T \]

Condition
Matrices ( A ) and ( B ) must have the same dimensions.

Intuition
Transposition distributes over addition.


3. Transpose of a Scalar Multiple #

\[ (cA)^T = cA^T \]

Intuition
Scaling a matrix does not affect how rows and columns are swapped.


4. Transpose of a Product #

\[ (AB)^T = B^T A^T \]

Important
The order of multiplication reverses.

Intuition
Matrix multiplication depends on row–column pairing.
Transposition swaps this pairing, which reverses the order.


5. Transpose of the Identity Matrix #

\[ I^T = I \]

Intuition
The identity matrix is symmetric about its main diagonal.


6. Transpose of a Zero Matrix #

\[ 0^T = 0 \]

Intuition
All entries are zero, so swapping rows and columns changes nothing.


7. Transpose and Inverse (Invertible Matrices) #

\[ (A^{-1})^T = (A^T)^{-1} \]

Intuition
Inversion and transposition commute for invertible matrices.


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