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Transpose of a Matrix

Transpose of a Matrix

Edited By Komal Miglani | Updated on Jul 02, 2025 05:55 PM IST

Before we learn the concept of transpose of the matrix, let's first understand what a matrix is. A matrix is a rectangular arrangement of symbols along rows and columns that might be real or complex numbers. Thus, a system of m x n symbols arranged in a rectangular formation along m rows and n columns and bonded by the brackets [ ] is called an m by n matrix (which is written as m x n matrix). In real life, transpose is a commonly used tool in computer graphics for manipulating geometric objects. For transformations like translation, scaling, and rotation, it is quite useful.

This Story also Contains
  1. Transpose of matrix
  2. Steps to find Transpose of Matrix
  3. Properties of the transpose of a matrix:
  4. Solved Example Based on Transpose of Matrix
Transpose of a Matrix
Transpose of a Matrix

In this article, we will cover the concept of the Transpose of Matrix. This category falls under the broader category of Matrices, which is a crucial Chapter in class 11 Mathematics. It is not only essential for board exams but also for competitive exams like the Joint Entrance Examination(JEE Main) and other entrance exams such as SRMJEE, BITSAT, WBJEE, BCECE, and more. Over the last ten years of the JEE Main Exam (from 2013 to 2023), a total of 8 questions have been asked on this concept, including one in 2019, one in 2020, one in 2021, three in 2022, and three in 2023.

Transpose of matrix

A matrix can be transposed by interchanging its rows into columns or its columns into rows. The letter "T" in the superscript of the matrix is used to denote the transpose of the matrix.

In simple language, the transpose of a matrix is changing its rows into columns or columns into rows.

Let $\mathrm{A}=\left[\mathrm{a}_{\mathrm{ij}}\right]_{\mathrm{m} \times \mathrm{n}}$ be a matrix, then matrix obtained by changing rows into columns or vice-versa will give transpose of $\mathrm{A}$ which is denoted as $\mathrm{A}^{\prime}$ or $\mathrm{A}^{\top}$. Hence $\mathrm{A}^{\prime}=\left[\mathrm{a}_{\mathrm{ji}}\right]_{\mathrm{n} \times \mathrm{m}}$

Steps to find Transpose of Matrix

For the time being, let's assume that a matrix is a 2×3 matrix. Its measurements are two rows by three columns. When a matrix is transposed, the elements in the first row of the original matrix are recorded in the first column of the new matrix. The entries from the second row of the original matrix are similarly contained in the second column of the new matrix. The new matrix's order is now 3×2, as it has two columns and three rows.

Example,

$
\mathrm{A}=\left[\begin{array}{lll}
a_{11} & a_{12} & a_{13} \\
a_{21} & a_{22} & a_{23} \\
a_{31} & a_{32} & a_{33}
\end{array}\right] \Rightarrow \mathrm{A}^{\prime}=\left[\begin{array}{lll}
a_{11} & a_{21} & a_{31} \\
a_{12} & a_{22} & a_{32} \\
a_{13} & a_{23} & a_{33}
\end{array}\right]
$

If, $A=\left[\begin{array}{ll}2 & 6 \\ 3 & 7 \\ 5 & 8\end{array}\right]$ then, $A^{\prime}=\left[\begin{array}{lll}2 & 3 & 5 \\ 6 & 7 & 8\end{array}\right]$

Properties of the transpose of a matrix:

If $A^{\prime}$ and $B^{\prime}$ denote the transpose of the matrices $A$ and $B$, then :

i) Transpose of the Transpose Matrix

The matrix that results from taking the transpose of the transpose matrix is equal to the original matrix. Hence $\left(A^{\prime}\right)^{\prime}=A$

ii) Addition of Transpose Matrix

The resultant transpose of the addition of two matrices $A$ and $B$ is precisely equal to the total of the transposes of $A$ and $B$ separately

Hence, $(A \pm B)^{\prime}=A^{\prime} \pm B^{\prime}$ (given that $A$ and $B$ are conformable for matrix addition)

iii) Multiplication by constant

The matrix acquired is identical to the transpose of the original matrix multiplied by the constant when a matrix is multiplied by a constant and its transpose is taken.

In other words, $(k A)^{\prime}=k A^{\prime}$

iv) Multiplication Properties of Transpose

The product of the transpose of the two matrices in reverse order equals the transpose of the product of two matrices.

That's $(A B)^{\prime}=B^{\prime} A^{\prime}($ given that $A$ and $B$ are conformable for matrix product $A B)$

Recommended Video Based on Transpose of Matrix:

Solved Example Based on Transpose of Matrix

Example 1: Let $
\mathrm{A}=\left[\begin{array}{l}
1 \\
1 \\
1
\end{array}\right] \text { and } \mathrm{B}=\left[\begin{array}{ccc}
9^2 & -10^2 & 11^2 \\
12^2 & 13^2 & -14^2 \\
-15^2 & 16^2 & 17^2
\end{array}\right]
$ then the value of $\mathrm{A}^{\prime} \mathrm{BA}$ is: [JEE Main 2022]

Solution:

$
\begin{aligned}
\mathrm{A}^{\prime} \mathrm{B} & =\left[\begin{array}{lll}
1 & 1 & 1
\end{array}\right]\left[\begin{array}{ccc}
9^2 & -10^2 & 11^2 \\
12^2 & 13^2 & -14^2 \\
-15^2 & 16^2 & 17^2
\end{array}\right] \\
& =\left[9^2+12^2-15^2-10^2+13^2+16^2 \quad 11^2-14^2+17^2\right]
\end{aligned}
$
(A'B)
$
\begin{aligned}
A & =\left[9^2+12^2-15^2-10^2+13^2+16^2 11^2-14^2+17^2\right]\left[\begin{array}{l}
1 \\
1 \\
1
\end{array}\right] \\
& =\left[9^2+12^2-15^2-10^2+13^2+16^2+11^2-14^2+17^2\right] \\
& =\left[\left(9^2-10^2\right)+\left(11^2+12^2\right)+\left(13^2-14^2\right)+\left(-15^2+16^2\right)+17^2\right] \\
& =[-19+265-27+31+289] \\
& =[539]
\end{aligned}
$

Hence the value $\mathrm{A}^{\prime} \mathrm{BA}$ is [539]

Example 2: Let $\mathrm{S}$ be the set containing all $3 \times 3$ matrices with entries from $\{-1,0,1\}$. The total number of matrices $\mathrm{A} \in \mathrm{S}$ such that the sum of all the diagonal elements of $\mathrm{A}^{\mathrm{T}} \mathrm{A}$ is 6 is $\qquad$

[JEE Main 2022]
Solution:
$
\begin{aligned}
& \operatorname{Tr}_{\mathrm{r}}\left(\mathrm{AA}^{\top}\right)=6 \\
& \mathrm{AA}^{\top}=\left[\begin{array}{lll}
a & d & g \\
b & e & h \\
c & f & i
\end{array}\right]\left[\begin{array}{lll}
a & b & c \\
d & e & f \\
g & h & i
\end{array}\right]
\end{aligned}
$

Now given $\mathrm{a}^2+\mathrm{d}^2+\mathrm{y}^2+\mathrm{b}^2+\mathrm{e}^2+\mathrm{h}^2+\mathrm{c}^2+\mathrm{f}^2+\mathrm{i}^2=6$
$
\begin{aligned}
& ={ }^9 \mathrm{c}_3 \times 2^6 \\
& =5376
\end{aligned}
$

Hence, The total number of matrices $\mathrm{A} \in \mathrm{S}$ such that the sum of all the diagonal elements of $\mathrm{A}^{\mathrm{T}} \mathrm{A}$ is 6 is 5376.

Example 3: Let $\mathrm{X}=\left[\begin{array}{l}1 \\ 1 \\ 1\end{array}\right]$ and $\mathrm{A}=\left[\begin{array}{ccc}-1 & 2 & 3 \\ 0 & 1 & 6 \\ 0 & 0 & -1\end{array}\right]$. For $\mathrm{k} \in \mathbb{N}$, if $\mathrm{X}^{\prime} \mathrm{A}^{\mathrm{k}} \mathrm{X}=33$, then $\mathrm{k}$ is equal to $\qquad$

Solution:

$
\begin{aligned}
& \mathrm{A}^2=\left[\begin{array}{ccc}
-1 & 2 & 3 \\
0 & 1 & 6 \\
0 & 0 & -1
\end{array}\right]\left[\begin{array}{ccc}
-1 & 2 & 3 \\
0 & 1 & 6 \\
0 & 0 & -1
\end{array}\right] \\
& \quad=\left[\begin{array}{lll}
1 & 0 & 6 \\
0 & 1 & 0 \\
0 & 0 & 1
\end{array}\right]=\mathrm{I}+\left[\begin{array}{lll}
0 & 0 & 6 \\
0 & 0 & 0 \\
0 & 0 & 0
\end{array}\right] \\
& \text { Let }\left[\begin{array}{lll}
0 & 0 & 6 \\
0 & 0 & 0 \\
0 & 0 & 0
\end{array}\right]=\mathrm{B} \\
& \mathrm{B}^2=0, \\
& \therefore \mathrm{B}^3=0=\mathrm{B}^4=\mathrm{B}^5=\cdots \\
& \text { Now }\left(\mathrm{A}^2\right)^{\mathrm{P}}=(\mathrm{I}+\mathrm{B})^{\mathrm{P}} . \\
& \quad=\mathrm{I}+\mathrm{pB} \\
& \quad=\left[\begin{array}{lll}
1 & 0 & 6 \mathrm{p} \\
0 & 1 & 0 \\
0 & 0 & 1
\end{array}\right]
\end{aligned}
$

Now $x^{\prime} A^k x$
Let $\mathrm{k}$ be even and $\mathrm{k}=2 \mathrm{p}$
$
\begin{aligned}
& {\left[\begin{array}{lll}
1 & 1 & 1
\end{array}\right]\left[\begin{array}{lll}
1 & 0 & 6 \mathrm{p} \\
0 & 1 & 0 \\
0 & 0 & 1
\end{array}\right]\left[\begin{array}{l}
1 \\
1 \\
1
\end{array}\right]} \\
& =\left[\begin{array}{lll}
1 & 1 & 6 \mathrm{p}+1
\end{array}\right]\left[\begin{array}{l}
1 \\
1 \\
1
\end{array}\right] \\
& =[6 \mathrm{p}+3]
\end{aligned}
$

Now $6 \mathrm{p}+3=33$
$
\begin{aligned}
& \Rightarrow \mathrm{p}=5 \\
& \mathrm{k}=2 \mathrm{p}=10
\end{aligned}
$

Hence, the answer is 10.

Example 4: Let $A$ be a $2 \times 2$ matrix with real entries such that $A^{\prime}=\alpha A+I$, where a $\epsilon \mathbb{R}-\{-1,1\}$. If $\left|\mathrm{A}^2-\mathrm{A}\right|=4$, then the sum of all possible values of $\alpha$ is equal to :

Solution:

$
\begin{aligned}
& \mathrm{A}^{\mathrm{T}}=\alpha \mathrm{A}+\mathrm{I} \\
& \mathrm{A}=\alpha \mathrm{A}^{\mathrm{T}}+\mathrm{I} \\
& \mathrm{A}=\alpha(\alpha \mathrm{A}+\mathrm{I})+\mathrm{I} \\
& \mathrm{A}=\alpha^2 \mathrm{~A}+(\alpha+1) \mathrm{I} \\
& \mathrm{A}\left(1-\alpha^2\right)=(\alpha+1) \mathrm{I} \\
& \mathrm{A}=\frac{\mathrm{I}}{1-\alpha} \ldots(1) \\
& |\mathrm{A}|=\frac{1}{(1-\alpha)^2} \ldots(2) \\
& \left|\mathrm{A}^2-\mathrm{A}\right|=|\mathrm{A}||\mathrm{A}-\mathrm{I}| \ldots(3) \\
& \mathrm{A}-\mathrm{I}=\frac{\mathrm{I}}{\mathrm{I}-\alpha}-\mathrm{I}=\frac{\alpha}{1-\alpha} \mathrm{I} \\
& |\mathrm{A}-\mathrm{I}|=\left(\frac{\alpha}{1-\alpha}\right)^2 \ldots(4)
\end{aligned}
$

Now $\left|\mathrm{A}^2-\mathrm{A}\right|=4$
$
|\mathrm{A}||\mathrm{A}-\mathrm{I}|=4
$

$
\begin{aligned}
& \Rightarrow \frac{1}{(1-\alpha)^2} \frac{\alpha^2}{\left(1-\alpha^2\right)}=4 \\
& \Rightarrow \frac{\alpha}{(1-\alpha)^2}= \pm 2 \\
& \Rightarrow 2(1-\alpha)^2= \pm \alpha \\
& \left(C_1\right) 2(1-\alpha)^2=\alpha \\
& \left(C_2\right) 2(1-\alpha)^3=-\alpha \\
& 2 \alpha^2-5 \alpha+2=0 \alpha_1 \\
& 2 \alpha^2-3 \alpha+2=0 \\
& \alpha_1+\alpha_2=\frac{5}{2} \\
& \alpha \notin \mathrm{R}
\end{aligned}
$

Hence, the sum of all possible values of $\alpha$ is equal to $\frac{5}{2}$

Frequently Asked Questions (FAQs)

1. How to calculate the Transpose of a matrix?

Assume for the moment that a matrix is a 2×3 matrix. Its dimensions are 2 rows by 3 columns. The items in the first row of the original matrix are recorded in the first column of the new matrix when determining the transpose of a matrix. In a similar manner, the new matrix's second column contains the items from the second row of the original matrix. Because the new matrix has 3 rows and 2 columns, its order is now 3×2.

2. What is the Addition property of the Transpose of a Matrix?

The resultant transpose of the addition of two matrices A and B is precisely equal to the total of the transposes of A and B separately

3. How many orders does the transpose of an order m x n matrix have?

A matrix can be transposed by changing its rows into columns or its columns into rows. The order of the transpose of a matrix of order m x n is hence "n x m".

4. What is the transpose matrix's multiplication property?

The product of the transpose of the two matrices in reverse order equals the transpose of the product of two matrices.

Considering that (AB)' = B'A' indicates that A and B are conformable for matrix product AB.

5. What does Matrix transpose mean?

A matrix can be transposed by changing its rows into columns or its columns into rows. In the given matrix, the superscript "T" is used.

In simple language, the transpose of a matrix is changing its rows into columns or columns into rows. 

Let A=[aij]m×n be a matrix, then matrix obtained by changing rows into columns or vice-versa will give transpose of A which is denoted as A′ or A⊤. Hence A′=[aji]n×m

6. What happens to a square matrix when it's transposed?
A square matrix remains square after transposition, but its elements are rearranged. The size doesn't change, but the rows become columns and vice versa.
7. How does the size of a matrix change when it's transposed?
When a matrix is transposed, its dimensions are reversed. If the original matrix is m × n (m rows and n columns), its transpose will be n × m (n rows and m columns).
8. Can you transpose a 1 × n matrix? What's the result?
Yes, you can transpose a 1 × n matrix (a row matrix). The result is an n × 1 matrix (a column matrix). This effectively turns a horizontal row of numbers into a vertical column.
9. What's the difference between A and A^T in matrix notation?
A represents the original matrix, while A^T (read as "A transpose") represents the transposed version of matrix A. The superscript T indicates the transpose operation.
10. Is (A^T)^T equal to A?
Yes, (A^T)^T is equal to A. Transposing a matrix twice returns the original matrix. This property is known as the involution of matrix transposition.
11. How do you find the transpose of a 2 × 2 matrix?
To transpose a 2 × 2 matrix, swap the elements on the main diagonal (top-left to bottom-right), and swap the other two elements. For example, if A = [[a, b], [c, d]], then A^T = [[a, c], [b, d]].
12. How do you find the transpose of a 3 × 3 matrix?
To transpose a 3 × 3 matrix, keep the main diagonal elements in place and swap the other elements across the main diagonal. For example, if A = [[a, b, c], [d, e, f], [g, h, i]], then A^T = [[a, d, g], [b, e, h], [c, f, i]].
13. What is the transpose of a matrix?
The transpose of a matrix is a new matrix obtained by flipping the original matrix over its main diagonal (from top-left to bottom-right). This means the rows of the original matrix become the columns of the new matrix, and vice versa.
14. Can you transpose a matrix with complex numbers?
Yes, you can transpose a matrix with complex numbers. When transposing a complex matrix, you typically also take the complex conjugate of each element. This operation is called the conjugate transpose or Hermitian transpose.
15. What's the transpose of an identity matrix?
The transpose of an identity matrix is the identity matrix itself. This is because an identity matrix is symmetric and has 1s on the main diagonal and 0s elsewhere.
16. What's a symmetric matrix and how does it relate to transposition?
A symmetric matrix is a square matrix that is equal to its own transpose (A = A^T). In a symmetric matrix, the elements are symmetric about the main diagonal.
17. What's an orthogonal matrix and how does it relate to transposition?
An orthogonal matrix is a square matrix whose transpose is equal to its inverse. In other words, for an orthogonal matrix Q, Q * Q^T = Q^T * Q = I, where I is the identity matrix.
18. What's the transpose of a zero matrix?
The transpose of a zero matrix (a matrix with all elements equal to zero) is another zero matrix, possibly with different dimensions. If A is an m × n zero matrix, A^T will be an n × m zero matrix.
19. What's the relationship between eigenvalues and transposition?
The eigenvalues of a matrix and its transpose are the same. However, the eigenvectors may be different.
20. What's the relationship between transposition and matrix similarity?
If two matrices A and B are similar (B = P^-1 * A * P for some invertible matrix P), then their transposes A^T and B^T are also similar. Specifically, B^T = (P^T)^-1 * A^T * P^T.
21. How does transposition affect the nullspace of a matrix?
The nullspace of A^T is related to the row space of A. Specifically, the nullspace of A^T is the orthogonal complement of the row space of A. This relationship is part of the Fundamental Theorem of Linear Algebra.
22. How does transposition affect the condition number of a matrix?
The condition number of a matrix is unchanged by transposition. This is because the condition number depends on the singular values of the matrix, which are the same for A and A^T.
23. What's the relationship between transposition and matrix factorization?
Many matrix factorizations have corresponding forms for the transpose. For example, if A = LU is the LU decomposition of A, then A^T = (LU)^T = U^T * L^T, which is the LU decomposition of A^T.
24. How does transposition relate to the four fundamental subspaces of linear algebra?
Transposition swaps the column space with the row space, and the nullspace with the left nullspace. This relationship is key to understanding the duality in linear algebra.
25. How does transposition affect the eigendecomposition of a matrix?
If A = PDP^-1 is the eigendecomposition of A, where D is diagonal and P is the matrix of eigenvectors, then A^T = (P^-1)^T * D * P^T. The eigenvalues (diagonal elements of D) remain the same, but the eigenvectors change.
26. What's the relationship between transposition and matrix norms?
Many matrix norms are invariant under transposition. For example, the spectral norm (largest singular value) and the Frobenius norm are the same for A and A^T.
27. How does transposition affect the solution of linear systems?
If Ax = b is a linear system, then A^Ty = c is called the transposed system. The solutions of these systems are related: if x solves Ax = b, then x^T solves y^TA^T = b^T.
28. How does transposition affect the singular value decomposition (SVD) of a matrix?
If A = UΣV^T is the SVD of A, then A^T = VΣU^T. The singular values (diagonal elements of Σ) remain the same, but U and V swap roles.
29. What's the relationship between transposition and matrix polynomials?
For a matrix polynomial p(A) = a0I + a1A + a2A^2 + ... + anA^n, we have p(A^T) = p(A)^T. This means you can either transpose first and then apply the polynomial, or apply the polynomial and then transpose.
30. How does transposition affect the Kronecker product of matrices?
For the Kronecker product, (A ⊗ B)^T = A^T ⊗ B^T. This property is useful in many applications, including in quantum computing and signal processing.
31. What's the transpose of a Hankel matrix?
The transpose of a Hankel matrix (a matrix where each skew-diagonal is constant) is also a Hankel matrix. This is because the skew-diagonals in the original matrix become the skew-diagonals in the transposed matrix.
32. How does transposition relate to the adjugate of a matrix?
The adjugate of the transpose is equal to the transpose of the adjugate: adj(A^T) = (adj(A))^T. This relationship is useful in various matrix computations and proofs.
33. What's the effect of transposition on the Jordan canonical form of a matrix?
If J is the Jordan canonical form of A, then J^T is the Jordan canonical form of A^T. The sizes of the Jordan blocks remain the same, but their order may change.
34. How does transposition affect matrix exponentials?
For matrix exponentials, (e^A)^T = e^(A^T). This property is useful in solving systems of differential equations and in control theory.
35. What's the relationship between transposition and matrix logarithms?
For matrix logarithms, (log(A))^T = log(A^T), assuming the logarithms exist. This property is a consequence of the relationship between matrix exponentials and logarithms.
36. How does transposition relate to the Schur decomposition of a matrix?
If A = QUQ* is the Schur decomposition of A (where Q is unitary and U is upper triangular), then A^T = Q*U^TQ is the Schur decomposition of A^T. The Schur form U^T is lower triangular instead of upper triangular.
37. What happens to the main diagonal of a square matrix when it's transposed?
The main diagonal of a square matrix remains unchanged when the matrix is transposed. Elements on the main diagonal stay in the same position.
38. How does transposition affect matrix addition?
Transposition distributes over matrix addition. This means (A + B)^T = A^T + B^T, where A and B are matrices of the same size.
39. What's the relationship between matrix multiplication and transposition?
For matrix multiplication, (AB)^T = B^T * A^T. This means the transpose of a product is equal to the product of the transposes in reverse order.
40. Can you add a matrix to its transpose?
Yes, you can add a matrix to its transpose if the original matrix is square. The result will always be a symmetric matrix.
41. What's the transpose of a diagonal matrix?
The transpose of a diagonal matrix is the same as the original matrix. This is because all non-diagonal elements are zero, and remain zero after transposition.
42. How does transposition affect the determinant of a matrix?
Transposition does not change the determinant of a matrix. The determinant of a matrix is equal to the determinant of its transpose: det(A) = det(A^T).
43. How does transposition affect matrix inverse?
For an invertible matrix A, (A^T)^-1 = (A^-1)^T. This means the inverse of the transpose is equal to the transpose of the inverse.
44. What's a skew-symmetric matrix and how does it relate to transposition?
A skew-symmetric matrix is a square matrix whose transpose is equal to its negative (A^T = -A). In a skew-symmetric matrix, the main diagonal elements are all zero.
45. What's the difference between transpose and conjugate transpose?
The transpose only switches rows and columns, while the conjugate transpose (also called Hermitian transpose) switches rows and columns and takes the complex conjugate of each element. For real matrices, these operations are the same.
46. How does transposition affect the rank of a matrix?
Transposition does not change the rank of a matrix. The rank of a matrix is equal to the rank of its transpose: rank(A) = rank(A^T).
47. How does transposition affect the trace of a square matrix?
The trace of a square matrix (sum of elements on the main diagonal) remains unchanged after transposition. This is because the main diagonal elements don't change position during transposition.
48. Can you transpose a matrix with only one element?
Yes, you can transpose a 1 × 1 matrix (a matrix with only one element), but it remains unchanged. A single element can be viewed as both a row and a column.
49. What's the transpose of a lower triangular matrix?
The transpose of a lower triangular matrix is an upper triangular matrix. All elements below the main diagonal become zero, and the non-zero elements appear above the main diagonal in the transposed matrix.
50. How does transposition affect matrix exponentiation?
For matrix exponentiation, (A^n)^T = (A^T)^n, where n is a positive integer. This means the transpose of a matrix raised to a power is equal to the transpose of the matrix raised to the same power.
51. What's the transpose of a block matrix?
To transpose a block matrix, you transpose each block and then arrange these transposed blocks in the transposed position. For example, if A = [[A11, A12], [A21, A22]], then A^T = [[A11^T, A21^T], [A12^T, A22^T]].
52. How does transposition affect the Frobenius norm of a matrix?
The Frobenius norm of a matrix (the square root of the sum of squares of its elements) is unchanged by transposition. This is because transposition doesn't change the values of the elements, only their positions.
53. What's the transpose of a Toeplitz matrix?
The transpose of a Toeplitz matrix (a matrix with constant diagonals) is also a Toeplitz matrix. However, the direction of the constant diagonals is reversed.
54. What's the transpose of a Vandermonde matrix?
The transpose of a Vandermonde matrix is not generally a Vandermonde matrix. However, it preserves some special properties, such as having a determinant that can be expressed as a product of differences.
55. What's the transpose of a permutation matrix?
The transpose of a permutation matrix is its inverse. This is because permutation matrices are orthogonal (P^T = P^-1).
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