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Unitary matrix

Unitary matrix

Edited By Komal Miglani | Updated on Jul 02, 2025 06:34 PM IST

A matrix (plural: matrices) 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 is called an m by n matrix (which is written as m x n matrix). There are special types of matrices like Orthogonal matrices, Unitary matrices, and Idempotent matrices. In real life, we use unitary matrices in quantum mechanics.

This Story also Contains
  1. Square matrix
  2. Unitary matrix
  3. Properties of Unitary Matrices
  4. Solved Examples Based on Unitary Matrix
Unitary matrix
Unitary matrix

In this article, we will cover the concept of unitary matrices. This category falls under the broader category of Matrices, which is a crucial Chapter in class 12 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. A total of twelve questions have been asked on this topic in JEE MAINS(2013 - 2023) including one in 2021 and one in 2023.

Square matrix

The square matrix is the matrix in which the number of rows = number of columns. So a matrix $\mathrm{A}=\left[\mathrm{a}_{\mathrm{ij}}\right]_{\mathrm{m} \times \mathrm{n}}$ is said to be a square matrix when m = n.

E.g.

$\left[\begin{array}{lll}a_{11} & a_{12} & a_{13} \\ a_{21} & a_{22} & a_{23} \\ a_{31} & a_{32} & a_{33}\end{array}\right]_{3 \times 3}$ or, $\left[\begin{array}{cc}2 & -4 \\ 7 & 3\end{array}\right]_{2 \times 2}$

Unitary matrix

A unitary matrix is a square matrix of complex numbers, whose inverse is equal to its conjugate transpose.

The product of a unitary matrix and the conjugate transpose of a unitary matrix is equal to the identity matrix.

Let A be a square matrix, and if AAH = I, where I is the identity matrix, then A is said to be a unitary matrix, and AH is its conjugate transpose.

Properties of Unitary Matrices

If A is unitary matrices, I is identity matrices, A-1 is the Inverse of matrix A, and AH is the conjugate transpose of matrix A.

1) If A AH = I, then A-1 = AH

2) If A and B are unitary, Then AB is also unitary.

3) If A is unitary, then A-1 and AH are also unitary.

4) A AH = AH A= I

5) A unitary matrix is a non-singular matrix.

6) The determinant of the unitary matrix is not equal to zero.

7) The inverse of a unitary matrix is another unitary matrix.

8) A matrix is unitary, if and only if its transpose is unitary

9) The unitary matrices can also be non-square matrices but have orthonormal columns and rows.

10) The sum or difference of two unitary matrices does NOT need to be a unitary matrix. For example, if A is a unitary matrix, then A - A = O (null matrix), which is NOT unitary.

Recommended Video Based on Unitary Matrix


Solved Examples Based on Unitary Matrix

Example 1: Which of the following properties is true for a unitary matrix \( U \)?

1) \( U^{-1} = U^T \)
2) The columns of \( U \) are orthonormal vectors.
3) The determinant of \( U \) is always zero.
4) \( U U^T = I \)

Solution:
1) False. For a unitary matrix \( U \), \( U^{-1} = U^* \), where \( U^* \) is the conjugate transpose of \( U \). \( U^T \) is used for orthogonal matrices.
2) True. The columns (and rows) of a unitary matrix are orthonormal vectors.
3) False. The determinant of a unitary matrix has an absolute value of 1, not zero.
4) False. For a unitary matrix, \( U U^* = I \), not \( U U^T \).

Hence, the answer is option 2.

Example 2: If the matrix $A=\left[\begin{array}{cc}a+b i & -c+i d \\ c+i d & a-i b\end{array}\right]$ is a Unitary matrix then
1) $a^2+b^2+c^2+d^2=1$
2) $a^2+b^2=c^2+d^2$
4) $a^2+b^2+c^2+d^2=0$
3) $a^2+c^2=b^2+d^2$

Solution

$
\begin{aligned}
& A=\left[\begin{array}{cc}
a+b i & -c+i d \\
c+i d & a-i b
\end{array}\right] \\
& A \cdot A^\theta=\left[\begin{array}{cc}
a+b i & -c+i d \\
c+i d & a-i b
\end{array}\right] \cdot\left[\begin{array}{cc}
a-b i & c-i d \\
-c-i d & a+i b
\end{array}\right]=\left[\begin{array}{ll}
1 & 0 \\
0 & 1
\end{array}\right] \\
& {\left[\begin{array}{cc}
a^2+b^2+c^2+d^2 & 0 \\
0 & a^2+b^2+c^2+d^2
\end{array}\right]=\left[\begin{array}{ll}
1 & 0 \\
0 & 1
\end{array}\right]} \\
& a^2+b^2+c^2+d^2=1
\end{aligned}
$
Hence, the answer is option 1.

Example 3: If \( V \) is a 3x3 unitary matrix, what is the possible value of \( \det(V) \)?

A) 0
B) 1
C) -1
D) 1 or -1

Solution:
For a unitary matrix \( V \), the determinant must lie on the unit circle in the complex plane, which means it has an absolute value of 1. Therefore, the possible values are \( e^{i\theta} \) where \( \theta \) is any real number. Specifically, the determinant can be \( \pm 1 \) or any complex number of absolute value 1.

Hence, the answer is option 4.

Example 4: $\frac{1}{\sqrt{3}}\left[\begin{array}{cc}1 & 1+i \\ 1-i & -1\end{array}\right]$ is a
1)Nilpotent Matrix
2)Unitary Matrix
3)Symmetric Matrix
4)Skew-Symmetric Matrix

Solution
Let $\mathrm{A}=\frac{1}{\sqrt{3}}\left[\begin{array}{cc}1 & 1+i \\ 1-i & -1\end{array}\right]$
Then $A^{\Theta}=\frac{1}{\sqrt{3}}\left[\begin{array}{cc}1 & 1-i \\ 1+i & -1\end{array}\right]$
Multiplying both the matrices, we get:

$
A A^{\Theta}=I
$
Thus, it is a unitary matrix.

Hence, the answer is the option (2).

Example 5: If A and B are unitary matrix. Then which of the following option is True.

1) A+B is unitary matrix.(always)

2) A-B is unitary matrix. (always)

3) AB is a unitary matrix.(always)

4) (1) and (3) both

Solution:

As we have learnt

Unitary matrix -

$
A A^{\Theta}=I
$
$A^{\Theta}$ is complex conjugate transpose matrix of matrix $A$ and $I$ is identity matrix
$A \cdot A^\theta=I$ and $B B^\theta=I$
(a) $
(A+B)^\theta(A+B)=\left(A^\theta+B^\theta\right)(A+B)=A^\theta A+A^\theta B+B^\theta A+B^\theta B
$

(b) $
(A-B)^\theta(A-B)=\left(A^\theta-B^\theta\right)(A-B)=A^\theta A-B^\theta A-A^\theta B+B^\theta B
$

(c) $(A B)^\theta(A B)=B^\theta A^\theta A B=B^\theta(I) B=B^\theta B=I$

Hence, the answer is option 4.

Frequently Asked Questions (FAQs)

1. What is the unitary matrix?

 A unitary matrix is a square matrix of complex numbers, whose inverse is equal to its conjugate transpose. The product of a unitary matrix and the conjugate transpose of a unitary matrix is equal to the identity matrix.

2. Can non-square matrices be unitary matrices?

Yes, the unitary matrices can also be non-square matrices but have orthonormal columns and rows.

3. Is the sum or difference of any two unitary matrices be unitary matrices?

 No, the sum or difference of two unitary matrices does NOT need to be a unitary matrix. For example, if A is a unitary matrix, then A - A = O (null matrix), which is NOT unitary.

4. Is a unitary matrix a singular matrice or non-singular matrice?

A unitary matrix is a non-singular matrix. A square matrix is called a non-singular matrix if its determinant is not 0. Let's say A is a square matrix then it is non-singular if |A| ≠ 0.

5. If A is a unitary matrices then its its conjugate transpose and inverse are also unitary matrices or not.

 Yes,  If A is a unitary matrix then its its conjugate transpose and inverse are also unitary matrices.

6. What are the key properties of a unitary matrix?
Key properties of unitary matrices include:
7. Why are unitary matrices important in quantum mechanics?
Unitary matrices are crucial in quantum mechanics because they represent quantum operations that preserve the total probability of a system. They ensure that the sum of probabilities of all possible outcomes remains 1, which is a fundamental requirement in quantum theory. Unitary transformations also preserve the orthogonality of quantum states.
8. How can you determine if a matrix is unitary?
To determine if a matrix U is unitary:
9. Can a unitary matrix have real entries only?
Yes, a unitary matrix can have real entries only. In this case, it becomes an orthogonal matrix. Orthogonal matrices are a subset of unitary matrices where all entries are real. They satisfy the condition U^T × U = I, which is equivalent to U* × U = I when all entries are real.
10. What is the significance of eigenvalues in unitary matrices?
The eigenvalues of a unitary matrix always have a magnitude of 1. This means they lie on the complex unit circle. This property is crucial in many applications, particularly in quantum mechanics, where eigenvalues represent measurable quantities. The fact that eigenvalues have magnitude 1 ensures that probabilities are conserved in quantum systems.
11. What is the polar decomposition of a matrix, and how are unitary matrices involved?
The polar decomposition states that any square matrix A can be decomposed as A = UP, where U is a unitary matrix and P is a positive semidefinite Hermitian matrix. U represents the rotational part of the transformation, while P represents the scaling and shearing. This decomposition is useful in various applications, including computer graphics and signal processing.
12. What is the difference between a unitary matrix and a Hermitian matrix?
While both are important in quantum mechanics, they have different properties:
13. How does matrix multiplication affect unitarity?
The product of two unitary matrices is always unitary. This means that if U and V are unitary matrices, then UV is also unitary. This property is important in quantum mechanics, where sequences of unitary operations can be combined into a single unitary operation.
14. How do unitary matrices relate to the Singular Value Decomposition (SVD)?
In the Singular Value Decomposition, any matrix A can be decomposed as A = UΣV*, where U and V are unitary matrices, and Σ is a diagonal matrix of singular values. The unitary matrices U and V represent rotations or reflections in the input and output spaces, while Σ represents scaling. This decomposition is powerful because it separates a linear transformation into basic geometric operations.
15. What is the exponential of a skew-Hermitian matrix, and how does it relate to unitary matrices?
The exponential of a skew-Hermitian matrix is always a unitary matrix. A skew-Hermitian matrix S satisfies S* = -S. The matrix exponential e^S of such a matrix is unitary. This relationship is important in quantum mechanics and Lie group theory, as it provides a way to generate unitary matrices from simpler objects.
16. What is a unitary matrix?
A unitary matrix is a complex square matrix whose conjugate transpose is equal to its inverse. In other words, if U is a unitary matrix, then U* × U = U × U* = I, where U* is the conjugate transpose of U and I is the identity matrix. This property ensures that unitary matrices preserve inner products and lengths of vectors.
17. How does a unitary matrix differ from an orthogonal matrix?
While both unitary and orthogonal matrices preserve lengths and angles, the main difference is that unitary matrices work with complex numbers, while orthogonal matrices are restricted to real numbers. Unitary matrices satisfy U* × U = I, where U* is the conjugate transpose, while orthogonal matrices satisfy U^T × U = I, where U^T is the transpose.
18. What is the relationship between unitary matrices and isometries?
Unitary matrices represent isometries in complex vector spaces. An isometry is a transformation that preserves distances between points. In the context of linear algebra, unitary matrices preserve the inner product between vectors, which in turn preserves their lengths and angles. This makes unitary matrices the complex counterpart to orthogonal matrices, which represent isometries in real vector spaces.
19. What is the connection between unitary matrices and rotations?
Unitary matrices can be thought of as generalized rotations in complex vector spaces. In 2D and 3D real spaces, orthogonal matrices (which are real unitary matrices) represent rotations. In higher dimensions and complex spaces, unitary matrices play a similar role, preserving the "shape" of the space by maintaining distances and angles between vectors.
20. How do unitary matrices relate to the concept of orthonormal bases?
The columns (or rows) of a unitary matrix form an orthonormal basis for the vector space. This means that these vectors are mutually orthogonal and have unit length. Conversely, any matrix whose columns form an orthonormal basis is unitary. This property makes unitary matrices useful for changing between different orthonormal bases in a vector space.
21. How are unitary matrices used in error-correcting codes?
Unitary matrices play a role in certain quantum error-correcting codes. In these codes, information is encoded in a way that allows errors to be detected and corrected. Unitary operations are used to encode the information and to perform error correction, as they preserve the quantum nature of the information while allowing manipulations that can identify and fix errors.
22. How do unitary matrices feature in the theory of quantum error correction?
In quantum error correction, information is encoded in a way that allows errors to be detected and corrected. The encoding and decoding operations, as well as the error correction procedures, must all be represented by unitary matrices to preserve the quantum nature of the information. The design of effective quantum error-correcting codes often involves finding appropriate unitary transformations that can protect quantum information against likely errors.
23. How are unitary matrices used in the theory of quantum channels?
Quantum channels describe the most general physical operations possible on quantum systems. While not all quantum channels are unitary, any quantum channel can be represented as a unitary operation on a larger system (the system plus an environment). This representation, known as a Stinespring dilation, shows that all quantum operations can be understood in terms of unitary evolution followed by partial measurement.
24. How do unitary matrices feature in the description of adiabatic quantum computation?
In adiabatic quantum computation, the system evolves slowly under a time-dependent Hamiltonian. While the evolution is continuous, it can be approximated by a series of small unitary transformations. The adiabatic theorem ensures that if the evolution is slow enough, the system will remain in the ground state of the instantaneous Hamiltonian, which is crucial for the operation of adiabatic quantum algorithms.
25. How are unitary matrices related to the concept of quantum teleportation?
Quantum teleportation involves transmitting quantum information using entanglement and classical communication. While the teleportation process itself is not a unitary operation (due to the measurement step), the corrections applied at the receiving end to recover the original state are represented by unitary matrices. These unitary corrections are crucial for completing the teleportation protocol.
26. What is the role of unitary matrices in quantum key distribution protocols?
In quantum key distribution protocols like
27. How do unitary matrices preserve probability in quantum mechanics?
In quantum mechanics, the state of a system is represented by a vector in a complex Hilbert space. The squared magnitude of each component of this vector represents a probability. Unitary matrices, when applied to these state vectors, preserve the sum of these squared magnitudes. This ensures that the total probability remains 1, which is a fundamental requirement in quantum theory.
28. What is the relationship between unitary matrices and the Schur decomposition?
The Schur decomposition states that any square matrix A can be written as A = QTQ*, where Q is a unitary matrix and T is an upper triangular matrix. The unitary matrix Q represents a change of basis that transforms A into triangular form. This decomposition is useful in numerical linear algebra and for studying the properties of matrices.
29. How do unitary matrices relate to the concept of energy conservation in physics?
Unitary matrices are closely related to energy conservation in physics. In many physical systems, the total energy must be conserved during time evolution. When the system's evolution is described by a unitary matrix, it ensures that the norm of the state vector (which often represents the total probability or energy) remains constant. This property makes unitary matrices fundamental in describing many physical processes.
30. What is a special unitary matrix, and how does it differ from a general unitary matrix?
A special unitary matrix is a unitary matrix with a determinant equal to 1. While general unitary matrices have complex determinants with magnitude 1 (e^(iθ)), special unitary matrices are restricted to det(U) = 1. Special unitary matrices form a subgroup of unitary matrices and are important in physics, particularly in the description of certain symmetries in particle physics.
31. How are unitary matrices used in quantum computing?
In quantum computing, unitary matrices represent quantum gates, which are the basic building blocks of quantum circuits. Every operation in a quantum computer must be unitary to preserve the quantum nature of the information. Common quantum gates like the Hadamard gate, CNOT gate, and phase gates are all represented by unitary matrices.
32. What is the connection between unitary matrices and the Fourier transform?
The Discrete Fourier Transform (DFT) can be represented as a unitary matrix. When normalized properly, the DFT matrix F satisfies F* × F = I, making it unitary. This unitary property of the Fourier transform ensures that it preserves the total energy of a signal, which is crucial in many signal processing applications.
33. How do unitary matrices relate to the concept of reversibility in computations?
Unitary matrices represent reversible operations. Since a unitary matrix U has an inverse U*, any transformation represented by U can be undone by applying U*. This property is crucial in quantum computing, where all operations must be reversible to maintain quantum coherence. It's also relevant in the study of reversible classical computation.
34. What is the significance of the eigendecomposition of a unitary matrix?
The eigendecomposition of a unitary matrix U can be written as U = VDV*, where V is another unitary matrix and D is a diagonal matrix with complex entries of magnitude 1. This decomposition reveals that any unitary transformation can be understood as a combination of rotations in different planes of the vector space. It's particularly useful in understanding the action of unitary operators in quantum mechanics.
35. How do unitary matrices preserve the determinant in matrix multiplication?
When a unitary matrix U multiplies another matrix A, it preserves the magnitude of the determinant: |det(UA)| = |det(A)|. This is because |det(U)| = 1 for any unitary matrix. This property is useful in various applications, including in the study of volume-preserving transformations in physics and geometry.
36. What is the role of unitary matrices in principal component analysis (PCA)?
In PCA, the principal components are the eigenvectors of the covariance matrix. These eigenvectors form an orthonormal basis and can be arranged as columns of a unitary matrix. This unitary matrix represents the rotation of the original coordinate system to align with the directions of maximum variance in the data, allowing for dimensionality reduction while preserving important features of the dataset.
37. How are unitary matrices related to the concept of adjoint operators in linear algebra?
A unitary matrix U represents an operator whose adjoint (represented by U*) is equal to its inverse. In other words, U*U = UU* = I. This property makes unitary operators special cases of normal operators (operators that commute with their adjoints). The concept of adjoint operators is fundamental in functional analysis and quantum mechanics.
38. What is the significance of unitary matrices in the theory of Lie groups?
The set of all n×n unitary matrices forms a Lie group called the unitary group U(n). This group plays a crucial role in various areas of mathematics and physics. The special unitary group SU(n), consisting of unitary matrices with determinant 1, is particularly important in particle physics for describing symmetries of fundamental particles.
39. How do unitary matrices relate to the concept of unitarity in quantum field theory?
In quantum field theory, unitarity refers to the conservation of probability in particle interactions. The S-matrix, which describes these interactions, must be unitary to ensure that the total probability of all possible outcomes of a particle interaction equals 1. This requirement places important constraints on the possible interactions in quantum field theories.
40. What is the connection between unitary matrices and the Bloch sphere representation in quantum mechanics?
The Bloch sphere is a geometric representation of the state space of a qubit. Any single-qubit unitary operation can be visualized as a rotation of the Bloch sphere. The group of these rotations is isomorphic to SU(2), the group of 2×2 special unitary matrices. This connection provides an intuitive geometric understanding of single-qubit operations in quantum computing.
41. What is the role of unitary matrices in the Heisenberg picture of quantum mechanics?
In the Heisenberg picture, quantum states remain fixed while operators evolve over time. This evolution is described by a unitary transformation: A(t) = U*(t)A(0)U(t), where U(t) is a time-dependent unitary matrix. This unitary evolution ensures that the fundamental properties of the operators, such as their commutation relations, are preserved over time.
42. What is the significance of unitary matrices in random matrix theory?
In random matrix theory, ensembles of random unitary matrices (such as the Circular Unitary Ensemble) are studied for their statistical properties. These ensembles have applications in various fields, including nuclear physics, quantum chaos, and number theory. The eigenvalue statistics of random unitary matrices often exhibit universal behavior that appears in many seemingly unrelated physical systems.
43. How do unitary matrices relate to the concept of quantum entanglement?
While unitary matrices themselves do not create entanglement, certain unitary operations on multi-qubit systems can generate or modify entanglement between qubits. For example, the CNOT gate, represented by a 4×4 unitary matrix, can create entanglement between two qubits. Understanding which unitary operations can create or manipulate entanglement is crucial for quantum information processing.
44. What is the connection between unitary matrices and the no-cloning theorem in quantum mechanics?
The no-cloning theorem states that it's impossible to create an identical copy of an arbitrary unknown quantum state. This theorem can be proved using the properties of unitary matrices. If a cloning operation were possible, it would have to be represented by a unitary matrix, but one can show that no such unitary matrix can perform perfect cloning for all input states.
45. How are unitary matrices used in quantum state tomography?
Quantum state tomography is the process of reconstructing a quantum state from measurements. This often involves applying different unitary transformations to the state before measurement. These unitary operations, represented by unitary matrices, allow access to different aspects of the quantum state, enabling a complete reconstruction of the density matrix.
46. What is the role of unitary matrices in the theory of quantum walks?
Quantum walks are quantum analogues of classical random walks. The evolution of a quantum walk is described by a unitary matrix, unlike the stochastic matrix used for classical random walks. This unitary evolution leads to very different behavior, including faster spreading and interference effects, which are exploited in certain quantum algorithms.
47. What is the significance of unitary matrices in the theory of quantum circuits?
In the quantum circuit model of computation, every operation is represented by a unitary matrix. The entire computation can be viewed as a large unitary matrix formed by composing the matrices of individual gates. This unitary nature ensures that quantum computations are reversible and that quantum information is preserved throughout the computation process.
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