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.
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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.
The square matrix is the matrix in which the number of rows = number of columns. So a matrix is said to be a square matrix when m = n.
E.g.
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.
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.
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 is a Unitary matrix then
1)
2)
3)
4)
Solution
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: is a
1)Nilpotent Matrix
2)Unitary Matrix
3)Symmetric Matrix
4)Skew-Symmetric Matrix
Solution
Let A =
Then
Multiplying both the matrices, we get:
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 -
- wherein
is complex conjugate transpose matrix of matrix and is identity matrix
(a)
(b)
(c)
Hence, the answer is option 4.
A unitary matrix is a special type of matrix. Unitary matrices play a fundamental role in quantum mechanics, signal processing, and data compression, ensuring accurate representation and efficient computation. Unitary matrix provides a relationship between linear algebra and real-world applications, making them versatile tools in various scientific and engineering disciplines.
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.
Yes, the unitary matrices can also be non-square matrices but have orthonormal columns and rows.
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.
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.
Yes, If A is a unitary matrix then its its conjugate transpose and inverse are also unitary matrices.
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