Finding the missing vector such that the matrix is orthonormal

In summary, a matrix is orthonormal if its vectors have a magnitude of 1 and are perpendicular, with a dot product of 0. To make the given matrix orthonormal, the missing vector must satisfy the equations \frac{1}{\sqrt{5}}x + \frac{2}{\sqrt{5}} = 0 and \sqrt{x^2 + y^2} = 1. By setting x = y, the solution \frac{1}{\sqrt{5}}x = -\frac{2}{\sqrt{5}} is obtained.
  • #1
g.lemaitre
267
2

Homework Statement


A matrix is orthonormal if the magnitude of its vectors = 1 and all vector pairs are perpendicular, that is, their dot product = 0. Find the missing vector which would make the following matrix orthonormal:
[tex]
\begin{bmatrix}
\frac{1}{\sqrt{5}} & x \\
\frac{2}{\sqrt{5}} & y \\
\end{bmatrix}[/tex]
Most textbooks use [tex] x_1 and x_2[/tex] but I find x and y easier

Homework Equations


The Attempt at a Solution


[tex]
\frac{1}{\sqrt{5}}x + \frac{2}{\sqrt{5}} = 0 ... space here ...
\sqrt{x^2 + y^2} = 1
[/tex]
I tried setting x = y and I got
[tex]
\frac{1}{\sqrt{5}}x = -\frac{2}{\sqrt{5}}[/tex]
But that's as far as I could with that problem.
 
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  • #2
I solved this problem.
 
  • #3
I've solved this problem.
 

What is the definition of an orthonormal matrix?

An orthonormal matrix is a square matrix in which all the rows and columns are orthogonal unit vectors, meaning they have a length of 1 and are perpendicular to each other. This matrix also has an inverse that is equal to its transpose.

Why is finding the missing vector important in creating an orthonormal matrix?

In order for a matrix to be orthonormal, all of its vectors must be orthogonal and have a length of 1. If one vector is missing or incorrect, the matrix will not be orthonormal and may not have the desired properties for certain mathematical operations.

What is the process for finding the missing vector in an orthonormal matrix?

The process for finding the missing vector involves using the properties of orthogonality and unit length to solve for the missing values. This can be done by setting up equations and solving for the unknown values, or by using geometric methods such as dot products and vector projections.

Are there any specific techniques or algorithms that can be used to find the missing vector in an orthonormal matrix?

Yes, there are several techniques and algorithms that can be used to find the missing vector in an orthonormal matrix. These include the Gram-Schmidt process, QR decomposition, and singular value decomposition (SVD). Each method has its own advantages and may be more suitable for certain types of matrices.

What are some real-world applications of orthonormal matrices and finding missing vectors?

Orthonormal matrices and finding missing vectors have many applications in fields such as computer graphics, signal processing, and quantum mechanics. They are used to rotate and transform objects, compress data, and analyze quantum states. They also play a crucial role in solving systems of equations and eigenvalue problems.

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