Linear Algebra- find an orthogonal matrix with eigenvalue=1 or -1

In summary, the task is to find an orthogonal matrix with an eigenvalue that is not equal to 1 or -1. The definition of an orthogonal matrix is provided, along with the fact that their inverse is equal to their transpose. The poster's attempt at a solution, involving a 1x1 matrix, is mentioned but ultimately deemed incorrect. The conversation ends with a suggestion to try a 2x2 matrix with nonreal eigenvalues, which is successfully found.
  • #1
RossH
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Homework Statement


I have to find an orthogonal matrix with an eigenvalue that does not equal 1 or -1. That's it. I'm completely stumped.

Homework Equations


An orthogonal matrix is defined as a matrix whose columns are an orthonormal basis, that is they are all orthogonal to each other and each vector has length 1. These matrices have the property that their inverse is the same as their transpose. I don't think their are any other equations.

The Attempt at a Solution


My professor claims that this is possible. So far I thought about a 1x1 matrix, as that is defined as each vector being orthogonal to each other, but the vector only has length 1 if the matrix is [1] or [-1]. And rectangular matrices don't have inverses. I'm stumped.
 
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  • #2
RossH said:

Homework Statement


I have to find an orthogonal matrix with an eigenvalue that does not equal 1 or -1. That's it. I'm completely stumped.

Homework Equations


An orthogonal matrix is defined as a matrix whose columns are an orthonormal basis, that is they are all orthogonal to each other and each vector has length 1. These matrices have the property that their inverse is the same as their transpose. I don't think their are any other equations.

The Attempt at a Solution


My professor claims that this is possible. So far I thought about a 1x1 matrix, as that is defined as each vector being orthogonal to each other, but the vector only has length 1 if the matrix is [1] or [-1]. And rectangular matrices don't have inverses. I'm stumped.
See if you can cook up a 2x2 matrix that is orthogonal and whose eigenvalues are neither 1 nor -1. Don't limit yourself to real eigenvalues.
 
  • #3
BTW, this really should be in the Calculus & Beyond section.
 
  • #4
Mark44 said:
See if you can cook up a 2x2 matrix that is orthogonal and whose eigenvalues are neither 1 nor -1. Don't limit yourself to real eigenvalues.

Thanks for the help. I found one:
1/sqrt2 -1/sqrt2
1/sqrt2 1/sqrt2

It's orthogonal and has nonreal eigenvalues. Sorry about putting this post in the wrong forum. I always thought of linear algebra as being a "lower" math than calculus.
 

FAQ: Linear Algebra- find an orthogonal matrix with eigenvalue=1 or -1

What is an orthogonal matrix?

An orthogonal matrix is a square matrix where all the columns and rows are orthogonal to each other. This means that the dot product of any two columns (or rows) is equal to 0, indicating that the columns (or rows) are perpendicular to each other.

How do you find the eigenvalues of a matrix?

The eigenvalues of a matrix can be found by solving the characteristic equation (|A-λI|=0), where A is the matrix and λ is the eigenvalue. The solutions to this equation are the eigenvalues of the matrix.

Why are eigenvalues important in linear algebra?

Eigenvalues are important in linear algebra because they provide information about the behavior and properties of a matrix. They can help determine if a matrix is invertible, diagonalizable, or has an inverse. They are also used in solving systems of linear equations and in applications such as data analysis and image processing.

How do you find an orthogonal matrix with a specific eigenvalue?

To find an orthogonal matrix with a specific eigenvalue (such as 1 or -1), you can use the Gram-Schmidt process to orthogonalize a set of basis vectors. This process involves finding the orthogonal complement of a vector and then normalizing it. Repeating this process will result in an orthogonal basis, and the matrix formed by these basis vectors will be an orthogonal matrix with the desired eigenvalue.

What is the significance of an orthogonal matrix with eigenvalue=1 or -1?

An orthogonal matrix with an eigenvalue of 1 or -1 is significant because it represents a rotation or reflection transformation in a vector space. These transformations are important in various applications, such as in 3D graphics and physics. Additionally, orthogonal matrices have many useful properties, such as preserving lengths and angles, making them valuable in practical calculations.

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