Is There a Standard Order for Eigenvalues in a Matrix?

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  • #1
g.lemaitre
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Homework Statement


the order of eigenvalues is important, but when you calculate an eigenvalue polynomial i am still not aware of any rule that dictates which eigenvalue comes first and which does not. let me explain what i mean. take the matrix
[tex]
\begin{bmatrix}
3 & -2 \\
5 & -4
\end{bmatrix}
[/tex]
The eigenvalues are -2, and 1
I forget the technical name but when you construct a matrix composed of eigenvalues you can have either
[tex]
\begin{bmatrix}
-2 & 0 \\
0 & 1
\end{bmatrix}
[/tex]
or
[tex]
\begin{bmatrix}
1 & 0 \\
0 & -2
\end{bmatrix}
[/tex]
There's a big difference between those two matrices so which one is correct? Up until now it seems that the larger number always occupies the upper left corner but i haven't been paying much attention to it.
 
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  • #2
g.lemaitre said:

Homework Statement


the order of eigenvalues is important, but when you calculate an eigenvalue polynomial i am still not aware of any rule that dictates which eigenvalue comes first and which does not. let me explain what i mean. take the matrix
[tex]
\begin{bmatrix}
3 & -2 \\
5 & -4
\end{bmatrix}
[/tex]
The eigenvalues are -2, and 1
I forget the technical name but when you construct a matrix composed of eigenvalues you can have either
[tex]
\begin{bmatrix}
-2 & 0 \\
0 & 1
\end{bmatrix}
[/tex]
or
[tex]
\begin{bmatrix}
1 & 0 \\
0 & -2
\end{bmatrix}
[/tex]
There's a big difference between those two matrices so which one is correct? Up until now it seems that the larger number always occupies the upper left corner but i haven't been paying much attention to it.

There is no rule for ordering eigenvalues, and the order is not important. What IS important is to maintain the same order from the start to the finish of a problem, so if you start with the order -2, 1 you should keep it throughout until your calculations have finished. Of course, some algorithms will assume an eigenvalue order such as [itex] \lambda \leq \lambda_2 \leq \cdots \leq \lambda_n[/itex] in the real-eigenvalue case, or perhaps [itex] |\lambda_1| \leq |\lambda_2| \leq \cdots \leq |\lambda_n|[/itex] for the general case, but that will (or ought to be) specified in the user's manual.

RGV
 

FAQ: Is There a Standard Order for Eigenvalues in a Matrix?

What is the order of eigenvalues?

The order of eigenvalues refers to the arrangement or sequence of the eigenvalues of a given matrix. This can be either ascending or descending, depending on the context.

How is the order of eigenvalues determined?

The order of eigenvalues is determined by arranging the eigenvalues in ascending or descending order. This can be done by finding the roots of the characteristic polynomial of the matrix or by using a calculator or software.

Why is the order of eigenvalues important?

The order of eigenvalues is important because it affects the properties and behavior of the matrix. For example, the largest or smallest eigenvalue can determine the stability or instability of a system described by the matrix.

Can the order of eigenvalues change?

Yes, the order of eigenvalues can change depending on the operations performed on the matrix. For example, if a matrix is multiplied by a scalar, the eigenvalues will also be multiplied by that scalar, which can change the order.

How does the order of eigenvalues relate to the eigenvectors?

The order of eigenvalues corresponds to the order of the corresponding eigenvectors. For example, the first eigenvalue will have its corresponding eigenvector as the first column of the matrix of eigenvectors. This relationship is important in solving systems of equations using eigenvalues and eigenvectors.

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