Can Eigenvalues and Determinants Determine the Elements of a Square Matrix?

In summary, the conversation discusses the possibility of determining the real elements of a matrix with known eigenvalues and determinant. It is determined that knowing the eigenvalues alone does not provide enough information, but knowing the eigenvalues and eigenvectors can determine the matrix up to a similarity transformation. If the eigenvectors are distinct, the matrix can be determined exactly without any possibility of interchanging rows or columns. The conversation ends with a realization that the speaker already knew this information.
  • #1
Cygni
38
0
Hello,

Given that we have some matrix M with unknown real elements a, b, c, d and we know its eigenvalues [tex]\lambda_{1}[/tex] and [tex]\lambda_{1}[/tex] (no eigenvectors though) and the value of the determinant is it possible to find the elements and hence the matrix M using this informaiton?

Thanks
 
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  • #2
No, there are infinite matrices with the same eigenvalues, but different eigenvectors. For example

[tex]\left(\begin{array}{cc}1&2\\0&3\end{array}\right)\qquad\textrm{and}\qquad\left(\begin{array}{cc}3&4\\0&1\end{array}\right)[/tex]

have the same eigenvalues, but are...different!

By the way, the determinant is just the product of the eigenvalues, so it doesn't give further information.
 
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  • #3
I think that the below is basically correct...

Provided you have n eigenvalues for the nxn matrix, then if you know the eigenvalues then you know the matrix up to a similarity transformation.

If you also know the eigenvectors then that gives you the similarity transformation and thus you know the matrix up to permutation of rows. (provided the eigenvectors are distinct)
 
  • #4
Simon_Tyler said:
If you also know the eigenvectors then that gives you the similarity transformation and thus you know the matrix up to permutation of rows. (provided the eigenvectors are distinct)

Actually in this case you know the matrix exactly, without any possibility of interchanging rows or columns, because if you change the order of the eigenvalues you have to change the order of the eigenvectors as well, and the result is always the same matrix.
 
  • #5
@Petr

I knew (and have taught) that!
That should teach me not to post whilst watching tv.
 

FAQ: Can Eigenvalues and Determinants Determine the Elements of a Square Matrix?

What is a square matrix?

A square matrix is a type of matrix in which the number of rows is equal to the number of columns. This means that it has an equal number of elements in each row and column. It is denoted by the notation "n x n", where n is the number of rows (or columns).

How do you construct a square matrix?

To construct a square matrix, you first need to determine the size of the matrix, which is denoted by the number of rows (or columns). Then, you can input the elements of the matrix in a systematic way, filling up each row and column until the matrix is complete. Alternatively, you can use mathematical operations such as addition, subtraction, and multiplication to construct a square matrix.

What is the importance of constructing a square matrix?

Constructing a square matrix is important in various fields of mathematics, science, and engineering. It is particularly useful in linear algebra, where it is used to represent systems of linear equations and perform operations such as matrix multiplication and inversion. Square matrices also have applications in computer graphics, physics, and statistics.

Can a square matrix have non-numeric elements?

Yes, a square matrix can have non-numeric elements, such as variables, symbols, or words. In fact, matrices are not limited to numbers and can be used to represent any type of data or information. In some cases, non-numeric elements in a square matrix can be useful in solving equations or performing transformations.

What is the difference between a square matrix and a non-square matrix?

The main difference between a square matrix and a non-square matrix is their size. A square matrix has an equal number of rows and columns, while a non-square matrix can have a different number of rows and columns. Additionally, square matrices have certain properties and operations that are specific to their size, such as being invertible and having a determinant.

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