Calculating eigenvalues of one matrix

In summary, the conversation discusses the difficulty of finding eigenvalues for a 4*4 matrix using programs like MATLAB and Mathematica. However, Mathematica is able to provide a solution for the matrix, but it involves a quartic equation and the use of ToRadicals. The conversation then explores the idea of expanding the eigenvalues for small values of x, y, and z. The formula "Series[..., {x,0,2},{y,0,2}, {z,0,2}]" is suggested as a potential solution.
  • #1
quin
50
0
hi friends

i want to find eigenvalues of a 4*4 matrix but niether MATLAB nor MATHEMATICA can't solve it. Both of programs said that eiganvalues of matrix is too complicated and have infinite sentences.
now what can i do?is there anyway that simplify the steps for MATLAB or mathematica?

thanks for your help

the matrix is here:
 

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  • #2
Mathematica gives four eigenvalues in a few seconds for

a = {{0, 1 + E^(-I*x) + E^(-I*z) + E^(-I*(x + z)), 1 + E^(-I*x) + E^(-I*y) + E^(-I*(x + y)), 1 + E^(-I*y) + E^(-I*z) + E^(-I*(y + z))},
{1 + E^(I*x) + E^(I*z) + E^(I*(x + z)), 0, 1 + E^(-I*y) + E^(I*z) + E^(-I*(y - z)), 1 + E^(I*x) + E^(-I*y) + E^(I*(x - y))},
{1 + E^(I*x) + E^(I*y) + E^(I*(x + y)), 1 + E^(I*y) + E^(-I*z) + E^(I*(y - z)), 0, 1 + E^(I*x) + E^(-I*z) + E^(I*(x - z))},
{1 + E^(I*y) + E^(I*z) + E^(I*(y + z)), 1 + E^(-I*x) + E^(I*y) + E^(-I*(x - y)), 1 + E^(-I*x) + E^(I*z) +E^(-I*(x - z)), 0}};
Eigenvalues[a]

Each of those is a root of a quartic equation. Using ToRadicals on each of those will give you the explicit solution
 
  • #3
Bill Simpson said:
Mathematica gives four eigenvalues in a few seconds for

a = {{0, 1 + E^(-I*x) + E^(-I*z) + E^(-I*(x + z)), 1 + E^(-I*x) + E^(-I*y) + E^(-I*(x + y)), 1 + E^(-I*y) + E^(-I*z) + E^(-I*(y + z))},
{1 + E^(I*x) + E^(I*z) + E^(I*(x + z)), 0, 1 + E^(-I*y) + E^(I*z) + E^(-I*(y - z)), 1 + E^(I*x) + E^(-I*y) + E^(I*(x - y))},
{1 + E^(I*x) + E^(I*y) + E^(I*(x + y)), 1 + E^(I*y) + E^(-I*z) + E^(I*(y - z)), 0, 1 + E^(I*x) + E^(-I*z) + E^(I*(x - z))},
{1 + E^(I*y) + E^(I*z) + E^(I*(y + z)), 1 + E^(-I*x) + E^(I*y) + E^(-I*(x - y)), 1 + E^(-I*x) + E^(I*z) +E^(-I*(x - z)), 0}};
Eigenvalues[a]

Each of those is a root of a quartic equation. Using ToRadicals on each of those will give you the explicit solution

thank you so much dear it worked

But I have another question too
I found 4 eigenvalues and they are 4 sentences in terms of x,y,z

now I want to expand all of them (4 of them) for "small x and small y and small z"

can you give me the the suitable formula for mathematica for small argument expansion?

thank you
 
Last edited:
  • #4
If you had an "ordinary" expression then

Limit[Limit[Limit[p, x -> 0], y -> 0], z -> 0]

would give you the limit as your three variables go to zero, but Mathematica ToRules and Limit doesn't seem happy that everything you have is in terms of of complex exponentials.

Perhaps this will help you

Eigenvalues[a] //. {x -> 10^-9, y -> 10^-9, z -> 10^-9}

returns

{-2 - E^(-I/1000000000) - E^(I/1000000000),
-2 - E^(-I/1000000000) - E^(I/1000000000),
-2 - E^(-I/1000000000) - E^(I/1000000000),
3*(2 + E^(-I/1000000000) + E^(I/1000000000))}

BUT that is only approaching zero from one special direction and that direction is going to result in a lot of cancellations in your eigenvalues.

Perhaps you need to think carefully about exactly what you are trying to accomplish. That might give you an idea of what direction you want to approach this from. No pun intended.
 
Last edited:
  • #5
Thanks for your answer
and also now I found the formula "series" that expands the expression in terms of small x and small y and small z :
Series[..., {x,0,2},{y,0,2}, {z,0,2}]
 

1. What are eigenvalues and why do we need to calculate them?

Eigenvalues are a set of numbers that represent the scaling factor of eigenvectors in a matrix. They are important because they can be used to understand the behavior of a system, such as stability and convergence, and to solve systems of linear equations.

2. How do you calculate eigenvalues of a matrix?

The most common method is to use the characteristic polynomial of the matrix, which is a polynomial equation that involves the eigenvalues. By solving this equation, we can find the eigenvalues of the matrix. Another method is to use the power iteration algorithm, which involves repeatedly multiplying the matrix by a vector until it converges to an eigenvector.

3. Can all matrices have eigenvalues?

No, not all matrices have eigenvalues. A matrix must be square (same number of rows and columns) in order to have eigenvalues. Additionally, the matrix must have linearly independent eigenvectors in order for the eigenvalues to be unique.

4. How do eigenvalues relate to diagonalization?

Diagonalization is the process of finding a diagonal matrix that is similar to the original matrix. Eigenvalues and eigenvectors play a crucial role in diagonalization, as the diagonal matrix will have the eigenvalues along the diagonal and the corresponding eigenvectors as its columns.

5. What is the significance of the size of the eigenvalues?

The size of the eigenvalues can tell us important information about the matrix. For example, if all the eigenvalues are positive, the matrix is called positive definite and has important properties in optimization problems. If all the eigenvalues are zero, the matrix is called nilpotent and has different properties in linear algebra.

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