Proving Integer Eigenvalues of Matrix A

  • Thread starter hadizainud
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In summary, the author suggests that if you are having trouble solving an equation involving eigenvalues, try one of the methods of solving linear equations first. If that doesn't work, then try another method.
  • #1
hadizainud
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Homework Statement



Prove: If a, b, c, and d are integers such that a+b=c+d, then
A=
[a b]​
[c d]​
has integer eigenvalues, namely,[itex]λ_1{}[/itex]=a+b and [itex]λ_2{}[/itex]=a-c

Homework Equations



No relevant equation.

The Attempt at a Solution



No idea :(
 
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  • #2
Do you know how to compute the eigenvalues of a 2x2 matrix? Try that first before applying the additional information given in the problem.
 
  • #3
You don't really need to calculate the eigenvalues, you are only asked to show that a+b and a- c are eigenvalues- and to do that you use the definition of "eigenvalue".

That is, do there exist values, x and y, such that
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}x \\ y\end{bmatrix}= (a+b)\begin{bmatrix}u \\ v\end{bmatrix}[/tex]
or values u and y such that
[tex]\begin{bmatrix}a & b \\ c & d\end{bmatrix}\begin{bmatrix}u \\ v\end{bmatrix}= (a-b)\begin{bmatrix}u \\ v\end{bmatrix}[/tex]
?
 
  • #4
Welcome to PF, hadizainud! :smile:

The methods of fzero and HallsofIvy will bring you your answer.
Just for fun, here's yet another method.

The product of the eigenvalues is equal to the determinant.
The sum of the eigenvalues is equal to the trace.
In a quadratic equation the roots are uniquely identified by their product and their sum.
Use a+b=c+d to eliminate d in your equations.
 
  • #5
I like Serena said:
Welcome to PF, hadizainud! :smile:

The methods of fzero and HallsofIvy will bring you your answer.
Just for fun, here's yet another method.

The product of the eigenvalues is equal to the determinant.
The sum of the eigenvalues is equal to the trace.
In a quadratic equation the roots are uniquely identified by their product and their sum.
Use a+b=c+d to eliminate d in your equations.

Hmm, that's cute :smile:
 

FAQ: Proving Integer Eigenvalues of Matrix A

What is the process for proving integer eigenvalues of a matrix?

The process for proving integer eigenvalues of a matrix involves several steps. First, you must calculate the characteristic polynomial of the matrix. Then, you must factor the polynomial to find the roots, which will be the eigenvalues. Finally, you must verify that the eigenvalues are integers by plugging them back into the characteristic polynomial and ensuring that the result is equal to zero.

Why is it important to prove integer eigenvalues of a matrix?

Proving integer eigenvalues of a matrix is important because it allows us to understand the behavior and properties of the matrix. It also helps us to solve systems of linear equations and make predictions about the matrix's transformations.

What are some common techniques used to prove integer eigenvalues of a matrix?

Some common techniques used to prove integer eigenvalues of a matrix include the Cayley-Hamilton theorem, the rational root theorem, and the remainder theorem. These techniques involve manipulating and factoring the characteristic polynomial to find the eigenvalues.

Are there any cases where proving integer eigenvalues of a matrix is not possible?

Yes, there are cases where proving integer eigenvalues of a matrix is not possible. For example, if the matrix is not square or if its characteristic polynomial cannot be factored into integer roots, then it may not have integer eigenvalues. In these cases, other methods may be used to analyze the matrix.

What are some real-world applications of proving integer eigenvalues of a matrix?

Proving integer eigenvalues of a matrix has many practical applications. For example, it is used in engineering to analyze the stability of structures, in physics to study the behavior of quantum systems, and in computer science to design efficient algorithms for data processing. It is also essential in various fields of mathematics, such as linear algebra and differential equations.

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