Calculating Eigenvalues: 0 Root Meanings

In summary, a zero eigenvalue for a matrix means that one of the eigenvalues is zero, but it does not have any special meaning for the eigenvectors. The corresponding eigenvectors form the basis for the null space of the matrix, but they are not uniquely determined. Eigenvectors are never uniquely determined, unless the scalar field is GF(2).
  • #1
wakko101
68
0
This is just a general question:

If, when you are calculating the eigenvalues for a matrix, you get a root of 0 (eg. x^3 - x) --> x(x-1)(x+1), what does that mean for the eigenvectors?

thanks,
w.
 
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  • #2
Nothing. It just means that one of the eigenvalues is zero, it doesn't mean anything special about eigenvectors... When diagonalized the matrix of the operator looks like
[tex]
\left(
\begin{array}{ccc}
-1 & 0 & 0 \\
0 & 0 & 0 \\
0& 0 & 1
\end{array}
\right)\;.
[/tex]
In this basis, the eigenvector with eigenvalue -1 is (1,0,0) and the eigenvector with eigenvalue 0 is (0,1,0) and the eigenvector with eigenvalue 1 is (0,0,1).
 
  • #3
There is nothing wrong with an eigenvalue being zero, and it is not more special than an eigenvalue being -1, i or [itex]\pi[/itex].

Only an eigenvector cannot be zero. Which makes sense, because the zero vector trivially satisfies A 0 = [itex]\lambda[/itex] 0 for any number [itex]\lambda[/itex].
 
  • #4
A zero eigenvalue means the matrix in question is singular. The eigenvectors corresponding to the zero eigenvalues form the basis for the null space of the matrix.
 
  • #5
According to definition: Ax=cx,x is nonzero vector,then
we have Ax=0,
which means it has nonzero solutions,
also means A is signular,
also means the corresponding eigenvector is not uniquely determined.
 
  • #6
uiulic said:
also means the corresponding eigenvector is not uniquely determined.
Eigenvectors are never1 uniquely determined; at the very least, any nonzero scalar multiple of an eigenvector is an eigenvector.

1: Unless your scalar field is GF(2).
 
  • #7
And who, might I ask, is GF(2) ? :eek:
 
  • #8
Thank Hurkyl for pointing out my misunderstanding (I was thinking about sth else.)
 
  • #9
GF(2) is the finite field with two elements. It's isomorphic to the integers modulo 2.
 

Related to Calculating Eigenvalues: 0 Root Meanings

1. What are eigenvalues and why are they important in science?

Eigenvalues are a mathematical concept that represent the scaling factor of a vector in a linear transformation. They are important in science because they help us understand and analyze complex systems and phenomena, such as in quantum mechanics and fluid dynamics.

2. How do you calculate eigenvalues?

The process of calculating eigenvalues involves finding the roots of a characteristic polynomial, which is obtained by subtracting the identity matrix from the original matrix and taking its determinant. This can be done manually or with the help of specialized software or calculators.

3. What does it mean when an eigenvalue is equal to 0?

When an eigenvalue is equal to 0, it means that the corresponding eigenvector is unaffected by the linear transformation. This could indicate a special property of the system or a degenerate case where there is more than one solution.

4. How can eigenvalues be used in real-world applications?

Eigenvalues have numerous applications in fields such as physics, engineering, and computer science. They can help us understand the behavior of systems, optimize processes, and even solve differential equations.

5. Can eigenvalues have complex values?

Yes, eigenvalues can have complex values. In fact, complex eigenvalues and eigenvectors are often used in systems with oscillatory behavior, such as in electrical circuits or quantum systems.

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