What is the geometric multiplicity of \lambda=0 as an eigenvalue of A?

In summary, the geometric multiplicity of the eigenvalue \lambda=0 for the matrix A is 5, as shown by finding 4 free variables when row reducing the matrix. This means that there are 5 basis vectors for the eigenspace corresponding to \lambda=0.
  • #1
chuy52506
77
0

Homework Statement


[tex]\lambda[/tex]=0 is an eigenvalue of
A=
|1 1 1 1 1|
|1 1 1 1 1|
|1 1 1 1 1|
|1 1 1 1 1|
|1 1 1 1 1|

Homework Equations


Find the geometric multiplicity of [tex]\lambda[/tex]=0 as an eigenvalue of A


The Attempt at a Solution


I row reduced it then got the last four rows of all 0s but don't know where to go from there??
 
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  • #2
now i have x1=-x2-x3-x4-x5
does that mean it has geom mult of 5?
 
  • #3
Now you have 4 free variables, namely [itex]x_2, x_3, x_4, x_5 [/itex]. If that doesn't tell you right away, set [itex]x_2 = t_1 [/itex], [itex]x_3 = t_2 [/itex], etc. This gives you
[tex]
\begin{pmatrix}
x_1 \\
x_2 \\
x_3 \\
x_4 \\
x_5
\end{pmatrix}=
\begin{pmatrix}
-t_1 - t_2 - t_3 - t_4 \\
t_1 \\
t_2 \\
t_3 \\
t_4
\end{pmatrix}
[/tex]

Now separate out the different variables and see how many basis vectors this gives you.
 

What is geometric multiplicity?

Geometric multiplicity is a term used in linear algebra to describe the number of dimensions in the eigenspace of a matrix. It represents the number of linearly independent eigenvectors corresponding to a particular eigenvalue.

How is geometric multiplicity different from algebraic multiplicity?

Algebraic multiplicity is the number of times an eigenvalue appears as a root of the characteristic polynomial of a matrix, while geometric multiplicity is the number of linearly independent eigenvectors associated with that eigenvalue. In other words, the algebraic multiplicity counts the number of times an eigenvalue appears, while the geometric multiplicity counts the number of different directions in which the eigenvectors point.

How do you calculate the geometric multiplicity of an eigenvalue?

To calculate the geometric multiplicity of an eigenvalue, you need to find the null space of the matrix A - λI, where A is the original matrix and λ is the eigenvalue. The dimension of this null space is the geometric multiplicity of the eigenvalue.

Can the geometric multiplicity be greater than the algebraic multiplicity?

Yes, it is possible for the geometric multiplicity to be greater than the algebraic multiplicity. This happens when there are repeated eigenvalues, but each eigenvalue has a different set of eigenvectors associated with it. In this case, the geometric multiplicity will be the sum of the dimensions of each eigenspace.

Why is geometric multiplicity important?

Geometric multiplicity is important because it provides information about the linear independence of eigenvectors and the stability of a system. It also helps in understanding the behavior and properties of a matrix, such as invertibility and diagonalizability.

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