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

Click For Summary
SUMMARY

The geometric multiplicity of the eigenvalue \(\lambda=0\) for the matrix \(A\) defined as a 5x5 matrix of ones is determined through row reduction. After performing row reduction, the last four rows yield all zeros, indicating that there is one leading variable and four free variables. This results in a geometric multiplicity of 4, as the number of free variables corresponds to the dimension of the eigenspace associated with \(\lambda=0\).

PREREQUISITES
  • Understanding of eigenvalues and eigenvectors
  • Familiarity with row reduction techniques in linear algebra
  • Knowledge of vector spaces and their dimensions
  • Basic proficiency in matrix operations
NEXT STEPS
  • Study the concept of eigenvalue multiplicity in linear algebra
  • Learn about the relationship between free variables and the dimension of eigenspaces
  • Explore row echelon form and reduced row echelon form in matrix theory
  • Investigate applications of eigenvalues in systems of differential equations
USEFUL FOR

Students of linear algebra, educators teaching matrix theory, and anyone interested in understanding eigenvalue properties and their implications in mathematical applications.

chuy52506
Messages
77
Reaction score
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??
 
Physics news on Phys.org
now i have x1=-x2-x3-x4-x5
does that mean it has geom mult of 5?
 
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}<br /> x_1 \\<br /> x_2 \\<br /> x_3 \\<br /> x_4 \\<br /> x_5<br /> \end{pmatrix}=<br /> \begin{pmatrix}<br /> -t_1 - t_2 - t_3 - t_4 \\<br /> t_1 \\<br /> t_2 \\<br /> t_3 \\<br /> t_4<br /> \end{pmatrix}[/tex]

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

Similar threads

  • · Replies 6 ·
Replies
6
Views
1K
Replies
2
Views
2K
  • · Replies 2 ·
Replies
2
Views
2K
  • · Replies 3 ·
Replies
3
Views
2K
  • · Replies 2 ·
Replies
2
Views
1K
Replies
5
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
Replies
3
Views
2K
  • · Replies 4 ·
Replies
4
Views
3K
  • · Replies 5 ·
Replies
5
Views
3K