Complex Eigenvalues and Eigenvectors
A square matrix with real entries can have complex eigenvalues!
As usual, given a matrix A, we find eigenvalues λ and corresponding eigenvectors x.
Note: Every n×n matrix has exactly n complex eigenvalues (counting any multiplicities).
Steps
Given a real matrix A, find the eigenvalues/eigenvectors as follows:
- As usual, find det(A−λI) and set it equal to zero. Solve for λ. →If one of the eigenvalues is complex, you should see that its complex conjugate is also an eigenvalue.
- Take each eigenvalue one at a time and solve for its corresponding eigenvector(s): →Find x such that (A−λI)x=0
- After finding an eigenvector for a complex eigenvalue, you can easily find the eigenvector for the conjugate eigenvalue: →Simply take the complex conjugate of the eigenvector you've already found!
Example: Complex Eigenvalues and Eigenvectors
Suppose we are given a real 3×3 matrix and we are told two of its eigenvalues are λ1=4 and λ2=2−3i.
If their corresponding eigenvectors are x1=[11] and x2=[2+i5], find the missing eigenvalue and eigenvector pair.
Since λ2 is complex, its complex conjugate must also be an eigenvalue!
Therefore, λ3=λ2 ⟹ λ3=2+3i
Similarly, since we know the complex eigenvector associated with λ2, we simply take its conjugate to find the eigenvector for λ3:
x3=x2 ⟹ x3=[2−i5]
Example: Complex Eigenvalues and Eigenvectors
Find the eigenvalues and eigenvectors of A=[31−5−1].
Find the Eigenvalues
Solve the equation:
det(A−λI)3−λ1−5−1−λ(3−λ)(−1−λ)−(−5)(1)(λ2−2λ−3)+5λ2−2λ+2=====00000
We can solve for λ using the quadratic formula:
λ = 2(1)−(−2)±(−2)2−4(1)(2) = 22±−4 = 22±2i = 1±i
Then the eigenvalues are λ1=1+i and its conjugate, λ2=1−i.
Find the Eigenvectors
λ1=1+i
Substituting this eigenvalue into the matrix above (A−λI), our goal is to solve for x1:
[3−(1+i)1−5−1−(1+i)]x1=[00]
Solve by writing the augmented matrix of this system and row-reducing:
⟶⟶[2−i1−5−2−i00] R2↔R1[12−i−2−i−500] R2−(2−i)R1Note: (−2−i)(2−i)=−4−2i+2i+i2=−5[10−2−i000]
Including a parameter for the second variable (since there is no leading 1 in the second column), we get the equations:
{1x1+(−2−i)x2x2==0t⟹{x1x2==(2+i)tt⟹x1=t[2+i1]
So an eigenvector associated with λ1=1+i is: x1=[2+i1]
λ2=1−i
Since the second eigenvalue is the conjugate of the first, its eigenvector is simply the conjugate of the first eigenvector!
Therefore, negating all of the imaginary parts, we have: x2=[2−i1]
For practice, check your work by applying the definition of eigenvalues/eigenvectors: Ax=λx.