Is Lambda = 1 an Eigenvalue of the Given Matrix?

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Homework Help Overview

The discussion revolves around determining whether lambda = 1 is an eigenvalue of a given 3x3 matrix and finding the eigenvalues and corresponding eigenvectors. The matrix in question is composed of specific integer values.

Discussion Character

  • Exploratory, Conceptual clarification, Mathematical reasoning

Approaches and Questions Raised

  • Participants discuss the definition of eigenvalues and the conditions under which a value qualifies as an eigenvalue. There is an exploration of the matrix equation related to eigenvalues and attempts to derive the characteristic polynomial.

Discussion Status

Some participants have made progress in deriving the characteristic polynomial and are checking their work. There is acknowledgment that lambda = 1 is indeed an eigenvalue, but there are concerns regarding the accuracy of the derived polynomial.

Contextual Notes

Participants are navigating through the complexities of polynomial equations and eigenvalue definitions, with some expressing uncertainty about their calculations and the implications of their findings.

matt_crouch
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Homework Statement



Show that lambda = 1 is an eigenvalue of the matrix

2,-1, 6
3,-3, 27
1,-1, 7

and find the eigenvalues and the corresponding eigenvectors


Homework Equations





The Attempt at a Solution



I don't understand how to actually get eigenvalues and eigenvectors
could someone help me out please
=]
 
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Do you understand the definition of "eigenvalue"? "[itex]\alpha[/itex]" is an eigenvaue of matrix A if and only if there is some non-zero vector, v, such that [itex]Av= \alpha v[/itex].

In particular, "1" is an eigenvalue of this matrix if and only if
[tex]\begin{bmatrix}2 &-1 & 6 \\ 3 & -3 & 27 \\ 1 & -1 & 7\end{bmatrix}\begin{bmatrix} x \\ y \\ z\end{bmatrix}= 1\begin{bmatrix}x \\ y \\ z\end{bmatrix}[/tex]
for some not all of x, y, z zero.

Multiplying that left side gives
[tex]\begin{bmatrix}2x- y+ 6z \\3x- 3y+ 27z \\ x- y+ 7z\end{bmatrix}= \begin{bmatrix}x \\ y \\ z\end{bmatrix}[/tex]

Now, solve that using whatever method (row reduction, determinants, etc.) you choose. The most basic is to write that as the system of equations
2x- y+ 6z= x, 3x- 3y+ 27z= y, and x- y+ 7z= z. Those are the same as x- y+ 6z= 0, 3x- 2y+ 27z= 0, and x- y+ 6z= 0.

Notice that the first and second equations are the same- we really have only two equations, not 3 and so there is no unique answer. That had to happen. Obviously, v= 0 is a solution to [itex]Av= \alpha v[/itex] for any A and [itex]\alpha[/itex]. Saying there is a non-zero vector such that that is true means there is NO "unique" answer.

Getting back to our equations: if we multiply x- y+ 6z= 0 by 2 we get 2x- 2y+ 12z= 0 while the second equation above was 3x- 2y+ 27z= 0. Subtracting 2x- 2y+ 12z= 0 from that, x+ 15z= 0 so x= -15z. That's as far as we can go, we cannot solve for a specific 5value of x. But putting x= -15z into x- y+ 6z= 0 gives -15x- y+ 6z= 0 or y= -7z.

What does that mean? That means that any vector of the form v= <15z, -7z, z> satisfies Av= v, no matter what z is. Any such vector, for non-zero z, is an eigenvector corresponding to eigenvalue [itex]\lambda[/itex].

More generally, if [itex]Av= \lambda v[/itex], then [itex]Av- \lambda v= (A- \lamba I)v= 0[/itex]. The point of writing it that way is that equation always has the solution v= 0 and will have a non-zero answer only if v= 0 is not unique. If [itex]A- \lambda I[/itex] had an inverse matrix, then we could multiply on both sides by that inverse and get the unique answer [itex]v= (A- \lambda I)^{-1}0= 0[/itex]. That is, [itex]Av= \lambda v[/itex] has a non-zero solution if and only if [itex]A- \lambda I[/itex] is not invertible which is the same as saying it has determinant 0.

The "eigenvalue equation" or "characteristic equation" for matrix A is "[itex]det(A- \lambda I)= 0[/itex]". For your example, that is
[tex]\left|\begin{array}{ccc}2-\lambda & -1 & 6 \\ 3 & -3-\lambda & 27 \\ 1 & -1 & 7-\lambda \end{array}\right|= 0[/tex]
Working out that determinant on the left will give you a cubic polynomial equation (the "eigenvalue equation" or "characteristic equation" for an n by n matrix is typically an [itex]n^{th}[/itex] degree polynomial). Since you already know that [itex]\lambda= 1[/itex] is a solution, you can reduce it to a quadratic equation for the other two eigenvalues.
 
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ok i got to the cubic polynomial and just want to check that i have the right polynomial

im rubbish with latex so let x = lambda

x3+6x2+20x=0

i then simplified to get

-x(x2-6x-20)=0
 


matt_crouch said:
ok i got to the cubic polynomial and just want to check that i have the right polynomial

im rubbish with latex so let x = lambda

x3+6x2+20x=0

i then simplified to get

-x(x2-6x-20)=0
Unfortunately, there is one serious problem with that! Remember that you were asked to show that "1" is an eigenvalue? (It is.) But [itex]1^3+ 5(1)+ 10= 26[/itex], not 0.
 

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