Eigenvectors and eigenvalues

In summary: Oops sorry its meant to be ##exp(3a) + 5##Don't worry. So what are the eigenvalues? Don't worry. So what are the eigenvalues?In summary, the eigenvalues of the matrix B = exp(3A) + 5I are ##e^{3a} + 5## with the same eigenvectors as A.
  • #1
Physgeek64
247
11

Homework Statement


Find the eigenvalues and eigenvectors of the matrix
##A=\matrix{{2, 0, -1}\\{0, 2, -1}\\{-1, -1, 3} }##

What are the eigenvalues and eigenvectors of the matrix B = exp(3A) + 5I, where I is

the identity matrix?

Homework Equations

The Attempt at a Solution


So I've found the eigenvectors for A to be ##\frac{1}{\sqrt{6}}\vec{1,1,-2}##, ##\frac{1}{\sqrt{3}}\vec{1,1,1}##, ##\frac{1}{\sqrt{2}}\vec{-1,1,0}## with eigenvalues 4,1 one 2 respectively. but i don't know how to do the second part

Many thanks
 
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  • #2
Can you calculate the eigenvalues of ##exp(A)##?
 
  • #3
PeroK said:
Can you calculate the eigenvalues of ##exp(A)##?
They are the exponentials of the eigenvalues of A
 
  • #4
Physgeek64 said:
They are the exponentials of the eigenvalues of A

Well, that's a good start. What about ##exp(3A)##?
 
  • #5
PeroK said:
Well, that's a good start. What about ##exp(3A)##?
##e^{3\lambda}##?
 
  • #6
Physgeek64 said:
##e^{3\lambda}##?

How could you prove that if you are not sure? Hint: it's not hard. Try letting ##B = 3A##
 
  • #7
PeroK said:
How could you prove that if you are not sure? Hint: it's not hard. Try letting ##B = 3A##
the eigenvalues of ##exp(B)## are ##e^b## but ##b=3a## where a are the eigenvalues of A for ##B=3A##. Hence the eigenvalues are ##e^{3a}##
 
  • #8
Physgeek64 said:
the eigenvalues of ##exp(B)## are ##e^b## but ##b=3a## where a are the eigenvalues of A for ##B=3A##. Hence the eigenvalues are ##e^{3a}##

Yes. Although, I would start with something like:

Let ##v## be an eigenvector of ##A## with eigenvalue ##\lambda \dots##
 
  • #9
PeroK said:
Yes. Although, I would start with something like:

Let ##v## be an eigenvector of ##A## with eigenvalue ##\lambda \dots##
Okay. But how do you find the eigenvalues of ##exp(3A)+5I##?
 
  • #10
Physgeek64 said:
Okay. But how do you find the eigenvalues of ##exp(3A)+5I##?

I thought you had worked it out. Where do you think you are stuck?
 
  • #11
PeroK said:
Yes. Although, I would start with something like:

Let ##v## be an eigenvector of ##A## with eigenvalue ##\lambda \dots##

##\dots Bv = (\exp(3A) + 5I)v = \dots##

Does that help?
 
  • #12
Physgeek64 said:

Homework Statement


Find the eigenvalues and eigenvectors of the matrix
##A=\matrix{{2, 0, -1}\\{0, 2, -1}\\{-1, -1, 3} }##

What are the eigenvalues and eigenvectors of the matrix B = exp(3A) + 5I, where I is

the identity matrix?

Homework Equations

The Attempt at a Solution


So I've found the eigenvectors for A to be ##\frac{1}{\sqrt{6}}\vec{1,1,-2}##, ##\frac{1}{\sqrt{3}}\vec{1,1,1}##, ##\frac{1}{\sqrt{2}}\vec{-1,1,0}## with eigenvalues 4,1 one 2 respectively. but i don't know how to do the second part

Many thanks
For future reference: you can format a matrix nicely as
$$A = \pmatrix{2 & 0 & -1\\0 & 2 & -1 \\ -1 & -1 & 3}$$
The instructions that do that are "\pmatrix{2 & 0 & -1\\0 & 2 & -1 \\ -1 & -1 & 3}". Note the use of '&' as a separator, not a comma, and there is only one pair of curly brackets "{ }".

Also, your eigenvalues read as ##\langle \frac{1}{\sqrt{6}} 1 , 1, -2 \rangle##, but you might have meant ##\frac{1}{\sqrt{6}} \langle 1,1,-2 \rangle##, which is very different. Using ##\vec{\mbox{ }}## does not work well for an array of more than about two characters in length, so ##\vec{v_1}## looks OK but ##\vec{v_1, v_2, v_3,v_4}## does not.
 
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  • #13
PeroK said:
##\dots Bv = (\exp(3A) + 5I)v = \dots##

Does that help?
Will have eigenvalues ##e^{3a+5}## with the same eigenvectors

Thank you for your help
 
  • #14
Physgeek64 said:
Will have eigenvalues ##e^{3a+5}## with the same eigenvectors

Thank you for your help

Is that ##exp(3a+5)## or ##exp(3a) + 5##?
 
  • #15
PeroK said:
Is that ##exp(3a+5)## or ##exp(3a) + 5##?
Oops sorry its meant to be ##exp(3a) + 5##
 

What are eigenvectors and eigenvalues?

Eigenvectors and eigenvalues are concepts in linear algebra that are used to analyze the properties of a linear transformation. Eigenvectors are the vectors that do not change their direction when a linear transformation is applied to them, while eigenvalues are the corresponding scalar values that represent how much the eigenvector is scaled by the transformation.

Why are eigenvectors and eigenvalues important?

Eigenvectors and eigenvalues are important because they provide a way to understand how a linear transformation affects a vector space. They can be used to simplify complex calculations and solve systems of linear equations, and are also used in various applications such as data analysis and computer graphics.

How are eigenvectors and eigenvalues calculated?

To calculate eigenvectors and eigenvalues, the characteristic polynomial of the linear transformation must first be found. This polynomial is then solved to find the eigenvalues, which can then be used to find the corresponding eigenvectors. Alternatively, eigenvectors and eigenvalues can also be calculated using matrix operations such as finding the determinant and solving for the null space.

What is the significance of the relationship between eigenvectors and eigenvalues?

The relationship between eigenvectors and eigenvalues is significant because it allows us to understand how a linear transformation affects vectors in a vector space. The eigenvectors provide the directions in which the transformation acts, while the eigenvalues determine the scaling factor for each eigenvector. This relationship also has applications in various fields such as quantum mechanics and statistics.

Can a matrix have more than one eigenvector and eigenvalue?

Yes, a matrix can have multiple eigenvectors and eigenvalues. In fact, the number of eigenvectors and eigenvalues is equal to the dimension of the matrix. However, each eigenvector must have a unique eigenvalue, and a matrix can have repeated eigenvalues with different eigenvectors.

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