Therefore, p(A)X=p(c)X.This proves that p(c) is an eigenvalue of p(A).

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In summary: It's good to see that evilpostingmong is learning very quickly.Keep it up evilpostingmong! You are definitely on the right track.
  • #1
evilpostingmong
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Another proof...

Homework Statement



Suppose c is an eigenvalue of a square matrix A with eigenvector X=/=0.
Show that p(c) is an eigenvalue of p(A) for any nonzero polynomial p(x).

Homework Equations





The Attempt at a Solution


Knowing that c is an eigenvalue of A, it is true that AX=cX.

p(A)X=a0(X)+a1AX+...+anA^nX
And p(c)X=a0(X)+a1cX+...+anc^nX.
Since AX=cX, A^kX=c^kX.
So if AX-c^kX=0, A^kX-c^kX=0.
Now to prove p(A)X-p(c)X=0,
(AX-cX)a1+...+(A^nX-c^nX)an=(0)*a1+...+(0)*an=0
 
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  • #2


Can't you just take
p(A)X=a0(X)+a1AX+...+anA^nX
and recursively replace Ax by cx (and pull all the c's to the front) to get
p(A)X=a0 X + a1 c X + ... + an c^n X = p(c) X?
 
  • #3


CompuChip said:
Can't you just take
p(A)X=a0(X)+a1AX+...+anA^nX
and recursively replace Ax by cx (and pull all the c's to the front) to get
p(A)X=a0 X + a1 c X + ... + an c^n X = p(c) X?

Yeah, I killed a mouse with an A-bomb, instead of a knife, so to speak.:biggrin:
 
  • #4


That works. You might think about writing it like p(A)X=a0*(X)+a1*(AX)+...+an*(A^nX)=a0(X)+a1*c*X+...an*c^n*X=(a0+a1*c+...+an*c^n)X=p(c)X, showing p(A)X=p(c)X directly rather than showing p(A)X-p(c)X=0. But that's a just a question of taste. Your proof is fine. But the last line should be, "Since p(A)X=p(c)X we see X is a eigenvector of p(A) with eigenvalue p(c)." Since that's what they actually want you to prove.
 
  • #5


Alright, got to finish up that way.
 
  • #6


Right. It always helps to explicitly say why all of the messing around you just did proves what they want you to prove. Soon you will be writing EXCELLENT proofs.
 
  • #7


Dick said:
Right. It always helps to explicitly say why all of the messing around you just did proves what they want you to prove. Soon you will be writing EXCELLENT proofs.
Thank you Dick, I really think that looking at someone's answer won't help nearly
as much as taking an active role, and yeah, God forbid I write a textbook like that.
Gotta get my point across besides using some algorithmic approach.
I hate books that go like this
PROOF:
[tex]\sum[/tex][tex]\sum[/tex]f(x)[tex]\otimes\ominus[/tex][tex]\subset[/tex]A
clearly A[tex]\subseteq[/tex]G thus A=G which is clear. But f(x)=/=[tex]\Gamma[/tex]
[tex]\Delta[/tex] thus f(x)=[tex]\Psi[/tex] as given. Then I forget what the author was
proving in the first place.
 
  • #8


evilpostingmong said:
Thank you Dick, I really think that looking at someone's answer won't help nearly
as much as taking an active role, and yeah, God forbid I write a textbook like that.
Gotta get my point across besides using some algorithmic approach.
I hate books that go like this
PROOF:
[tex]\sum[/tex][tex]\sum[/tex]f(x)[tex]\otimes\ominus[/tex][tex]\subset[/tex]A
clearly A[tex]\subseteq[/tex]G thus A=G which is clear. But f(x)=/=[tex]\Gamma[/tex]
[tex]\Delta[/tex] thus f(x)=[tex]\Psi[/tex] as given. Then I forget what the author was
proving in the first place.

That is easily the best parody proof I've ever read. Good work.

Since you've got the answer to the thread, here's a tangent question that should be easy, but sometimes gets skipped over without consideration: In the OP question, what is p(A) if p(x) = 2?
 
  • #9


Office_Shredder said:
That is easily the best parody proof I've ever read. Good work.

Since you've got the answer to the thread, here's a tangent question that should be easy, but sometimes gets skipped over without consideration: In the OP question, what is p(A) if p(x) = 2?

2 is the a0 here, since the proof says that p(A)X=a0X+a1AX+...+anA^nX,
p(A)=2I
 
  • #10


Sure. If p(x)=2, P(A)=2I. Since A^0=I. I'm not exactly sure why Office_Shredder asked that. You are getting a lot better at this, evilpostingmong.
 
  • #11


Dick said:
Sure. If p(x)=2, P(A)=2I. Since A^0=I. I'm not exactly sure why Office_Shredder asked that. You are getting a lot better at this, evilpostingmong.

Thank you! I want to get better at proofs, I think they're fun. I'm not sure why he asked
it either, to be honest.
 
  • #12


They are fun. That's why we do them.
 
  • #13


Dick said:
Sure. If p(x)=2, P(A)=2I. Since A^0=I. I'm not exactly sure why Office_Shredder asked that.
It was a bit trivial. Maybe the point was to stress that p(x) is an "ordinary" polynomial in the sense that you plug in a number and get a number, as you are used to (apart from some subtleties, of course :smile:); but when you apply it to a matrix like p(A) you always get a matrix. Even when p(x) is a constant function -- i.e., proportional to the identity number 1 -- p(A) gives a matrix -- i.e., proportional to the identity matrix I.

Dick said:
You are getting a lot better at this, evilpostingmong.
Definitely. As I said in an earlier thread: doing a lot of proofs and asking others to be very critical is the best way to quickly make improvements.
 

Related to Therefore, p(A)X=p(c)X.This proves that p(c) is an eigenvalue of p(A).

1. What is the significance of p(A)X = p(c)X in relation to p(c) being an eigenvalue of p(A)?

This equation shows that the vector X is an eigenvector of matrix A with eigenvalue c. In other words, when matrix A is multiplied by the vector X, the result is a scalar multiple (c) of the vector X. This is a key property of eigenvalues and eigenvectors.

2. How can this equation be used to find the eigenvalues of a matrix?

If we know the matrix A and the vector X, we can solve for the scalar c by dividing both sides of the equation by X. This will give us the eigenvalue c. We can repeat this process for different values of X to find all the eigenvalues of the matrix A.

3. Can p(c) be any value for this equation to hold true?

No, p(c) must be equal to the eigenvalue of matrix A for the equation to hold true. This is because p(c) represents the characteristic polynomial of matrix A, which is used to find the eigenvalues of a matrix.

4. Is there a relationship between the eigenvalues and eigenvectors of a matrix?

Yes, each eigenvalue of a matrix has a corresponding eigenvector. The eigenvector is a direction in which the matrix only stretches or compresses, while the eigenvalue represents the amount of stretching or compression in that direction.

5. How are eigenvalues and eigenvectors used in practical applications?

Eigenvalues and eigenvectors have many applications in fields such as physics, engineering, and computer science. They are used for solving systems of differential equations, optimizing algorithms, and analyzing data in dimensional reduction techniques. They also play a crucial role in the diagonalization of matrices, which simplifies many mathematical operations.

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