Proving Linear Independence of (v,Tv,...,T^{m-1}v): A Solution

In summary, the conversation discusses how to prove that a set of vectors is linearly independent, given that they are nonzero and T is a linear transformation with T^mv = 0. It is suggested to use the fact that T(0) = 0, but this is not necessary for the proof. The conversation also mentions that some students may not be familiar with basic facts about linear maps.
  • #1
Treadstone 71
275
0
Here's a simple question that I can't seem to get:

"Suppose for some v [tex]T^{m-1}v\neq 0[/tex] and [tex]T^mv=0[/tex]. Prove that [tex](v,Tv,...,T^{m-1}v)[/tex] is linearly independent."

I know that [tex]m\leq \dim V[/tex] and [tex]v,Tv,...,T^{m-1}v[/tex] are all nonzero.
 
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  • #2
What happens if [tex]0 = a_1 v + a_2Tv+ ... + a_mT^{m-1}v[/tex]? You want to show that all a_i are 0 and you have two bits of information:
(1) T is linear
(2) [tex]T^mv=0[/tex]
How can you use this to get information about a_1?
Also, do you know what T(0) is?
 
  • #3
I was just about to post that I got it. T(0) is not used it my proof. Thanks anyway.
 
  • #4
Treadstone 71 said:
I was just about to post that I got it. T(0) is not used it my proof. Thanks anyway.
If, as I assume, T is a linear transformation then T(0)= 0 and there would be no reason to use it!
 
  • #5
Well, there is a proof that depends on T(0) (with T a square matrix). If you left-multiply by T enough times you will get a1T^(m-1)v = 0 showing that a1 = 0. Then from that, if you left-multiply one fewer time you can get a2 = 0, and so on.
 
  • #6
How does that utilize T(0), which is 0 since T is a linear map? And T is necessariyl square if we are forced to pick a basis (which we should never do unless we have to; it is a crutch to understanding) since T is in End(V) (as is contextually clear; we cannot apply T to Tv otherwise).
 
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  • #7
Well, every time you multiply you have to say on the left T(0) = 0 = (rest of expression).
 
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  • #8
Ah, I see what you're saying. But since T is a linear map I wouldn't have even mentioned this explicitly, which is probably what is puzzling me (and HallsOf Ivy): why (did Euclid) even mention this?
 
  • #9
I only mentioned it because I wasn't sure if it was a well-known fact to Treadstone. The proof I was thinking of would have involved applying T repeatedly to both sides of that equation above. If you weren't aware that T(0)=0, then you might not have noticed this proof.
 
  • #10
Hopefully it is a well known fact to everyone (who knows what a linear map is), since it is part of the defining charactistic of being linear. Of course I've always been too idealistic about things like that.
 
  • #11
You'd be surprised. I was a TA for linear algebra, and I was shocked by how many students (at the end of the term) still didn't know basic facts about linear maps.
 
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1. What is the definition of linear independence?

Linear independence is a property of a set of vectors in a vector space, where no vector in the set can be written as a linear combination of the other vectors in the set. In other words, the vectors must be "independent" of each other and cannot be expressed as a multiple of another vector.

2. How do you prove linear independence?

To prove linear independence, you must show that the only solution to the equation c1v1 + c2v2 + ... + cnvn = 0 is when all the coefficients (c1, c2, ..., cn) are equal to 0. This can be done by setting up a system of equations and solving for the coefficients, or by using other methods such as determinants or rank.

3. What is the significance of proving linear independence?

Proving linear independence is important in linear algebra and other areas of mathematics as it allows us to understand the relationships between vectors in a vector space. It also allows us to determine the dimension of a vector space, which is a fundamental concept in linear algebra.

4. What is the purpose of proving linear independence of (v,Tv,...,T^{m-1}v): A Solution?

In this specific case, proving the linear independence of (v,Tv,...,T^{m-1}v) allows us to understand the linear independence of the vectors in a sequence generated by the linear transformation T. This can have applications in areas such as differential equations, where linear independence is crucial in finding solutions.

5. Are there any other methods for proving linear independence?

Yes, there are multiple methods for proving linear independence, such as using the Gram-Schmidt process, checking for linear dependence using the span of the vectors, or using the concept of linear span and basis. It is important to choose the most appropriate method depending on the given situation and the properties of the vectors.

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