Action of a linear operator on vectors

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Homework Help Overview

The discussion revolves around a problem in linear algebra concerning the action of a linear operator on vectors in an N-dimensional vector space. The original poster presents a scenario where a set of vectors generated by applying a linear operator to a vector is linearly dependent, and they seek to demonstrate a property of the span of these vectors.

Discussion Character

  • Exploratory, Assumption checking

Approaches and Questions Raised

  • Participants explore the implications of linear dependence among the vectors generated by the operator. They discuss the conditions under which the operator applied to a vector in the span remains within that span, questioning the cases where certain coefficients may be zero.

Discussion Status

Participants have engaged in a detailed exploration of the problem, with some providing insights into handling different cases of linear dependence. There is an ongoing examination of the implications of the linear dependence and how it affects the application of the operator.

Contextual Notes

Some participants express uncertainty about the treatment of cases where the highest index of the operator applied is less than N, indicating a need for further clarification on the implications of linear dependence in those scenarios.

DrClaude
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Not really a homework problem, just doing some self-studying.

Homework Statement


Let ##| a \rangle## by any vector in an ##N##-dimensional vector space ##\mathcal{V}##, and ##\mathbf{A}## a linear operator on ##\mathcal{V}##. The vectors
$$
| a \rangle, \mathbf{A} | a \rangle, \mathbf{A}^2 | a \rangle, \ldots, \mathbf{A}^N | a \rangle
$$
are linearly dependent. Let ##\mathcal{M} \equiv \text{Span}\{ \mathbf{A}^k | a \rangle\}_{k=0}^N##. Show that ##\mathcal{M}## has the property that for any vector ##| x \rangle \in \mathcal{M}##, the vector ##\mathbf{A} | x \rangle## also belongs to ##\mathcal{M}##.

Homework Equations





The Attempt at a Solution


Since the above vectors span ##\mathcal{M} ##, I can always find ##\{c_k\}## such that I can write
$$
| x \rangle = \sum_{k=0}^N c_k \mathbf{A}^k | a \rangle
$$
Now, if ##c_N = 0##, and since ##\mathbf{A}## is a linear operator, I have
$$
\begin{array}{rl}
\mathbf{A} | x \rangle & = \mathbf{A} \sum_{k=0}^{N-1} c_k \mathbf{A}^k | a \rangle \\
& = \sum_{k=0}^{N-1} c_{k} \mathbf{A}^{k+1} | a \rangle
\end{array}
$$
which, by definition, is in ##\mathcal{M}##.

But what if ##c_N \neq 0##? I need to show that ##\mathbf{A}^{N+1} | a \rangle## is in ##\mathcal{M}##. I'm tempted to use the fact that the vectors are linearly dependent to state that I can write
$$
\mathbf{A}^{N} | a \rangle = \sum_{k=0}^{N-1} \alpha_k \mathbf{A}^k | a \rangle
$$
but nothing guarantees me that ##\mathbf{A}^{N} | a \rangle ## is not orthogonal to the other vectors, or does it?

Any help appreciated.
 
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DrClaude said:
But what if ##c_N \neq 0##? I need to show that ##\mathbf{A}^{N+1} | a \rangle## is in ##\mathcal{M}##. I'm tempted to use the fact that the vectors are linearly dependent to state that I can write
$$
\mathbf{A}^{N} | a \rangle = \sum_{k=0}^{N-1} \alpha_k \mathbf{A}^k | a \rangle
$$
but nothing guarantees me that ##\mathbf{A}^{N} | a \rangle ## is not orthogonal to the other vectors, or does it?

You can't really write this. Linear dependent means (by definition) that there are scalars ##\alpha_k## which are not all zero such that

[tex]\alpha_0 | a \rangle + \alpha_1 \mathbf{A}| a \rangle + ... + \alpha_N \mathbf{A}^N| a \rangle=\mathbf{0}[/tex]

Now, you have two situations. Either ##\alpha_N\neq 0##, and in that case, you can write something like you wrote in the quote. In the case that ##\alpha_n=0##, you need to do something differently. In this case, they key fact is that at least one of the ##\alpha_k## is nonzero.

You can handle both cases simultaniously by remarking that there exists an ##M\leq N## and ##\alpha_k## scalars such that

[tex]\mathbf{A}^M | a \rangle = \sum_{k=0}^{M-1} \alpha_k \mathbf{A}^k| a \rangle[/tex]
 
Last edited:
This isn't precalculus (although at my university, we studied it before calculus. :smile: ) I'm moving it to calculus & beyond.
 
Fredrik said:
This isn't precalculus (although at my university, we studied it before calculus. :smile: ) I'm moving it to calculus & beyond.

Sorry about that. I hesitated for a while as to which forum to post to.

micromass said:
You can't really write this. Linear dependent means (by definition) that there are scalars ##\alpha_k## which are not all zero such that

[tex]\alpha_0 | a \rangle + \alpha_1 \mathbf{A}| a \rangle + ... + \alpha_N \mathbf{A}^N| a \rangle=\mathbf{0}[/tex]

Now, you have two situations. Either ##\alpha_N\neq 0##, and in that case, you can write something like you wrote in the quote. In the case that ##\alpha_n=0##, you need to do something differently. In this case, they key fact is that at least one of the ##\alpha_k## is nonzero.


That sums up my problem quite well. If indeed ##\alpha_N=0##, then ##\mathbf{A}^N | a \rangle## is linearly independent of the other vectors, so what does that say about ##\mathbf{A}^{N+1} | a \rangle##?

micromass said:
You can handle both cases simultaniously by remarking that there exists an ##M\leq N## and ##\alpha_k## scalars such that

[tex]\mathbf{A}^M | a \rangle = \sum_{k=0}^{M-1} \alpha_k \mathbf{A}^k| a \rangle[/tex]
Again, I don't see how to treat the case where ##M < N##.
 
DrClaude said:
Again, I don't see how to treat the case where ##M < N##.

OK. Can you tell me how you would dela with the case ##M=N##? You don't have to write it out completely, a summary would suffice.
 
Assuming that
$$
\mathbf{A}^N |a \rangle = \sum_{k=0}^{N-1} \alpha_{k} \mathbf{A}^k |a \rangle
$$
we have
$$
\begin{align}
\mathbf{A}^{N+1} |a \rangle &= \mathbf{A} \sum_{k=0}^{N-1} \alpha_{k} \mathbf{A}^k |a \rangle \\
&= \sum_{k=0}^{N-1} \alpha_{k} \mathbf{A}^{k+1} |a \rangle \\
&= \sum_{k=1}^{N} \alpha_{k-1} \mathbf{A}^{k} |a \rangle
\end{align}
$$
which, by definition of ##\mathcal{M}## is in ##\mathcal{M}##, meaning that ##\mathbf{A} \left( \mathbf{A}^{N} |a \rangle \right) \in \mathcal{M}##, completing the "proof" that ##\mathbf{A} | x \rangle \in \mathcal{M}## for ##| x \rangle \in \mathcal{M}##.
 
Alright. So the basic idea was to multiply by ##\mathbf{A}##.

This doesn't work in the case ##M<N##. But maybe multiplying with something else works? Like ##\mathbf{A}^2## or ##\mathbf{A}^3##?
 
Aside: Since I have joined PF, I've mostly posted answers to questions posed by others. It feels very strange to be on the other side. It's been a long time since I've been a student...

Ok, I think I see the light. From the linear dependence of the vectors spanning ##\mathcal{M}##, we have that for some ##M \leq N##
$$
\mathbf{A}^M | a \rangle = \sum_{k=0}^{M-1} \alpha_k \mathbf{A}^k | a \rangle
$$
with at least one ##\alpha_k \neq 0##. Setting ##p = N-M+1##, we find
$$
\begin{align}
\mathbf{A}^p \mathbf{A}^M | a \rangle &= \mathbf{A}^p \sum_{k=0}^{M-1} \alpha_k \mathbf{A}^k | a \rangle \\
&= \sum_{k=0}^{M-1} \alpha_k \mathbf{A}^{p+k} | a \rangle \\
\mathbf{A}^{N+1} | a \rangle &= \sum_{k=p}^{N} \alpha_{k-p} \mathbf{A}^{k} | a \rangle
\end{align}
$$
from which we conclude that ##\mathbf{A}^{N+1} | a \rangle \in \mathcal{M}##.

Hope I got it right. Thanks micromass for the help.
 
That's it! Congratz!
 

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