What is the spectrum of A in terms of S and its eigenvalues?

In summary: I think that analogy is correct. But also I think since the problem states that your sequence is in \ell_2 that the 'continuum' states don't count as part of the spectrum.Hmm... I don't think I understand exactly what you mean. Why can't an operator on \ell2 have a continuous spectrum? Maybe I'm just misunderstanding the concept of spectrum. Can you explain more?
  • #1
Ansatz7
29
0

Homework Statement


Let A be a linear transformation on the space of square summable sequences [itex]\ell[/itex]2 such that (A[itex]\ell[/itex])n = [itex]\ell[/itex]n+1 + [itex]\ell[/itex]n-1 - 2[itex]\ell[/itex]n. Find the spectrum of A.

2. The attempt at a solution
I see that A is self-adjoint, so its spectrum must be a subset of the real line. We also showed in class that it is bounded, and it's clearly the discrete analog of the second derivative, but I'm not sure how to use these facts. It seems to me that for any real λ one can construct a sequence [itex]\ell[/itex] such that (A - λ)[itex]\ell[/itex] = 0, since we then have the condition [itex]\ell[/itex]n+1 = -[itex]\ell[/itex]n-1 + (2 + λ)[itex]\ell[/itex]n, which can be used to recursively construct a sequence setting [itex]\ell[/itex]0 = a and [itex]\ell[/itex]1 = b for arbitrary a and b. I'm guessing that the problem with this is that such a sequence would only converge for certain values of λ, but I don't really know how I could show this. Any help would be greatly appreciated!
 
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  • #2
Try exploiting your hunch that it looks like a second derivative operator. Then what should eigensequences look like?
 
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  • #3
Dick said:
Try exploiting your hunch that it looks like a second derivative operator. Then what should eigensequences look like?

Oh, I think I understand! This finite difference approximation has error of order h^3, so if the terms in my series are e^(kn) expanded to order n^2 I should have an eigensequence. But it seems like this sequence isn't square summable except of course for k = 0, because otherwise it will diverge at one end... so the point spectrum is just 0, and the rest of the real line is in the continuous spectrum?
 
  • #4
Ansatz7 said:
Oh, I think I understand! This finite difference approximation has error of order h^3, so if the terms in my series are e^(kn) expanded to order n^2 I should have an eigensequence. But it seems like this sequence isn't square summable except of course for k = 0, because otherwise it will diverge at one end... so the point spectrum is just 0, and the rest of the real line is in the continuous spectrum?

I don't know, I haven't followed the whole argument out. I'm not really an expert, that was just supposed to be a hint. But I do think e^(kn) is an eigensequence if k<0 and it is square summable. What's the eigenvalue? You probably know more about this than I do.
 
  • #5
Dick said:
I don't know, I haven't followed the whole argument out. I'm not really an expert, that was just supposed to be a hint. But I do think e^(kn) is an eigensequence if k<0 and it is square summable. What's the eigenvalue? You probably know more about this than I do.

Oh, I don't think I mentioned that these are two-sided sequences, so e^(kn) for k<0 would diverge at -∞. I guess the problem is that I don't yet have a clear understanding of what a spectrum contains beyond eigenvalues. I seem to remember from class an example where an operator "seemed" to have an eigenvector, but the vector wasn't an element of the Hilbert space, so the value it corresponded to wasn't an eigenvalue, but was still an element of the spectrum. I believe the example given was the hydrogen atom potential, where the bound states are eigenvectors and the scattering states are part of the continuous spectrum since they aren't normalizable. It seems to me that this operator is similar, with the e^(kn)-like sequences acting like scattering states for all k (including k=0, I don't know what I was saying before). Can anyone clarify this?
 
  • #6
Ansatz7 said:
Oh, I don't think I mentioned that these are two-sided sequences, so e^(kn) for k<0 would diverge at -∞. I guess the problem is that I don't yet have a clear understanding of what a spectrum contains beyond eigenvalues. I seem to remember from class an example where an operator "seemed" to have an eigenvector, but the vector wasn't an element of the Hilbert space, so the value it corresponded to wasn't an eigenvalue, but was still an element of the spectrum. I believe the example given was the hydrogen atom potential, where the bound states are eigenvectors and the scattering states are part of the continuous spectrum since they aren't normalizable. It seems to me that this operator is similar, with the e^(kn)-like sequences acting like scattering states for all k (including k=0, I don't know what I was saying before). Can anyone clarify this?

I think that analogy is correct. But also I think since the problem states that your sequence is in [itex]\ell_2[/itex] that the 'continuum' states don't count as part of the spectrum.
 
  • #7
Hmm... I don't think I understand exactly what you mean. Why can't an operator on [itex]\ell[/itex]2 have a continuous spectrum? Maybe I'm just misunderstanding the concept of a continuous spectrum, but it seems to me that the sequences [itex]\ell[/itex]n = ekn (everything I said before about wanting to expand this into polynomials was rubbish) behave exactly like the scattering states of a potential. (A[itex]\ell[/itex])n = (ek + e-k - 2)[itex]\ell[/itex]n, but the sequence isn't square summable. Why does the fact that it is a sequence space rather than a function space change things?
 
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  • #8
You can write [itex]A=S+S^*-2I[/itex] with S the shift operator.

Now, do you know the spectral mapping theorem?? This states that for certain f

[tex]\sigma( f(L))=f(\sigma(L))[/tex]

Use this.
 
  • #9
Hmm... I don't know that theorem and I don't remember it being mentioned in class (we don't have any clear cut textbook or syllabus) but I might have missed it. I'll take a look once I get the chance.
 
  • #10
Okay, I've been trying to understand the spectral mapping theorem. So x is an operator, σ(x) is its spectrum, and f(x) is some function. Suppose σ(x) = [0, 1], and f(x) = x2 - 3I. Then the spectral mapping theorem says that the spectrum of the operator A = x2 - 3I is given by the image of f(y) = y2 - 3 on y[itex]\in[/itex][0, 1], which in this case would be [-3, -2]. Is this right?
 
  • #11
Ansatz7 said:
Okay, I've been trying to understand the spectral mapping theorem. So x is an operator, σ(x) is its spectrum, and f(x) is some function. Suppose σ(x) = [0, 1], and f(x) = x2 - 3I. Then the spectral mapping theorem says that the spectrum of the operator A = x2 - 3I is given by the image of f(y) = y2 - 3 on y[itex]\in[/itex][0, 1], which in this case would be [-3, -2]. Is this right?

I've been brushing up on the subject a little since I last realized I didn't know what I was talking about. And I think I know enough to confirm that that sounds right.
 
  • #12
Dick said:
I've been brushing up on the subject a little since I last realized I didn't know what I was talking about. And I think I know enough to confirm that that sounds right.

In that case, since A = S + S* - 2I, and we know that the spectrum of S is |λ| = 1, the spectrum of A should be given by ei[itex]\theta[/itex] + e-i[itex]\theta[/itex] - 2 = 2cos[itex]\theta[/itex] - 2, 0 ≤ [itex]\theta[/itex] < 2∏, which is [-4, 0]. Is this correct? This seems like it might be equivalent to constructing the sequences ekn, but restricting k to be imaginary... I'm not sure if makes sense to think of it that way though.
 
  • #13
Ansatz7 said:
In that case, since A = S + S* - 2I, and we know that the spectrum of S is |λ| = 1, the spectrum of A should be given by ei[itex]\theta[/itex] + e-i[itex]\theta[/itex] - 2 = 2cos[itex]\theta[/itex] - 2, 0 ≤ [itex]\theta[/itex] < 2∏, which is [-4, 0]. Is this correct? This seems like it might be equivalent to constructing the sequences ekn, but restricting k to be imaginary... I'm not sure if makes sense to think of it that way though.

Sure, A=f(S) where f(z)=z+1/z-2. So if you know the spectrum of S, then you know the spectrum of f(S). I think. I'm a little vague on some of this as well, so I hope micromass will check in.
 

1. What is the spectrum of a linear operator?

The spectrum of a linear operator is the set of all complex numbers for which the operator does not have an inverse. In other words, it is the set of all values that cannot be obtained by applying the operator to any vector.

2. How is the spectrum related to eigenvalues and eigenvectors?

The eigenvalues of a linear operator are elements of the spectrum, and the corresponding eigenvectors are elements of the corresponding eigenspace. This means that the spectrum contains information about the possible eigenvalues and eigenvectors of a linear operator.

3. What is the importance of the spectrum in understanding linear operators?

The spectrum provides information about the behavior and properties of a linear operator. It can help determine if the operator is invertible, diagonalizable, or has any special properties. The spectrum can also be used to analyze the stability and convergence of certain numerical methods for solving linear equations.

4. How is the spectrum of a linear operator affected by changes in the underlying vector space?

The spectrum of a linear operator can change if the underlying vector space is altered, such as by scaling or rotating the vectors. However, the spectrum is an intrinsic property of the operator itself and will remain unchanged as long as the operator itself is not modified.

5. Are there any applications of the spectrum of linear operators?

Yes, the spectrum has many applications in various fields of mathematics and physics. It is used in solving differential equations, analyzing quantum systems, and understanding the behavior of dynamical systems. The spectrum also has practical applications in engineering, such as in signal processing and control theory.

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