Understanding the Spectrum of a Linear Operator

In summary, the spectrum of a linear operator is the set of all possible eigenvalues of the operator. If 0 belongs to the spectrum, then the operator is not invertible. This can be illustrated with simple examples such as (Af)(x) = sin xf(x) or (Af)(x) = exf(x). However, a precise definition of the spectrum includes the point spectrum, which only contains eigenvalues. An operator is not injective if and only if 0 belongs to the spectrum.
  • #1
member 428835
Hi PF!

What is meant by the spectrum of a linear operator ##A##? I read somewhere that if ##0## belongs in the spectrum, then ##A## is not invertible. Can anyone finesse this for me?

I read the wikipedia page, but this was tough for me to understand. Perhaps illustrating with a simple example, say ##(Af)(x) = \sin x f(x)##, or ##(Af)(x) = e^x f(x)## or really anything that's easy to understand.
 
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  • #2
The spectrum of a linear operator ##A:V \to W## between ##\mathbb{F}##-vector spaces (in most cases ##\mathbb{F} \in \{\mathbb{R}, \mathbb{C}\})## is the set of all possible eigenvalues of ##A##. Put concretely

$$\operatorname{spec}(A) := \{\lambda \in \mathbb{F}\mid \exists x \in V \setminus \{0\}: Ax = \lambda x\}$$

Now,

##A## has eigenvalue ##0##
##\iff \exists x \neq 0: Ax = 0x = 0##
##\iff \ker A \neq 0##
##\iff A## is non-injective

thus an operator is not injective if and only if ##0## belongs to the spectrum.
 
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  • #3
Maybe this is of more help: https://www.physicsforums.com/insights/hilbert-spaces-relatives-part-ii/
However, a precise definition is a bit more than just saying: The spectrum are the eigenvalues. One has to distinguish the spectrum of an operator and its point spectrum which are the eigenvalues. E.g. (the closure of) the Dirac operator of the free electron has a spectrum ##(-\infty,-1] \cup [1,\infty)## but no eigenvalues.

A number is in the spectrum of an operator ##\lambda\in \sigma(T)## if the operator ##\lambda−T## is either not invertible or unbounded.

Your first example ##A(f(x))=\sin x f(x)## is bounded, but has no eigenvalues, so ##\lambda - A## must be invertible: ##(\lambda -A)^{-1} (f(x)) := \dfrac{f(x)}{\lambda - \sin x}##, and the spectrum is empty.

Your second example is unbounded, and so are ##\lambda -A## for all ##\lambda##. In this case all numbers are in the spectrum.

A non trivial example is the one I mentioned above, a simple one is ##A(f) = cf## with a spectrum ##\{\,c\,\}##.
 
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  • #4
Math_QED said:
Now,

##A## has eigenvalue ##0##
##\iff \exists x \neq 0: Ax = 0x = 0##
##\iff \ker A \neq 0##
##\iff A## is non-injective

thus an operator is not injective if and only if ##0## belongs to the spectrum.
So you're talking about an operator being injective, which is only a necessary condition for invertibility, right? I don't see how a matrix ##A## being injective implies anything about invertibility.

Also, does ##A## have ##0## as an eigenvalue? In the first example we have ##(\lambda - \sin x)f(x) = 0## and ##\lambda = 0 \implies -\sin x f(x) = 0 \implies f(x) = 0##, which seems wrong.
 
  • #5
joshmccraney said:
So you're talking about an operator being injective, which is only a necessary condition for invertibility, right? I don't see how a matrix ##A## being injective implies anything about invertibility.
I guess @Math_QED talked only about the point spectrum. This is a subset of the spectrum. All eigenvalues are in the spectrum, but not the other way around.
Also, does ##A## have ##0## as an eigenvalue? In the first example we have ##(\lambda - \sin x)f(x) = 0## and ##\lambda = 0 \implies -\sin x f(x) = 0 \implies f(x) = 0##, which seems wrong.
It is wrong. An eigenvalue zero requires an eigenvector unequal zero. The spectrum is empty in this case.
 
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  • #6
Thanks!
 

1. What is the spectrum of a linear operator?

The spectrum of a linear operator refers to 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 the operator cannot map back to its original input.

2. How is the spectrum of a linear operator related to its eigenvalues?

The eigenvalues of a linear operator are a subset of its spectrum. They are the values for which the operator can be inverted, and therefore they lie outside of the spectrum.

3. What are the three types of spectra for a linear operator?

The three types of spectra for a linear operator are the point spectrum, the continuous spectrum, and the residual spectrum. The point spectrum consists of isolated eigenvalues, the continuous spectrum consists of a continuous range of values, and the residual spectrum consists of all other values in the spectrum.

4. How is the spectrum of a linear operator related to the concept of boundedness?

A linear operator is bounded if and only if its spectrum is contained within a bounded region of the complex plane. This means that the operator does not have any values in its spectrum that are too large or too small, and it can be inverted for all values outside of the spectrum.

5. Can a linear operator have an empty spectrum?

Yes, it is possible for a linear operator to have an empty spectrum. This would mean that the operator is invertible for all complex numbers, and therefore it has no eigenvalues. However, this is a rare occurrence and most linear operators will have a non-empty spectrum.

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