What is the Role of Eigenfunctions in Understanding Quantum Mechanics?

In summary, the conversation discusses the concept of the Dirac delta "function" as a distribution rather than a function, and the difficulty of using it as an example in teaching about eigenfunctions and eigenvalues. It also touches on the use of rigged Hilbert spaces and Fourier transforms to deal with the non-normalizability of functions like ##e^{ikx}##, which represent generalized eigenstates of momentum. There is a difference of opinion on whether it is important to emphasize this distinction in pedagogy.
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<Moderator's note: this thread was split off from https://www.physicsforums.com/threads/eigenstates-eigenvalues.904774/>

vanhees71 said:
The Dirac ##\delta## "function" is not a function but a distribution (in the sense of "generalized function"). It should be forbidden to all textbook writers to call it a function!

A pure state is described by a square integrable function, and neither the ##\delta## distribution nor the plane-wave ##\exp(\mathrm{i} \vec{k} \cdot \vec{x})## are square integrable. So these "generalized eigenfunctions" of position or momentum, respectively, do not represent pure states of a particle.

Well, the unfortunate thing, pedagogically, is that in teaching about eigenfunctions and eigenvalues, the most obvious operators to use for examples are the position operator and the momentum operator. But those operators don't correspond to normalizable eigenfunctions. So you're left without any examples to motivate the idea of an eigenvalue and eigenfunction.

I suppose you can use matrices to motivate the ideas. But for wave functions, it's hard to see what's a simple example that doesn't have some problem or other. Maybe the harmonic oscillator wave function being an eigenfunction of energy?
 
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  • #2
There are actually a few ways to get around the difficulty of not normalizing like ## e^{ikx} ## function. One way is to consider a particle in a finite region of space (particle in a box) and to tend to infinity the width of the box. The other way is to not be considered a pure quantum state, but to consider it, more realistically with a wave packet. The difficulty comes from the fact that for a function like ##e^{ikx}## the particle is not confined to region of space, so that the probability of finding it everywhere is zero.
 
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  • #3
Karolus said:
I don't understand: in this case if you measured and obtained a defined momentum (eigenvalue momentum), don't you lose any information about the position? So the equation of the Dirac delta seems contradictory with the equation of eigenvalue of the momentum: In this way it seems that position and momentum are defined simultaneously, violating HUP (?)

The answer lies in Rigged Hilbert Spaces which barely is at the I level - an advanced undergraduate could understand it. See attached document.

Thanks
Bill
 

Attachments

  • Quantum Mechanics In Rigged Hilbert Space Language.pdf
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  • #4
Karolus said:
There are actually a few ways to get around the difficulty of not normalizing like ## e^{ikx} ## function.

The usual way is distribution theory and Rigged Hilbert Spaces.

Thanks
Bill
 
  • #5
Karolus said:
The difficulty comes from the fact that for a function like ##e^{ikx}## the particle is not confined to region of space, so that the probability of finding it everywhere is zero.

The probability of finding it everywhere is one - quirky distribution theory stuff. You must be careful about taking limits. Your box tending to infinity is analogous.

Thanks
Bill
 
  • #6
Again: The function ##u_k(x)=\exp(\mathrm{i} k x)## does not represent a quantum state! It's not square integrable! It is a generalized eigenstate of momentum and belongs not to the Hilbert space ##\mathrm{L}^2(\mathbb{R},\mathbb{C})## but to the dual of the domain of the self-adjoint operators for position and momentum. It's very important to emphasize this in order not to be confused as a beginner in learning QT!

The Fourier transform of the generalized position eigenstate is
$$F(k)=\int_{\mathbb{R}} \mathrm{d} x \delta(x-x_0) \exp(-\mathrm{i} k x) \delta(x-x_0)=\exp(-\mathrm{i} k x_0).$$
I used the usual convention for the Fourier transform as in high-energy physics concerning the sign and the factors of ##2 \pi##, i.e., with a minus sign in the exponential for the integral over position to get the wave function in momentum representation and no factors of ##2 \pi## in this integral:
$$\tilde{\psi}(k)=\int_{\mathbb{R}} \mathrm{d} x \psi(x) \exp(-\mathrm{i} k x).$$
Then the inverse transformation then reads
$$\psi(x)=\int_{\mathbb{R}} \frac{\mathrm{d} k}{2 \pi} \tilde{\psi}(k) \exp(+\mathrm{i} k x).$$
 
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  • #7
vanhees71 said:
Again: The function ##u_k(x)=\exp(\mathrm{i} k x)## does not represent a quantum state! It's not square integrable! It is a generalized eigenstate of momentum and belongs not to the Hilbert space ##\mathrm{L}^2(\mathbb{R},\mathbb{C})## but to the dual of the domain of the self-adjoint operators for position and momentum. It's very important to emphasize this in order not to be confused as a beginner in learning QT!

That is the Rigged Hilbert Space formalism.

Thanks
Bill
 
  • #8
vanhees71 said:
Again: The function ##u_k(x)=\exp(\mathrm{i} k x)## does not represent a quantum state! It's not square integrable! It is a generalized eigenstate of momentum and belongs not to the Hilbert space ##\mathrm{L}^2(\mathbb{R},\mathbb{C})## but to the dual of the domain of the self-adjoint operators for position and momentum. It's very important to emphasize this in order not to be confused as a beginner in learning QT!

Well, this is a pedagogical question, whether it is important. The way that a lot of science teaching works is that you tell students something that is oversimplified, at first, and then later get into the reasons why it was an oversimplification, and how it can be fixed. It's a matter of opinion whether this is doing a disservice to the student.

The treatments that I've seen start off talking about plane waves as momentum eigenstates (with a remark that they aren't square-integrable, but that there are ways of dealing with this).
 
  • #9
stevendaryl said:
Well, this is a pedagogical question, whether it is important. The way that a lot of science teaching works is that you tell students something that is oversimplified, at first, and then later get into the reasons why it was an oversimplification, and how it can be fixed. It's a matter of opinion whether this is doing a disservice to the student.

The treatments that I've seen start off talking about plane waves as momentum eigenstates (with a remark that they aren't square-integrable, but that there are ways of dealing with this).
Yes, and the pedagogical answer is that it indeed is important. Myself I had quite some trouble to understand the concept of "generalized eigenstates", because nobody told us how to understand them right. Of course, too much mathematical rigor is also not helpful, but sometimes some of it helps!
 
  • #10
vanhees71 said:
Yes, and the pedagogical answer is that it indeed is important. Myself I had quite some trouble to understand the concept of "generalized eigenstates", because nobody told us how to understand them right.

But you understand it now. The question is: Did it harm you for you to have to learn the more sophisticated approach on your own, as opposed to being taught it from the start?
 
  • #11
Well, it didn't do me harm, but sometimes it doesn't do harm to either tell things correctly rather than be silent about the mathematical problems involved. I don't say that you should expose students immediately with higher functional analysis but one should give the usual plausibility arguments, how to understand distributions. The ##\delta## distribution is a good example. Among the best textbooks from a pedagogical point of view is

M. J. Lighthill, Introduction to Fourier analysis and generalised function, Cambridge University Press 1959
 
  • #12
vanhees71 said:
Well, it didn't do me harm, but sometimes it doesn't do harm to either tell things correctly rather than be silent about the mathematical problems involved. I don't say that you should expose students immediately with higher functional analysis but one should give the usual plausibility arguments, how to understand distributions. The ##\delta## distribution is a good example. Among the best textbooks from a pedagogical point of view is

M. J. Lighthill, Introduction to Fourier analysis and generalised function, Cambridge University Press 1959

The way that most people learn about the more sophisticated approaches, though, is to first learn a naive approach, and then go back and learn the more sophisticated approach after learning about the problems in the naive approach. Starting off with the more rigorous approach without first trying the naive approach and learning its limitations would seem like unmotivated rigor for rigor's sake.
 
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  • #13
stevendaryl said:
But you understand it now. The question is: Did it harm you for you to have to learn the more sophisticated approach on your own, as opposed to being taught it from the start?

It didn't do any harm to me at all to learn what is in the paper I posted. I wish I had come across it before learning it by myself. I had to go through many tomes down the ANU library near where I lived at the time. It took me a long time because what was required was not in one place - but in tomes like Gelfand and Shilov and other mathematical references. It was a long sojourn sorting it out before returning to QM proper.

That's one reason I like Ballentine. It gives a good overview of what's going on without delving into deep waters like nuclear Spaces.

Thanks
Bill
 
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  • #14
bhobba said:
It didn't do any harm to me at all to learn what is in the paper I posted. I wish I had come across it before learning it by myself. I had to go through many tomes down the ANU library near where I lived at the time. It took me a long time because what was required was not in one place - but in tomes like Gelfand and Shilov and other mathematical references. It was a long sojourn sorting it out before returning to QM proper.

But is it good, or bad, that it took a long personal journey to reach your current level of understanding?
 
  • #15
stevendaryl said:
But is it good, or bad, that it took a long personal journey to reach your current level of understanding?

Interesting question.

I did it this way.

I read the popularization - Schrodinger's Cat back in about 1983. It mentioned THE books were Dirac's - Principles of QM and Von-Neumann - Mathematical Foundations of QM. I devoured both but recognized immediately, just like Von-Neumann did, and was scathing about in his introduction, Dirac was a crock - supremely elegant - but a crock. Von-Neumann was easy because I already knew Hilbert spaces from my degree. But there had to be a reason Dirac worked. It was a long sojourn sorting it out.

I would rather have studied Balllentine first, then Distribution theory, then Rigged Hilbert Spaces. I even knew something was cuckoo with the Dirac Delta function from my study of differential equations, so should have looked into that first.

So I did it wrong, but I don't regret doing it.

Thanks
Bill
 

1. What is an eigenfunction?

An eigenfunction is a mathematical function that remains unchanged when multiplied by a constant. It is a special type of function that is associated with a specific set of values known as eigenvalues.

2. What is the importance of eigenfunctions?

Eigenfunctions are important in the field of mathematics and science because they provide insight into the behavior of physical systems. They are used to solve differential equations and can help in understanding the properties of quantum systems.

3. How are eigenfunctions related to eigenvectors?

Eigenfunctions and eigenvectors are related concepts. An eigenfunction is a function that is associated with a specific eigenvalue, while an eigenvector is a vector that is associated with a specific eigenvalue. In other words, an eigenfunction is a special type of eigenvector that is a function instead of a vector.

4. What is the difference between eigenfunctions and eigenstates?

Eigenfunctions and eigenstates are closely related, but there is a subtle difference between the two. An eigenstate is a state of a physical system that has a definite value for a specific observable, while an eigenfunction is a mathematical function that represents this state. In other words, eigenstates are physical manifestations of eigenfunctions.

5. How are eigenfunctions used in practical applications?

Eigenfunctions have many practical applications in various fields such as quantum mechanics, signal processing, and data analysis. They are used to analyze and understand complex systems, make predictions, and solve problems that would be difficult using traditional methods. For example, they are used in image recognition software and in predicting the behavior of financial markets.

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